Climate change Impacts, Vulnerability and Adaptation ... · Training Module - Climate Change...

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Training Module - Climate Change Impacts, Vulnerability and Adaptation Planning in Water 1 Climate change Impacts, Vulnerability and Adaptation Planning in Water Sector - Training Module Prepared by INRM Consultants Pvt. Ltd. Submitted to: Strengthening State Strategies for Climate Actions UNDP

Transcript of Climate change Impacts, Vulnerability and Adaptation ... · Training Module - Climate Change...

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Climate change Impacts, Vulnerability and Adaptation

Planning in Water Sector - Training Module

Prepared by

INRM Consultants Pvt. Ltd.

Submitted to:

Strengthening State Strategies for Climate Actions

UNDP

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About the Training ModuleUNDP and MoEFCC in partnership with Swiss Agency for Development and Cooperation (SDC) is coordinating to strengthen capacities in the select states for effective planning, implementation and monitoring of the State Action Plan on Climate Change (SAPCC).

A training need assessment has been conducted for the state nodal agencies on climate change and sectoral departments in Uttarakhand, Sikkim and Madhya Pradesh, to assess the current capacity at various levels to deal with climate change vulnerability, risk and adaptation assessment in the states. Required training modules and scientific information are identified in consultation with the state.

This document gives a comprehensive training module on climate change impacts, vulnerability and adaptation planning in water sector for master trainers (officials from sectoral departments, nodal agencies and relevant institutions).

Target groups of the training programmes

Climate change vulnerability assessment is an important process in the context of the National Adaptation Plan (NAP) and hence, is an integral part of the NAP process.

This training program is aimed to support all those who are engaged in designing adaptation options to reduce climate change vulnerability. They include:

• Officials from sectoral line departments

• Nodal agencies (climate change cells)

• Academic and research institutions (like, WALMI1) who can possibly partner with line departments as technical support

• Technical and adaptation experts

How to use this Module?

Before the trainingThe basic objective of the training is to strengthen the understanding of trainees on Climate Change Impacts, Vulnerability and Adaptation Planning in Water Sector. To get a better insight of the existing knowledge of the trainees on the climate change issues a questionnaire is provided at the end of each module that may be shared with trainees for self-assessment

During the TrainingBased on the outcomes of the self-assessment the module trainer will have a better clarity on the level of understanding that the trainees would have

1 Water and Land Management Institute

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on the climate change issues. Accordingly, the trainer would be required to customize the pedagogy by referring to the following section ‘Structure of Training Module’.

After the training

The trainees may be given an opportunity to respond to the same questionnaire as was provided before the training to gauge the increased level of understanding on Climate Change Impacts, Vulnerability and Adaptation Planning in Water Sector.

Structure of the Training Module

Training material is organised in four modules which include:

• Module I: Climate Change-Basic

Session 1: Climate Change-Basic

Purpose of this session is to provide basic understanding on key terminologies such as Weather, Climate, Climate Change, Greenhouse gases, Consequences of GHG concentration in the atmosphere (mainly temperature change) etc.

Approach and Tools: One Powerpoint Presentation, Pairing words, Glossary of terms-slide and questions and answers

Session 2: Climate change in India

Purpose of this session is to introduce national and sub national policies and programmes directed towards climate change adaptation and mitigation.

Approach and Tools: One PowerPoint Presentation

• Module II: Impact Assessment - Water Resources

Session 1: Introduction to CC Impacts

Purpose of this session is to provide overview of Impact of Climate Change on Water Resources that includes :

• IPCC Summary on Climate Change Impacts on Water Resources

• Climate Change Impact Assessment Tools-Bio Physical Models

Approach and Tools: One PowerPoint Presentation

Session 2: SWAT model overview and applications

Purpose of this session is to provide overview of SWAT Model and applications

Approach and Tools: One PowerPoint Presentation on SWAT

Session 3: Hands-on SWAT model

Purpose of this session to provide hands-on training on SWAT Modelling. In this session, the trainees will be given an overview of data inputs, simulation and output interpretation for the SWAT model.

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Approach and Tools: One PowerPoint Presentation on SWAT and laptops provided to the individual groups for the Hands-on exercise. These laptops should be preloaded with QSWAT, data inputs for the SWAT model and video tutorial on SWAT.

• Module III: Vulnerability Assessment

Session 1: Vulnerability Assessment-- General

Purpose of this session is to provide a detailed approach for conducting Vulnerability Assessment and overview of different vulnerability assessments methods

Approach and Tools: One PowerPoint Presentation on VA Models

Session 2: Group Exercise on the Vulnerability Assessment

Purpose of this session is to provide an overview of different methods used in conducting vulnerability assessment. In this session, the trainees will be segregated into four groups to construct Vulnerability Assessment matrix using sample raw vulnerability assessment data.

Approach and Tools: Group formation, deliberation of group works on work sheet, Group presentation, VA raw data on Agriculture and water to the respective groups (Refer Annexure II), four laptops with MS office, questions and answers, chart paper and sketch pens

• Module IV: General Adaptation Options in Water Sector

Session 1: Adaptation- Water Resources

Purpose of this session is to provide overview of methods to conduct Adaptation Planning in the water sector and sensitize participants about the adaptation technologies

Approach and Tools: One PowerPoint Presentation and Group Exercise using Adaptation Toolkit

Session 2: Group Exercise on the Adaptation Planning

Purpose of this session is to provide an overview of adaptation planning in the water sector. In this session, the trainees will be segregated into groups and assess vulnerability of various sectors through the use of Vulnerability Assessment Tools as well as local knowledge

Approach and Tools: Group formation, deliberation of group works on work sheet, Group presentation, A. sectoral briefs, VA matrix on Agriculture and water to the respective groups (Refer Annexure III), questions and answers, chart paper and sketch pens

Note: At the end of each module, an online self-assessment would be carried on the subject.

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Design of Training of Trainer Program

Day Duration Module Session

Day 1

1.5 Hours • Module I: Climate Change-Basic

• Welcome, Opening Introductions and Ice Breaking Session

1.5 Hours • Module I: Climate Change-Basic

• Session 1: Climate Change-Basic

1.5 Hours • Module I: Climate Change-Basic

• Session 2: Climate change in India

2.5 Hours • Module II: Impact Assessment - Water Resources

• Session 1: Introduction to CC Impacts

Day 2

2 Hours • Module II: Impact Assessment - Water Resources

• Session 2: SWAT model overview and applications

6 Hours

• Module II: Impact Assessment - Water Resources

• Session 3: Hands on SWAT model

Day 3

2 Hours • Module III: Vulnerability Assessment

• Session 1: Vulnerability Assessment- General

2 Hours • Module III: Vulnerability Assessment

• Session 2: Group Exercise on Vulnerability Assessment

2 Hours • Module IV: Adaptation- Water Resources

• Session 1: Adaptation- Water Resources

2 Hours • Module IV: Adaptation- Water Resources

• Session 2: Group Exercise on VA and Adaptation Planning

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Training Checklist

Sl No

Items

1 Training Modules, Folders, Note Pads. Pens and Agenda Schedule

2 Attendance sheets

3 Power Point Presentations

• Climate Change-Basic

• Climate change in India

• Introduction to CC Impacts

• SWAT model overview and applications

• Vulnerability Assessment- General

• Adaptation- Water Resources

4 Laptops (with group three exercises folders) preloaded with MS office and QSWAT software

• SWAT Modelling (Video tutorials, QSWAT, SWAT Input Data files)

• VA group exercise (VA raw data)

• Adaptation Planning group exercise (VA , Sectoral briefs, Adaptation Tool Kit)

5 Chart Papers, Pencils, Scissors, Sketch Pens

6 Markers and Board

7 Sectoral Briefs

8 Pairing Words Set

9 Projector and Speakers

10 Group Photo

11 Training Completion Certificate

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Table of ContentsModule I: Climate Change-Basic ...............................................................15

Session 1: Basic Climate Change Science: Global Warming, Climate change Models ....................................................................................................................... 15

What is climate change? .......................................................................................... 16

What causes climate change? ................................................................................. 16

Climate Variability and Change .............................................................................. 16

Scientific basis: .......................................................................................................... 16

Climate models - India ............................................................................................. 16

Shared Socio-economic Pathways .......................................................................... 17

Session 2: Climate change in India ........................................................................ 18

What will be the impacts of climate change for India? ........................................ 18

How is India combating climate change? .................................................18

Self-Assessment: Climate Change-Basic ...................................................29

Module II: -Impact Assessment- on Water Resources ...............................30

Session 1: IPCC Summary on Climate Change Impacts on Water Resources ......... 30

Impact of Climate Change on Water Resources ................................................... 31

Tools in Water Resource Impact Assessment – Biophysical Models ................... 32

Climate parameters to be monitored in context to water sector ....................... 34

Selection of Impact Models for Water Sector ....................................................... 35

Session 2 : SWAT Model Overview and Applications .......................................... 39

Session3; Hands-on SWAT Model .......................................................................... 41

Data requirements .................................................................................................... 41

Model Outputs .......................................................................................................... 41

Limitations .................................................................................................................. 41

Data Sources ............................................................................................................. 41

Self-Assessment Quiz: Impact Assessment .......................................................... 45

Module III: Vulnerability Assessment ........................................................46

Session 1: Vulnerability Assessment-General ....................................................... 46

Purpose of Vulnerability Assessment ..................................................................... 47

Vulnerability Assessment Methodology ................................................................ 47

Steps to Construct Vulnerability Index ................................................................... 49

Visualization ............................................................................................................... 51

Interpretation of Findings of Vulnerability Assessment ....................................... 51

Session 2: Group Exercise on the Vulnerability Assessment ............................... 52

Self-Assessment Quiz: Vulnerability Assessment ................................................. 53

Module IV: General Adaptation Options in Water Sector .........................54

Session 1: Adaptation- Water Resources ............................................................... 54

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Extract from Climate Change Adaptation Technologies

for Water - UN Environment .................................................................................... 55

Session 2: Group Exercise on the Adaptation Planning ...................................... 59

Self-Assessment Quiz: Adaptation Options in Water Sector ............................. 60

Appendix I- Some Relevant Model Description ................................................... 61

The Hydrologic Modelling System (HEC-HMS) - Surface Water Model ............. 61

Data requirements .................................................................................................... 61

Model Outputs .......................................................................................................... 61

Limitations .................................................................................................................. 61

VIC model (Variable Infiltration Capacity model) - Surface Water Model ......... 61

Data requirements .................................................................................................... 62

Model Outputs .......................................................................................................... 62

Limitations .................................................................................................................. 62

MIKE water resources products - Commercial ...................................................... 62

Data requirements .................................................................................................... 62

MODFLOW - The Ground Water Model ................................................................ 62

Data requirements .................................................................................................... 63

Model Output ............................................................................................................ 64

Limitations .................................................................................................................. 64

Water Evaluation and Planning Model (WEAP) - Water System Model ............. 64

Data Requirement ..................................................................................................... 65

Model Output ............................................................................................................ 65

Appendix II - Vulnerability Assessment ....................................................66

Normalization of Indicator Data ................................................................68

Example of normalisation of indicators using functional relationship ............... 72

Calculation of Weights ............................................................................................. 72

Method of Equal weights ......................................................................................... 72

Unequal Weights ...................................................................................................... 73

Cluster Analysis ......................................................................................................... 77

Derive Projected Vulnerability Category w.r.t. Baseline ....................................... 78

Appendix III Adaptation Planning Exercise ........................................................... 78

List of FiguresFigure 1: Shared Socio-economic Pathways ......................................................... 17

Figure 2: SAPCC Formulation Process ................................................................... 23

Figure 3: Supply Side Assessment (Impact Assessment) using a hydrological model ..................................................................................... 39

Figure 4: Framework to assess the impact of climate

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change on water resources ..................................................................................... 35

Figure 5: Distribution of changes in Water Balance Components for Madhya Pradesh during Northeast Monsoon ................................................. 40

Figure 6: Data and Information Needs .................................................................. 42

Figure 7: Conceptualization of risk by the IPCC. Source: IPCC (2014) AR5, WG-II, Ch. 19 ............................................................................... 46

Figure 8: Attributes of vulnerability assessments ................................................ 48

Figure 9: Climate change adaptation and water – overview of challenges and responses .................................................................. 55

Figure 10: Water adaptation technology taxonomy ............................................ 56

Figure 11: Extract from Water adaptation technologies for six broad water challenges relating to climate change ....................................... 57

List of TablesTable 1: Madhya Pradesh Vision Document, 2032 ............................................... 25

Table 2: Initiatives by the State Government ......................................................... 28

Table 3: Summary of the likely water cycle changes due to climate change .......................................................................................................... 31

Table 4: List of Probable Hydrological, Hydraulic and Water System Models ............................................................................................... 36

Table 5: Commonly employed terminology ......................................................... 66

Table 6: Data set to be used for Hands-on Exercise - raw ................................... 69

Table 7: Normalized data set according to functional relationship (Ref Table 4 ................................................................................................................ 71

Table 8: District wise water resources vulnerability Index values, ranks and vulnerability category under current andprojected climate scenarios .................................................................................... 79

Table 9: District wise agriculture vulnerability Index values, ranks and vulnerability category under current and projected climate scenarios ............................................................................. 82

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Glossary of Terms2

Adaptation: The process of adjustment to actual or expected climate and its effects. In human systems, adaptation seeks to moderate or avoid harm or exploit beneficial opportunities. In some natural systems, human intervention may facilitate adjustment to expected climate and its effects (WGII, III)

Adaptation deficit: The gap between the current state of a system and a state that minimizes adverse impacts from existing climate conditions and variability. (WGII)

Adaptation limit: The point at which an actor’s objectives (or system needs) cannot be secured from intolerable risks through adaptive actions. (WGII)

• Hard adaptation limit: No adaptive actions are possible to avoid intolerable risks.

• Soft adaptation limit: Options are currently not available to avoid intolerable risks through adaptive action.

Adaptive capacity: The ability of systems, institutions, humans and other organisms to adjust to potential damage, to take advantage of opportunities, or to respond to consequences. (WGII, III)

Baseline/reference: The baseline (or reference) is the state against which change is measured. A baseline period is the period relative to which anomalies are computed. In the context of transformation pathways, the term baseline scenarios refer to scenarios that are based on the assumption that no mitigation policies or measures will be implemented beyond those that are already in force and/or are legislated or planned to be adopted. Baseline scenarios are not intended to be predictions of the future, but rather counterfactual constructions that can serve to highlight the level of emissions that would occur without further policy effort. Typically, baseline scenarios are then compared to mitigation scenarios that are constructed to meet different goals for greenhouse gas (GHG) emissions, atmospheric concentrations or temperature change. The term baseline scenario is used interchangeably with reference scenario and no policy scenario. In much of the literature the term is also synonymous with the term business-as-usual (BAU) scenario, although the term BAU has fallen out of favour because the idea of business as usual in century-long socio-economic projections is hard to fathom. (WGI, II, III)

Climate: Climate in a narrow sense is usually defined as the average weather, or more rigorously, as the statistical description in terms of the mean and variability of relevant quantities over a period ranging from months to thousands or millions of years. The classical period for averaging these variables is 30 years, as defined

2 IPCC, 2014: Annex II: Glossary [Mach, K.J., S. Planton and C. von Stechow (eds.)]. In: Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, R.K. Pachauri and L.A. Meyer (eds.)]. IPCC, Geneva, Switzerland, pp. 117-130

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by the World Meteorological Organization. The relevant quantities are most often surface variables such as temperature, precipitation and wind. Climate in a wider sense is the state, including a statistical description, of the climate system. (WGI, II, III)

Climate change: Climate change refers to a change in the state of the climate that can be identified (e.g., by using statistical tests) by changes in the mean and/or the variability of its properties and that persists for an extended period, typically decades or longer. Climate change may be due to natural internal processes or external forcings such as modulations of the solar cycles, volcanic eruptions and persistent anthropogenic changes in the composition of the atmosphere or in land use. Note that the Framework Convention on Climate Change (UNFCCC), in its Article 1, defines climate change as: ‘a change of climate which is attributed directly or indirectly to human activity that alters the composition of the global atmosphere and which is in addition to natural climate variability observed over comparable time periods’. The UNFCCC thus makes a distinction between climate change attributable to human activities altering the atmospheric composition and climate variability attributable to natural causes. (WGI, II, III)

Climate model (spectrum or hierarchy): A numerical representation of the climate system based on the physical, chemical and biological properties of its components, their interactions and feedback processes and accounting for some of its known properties. The climate system can be represented by models of varying complexity; that is, for any one component or combination of components a spectrum or hierarchy of models can be identified, differing in such aspects as the number of spatial dimensions, the extent to which physical, chemical or biological processes are explicitly represented, or the level at which empirical parametrizations are involved. Coupled Atmosphere–Ocean General Circulation Models (AOGCMs) provide a representation of the climate system that is near or at the most comprehensive end of the spectrum currently available. There is an evolution towards more complex models with interactive chemistry and biology. Climate models are applied as a research tool to study and simulate the climate and for operational purposes, including monthly, seasonal and interannual climate predictions. (WGI, II, III)

Climate projection: A climate projection is the simulated response of the climate system to a scenario of future emission or concentration of greenhouse gases (GHGs) and aerosols, generally derived using climate models. Climate projections are distinguished from climate predictions by their dependence on the emission/concentration/radiative forcing scenario used, which is in turn based on assumptions concerning, for example, future socio-economic and technological developments that may or may not be realized. (WGI, II, III)

Climate-resilient pathways: Iterative processes for managing change within complex systems in order to reduce disruptions and enhance opportunities associated with climate change. (WGII)

Climate sensitivity: In IPCC reports, equilibrium climate sensitivity (units: °C) refers to the equilibrium (steady state) change in the annual global mean surface temperature following a doubling of the atmospheric equivalent carbon dioxide

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(CO2 ) concentration. Owing to computational constraints, the equilibrium climate sensitivity in a climate model is sometimes estimated by running an atmospheric general circulation model coupled to a mixed-layer ocean model, because equilibrium climate sensitivity is largely determined by atmospheric processes. Efficient models can be run to equilibrium with a dynamic ocean. The climate sensitivity parameter (units: °C (W m–2) –1) refers to the equilibrium change in the annual global mean surface temperature following a unit change in radiative forcing. (WGI, II, III)

Climate variability: Climate variability refers to variations in the mean state and other statistics (such as standard deviations, the occurrence of extremes, etc.) of the climate on all spatial and temporal scales beyond that of individual weather events. Variability may be due to natural internal processes within the climate system (internal variability), or to variations in natural or anthropogenic external forcing (external variability). (WGI, II, III)

Drought: A period of abnormally dry weather long enough to cause a serious hydrological imbalance. Drought is a relative term; therefore any discussion in terms of precipitation deficit must refer to the particular precipitation-related activity that is under discussion. For example, shortage of precipitation during the growing season impinges on crop production or ecosystem function in general (due to soil moisture drought, also termed agricultural drought) and during the runoff and percolation season primarily affects water supplies (hydrological drought). Storage changes in soil moisture and groundwater are also affected by increases in actual evapotranspiration in addition to reductions in precipitation. A period with an abnormal precipitation deficit is defined as a meteorological drought. A megadrought is a very lengthy and pervasive drought, lasting much longer than normal, usually a decade or more.

Emission scenario: A plausible representation of the future development of emissions of substances that are potentially radiatively active (e.g., greenhouse gases (GHGs), aerosols) based on a coherent and internally consistent set of assumptions about driving forces (such as demographic and socio-economic development, technological change, energy and land use) and their key relationships. Concentration scenarios, derived from emission scenarios, are used as input to a climate model to compute climate projections.

Ensemble: A collection of model simulations characterizing a climate prediction or projection. Differences in initial conditions and model formulation result in different evolutions of the modeled system and may give information on uncertainty associated with model error and error in initial conditions in the case of climate forecasts and on uncertainty associated with model error and with internally generated climate variability in the case of climate projections. (WGI, II)

Exposure: The presence of people, livelihoods, species or ecosystems, environmental functions, services, and resources, infrastructure, or economic, social, or cultural assets in places and settings that could be adversely affected. (WGII)

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Global warming: Global warming refers to the gradual increase, observed or projected, in global surface temperature, as one of the consequences of radiative forcing caused by anthropogenic emissions. (WGIII)

Hydrological cycle: The cycle in which water evaporates from the oceans and the land surface, is carried over the Earth in atmospheric circulation as water vapour, condenses to form clouds, precipitates over ocean and land as rain or snow, which on land can be intercepted by trees and vegetation, provides runoff on the land surface, infiltrates into soils, recharges groundwater, discharges into streams and ultimately flows out into the oceans, from which it will eventually evaporate again. The various systems involved in the hydrological cycle are usually referred to as hydrological systems. (WG I, II)

Impacts (consequences, outcomes): Effects on natural and human systems. In this module, the term impacts is used primarily to refer to the effects on natural and human systems of extreme weather and climate events and of climate change. Impacts generally refer to effects on lives, livelihoods, health, ecosystems, economies, societies, cultures, services and infrastructure due to the interaction of climate changes or hazardous climate events occurring within a specific time period and the vulnerability of an exposed society or system. Impacts are also referred to as consequences and outcomes. The impacts of climate change on geophysical systems, including floods, droughts and sea level rise, are a subset of impacts called physical impacts. (WG II)

Integrated models: Integrated models explore the interactions between multiple sectors of the economy or components of particular systems, such as the energy system. In the context of transformation pathways, they refer to models that, at a minimum, include full and disaggregated representations of the energy system and its linkage to the overall economy that will allow for consideration of interactions among different elements of that system. Integrated models may also include representations of the full economy, land use and land-use change (LUC) and the climate system

Land use and land-use change: Land use refers to the total of arrangements, activities and inputs undertaken in a certain land cover type (a set of human actions). The term land use is also used in the sense of the social and economic purposes for which land is managed (e.g., grazing, timber extraction and conservation). In urban settlements it is related to land uses within cities and their hinterlands. Urban land use has implications on city management, structure and form and thus on energy demand, greenhouse gas (GHG) emissions and mobility, among other aspects. (WG I, II, III)

Mitigation (of climate change): A human intervention to reduce the sources or enhance the sinks of greenhouse gases (GHGs) and assesses human interventions to reduce the sources of other substances which may contribute directly or indirectly to limiting climate change, including, for example, the reduction of particulate matter emissions that can directly alter the radiation balance (e.g., black carbon) or measures that control emissions of carbon monoxide, nitrogen oxides, Volatile Organic Compounds and other pollutants that can alter the concentration of tropospheric ozone which has an indirect effect on the climate. (WG I, II, II)

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Representative Concentration Pathways (RCPs): Scenarios that include time series of emissions and concentrations of the full suite of greenhouse gases (GHGs) and aerosols and chemically active gases, as well as land use/land cover (Moss et al., 2008). The word representative signifies that each RCP provides only one of many possible scenarios that would lead to the specific radiative forcing characteristics. The term pathway emphasizes that not only the long-term concentration levels are of interest, but also the trajectory taken over time to reach that outcome (Moss et al., 2010). RCPs usually refer to the portion of the concentration pathway extending up to 2100, for which Integrated Assessment Models produced corresponding emission scenarios.

RCP2.6 One pathway where radiative forcing peaks at approximately 3 W/m2 before 2100 and then declines (the corresponding Emission Concentration Pathways(ECP) assuming constant emissions after 2100).

RCP 4.5 and RCP6.0 Two intermediate stabilization pathways in which radiative forcing is stabilized at approximately 4.5 W/m2 and 6.0 W/m2 after 2100 (the corresponding ECPs assuming constant concentrations after 2150).

RCP 8.5 One high pathway for which radiative forcing reaches >8.5 W/m2 by 2100 and continues to rise for some amount of time (the corresponding ECP assuming constant emissions after 2100 and constant concentrations after 2250)

Resilience: The capacity of social, economic and environmental systems to cope with a hazardous event or trend or disturbance, responding or reorganizing in ways that maintain their essential function, identity and structure, while also maintaining the capacity for adaptation, learning and transformation . (WGII, III)

Sustainable Development Goals: Sustainable Development Goals (SDGs), otherwise known as the Global Goals, are a universal call to action to end poverty, protect the planet and ensure that all people enjoy peace and prosperity. These goals include:

(Source: http://www.undp.org/content/undp/en/home/sustainable-development-goals.html)

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Uncertainty: A state of incomplete knowledge that can result from a lack of information or from disagreement about what is known or even knowable. It may have many types of sources, from imprecision in the data to ambiguously defined concepts or terminology, or uncertain projections of human behaviour. Uncertainty can therefore be represented by quantitative measures (e.g., a probability density function) or by qualitative statements (e.g., reflecting the judgment of a team of experts)

Vulnerability: The propensity or predisposition to be adversely affected. Vulnerability encompasses a variety of concepts and elements including sensitivity or susceptibility to harm and lack of capacity to cope and adapt. (WG II)

Module I: Climate Change-Basic

Session 1: Basic Climate Change Science: Global Warming, Climate change Models

Ice Breaking Session

Sequential introduction of participants along with the explanation of key terms mentioned in the glossary of terms.

• Individual participants will pick one of the pairing word and will identify their respective partners by referring glossary of terms(Slide)

• Introduction of Partners and explanation of Climate Change glossary terms

Climate change is not only a major global environmental problem but is also an issue of great concern to a developing country like India. The earth’s climate has demonstrably changed on both global and regional scales since the pre-industrial era, with some of these changes attributable to human activities.3

Climate change is the significant change in weather patterns over multiple decades, typically 30 years or longer. Global warming is clearly evident in instrumental records of temperature, sea levels, and melting snow and ice. Past climate changes have been driven by natural processes, but now scientist agree that climate change is accelerated as a result of human activity: The temperature increase over the past few decades is largely driven by greenhouse gas emissions from human activities. Climate models are tools for understanding why the globe is warming. Climate model projections indicate that the future climate is likely to be different to that of the past.

Inferences drawn from IPCC AR5 shows that air and water temperatures are increasing, precipitation patterns are changing, there are increasing incidents

3 India Second National Communication To The United Nations, 2012, unfccc.int/resource/ docs/natc/indnc2.pdf

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of extreme weather, sea level is rising and there are changes in the ocean environment. These changes are projected to continue into the future.4

What is climate change?Climate change refers to a statistically significant variation in either the mean state of the climate (like daily mean temperature or annual rainfall) in its variability, persisting for an extended period (typically decades or longer).

What causes climate change?Climate change may be due to natural internal processes (natural drivers of climate change include subtle shifts and wobbles in the Earth’s orbit or external forcings (variations in ocean currents, solar output or volcanic eruptions), or to persistent anthropogenic changes in the composition of the atmosphere (greenhouse effect/ burning of fossil fuels) or in land use (landuse change due to industrialization, deforestation).

Climate Variability and ChangeClimate variability is the climate fluctuation yearly above or below a long-term average value (generally 30-year average of a weather variable) and Climate change is the long-term continuous change (increase or decrease) to average weather conditions (e.g. average temperature) or the range of weather (e.g. more frequent high intensity rainfall).

Scientific basis:Global warming is clearly evident in instrumental records of temperature, sea levels, and melting snow and ice. Past climate changes have been driven by natural processes but now climate is change is accelerated as a result of human activity. The temperature increases over the past few decades is largely driven by greenhouse gas emissions from human activities. Indian annual mean temperature showed significant warming trend of 0.6oC per 100 years during the period 1901–2010.

Climate models - IndiaClimate models are tools for understanding why the globe is warming. Climate model projections indicate that the future climate is likely to be different to that of the past.

4 Transcript for Understanding Climate Change Impacts on Water Resources, 2016, https:// www.epa.gov/watershedacademy/understanding-climate-change-impacts-water-resources

Mitigation Climate change mitigation consists of actions to limit the magnitude or rate of long-term climate change

-IPCC

Adaptation The process of adjustment to actual or expected climate and its effects. In human systems, adaptation seeks to moderate or avoid harm or exploit beneficial opportunities. In some natural systems, human intervention may facilitate adjustment to expected climate and its effects. {WGII, III}

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Regional Climate Model (RCM)– Co-ordinated Regional Downscaling Experiment (Cordex) – Regional Climate Models.

IPCC Emission scenarios: IPCC AR5 Representative Concentration Pathways: a stringent mitigation scenario (RCP2.6), two intermediate scenarios (RCP4.5 and RCP6.0) and one scenario with very high GHG emissions (RCP8.5).

Projections for India: Projects for India based on multi-model ensemble of CORDEX RCM5:;

• The all India mean surface air temperature change for the near-term period 2016–2045 relative to 1976–2005 is projected to be in the range of 1.08°C to 1.44°C and projected to increase in the far future (2066–2095) by 1.35 ±0.23°C under RCP2.6, 2.41 ± 0.40°C under RCP4.5 and 4.19 ± 0.46°C under RCP8.5 scenario respectively.

• Precipitation changes throughout the 21st century remain highly uncertain.

• The all India annual precipitation extremes are projected to increase with relatively higher uncertainty under RCP8.5 scenario by the end of the 21st century.

Shared Socio-economic Pathways

• Socio-economic scenarios used to derive emissions scenarios without(baseline scenarios) and with climate policies (mitigation scenarios). These SSPs aim not directly at decision makers but at climate change analysts preparing climate policy analysis based on the SSPs(Figure 1).

• Climate change projections and socio-economic scenarios used to evaluate climate impacts and adaptation measures

• Previous set of socio-economic scenarios are 15 years old (SRES, 2000).

Therefore, new socio-economic pathway scenarios ( SSPs) are formulated by .

Figure 1: Shared Socio-economic Pathways(Source:https://unfccc.int/sites/default/files/part1_iiasa_rogelj_ssp_poster.pdf)

5 http://cccr.tropmet.res.in/home/docs/cccr/climate-change-report-2017.pdf

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Session 2: Climate change in IndiaWhat will be the impacts of climate change for India?Some of the impacts are shown below:Sea Level rise: West Bengal, Tamil Nadu, Orissa, Kerala, Karnataka

• Inundation of coastal areas

• Migration

Glacier melt

• Himalayan river systems (Ganga, Brahmaputra, Indus)

• Hydro power and irrigation projects (long term reduced inflow)

Water resources

• Water stressed basins: Ganga, Krishna, Cauvery, Luni, Tapi

• Water excess basins: Mahanadi, Baitarani

Agriculture

• Decrease in Yield: rice, wheat, potato, green gram, soybean, and chickpea (irrigated crop, due to temperature increase)

No change in rainfed Sorghum yield

Forest ecosystem

• Most vulnerable: Himalayan eco system

• Moderately vulnerable: coastal region and Western GhatsLeast vulnerable: North east region

Health

• Malaria Transmission windows (conducive in Northern and North Eastern states; reduction in Orissa, Andhra Pradesh and Tamil Nadu is projected

How is India combating climate change?National Action Plan on Climate Change (NAPCC)India’s National Action Plan on Climate Change (NAPCC) released in 20086 outlines its strategy to meet the challenge of Climate Change. NAPCC is guided by the principles of sustainable development (SD) and aligns the environmental and economic objectives. It outlines a national strategy that aims to enable the country to adapt to climate change and enhances the ecological sustainability of India’s development path. It stresses that maintaining a high growth rate is essential for increasing living standards of

the vast majority of people of India and reducing their vulnerability of the impacts of climate change. There are eight “National Missions” which form the core of the National action plan. They focus on promoting understanding of climate change, adaptation and mitigation, energy efficiency and natural resource conservation.

6 http://pmindia.nic.in/climate_change.htm

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At the national level, the integration of climate change in national development is guided by the Prime Minister’s Council on Climate Change, which includes representation of key Ministries, as well as experts, and representatives of industry and of media. The Council provides overall strategic guidance on mainstreaming climate change in development, identifies key intervention priorities, and monitors the implementation of these interventions.

Eight Missions of National Action Plan on Climate ChangeNational Solar Mission:• Make solar energy competitive with fossil-based energy options.• Launch an R&D programme facilitating international co-operation to enable

the creation of affordable, more convenient solar energy systems.• Promote innovations for sustained, long-term storage and use of solar power.

National Mission for Enhanced Energy Efficiency:• The Energy Conservation Act of 2001 provides a legal mandate for the

implementation of energy efficiency measures through the mechanisms of The Bureau of Energy Efficiency (BEE) in the designated agencies in the country.

• A number of schemes and programmes have been initiated which aim to save about 10,000 MW by the end of the 11th Five-Year Plan in 2012.

National Mission on Sustainable Habitats:• Make habitats sustainable through improvements in energy efficiency in

buildings, management of solid waste and a modal shift to public transport.• Promote energy efficiency as an integral component of urban planning and

urban renewal through its initiatives.

National Water Mission:• Conserving water, minimizing wastage, and ensuring more equitable

distribution and management of water resources.• Optimizing water use efficiency by 20% by developing a framework of

regulatory mechanisms.

National Mission for Sustaining the Himalayan Ecosystem:

• Empowering local communities especially Panchayats to play a greater role in managing ecological resources.

• Reaffirm the measures mentioned in the National Environment Policy, 2006.

National Mission for a Green India:

• To increase ecosystem services including carbon sinks.

• To increase forest and tree cover in India to 33% from current 23%.

National Mission for Sustainable Agriculture:

• Make Indian agriculture more resilient to climate change by identifying new varieties of crops (example: thermally resistant crops) and alternative cropping patterns.

• Make suggestions for safeguarding farmers from climate change like introducing new credit and insurance mechanisms and greater access to information.

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National Mission on Strategic Knowledge on Climate Change:

• Work with the global community in research and technology development by collaboration through different mechanisms. It also has its own research agenda supported by climate change related institutions and a Climate Research Fund.

• Encourage initiatives from the private sector for developing innovative technologies for mitigation and adaptation.

Four Proposed New MissionsThe government of India has proposed for addition of four new missions to the National Action Plan on Climate Change (NAPCC), they include;

• The Wind Mission is modelled on the National Solar Mission which seeks to increase the share of renewable energy in India’s energy mix.

• The ‘mission’ on India’s coastal areas to prepare an integrated coastal resource management plan and map vulnerabilities along the entire nearly 7000-km long shoreline.

• The waste-to-energy mission to incentivise efforts towards harnessing energy from all kinds of waste and is aimed at lowering India’s dependence on coal, oil and gas, for power production.

• The mission on dealing with climate impacts on human health to assess likely impact of climate change on human health in different regions of the country and to build up capacities to respond to these and also to health emergencies arising out of natural disasters.

National Water Mission (NWM)Nodal agency at national level : Ministry of Water Resources. Functioning of the National Water Mission will be at a ministry level and inter-sectoral groups have been constituted combining resources from other relevant ministries, industry, academia and civil society. A dedicated Mission Secretariat has also been proposed.

The main objective of the National Water Mission (NWM) is “conservation of water, minimizing wastage and ensuring its more equitable distribution both across and within States through integrated water resources development and management”.

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The five identified goals of the Mission are7:1. Comprehensive water data base in public domain and assessment of impact

of climate change on water resource.

2. Promotion of citizen and state action for water conservation, augmentation and preservation.

3. Focused attention to vulnerable areas including over-exploited areas.

4. Increasing water use efficiency by 20%.

5. Promotion of basin level integrated water resources management.

Strategies for Implementation- NWMThe mission will adopt strategies which lead to an integrated plan for sustainable development and efficient management of water resources, with active participation of the stakeholders. It will identify and evaluate various development scenarios and management practices, on the basis of dependable projection of the impacts of climate change on water resources based on reliable data and information. It will also focus on integrated water resources planning and convergence between various water resources programmes.

Other identified strategies of the Mission also aim to review:

• National Water Policy.

• Policy for financing water resources projects.

• Criteria for design and planning for water resources projects.

Important Thrust ActivitiesApart from the activities related to the identified strategies, some of the important thrust activities of the Mission will be:

• Research and studies on all aspects related to impact of climate change on water resources including quality aspects of water resources.

• Expeditious implementation of water resources projects particularly the multipurpose projects with carry over storages.

• Promotion of traditional system of water conservation.

• Intensive programme for ground water recharge in over-exploited areas

• Incentivize for recycling of water including wastewater.

• Intensive capacity building and awareness programme including those for Panchayati Raj Institutions, urban local bodies and youth.

• Sensitization of elected representatives of over exploited area on dimensions of the problem and to orient investment under NREGA towards water conservation.

7 http://www.indiawaterportal.org/articles/national-water-mission-under-national-ac tion-plan-climate-change-revised-comprehensive

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Studies at the national level• National Communication to UNFCCC – MoEF & CC

o Initial National Communication - 22 June 2004

o Second National Communication - 4 May 2012

o Third National Communication (being prepared)

• Indian Network for Climate Change Assessment (INCCA) – The 4x4 assessment, November 2010

Intended Nationally Determined Contributions (INDCs)Nationally determined contributions (NDCs) are at the heart of the Paris Agreement. These NDCs embody efforts by each country to reduce national emissions and adapt to the impacts of climate change. The Paris Agreement (Article 4, paragraph 2) requires each Party to prepare, communicate and maintain, successive nationally determined contributions (NDCs) that it intends to achieve. Parties shall pursue domestic mitigation measures, with the aim of achieving the objectives of such contributions. The intended contributions were determined without prejudice to the legal nature of the contributions.

India’s INDCs8 identifies water as the most critical component of life support system. The total catchment area is 252.8 million hectare (mha), covering more than 75% of the total area of the country. The adaptation strategies for the water sector focus on enhancing efficient use of water, ensuring access and tackling the adverse impact of Climate Change. The transboundary and regional issues also need to be factored in.

• The main objective of India’s National Water Mission (NWM) is “conservation of water, minimizing wastage and ensuring its more equitable distribution both across and within States through integrated water resources development and management”. One of the key goals of the mission is to enhance water use efficiency by 20%.

• Groundwater is the major component of the total available water resources. Rapid expansion of groundwater use in India in the last three decades has resulted in a steep decline in the groundwater table in vast areas of the country. Rainwater harvesting, which offers a promising solution to replenish and recharge the groundwater is a significant component of Watershed Development Programme, taken up under different schemes of the central and state governments. Several municipal authorities, including Delhi have amended their existing building bye-laws, making it compulsory for every large house or hotel (200 yards or more in area) to undertake rainwater harvesting.

8 http://www4.unfccc.int/ndcregistry/PublishedDocuments/India%20First/INDIA%20INDC%20 TO%20UNFCCC .pdf

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• Neeranchal is a recent programme by Government to give additional impetus to watershed development in the country.

• Another important initiative relating to rivers is the National Mission for Clean Ganga which seeks to rejuvenate the river along its length of more than 2,500 km through multifarious activities such as pollution inventorization, assessment and surveillance and laying of sewage networks, treatment plants etc.

• The total flood prone area in the country is about 45.64 million ha. Existing flood management mechanisms involve both Central and State Government.

• Government of India has also set up the National River Conservation Directorate for conservation of rivers, lakes and wetlands in the country and improving the water quality which covers stretches of 40 rivers in 190 towns spread over 20 States.

State Action Plan on Climate Change (SAPCC)

Madhya Pradesh, through its State Knowledge Management Centre on Climate Change (SKMCCC) managed by EPCO, has developed an ambitious and comprehensive SAPCC as envisaged in the NAPCC covering sectors of forest, agriculture and allied, water, livestock and fisheries, health sector, urban administration and transport, energy efficiency and renewable energy, industries, panchayat and rural development and environment. UNDP has provided support in the formulation of SAPCC (Figure 2).

Figure 2: SAPCC Formulation Process(Source: Madhya Pradesh SAPCC preparation process, UNDP)

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SAPCC implementation mechanisms in water sector

• Strengthening State Strategies for Climate Actions is a project, being implemented by United Nations Development Programme (UNDP) in partnership with Swiss Agency for Development and Cooperation (SDC) & Ministry of Environment, Forest and Climate Change (MoEFCC). The overall goal of the project is to integrate climate actions into sub-national planning, benefitting local communities in India. The goal is to be achieved by strengthening capacities of state nodal agencies on climate change and focus sectoral departments to operationalize SAPCC implementation mechanism in water and other climate sensitive sectors. The project is being implemented in three states namely, Madhya Pradesh, Uttarakhand and Sikkim. The interventions include mobilization of appropriate expertise, capacity building of resource persons/institutions, support to strategy implementation and knowledge sharing amongst states and across other countries embarking on sub national planning for climate change. Relevant sector-specific international expertise is being made available to the state governments as required.

• State Specific Action Plans (SSAP) for Water Sector are being prepared as part of the implementation of the State Action Plan on Climate Change formulated by the States under NAPCC. The State Specific Action Plans would essentially consist of-

(a) Present situation of water resources development and management, water governance, Institutional arrangements, water related policies, cross-boundary issues, agreements etc. This would constitute the Status Report on the State/Union Territory. The document should also define problems/issues related to all the aspects of water resources specific to the State.

(b) Identifying a set of probable solutions to address the key issues/problem areas giving pros and cons of the solutions.

(c) Preparation of detailed Action Plan for each of the Strategy/activity identified in the NWM to be implemented by the State/Union Territory.

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Madhya Pradesh Vision Document, 2032

The specific targets of Madhya Pradesh Vision Document for the water sector.

Table 1: Madhya Pradesh Vision Document, 2032

Strategies Activities 2020 2024 2032

1. Comprehensive water data base in public domain and assessment of the impact of Climate Change on water resources of the State

Collection of necessary additional hydro-meteorological, hydrogeological and hydrological data and ensure availability on public domain

Development of Water Resources Information System(except the data of sensitive and classified nature, all information to be in public domain),adding Climate Change scenarios to Water Data Analysis Centre and Hydrology Info Systems

Assessment of basin wise surface water availability in present and future climate scenario including water quality

Comprehensive Reassessment of the ground water resources up to Block level

Develop, revise and update inventory of wetlands, lakes on GIS platform

Promote scientific planning of groundwater development and conservation methods

Expansion of groundwater monitoring stations

✓2. Promote accelerat-

ed pace of surface water development in the state

Accelerated Command area development, completion and renovation of canal systems, field channels and land levelling covering the entire state

Effective implementation of participatory irrigation management (PIM) Act 2006

Climate proofing of irrigation projects in areas that are sensitive to Climate Change- identification of areas and undertaking pilot projects

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3. Water conservation, augmentation and preservation with special focus on areas with over-ex-ploited conditions of ground water

Establish State Water Authority to monitor regulation, management and allocation of water for different purposes

Promotion of traditional system of water conservation by implementation of programme for repair, renovation and restoration of water storing bodies viz wetlands, lakes, well and baoli’s in areas that are sensitive to Climate Change in a mission mode approach

Expeditious implementation of programme for conservation of water through recharge of ground water including rainwater harvesting and artificial recharge in areas / situations sensitive to CC

For effective management of water involve the communities through PRI’s in rural areas and WUA’s in urban areas

Legislation for use of GW regulation & management

✓Develop a convergence based viable Panchayat / District level model using NREGA funds towards GW conservation especially in over exploited areas

4. Increase water use efficiency in irriga-tion, domestic and industrial purposes

Development of PPP Model for recycling of waste water

Undertake pilots for developing technical & financial support for common waste water treatment & recycling plants(industrial as well as urban residential colonies)

Build capacity for improvement of efficiency of urban water supply system

Promote wise water practices and harvesting techniques

✓Establish mechanism for coordinated use of surface and ground water

Development and enforcement of appropriate pricing policy for water usage in industrial, agricultural, domestic aspects

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Adopt better design practices like closed conduit, cement lined carrier canals etc

Incentivising adoption of water efficient technologies

✓Mandatory water use audit for industries and allied sectors

✓5. Promote basin level

integrated water-shed management

Review of State Water Policy in view of National Policy and National Water Mission

Developing guidelines for different uses of water particularly in context of basin-wise situations and ensuring adoption/application of these guidelines

Assess scope and implications of further inter basin connections and thus adopt integrated water resource management and encourage basin development

Enhance activities within Integrated Watershed Development and management in climate sensitive areas

Giving due attention to water scarce areas and under developed basins develop management plans for the river basins of MP

Research studies on all aspects related to impact of CC on all water resources using Climate Change water resources modelling including quality aspects of water resources with collaboration of research organizations

Mapping of areas likely to experience floods, establish hydraulic and hydrological models and developing comprehensive schemes for flood management & reservoir sedimentation

Map the deep aquifers and facilitate natural recharge of these aquifers using remote sensing

Research / pilot projects in water stressed areas to enable improved efficiency in water use and maintaining its quality in agriculture, industry and domestic sector

6. Capacity building Training of Professionals from various departments / organizations / PRI / ULBs associated with water resources development and management.

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Initiatives by the State Government

The State government has been complementing climate change adaptation in the water sector through its various schemes and programs. Some of efforts against the targeted adaptation strategies are mentioned in the table below:

Table 2: Initiatives by the State Government

State Action Plan on Climate Change(SAPCC)Strategies

Departmental Schemes & Programs

Comprehensive water data base in public domain and assessment of the impact of Climate Change on water resources of the State

National Hydrology Project National Water Mission – State Specific

Action Plan (SSAP) MP Resource Atlas scheme Grant in aid to MapIT

Promote accelerated pace of surface water development in the state

Surface Water Schemes – Major Irrigation and Minor Irrigation Accelerated Irrigation Benefit Programme

(AIBP) DRIP (Dam Rehabilitation & Improvement

Project) Command Area Development Programme

Water conservation, augmentation and preservation with special focus on areas with overexploited conditions of ground water

Atal Bhujal Yojana – National Groundwater Management Improvement Program Bundelkhand Package Conservation of Urban Water Bodies National River Conservation Programme

(NRCP) Khent Kund Yojana &Balram Talab Yojna Jal Jagaran Abhiyaan Talabo Ka Unayanikaran

Increase water use efficiency in irrigation, domestic and industrial purposes-

Subsidies and incentives introduced by the state government for efficient water use and rainwater harvesting

State Water & Sanitation Mission Balram Khet Talab Yojana Pressured Piped Irrigation Scheme Micro Irrigation - Pradhan Mantri Krishi

Sinchayee Yojana

Promote basin level integrated watershed management

National Afforestation Progamme (National Mission for a Green India) Integrated Watershed Management

Programme (IWMP)

Building Institutional mechanism for Climate Change Action Plan

State Knowledge Management Centre on Climate Change

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Self-Assessment : Climate Change-Basic

1. Are you familiar with the following terms? Please tick (✓) the words you are familiar with.

IPCC(Intergovernmental Panel on Climate Change) Global warming

Green House Effect

UNFCCC (United Nations Framework Convention on Climate Change)

Drought Renew-able energy

Adaptation Mitigation Vulnera-bility

2. One of the differences between Weather and Climate is a

(i) measure of time period (ii) its area

(iii) difference in temperature (iv)its scope

3. What is India ’s global share of total Green House Gas emission according to the Initial National Communications to the Conference of Parties of the UNFCCC,

(i) 6.4% (ii) 7.25% (iii) 10.25% (iii) 2.5%

4. Climate change affect the following

(i) Water resources (ii) Plants and animals

(iii) none of the above (iv) all of the above

5. Which of the following is not a greenhouse gas?

(i) Carbon dioxide (ii) Methane

(iii) Nitrogen (iv) Ozone

6. What do you think you can do to conserve your environment and adapt to climate change?

(i) Promote afforestation ( True/False)

(ii) Integrated Water Resources Management(IWRM) (True/False)

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Module II: -Impact Assessment-on Water Resources

Water - Too much and Too little

As a result of climate change, the distribution pattern of rainfall has changed. Some areas receive high amount of rainfall whereas some areas receive very little or no rain. Because of too much water, some area faces different problems like landslides, floods etc while with too little water the drought intensifies the problem in other parts.

Session 1: IPCC Summary on Climate Change Impacts on Water Resources

Changes from historic norms have implications for water supplies, water quality, public health and safety, and ecological functioning. Climate change will affect water resources through its impact on the quantity, variability, timing, form, and intensity of precipitation.

IPCC 5th Assessment Report (20139) summarises impacts of climate change in Asia:

• Potential impacts of climate change are likely to be substantial without further adaptation.

• Warming trends and increasing temperature extremes have been observed over the past century (high confidence).

• Water scarcity is expected to be a major issue due to increased water demand and lack of good management (medium confidence).

• Decline in productivity and threat to food security (medium confidence).

• Terrestrial systems: shifts in the phonologies, growth rates, and the distributions of plant species, (high confidence).

• Multiple stresses caused by rapid urbanization, industrialization and economic development will be compounded by climate change (high confidence).

• Extreme climate events (Increases in floods and droughts) will have an increasing impact on human health, security, livelihoods (high confidence).

Summary of the likely water cycle changes due to climate change highlighted in AR5 towards the end of the 21st century is given in the table below.

9 http://cdkn.org/wp-content/uploads/2014/04/CDKN-IPCC-Whats-in-it-for-South-Asia-AR5. pdf

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Table 3: Summary of the likely water cycle changes due to climate change

Component Key issues and impacts

Evaporation – precipitation

• Changes in evaporation exceed precipitation (less runoff and recharge) in Central North America; Central America, Northern South America, Southern Chilean Coast, Southern Africa, western Europe, the Mediter-ranean, and south-central Asia.

• Precipitation exceeds evaporation (more runoff and recharge) in the high latitudes, eastern North America, Northwest South America; Cen-tral Africa, India and east Asia.

Groundwater • Surface water recharge is strongly tied to groundwater variability in unconfined aquifers.

• Increased abstraction from population growth and reduced surface wa-ter availability could result in declining groundwater levels, particular in areas experiencing warming and precipitation deficits.

Streamflow • Significant regional variation range in run-off and stream flow. Stream flows in high-latitude rivers increase.

• Increased precipitation intensity leads to greater floods and can exac-erbate droughts as well.

Coastal zones • Increased inundation and coastal flooding causing in salinization of groundwater and estuaries.

• Changes in the timing and volume of freshwater run-off affecting salini-ty, sediment and nutrient availability.

• Changes in water quality may come as a result of the impact of sea level rise on storm-water drainage operations and sewage disposal in coastal areas.

• Changes to the zonation of plant and animal species as well as the availability of freshwater for human use as a result of salinity advancing upstream due to decreased stream flow.

Water quality • Higher water temperatures may degrade water quality. This can be made worse by presence of pollution.

• Changes in flooding and droughts may affect water quality through sediments, nutrients, dissolved organic carbon, pathogens, pesticides and salt.

• Sea level rise is projected to extend areas of salinization of groundwa-ter and estuaries.

Demand, supply and sanitation

• Climate change will likely add further stress to water service issues including: supply, demand and governance.

(Source: CGE Hands training Materials on Vulnerability and Adaptation Assessment10)

Impact of Climate Change on Water ResourcesClimate change will have a significant impact on the sustainability of water supplies in the coming decades. Climate change impacts can have significant implications to the economic and social systems, which depend on water resources. It is becoming

10 https://unfccc.int/files/national_reports/non-annex_i_natcom/application/pdf/ch_6_wa ter_resources_rev1.pdf

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more and more evident that the changes brought about by climate change have ramifications, in terms of shifts in the intensity and seasonal distribution of precipitation, warmer temperatures leading to increased evapotranspiration and an increase in the frequencies of extreme events, including droughts.

Assessment of water availability under climate change scenarios is a complex and challenging activity given the uncertainties associated with its various processes. It requires the evaluation of not only water supplies, but also of the competing water demands for socio-economic development and maintaining a healthy ecosystem. Both water supplies and water demands are subject to significant seasonal and annual variation, which is expected to be exacerbated due to climate change in a complex manner. By analysing the temporal variation of water supplies and water demands, water availability can be presented in terms of probability or in a risk-based context11.

Increase in temperature affects the hydrologic cycle directly by increasing evaporation of available surface water and vegetation transpiration. Consequently, these changes can influence precipitation amounts, timings and intensity and indirectly impact the flux and storage of water in surface and subsurface reservoirs including soil moisture and groundwater. Groundwater will be less directly and more slowly impacted by climate change, as compared to surface water in rivers and water bodies.

Climate change impacts on surface water resources can be assessed using hydrological models with various climate scenario data. Impact assessment on groundwater is more complicated and poorly understood since groundwater will be affected after prolonged droughts manifested by declining trends in groundwater levels. Groundwater resources are related to climate change through its direct interaction with surface water resources, such as lakes and rivers, and indirectly through the recharge process. Quantifying the impact of climate change on groundwater resources requires accurate estimation of groundwater recharge and its relationship with rainfall intensity.

Other associated impacts of climate change on water include water quality deterioration12.

Uncertainty AnalysisUncertainty is intrinsic to climate change. Uncertainty stems largely from limitations of existing scientific knowledge of the climate system, and of how future greenhouse gas emissions will change. Models cannot perfectly simulate all climate processes, therefore, simulations from multiple models are produced, and a multi - model ensemble mean (or median) is thought to be the most probable future climate trajectory. The spread among the individual simulations in a multi - model ensemble are an estimate of uncertainty due to imperfect model

11 Atef Kassem, Tamas Hamory, Ivana Vouk & David Harvey,(2011), Risk-based assessment of water availability in a changing climate, Risk in Water Resources Management (Proceedings of Symposium H03 held during IUGG2011 in Melbourne, Australia, July 2011) (IAHS Publ. 347, 2011).12 http://www.researchinventy.com/papers/v1i5/F015043060.pdf

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representation of climate processes and imperfect knowledge of current climate conditions that serve as a starting point for projections13.

Whenever feasible, qualitative assessments of uncertainty should be replaced with quantitative ones. At a minimum, a standard error should be attached to any estimate, along with a description of how it was calculated. Ideally, an entire probability distribution should be provided14.

The relative contribution of impact model uncertainty compared to the uncertainty in climate projections depends on several factors, including (i) the climate variable and associated characteristics governing the impact being considered (e.g. impact mainly driven by average conditions or by extreme conditions), (ii) availability and quality of data to properly constrain calibration of the impact model, and (iii) credibility of impact model for extrapolation to a changing climate15.

Tools in Water Resource Impact Assessment – Biophysical ModelsThe assessment of climate change impacts, and vulnerability and adaptation to climate change require a wide range of physical, biological, and socio-economic models, methods, tools, and data3.Water resources are very sensitive to changing climate conditions. Thus, hydrological impacts of changing climate conditions are a potential threat to human societies as they often have serious consequences for agriculture, people living near water bodies, hydropower production and ecosystems. Therefore, it is necessary to provide information on potential future changes in the hydrological cycle to enable decision makers to develop possible mitigation and adaptation strategies.

Hydrological models are applied to simulate the impact of a changing climate on the water cycle as well as to project future hydrological regimes. To drive such a model, reliable information on climatologically variables (e.g., temperature, precipitation or evapotranspiration) and on their distribution in space and time are required. Hydrological models are used after validating the model on the observations of current water availability and environmental conditions.

Climate change will affect water resources through its impact on the quantity, variability, timing, and form. Spatial and temporal impact on water resources which are important for adaptation and water resource management plans is shown in Figure 3

13 http://www.ciesin.org/documents/Downscaling_CLEARED_000.pdf14 http://nldr.library.ucar.edu/repository/assets/osgc/OSGC-000-000-019-903.pdf15 Water Resources Climate Change Guidelines (2016), DHI (https://www.dhigroup.com/ inland-water/water-resources-climate-change-guidelines)

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Figure 3: Supply Side Assessment (Impact Assessment) using a hydrological model(Source: INRM Consultants)

Climate parameters to be monitored in context to water sector

Observational datasets of temperature, precipitation, evapotranspiration, pressure, wind and humidity are commonly used to monitor and understand how the climate has changed over time and to examine the occurrence of extremes in temperature, rainfall (volume, number of rainy days, hourly rain fall, dry spell and wet spell) and heat stress. The key climate parameters used in the water sector vulnerability assessment study are given below:

Climate Indicators Units

Average annual rainfall mm

Standard deviation in annual rainfall

No. of Rainy Days Number of Days

Extremely Wet Days-Annual total rainfall when rainfall>99th percentile

mm

Consecutive Dry Days-maximum number of Consecutive Days With Rainfall Less Than 1 mm

Number of Days

Consecutive Wet Days-maximum number of Consecutive Days Number of Days

Heat Index Severity of days

Temperature Humidity Index Severity of days

Streamflow days/dec

Runoff mm/day/dec

Evaporation mm/day/dec

Soil Moisture % sat/dec

Stream Gauge Data(Automatic/Telemetric/Data logging ) MCM

Groundwater level Automatic/Telemetric/Data logging ) Trend

Yield MCM

Note: MP VA study reports provide detailed indicators used in the Impact Modelling and VA .

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Below Figure(4), shows a general framework for assessing the impacts of climate change on water resources at different spatial and temporal scale.

Terrain Digital Elevation

Model, slope, Aspect

Landuse Agriculture, Forest, Urban, Water bodies

etc.

Soil Loamy, Sandy loam,

Clayey etc.

Observed Weather Daily: Rainfall, Temperature,

Relative humidity, Solar radiation,

Wind speed

Inputs

Impact Assessment on Water Resources

Calibrated

Hydrological Model

Water Yield Evapo-transpiration

Groundwater recharge Soil moisture Stream flow

Outputs

Subbasin (watersheds)

Daily Seasonal

Space - Time

AGGREGAT I ON

District State

Avg Annual Avg Monthly

Area weighted average – GIS overlay analysis

Projected Water Availability and Impacts

Climate Change Scenario

IPCC Scenarios Baseline, Mid, End

century Daily: Rainfall,

Temperature, Relative humidity, Solar

radiation, Wind speed

CALIBRATION Observed Stream flow, GW levels,

crop yield

Water Yield – Water availability

Evapotranspiration – Crop Water Demand

Weekly Soil moisture- Agricultural Drought

Stream flow – Flood magnitude, Flow dependability

Output Analysis

Ground water fluctuation

Figure 4: Framework to assess the impact of climate change on water resources(Source: INRM Consultants)

Selection of Impact Models for Water SectorImpact model selection mainly depends on the objective, spatial and temporal resolution and scope of the model system. Some basic consideration which can be kept in mind include, low cost and capacity needed to run and interpret the model, range of natural processes they cover, the ability to operate at a range of spatial scales, ease to interpret and apply the results, ability to be deployed on PC, availability of extensive documentation, ease of use, availability of model in public domain, access to source code, technical support and user groups.

Models which are available for water resources assessment, planning and management can be divided into two broad categories:

• Models that aim to simulate physical hydrologic processes within a river basin/catchment (advantage of using a basin wide hydrological model would help in Integrated Water Resource Management (IWRM). IWRM is a planning and

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management framework that considers a range of supply-side and demand-side water resources processes and actions, and incorporates stakeholder participation in decision-making). These models use mathematical constructs of the hydrologic cycle to make estimates of catchment runoff, stream flow, groundwater recharge, flood levels, etc., based upon input parameters including catchment characteristics and meteorological data. These models typically require a significant amount of observed data in order to achieve adequate model calibration and validation.

• Water management models include those that represent the temporal and spatial availability of water between different and often competing uses, within and across river basins and/or politically defined areas. These models include representations of important water infrastructure such as reservoirs, diversions, pipelines, demand centers, etc.

Table 44 gives a list of relevant and probable hydrological models useful for surface water assessment.

Table 4: List of Probable Hydrological, Hydraulic and Water System Models

Model Source Licens-ing and training

Description Link

List of Probable Hydrological Models

SWAT (hydrol-ogy)

US Ag-riculture Depart-ment (USDA)

Free SWAT (Soil and Water Assessment Tool) is a river basin scale model designed to quantify the impact of land management practices in large complex watersheds.

http://swatmod-el.tamu.edu/

HEC-HMS (hydrology) HEC-RAS (hydraulics)

US Army Corps of Engi-neers

Free The Suite of HEC (Hydrologic Engineering Centre-Hydrologic Modelling System) models are designed to perform a multitude of water resource tasks, including precipitation – run-off process of dendritic watershed systems; to quantify one-dimensional steady flow, unsteady flow, sediment; simulate reservoir operations at one or more reservoirs.

http://www.hec.usace.army.mil/software/hec-hms/

MIKE-SHE,(hy-drology) MIKE11/21(hy-draulics)

Danish Hydraulic Institute (DHI)

License required

MIKE-SHE is an integrated hydrological modelling system that simulates water flow in the land-based phase of the hydrological cycle. M11 is a hydrodynamic model.

http://mikebydhi.com/Products

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Delft3D (hydraulic)

Deltares License required

Delt3D is a three-dimensional model designed to investigate hydrodynamics, sediment transport and morphology and water quality for fluvial, estuarine and coastal environments.

http://www.deltaressystems.com/hydro

Variable Infiltration Capacity (VIC) Macroscale Hydrologic Model

University of Wash-ington

Open source

The Variable Infiltration Capacity (VIC) model is a semi-distributed grid-based macroscale hydrology model which solves for full water and energy balances.

http://www.hy-dro.washington.edu/Lettenmai-er/Models/VIC/SourceCode/Download.shtml

Strom Water Management Modelling (SWMM)

The Unit-ed States Environ-mental Pro-tection Agency (EPA)

Open source

SWMM is a dynamic hydrology-hydraulic water quality simulation model. It is used for single event or long-term (continuous) simulation of runoff quantity and quality from primarily urban areas. The runoff component operates on a collection of sub-catchment areas that receive precipitation and generate runoff and pollutant loads. The routing portion transports this runoff through a system of pipes, channels, storage/treatment devices, pumps, and regulators.

https://www.epa.gov/water-re-search/storm-wa-ter-manage-ment-mod-el-swmm

WaterGAP Global Hydrology Model WGHM

WGHM computes time-series of fast-surface and subsurface runoff, groundwater recharge and river discharge as well as storage variations of water in canopy, snow, soil, groundwater, lakes, wetlands and rivers. Thus it quantifies the total renewable water resources as well as the renewable groundwater resources of a grid cell, river basin.

https://www.uni-frankfurt.de/45218063/WaterGAP

List of Probable Ground Water Models

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MODFLOW U.S. Geo-logical Survey

Open source software devel-oped by the USGS

based on a block-centred finite difference algorithm. Relies on a large number of modular packages that add specific capabilities. Most packages are also open source and can therefore be modified by end users. Can be coupled to MT3DMS and other codes to simulate solute transport, as well as MIKE 11 for flow in river and stream networks.

https://water.usgs.gov/ogw/modflow/MOD-FLOW.html

FEFLOW Danish Hydraulic Institute (DHI)

License required

FEFLOW (Finite Element subsurface FLOW system) is a computer program for simulating groundwater flow, mass transfer and heat transfer in porous media and fractured media. The program uses finite element analysis to solve the groundwater flow equation of both saturated and unsaturated conditions as well as mass and heat trans-port, including fluid density effects and chemical kinetics for multi-component reaction systems.

https://www.mikepoweredby-dhi.com/prod-ucts/feflow

GMS Aquaveo, USA

License required

GMS (Groundwater Modeling System) is a complete pro-gram for building and simu-lating groundwater models. It features 2D and 3D geosta-tistics, stratigraphic modeling and a unique conceptual model approach. Currently supported models include MODFLOW, MODPATH, MT3DMS, RT3D, FEMWATER, SEEP2D, and UTEXAS.

h t t p s : / / w w w .aquaveo.com/s o f t w a r e /g m s - g r o u n d -w a t e r - m o d e l -ing-system-intro-duction

PMWIN Simcore Software

Open source software

Processing Modflow 5.3.3 (Freeware

developed by the USGS, based on a block-centred finite difference algorithm. Relies on a large number of modular packages that add specific capabilities. Most packages are also open source and can therefore be modified by end users. Can be coupled to MT3DMS and other codes to simulate solute transport, as well as MIKE 11 for flow in river and stream networks.

http://www.pm-win.net/index.htm, http://www.simcore.com/pm53

List of Water Resources Planning Model

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RIBASIM (w) Deltares License required

RIBASIM (w) http://www.deltaressystems.com

WEAP21 Stock-holm Environ-ment Institute (SEI)

Free to devel-oping counties

WEAP21 (b) Stockholm Envi-ronment Institute (SEI)

Session 2 : SWAT Model Overview and ApplicationsThe Soil and Water Assessment Tool (SWAT) model (Arnold et al., 199816, Neitsch et al., 200217) is a distributed parameter and continuous time simulation model. The SWAT model has been developed to predict the hydrological response of un-gauged catchments to natural inputs as well as the manmade interventions. Water and sediment yields can be assessed as well as water quality. The model (a) is physically based; (b) uses readily available inputs; (c) is computationally efficient to operate and (d) is continuous time and capable of simulating long periods for computing the effects of management changes. The major advantage of the SWAT model is that unlike the other conventional conceptual simulation models it does not require much calibration and therefore can be used on un-gauged watersheds (in fact the usual situation).The SWAT model is a long-term, continuous model for watershed simulation. It operates on a daily time step and is designed to predict the impact of land management practices on water, sediment, and agricultural chemical yields. The model is physically based, computationally efficient, and capable of simulating a high level of spatial details by allowing the watershed to be divided into a large number of sub-watersheds. Major model components include weather, hydrology, soil temperature, plant growth, nutrients, pesticides, and land management. The model has been validated for several watersheds.

16 Arnold, J. G., R. Srinivasan, R. S. Muttiah, and J. R. Williams. 1998. Large-area hydrologic modelling and assessment: Part I. Model development. J. American Water Res. Assoc. 34(1): 73-8917 Neitsch, S. L., J. G. Arnold, J. R. Kiniry, J. R. Williams, and K. W. King. 2002a. Soil and Water Assessment Tool - Theoretical Documentation (version 2000). Temple, Texas: Grass land, Soil and Water Research Laboratory, Agricultural Research Service, Blackl and Re search Center, Texas Agricultural Experiment Station.

The Soil and Water Assessment Tool (SWAT) is a pubic domain watershed mod-el jointly developed by USDA Agricultural Research Service (USDA-ARS) and Texas A&M AgriLife Research, part of The Texas A&M University System. The main strength of the SWAT model lies in its analytical capability useful for planners, managers, researchers, and strategist to predict and evaluate climate change effects on various management options on water, nutrients, sediments and pesticide loads at water-shed and basin scale. The SWAT is a wide-ly-used, continuous, and daily time-step watershed scale model.

(http://swatmodel.tamu.edu)

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SWAT Model output - Water Balance Components for Madhya Pradesh during Northeast Monsoon

Figure 5: Distribution of changes in Water Balance Components for Madhya Pradesh during Northeast Monsoon(Source: INRM Consultants)

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Session 3: Hands-on SWAT Model

Part 1: Orientation and preparation of input data sets

Data Sources for SWAT • Introduction to QSWAT/ArcGIS interface (GIS) • Watershed delineation • Landuse and soil overlay • HRU delineation • Weather and other inputs for the model (including point sources)

Part 2: Model Run and interpretation of outputs

• Run SWAT simulation using QSWAT/ArcGIS interface• Visualization and interpretation of Q SWAT outputs • Introduction of calibration and validation techniques • Address user questions and clarify anything covered in the

training

Group Activity • Divide participants into four groups and provide laptops preloaded with QGIS, SWAT and sample data sets for the SWAT Modelling

• Guide Participants through SWAT modelling videos• Feedback

Data requirementsTerrain, land use, soil, daily weather data (rainfall, maximum and minimum temperature, relative humidity and wind speed), cropping pattern, reservoirs and any man made structure with their characteristics.

Model OutputsThe outputs provided by the model are very exhaustive covering all the components of water balance spatially and temporally. The sub components of the water balance that are more significant and were used for analyses include:

• Precipitation

• Total flow (Water yield) consisting of surface runoff, lateral and base flow

• Actual evapotranspiration (Actual ET)

• Base flow

• Ground water recharge

LimitationsResolution of the input data (spatial detail required to correctly simulate environmental processes), SWAT does not simulate detailed event-based flood.

Data Sources

The Data and Information base

To assess the impacts, vulnerability and effective adaptation planning and mitigation measures, large range of data and information is required. There is no organization, agency or group that is singularly responsible for responding and

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adapting to climate change. Some of the important data requirement along with sources of these data has been given in the following paragraphs.

Data sources for water resources impact and vulnerability assessmentData and Information required both Climatic and Non-climatic is shown in Figure 6

Figure 6: Data and Information Needs(Source: INRM Consultants)

Terrain - Digital Elevation Model - DEM Administrative Maps• SRTM 30 m

o https://earthexplorer.usgs.gov/

o SRTM 1 Arc-Second Global elevation data offer worldwide coverage of void filled data at a resolution of 1 arc-sec-ond (30 meters)

• Indian Satellites: NRSC, Bhuvan

o Cartosat 1

• Global Administrative Areas

o Upto Block Levels

o The current version is 2.0 (Janu-ary 2012)

o http://www.gadm.org/

o Public domain (free)

• Registrar General – Census

o Hard copy

o Upto Villages

Satellite Imageries Landuse Land Cover

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• Landsat images

o USGS Archive: http://glovis.usgs.gov or http://earthexplorer.usgs.gov

o University of Maryland Global Land Cover Facility: http://glcf.umiacs.umd.edu/index.shtml

o Resolution 23.5 m

o Snapshots: 1980, 1990, 2000

• Modis (Terra and Aqua)

o GeoTIFF file

o Resolution: 2km,1km, 500m, 250m

o http://rapidfire.sci.gsfc.nasa.gov/subsets/

o The Moderate Resolution Imaging Spectroradiometer (MODIS) is a low-to-moderate resolution multi-spectral imaging system currently in operation aboard two NASA satellites, Terra and Aqua. Both satellites are acquiring imagery on a continuous basis, and NASA has created a website that allows access to near-real time georeferenced imagery from both satellites, as well as archived imagery from previous days

• Indian Satellites: NRSC

o Satellites: IRS-P3, IRS-P6, IRS-P5, IRS-P4, IRS-1D, IRS-1C

o Sensors and Resolution

o AWiFS: 56 m

o LISS III : 24 m

o LISS-4: 5m (IRSP6)

o PAN: 5m (IRS 1C/1D)

o Cartosat 2: 1m

o Cartosat 1: 2.5 m

• NRSC

o 2011-12

o National at 1:50,000

• IWMI

o Global Map of Land Use/Land Cover Areas (GMLULCA)

o IWMI’s Global Map of Irrigated Areas (GMIA) (Thenkabail, P.S., C.M. Biradar, H. Turral, P. Noojipady, Y.J. Li, J. Vithanage, V. Dheeravath, M. Velpuri, M. Schull, X.L. Cai, and R. Dutta, 2006. An Irrigated Area Map of the World (1999) derived from Remote Sensing, Research Report # 105, International Water Management Institute, Colombo, Sri Lanka [http://www.iwmigiam.org].)

o Source: http://www.iwmigiam.org/info/main/index.asp

• FAO

o Global Map of Irrigation Areas - version 4.0.1

o Resolution: 5 arc minute cells

o http://www.fao.org/nr/water/aquastat/irrigationmap/index10.stm

• FAO Global soil

o Source: http://www.lib.berkeley.edu/EART/fao.html

o 1:5M (50 km)

o Citation FAO/IIASA/ISRIC/ISSCAS/JRC, 2009. Harmonized World Soil Database (version 1.1). FAO, Rome, Italy and IIASA, Laxenburg, Austria.

• NBSSLUP

o 1:500,000

o http://nbsslup.nic.in/

Weather Observed River Discharge

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• IMD Regridded data

o Rainfall: daily, 0.25 deg X 0.25 deg, 0.5 deg X 0.5 deg

o Temperature: Daily 1 deg X 1 deg

o 1901-2016, 1951-2016

• IMD District Weather Forecast

o KNMI Climate Explorer: climate data and analysis tools (daily, Monthly

o http://climexp.knmi.nl/start.cgi?someone@somewhere

• Daily Global Historical Climatology Network (GHCN-DAILY) Version 2.1

o Actual observed up 1970

o http://www1.ncdc.noaa.gov/pub/data/ghcn/daily/

o http://iridl.ldeo.columbia.edu/SOURCES/.NOAA/.NCDC/.DAILY/.GLOBALSOD/

• Global River Discharge Database

o Monthly average discharge in cubic meters/sec

o station-specific, ranging from 1807 to 1991

o http://www.rivdis.sr.unh.edu/maps/

• CWC: Indian Non-Classified Rivers

o Dams and project details: National Register of Large Dams – 2014, http://india-wris.nrsc.gov.in/wrpapp.html

o hydrological observation parameters as gauge (river water level), discharge (amount of water released from a cross section in the river in a given time period) and sediment (Concentration of solid particles in water) observing stations of CWC (Central Water Commission)

India WRIS, http://india-wris.nrsc.gov.in/HydroObservationStationApp.html

Frequency: Daily from 1964-2015

Climate Change Scenarios Socio-economic & Agriculture

• CMIP5 - Coupled Model Inter-compari-son Project

o The Earth System Grid Federation (ESGF)

o https://esgf-node.llnl.gov/projects/esgf-llnl/

• CORDEX - Coordinated Regional cli-mate Downscaling Experiment

o http://cccr.tropmet.res.in/cordex/

o Pre registration (free)

o Resolution 50 km X 50 km

o All major parameters

• Registrar General & Census Commissioner, India: Primary Census Abstract (PCA)

• District Census Handbook, An-nual health survey

• Planning Commission, Govern-ment of India

• The Department of Animal Hus-bandry and Dairying (AH&D), Livestock census

• Directorate of Economics and Statistics, Ministry Of Agriculture

• http://dacnet.nic.in : Crop Yield, irrigation, fertilizer

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Self-Assessment Quiz: Impact Assessment

1. What are the impacts of Climate Change on Water Resources?a. Increased Floods (True or False)b. Increased Droughts (True or False)c. Variation in Rainfall Distribution (True or False)

2. Which are the key Climate parameters to be monitored for Climate Change Impact Assessment?

a. Number of rain days (True or False)b. Hourly Rainfall(True or False)c. Temperature (True or False)

3. Complete the Sentence: “The biophysical models use mathematical constructs of the hydrologic cycle to make estimates of ____________________________________________”

4. Match the following:

Component Match Impact

Coastal zones A I Crop water requirement

Demand B II Salinity

Evaporation C III Floods

Groundwater D IV Service issues

Stream flow E V Declining levels

5. What are the criteria for the selection of the Impact Models for Water Sector?a. Objective and scope of the model systemb. spatial c. temporal resolution d. all

6. Which impact model is suitable for the simulation of runoff quantity and quality for the urban areas?

a. SWMM b. SWAT c. Mike Hydrod. all

7. List few models for the modelling of supply and demand side management solutions.

a. SWAT (True or False)b. Mike Hydro (True or False)

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Module III: Vulnerability Assessment

Session 1: Vulnerability Assessment-General

The Intergovernmental Panel on Climate Change (IPCC) is the leading scientific international body for the assessment of climate change. According to the IPCC (2007)18 definition, vulnerability in the context of climate change is the degree to which a system is susceptible to, and unable to cope with, adverse effects of climate change, including climate variability and extremes. Vulnerability is a function of the character, magnitude, and rate of climate change and variation to which a system is exposed, its sensitivity, and its adaptive capacity.

The IPCC has modified their definition of vulnerability in AR5 by moving to a risk-based conceptual framework (Figure7). IPCC Fifth Assessment Report defines vulnerability to climate change broadly as: “the propensity or predisposition to be adversely affected. Vulnerability encompasses a variety of concepts including sensitivity or susceptibility to harm and lack of capacity to cope and adapt”.19

Figure 7: Conceptualization of risk by the IPCC. (Source: IPCC (2014) AR5, WG-II, Ch. 19)

Risk of climate-related impacts results from the interaction of climate-related hazards (including hazardous events and trends) with the vulnerability and exposure of human and natural systems. Changes in both the climate system (left) and socioeconomic processes including adaptation and mitigation (right) are drivers of hazards, exposure, and vulnerability.20

18 IPCC, 2007. Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Annex I., M.L. Parry, O.F. Canziani, J.P. Palutik of, P.J. van der Linden and C.E. Hanson, Eds., Cambridge University Press, Cambridge, UK, 976pp.19 https://www.ipcc.ch/pdf/assessment-report/ar5/syr/AR5_SYR_FINAL_Glossary.pdf20 Emergent Risks and Key Vulnerabilities - IPCChttps://www.ipcc.ch/pdf/assessment-report/ar5/ wg2/WGIIAR5-Chap19_FINAL.pdf

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While AR4 uses the concepts of sensitivity and adaptive capacity to describe the moderating attributes of the system, AR5 uses the concept of exposure (the presence of a system in places that could be adversely affected) and vulnerability (predisposition to be adversely affected). The terms ‘exposure’ and ‘vulnerability’ are used differently in AR4 and AR5. There are still many inconsistencies and ambiguities in the AR5 concept when it comes to practical application. It adopts the DRR concept which is designed for individual, well-defined events (hazards) which usually affect well-defined areas and elements (exposure) and can be statistically expressed as a probability (risk). However, climate change deals with long term trends which affect the entire globe with graduated spatial differences, without statistical probability.21

Currently, concepts of IPCC AR4 are better-established than the new AR5 concepts which lack clarity for operationalization.22

Climate vulnerability is characterized as a function of both biophysical and socio-economic vulnerabilities, each defined by the three dimensions of exposure, sensitivity and adaptive capacity. When combined with specific likelihood of occurrence (either associated with biophysical changes or socio-economic variables), climate vulnerability becomes climate risk (Preston and Stafford-Smith,200923 ).

Purpose of Vulnerability AssessmentVulnerability assessments can play a vital role in the design of appropriate adaptation and mitigation policies targeted towards climate changeAssessment of vulnerability to climate variability and change broadly helps in:

• Understanding and analyzing current vulnerability.

• Identifying and analyzing potential future vulnerabilities and forming a linkage between the present and future responses.

• Temporal and spatial comparison of vulnerability of different biophysical and socioeconomic systems.

• Identify the factors that render some regions/districts more vulnerable than others (hotspots).

• Inform and facilitate the decision-making process to prioritize and formulate appropriate adaptation strategies.

• Selection of appropriate adaptation strategies and practices.

Vulnerability Assessment MethodologyVulnerability assessments help in identifying current and potential hotspots, identifying entry points for intervention and tracking changes in vulnerability and monitoring and evaluation of adaptation21. Figure 8 gives key attributes of vulnerability assessment.

21 The Vulnerability Sourcebook Concept and guidelines for standardised vulnerability assess-ments (2014), the Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ), http://www.prevention-web.net/files/38849_38849vulnerabilitysourcebookguideli.pdf22 http://www.resin-cities.eu/resources/design-ivavia/23 Preston, B.L. & Stafford-Smith, M. 2009. Framing vulnerability and adaptive capacity assessment: Discussion paper. CSIRO Climate Adaptation Flagship Working Paper, No.1, CSIRO, Australia.

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Figure 8: Attributes of vulnerability assessments

There are several methods for evaluating the level of vulnerability. Selection of a particular method is determined by the context, purpose and scale of analysis as well as by the availability of appropriate data. A common method to quantify vulnerability to climate change is by using a set or composite of proxy indicators. Indicator approach constructs comparative indicators which helps to compare the vulnerability and adaptive capacity of different systems, groups

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or regions (Adger, W.N. et al., 200424 ).

The vulnerability studies based on ranking and comparing across regions, countries, and populations have increased in number during the past decade. The main objective of these kinds of studies is the allocation of resources for vulnerability reduction by including decision making authorities like government bodies and other organizations (Dinda, Soumyananda, 201525 ).

Composite index provide a starting point for analysis. While it can be used as summary index to guide policy work, it can also be decomposed such that the contribution of subcomponents and individual indices can be identified (OECD, 200826 ). De-constructing composite indicators can help extend the analysis to Identify the factors. Composite index is getting increasingly acknowledged as a tool for summarizing complex and multidimensional issues (Rovan, 201127 ). How the concepts of exposure, sensitivity, adaptive capacity, and vulnerability has been translated into numerical indices; which variables have been used and how they have been aggregated to construct Composite Vulnerability Indices (CVI) has been described in later section.

Limitations of Indicator Base MethodIndicator based assessment for ranking and comparing vulnerability across spatial units (districts)have following challenges and limitations mainly because of subjectivity involved in:• Selection and creation of appropriate indicators.

• Classification of indicators into exposure, sensitivity and adaptive capacity.

• Underlying assumptions in weighting variables.

• Dynamic nature of vulnerability which requires a constant updating of vulnerability scores.

Steps to Construct Vulnerability IndexQuantitative assessment of vulnerability is generally done by constructing a “vulnerability index” and is based on identified set of indicators which contribute to vulnerability. As discussed earlier vulnerability index is a single number, which can be used to compare different regions.Selection of appropriate spatial units, time period and relevant sectors is important before carrying out quantitative vulnerability assessment.

The steps involved in the vulnerability assessment based on IPCC AR4 concepts are:

24 Adger, W.N., Brooks, N., Bentham, G., Agnew, M., Eriksen, S., 2004. New Indicators of Vulnerabil-ity and Adaptive Capacity. Technical Report 7, Tyndall Centre for Climate Change Research, University of East Anglia, Norwich.25 Dinda, Soumyananda, 2015, Handbook of Research on Climate Change Impact on Health and Environmental Sustainability, IGI Global26 OECD. 2008. Handbook on constructing composite indicators: methodology and user guide. Paris, OECD Publishing.27 Rovan, Joze, 2011, “Composite Indicators”,”International Encyclopedia of Statistical Science”, Springer Berlin Heidelberg

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• Step 1: Identify set of indicators.

• Step 2: To classify indicators data (indicators) into three categories of adaptive capacity, sensitivity and exposure.

• Step 3: Secondary data collection for the indicators, projection of the selected indicators for future using impact assessment models (water resource, forest, agriculture, energy etc.).

• Step 4: Data cleaning and quality checking.

• Step 5: Normalize indicators data values to make the indicators comparable since indicators are expressed in a variety of statistical units, ranges or scales.

• Step 6: Determine unbiased weights using statistical method of multivariate analysis (Principal component analysis, PCA).

• Step 7: Aggregation of weights and normalized values to derive Composite Vulnerability Index.

• Step 8: Rank districts based on the calculated index values. Rank 1: least vulnerable (Lowest index values), Highest rank most vulnerable (Highest index values).

• Step 9: Perform cluster analysis28

on the calculated indices to group them in six vulnerable categories - very low (VL), low (L), moderate (M), high (H), very high (VH), and extremely high (EH).

• Step 10: Visualization of the results using spatial maps.

A short description of these steps is given in the following paragraphs. Appendix II gives details of the steps involved in computation of vulnerability index.

Selection of IndicatorsIndicators should be selected on the basis of their analytical soundness, measurability, spatial coverage, relevance to the phenomenon being measured and relationship to each other (OECD,200829). The indicators can be selected based on the availability of data across time and space existing literature research, consultation with domain experts and experiences drawn from previously carried out studies or research.

Identification of functional relationshipIt is important to identify functional relationship between the indicators and vulnerability before starting the analysis. Two possible functional relationships include (a) vulnerability increases with increase in value of the indicator (higher standard deviation in rainfall means less dependable rainfall leading to increase in vulnerability) (b) vulnerability decreases with increase in value of the indicator (higher literacy rate means better understanding and ability to process risk information/warning messages, enhances the acquisition of knowledge).

28 Cluster analysis helps to sort through the raw data and groups them into clusters. A cluster is a group of relatively homogeneous cases.29 OECD, European Commission, Joint Research Centre (2008) Handbook on constructing composite indicators: methodology and user guide. OECD Publishing.

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NormalizationIndicators values are measured in different units and scales. They have to be rendered unit less in order to aggregate them to obtain composite index. The indicators are normalised to make them free from the units and also to standardize their values so that they all lie between 0 and 1. A number of normalisation methods exist30, Min-Max method is the most popular method which normalises indicators to have an identical range [0, 1] by subtracting the minimum value and dividing by the range of the indicator values. It is important to consider the functional relationship while normalising the indicators. Appropriate normalization formula should be applied based on functional relationship of the indicator with vulnerability.

Weighting and AggregationThe literature covers many different weighting techniques (OECD 200826). They range from equal weights (simple average) to sophisticated statistical procedures. Some of the methods include; equal weighting (EW), principal components analysis (PCA), factor analysis (FA), budget allocation (BAP) and analytical hierarchy process (AHP). Alternatively, participatory methods that incorporate various stakeholders can be used to assign weights. Applying different weighting methods result in diversity in the weights which will influence the value of the composite index.

Similarly for aggregating individual indicators into composite indicators literature covers many methods. Some of the aggregation method includes, additive aggregation, geometric aggregation and Non-compensatory multi-criteria approach (MCA).

Weighted arithmetic aggregation is a common, simple and transparent aggregation procedure. Individual indicators are multiplied by their weights, summed and subsequently divided by the sum of their weights to calculate the composite indicator (CI) of a vulnerability component21. For meaningful aggregation results, all indicators should be aligned in the same way (a low score represents a ‘low’ value and a high score a ‘high’ value in terms of vulnerability).

VisualizationOutcome of Vulnerability assessments can be visualized in many ways using maps or charts. Vulnerability maps are generated using GIS. These maps can be supported by bar graphs, line graphs, radar chart, pie chart etc.Example of such visualization can be seen under Madhya Pradesh State Knowledge Management Centre on Climate Change (SKMCCC) and the climate change knowledge management portal, (http://www.climatechange.mp.gov.in/en/vulnerability-dashboard).

Interpretation of Findings of Vulnerability AssessmentIllustrations attract the reader’s attention and foster the comprehensibility of texts. Maps, diagrams and graphs are valuable and compelling tools for illustrating

30 Freudenberg, M. (2003): Composite Indicators of Country Performance: A Critical Assess-ment. OECD Science, Technology and Industry Working Papers , 2003/16 . Paris: OECD Publishing.

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assessment findings. These elements represent high-level views of data, and while there is a danger of misinterpretation, when used with a sufficient description and/or legend in the context of a detailed report, they can aid understanding of outcomes.

Session 2: Group Exercise on the Vulnerability Assessment

Process:

A. Divide participants into groups namely, water, agriculture and adaptation

B. Provide VA raw data on Agriculture, water to the respective groups (Refer Annexure i), chart paper and sketch pens to the groups

C. Groups need to conduct Normalisation of indicators, Calculation of indicator Weightages and Projected Vulnerability Category w.r.t. Baseline

D. Guiding Questions

a. Normalisation of indicators using functional relationships

b. Calculation of indicator Weightages using different statistical methods (Equal, Unequal and Judgemental)

c. Projected Vulnerability Category w.r.t. Baseline using statistical methods(cluster analysis

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Self-Assessment Quiz: Vulnerability Assessment1. What is the definition of Vulnerability as per IPCC?

2. Do you know following terms ?

a. Adaptive capacity (Yes or No)

b. Sensitivity (Yes or No)

c. Exposure (Yes or No)

3. Briefly explain the purpose of conducting Vulnerability Assessment?

a. Adaptation Planning (Yes or No)

b. Reduce Exposure to CC negative impacts(Yes or No)

Number the Steps for Constructing Vulnerability Index from 1 to 9

Visualization of the results using spatial maps Step -

Secondary data collection Step -

Rank districts Step -

Principal component analysis, PCA Step -

Normalization Step -

Identify set of indicators Step -

Derive Composite Vulnerability Index Step -

Cluster analysis Step -

Classify into three categories of adaptive capacity, sensitivity and exposure

Step -

4. Where do you source the following data requirements

a. Land Use Land Cover Change(LULUC) (I) Bhuvan (II) Earth Explorer

b. DEMS(I) Bhuvan-NRSC (II) Earth Explorer/USGS-SRTM

c. Soil maps and associated soil characteristics–(I) Bhuvan (II) Soil Survey of India (III)FAO Global soil

d. Weather Information

•Historic (i) IMD (II) WRD

• Projected(i) CORDEX (ii) IITM(III) CMIP5

5. Which of the following functional relationship is possible between vulnerability and selected indicators?

a. Vulnerability increases with increase in value of the indicator

b. Vulnerability decreases with increase in value of the indicator

c. Both (a) & (b)

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Module IV: General Adaptation Options in Water Sector

Session 1: Adaptation- Water Resources With the changing hydrological cycle, it is important to strengthen ability to cope up to these changes through adaptation for sustainable development.For managed watersheds, a list of potential adaptations to climate change is presented. These include both physical modifications to the watershed, and management options. These are supply-side adaptations.

Examples of Adaptation – Water Supply Examples of Adaptation – Water Demand

Construction/modification of physical infrastructure: (Hard adaptation).

• Canal linings

• Closed conduits instead of open channels

• Integrating separate reservoirs into a single system

• Reservoirs/hydro-plants/delivery systems

• Raising dam wall height

• Increasing canal size

• Removing sediment from reservoirs for more storage

• Inter-basin water transfers

Adaptive management of existing water supply systems: (soft adaptation).

• Change operating rules

• Use conjunctive surface/groundwater supply

• Physically integrate reservoir opera-tion system

• Co-ordinate supply/demand

Policy, conservation, efficiency, and technol-ogy.

• Domestic:

• Municipal and in-home re-use

• Leak repair

• Rainwater collection for non-potable uses

• Low flow appliances

• Dual supply systems (potable and non-po-table)

• Conservation programs

Agricultural• Irrigation timing and efficiency

• Lining of canals, closed conduits

• Drainage re-use, use of wastewater effluent

• High value/low water use crops

• Drip, micro-spray, low-energy, precision application irrigation systems

• Salt-tolerant crops that can use drain water

Industrial• Water re-use and recycling

• Closed cycle and/or air cooling

• More efficient hydropower turbines

• Cooling ponds, wet towers and dry towers

• Energy (hydropower).

• Reservoir re-operation

• Cogeneration (beneficial use of waste heat)

• Additional reservoirs and hydropower stations

• Low head run of the river hydropower

• Market/price-driven transfers to other activities

• Using water price to shift water use between sectors

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Extract from Climate Change Adaptation Technologies for Water - UN Environment

UN Environment – DHI Centre, Climate Technology Centre and Network (CTCN) and the UNEP DTU Partnership has published a new resource, Climate Change Adaptation Technologies for Water: A practitioner’s guide to adaptation technologies for increased water sector resilience.

Figure 9, taken from the UN Environment publication: gives an overview of challenges and responses faced in changing hydrological regime.

(Source UN Environment-DHI Centre31)Figure 9: Climate change adaptation and water – overview of

challenges and responses

A practitioner’s guide to adaptation technologies for increased water sector resilience has been developed based on six current climate-related water challenges as an entry point to identifying relevant adaptation responses, followed by identification of the specific water adaptation technologies relevant for each response.

This publication provides a comprehensive overview of specific water technologies and techniques that address challenges resulting from climate change, with the aim of helping to build adaptive capacity. The important

31 Climate Change Adaptation Technologies for Water: A practitioner’s guide to adaptation technologies for increased water sector resilience.(2017), UN Environment-DHI Centre, Climate Tech-nology Centre and Network (CTCN) and the UNEP DTU Partnership. https://www.dhigroup.com/global/news/2017/11/launched-climate-change-adaptation-technologies-for-water

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Fig

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Fig

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feature of this guide is the water climate change adaptation technology taxonomy (Figure 10 ) developed for systematising the most pressing climate change challenges in the water sector, along with their corresponding water adaptation technologies.

Further, this guide explores and explain each of the areas of water adaptation challenges, as well as their respective adaptation response options, in more detail. For each possible response to an adaptation challenge, a number of specific adaptation technologies are introduced (Figure 11).

This guide provides information on 102 water adaptation technologies and a short technology brief has also been developed for each of the technologies.

The focus of this guide is adaptation technologies relevant to ensuring a sustainable supply of clean and sufficient water, as well as management of water related disasters. It also includes an introduction on several approaches to selecting and prioritising adaptation technologies that are appropriate for the stakeholder.

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Session 2: Group Exercise on the Adaptation Planning

Process:

A. Divide participants into groups namely, water, agriculture and adaptation

B. Provide sectoral briefs, VA matrix on Agriculture, water to the respective groups (Refer Annexure III), chart paper and sketch pens to the groups

C. Groups need to formulate adaptation options based on the sectoral briefs and VA matrix

D. Guiding Questions

a. Identify Vulnerable Areas -Baseline vs Future

b. Climate Risks using impact modelling outputs

c. Identify Adaptation Options

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Self-Assessment Quiz: Adaptation Options in Water Sector

1. List major supply side interventions for the climate change adaptation in the areas with groundwater over-exploitation?

a. Recharge shafts

b. Surface Dykes

c. Check Dams

2. List major supply side &demand side interventions for the climate change adaptation in managed watersheds?

a. Micro Sprinklers

b. Conjunctive water use

3. How VA data will help in designing adaptation planning?

a. Geographic prioritizing

b. Funding allocation

c. Selection of Adaptation options

4. List innovative technologies learned from Climate Change Adaptation Technologies for Water: A practitioner’s guide?

a. Baseline level modelling and flood forecasting

b. Inter linking of rivers

5. Briefly explain the role of community in adaptation planning for water resources.

a. Promote afforestation

b. Watershed Management

6. Share few experiences (if any) of adaptation planning for water sector in your respective states.

a. Participatory groundwater management

b. Decision Support Systems

c. Balram khet Talab Yojana

d. IWMP

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Appendix I- Some Relevant Model Description

The Hydrologic Modelling System (HEC-HMS) - Surface Water ModelHEC-HMS (Fleming and Neary, 200432) is a classical conceptual semi-distributed rainfall-runoff model. It uses the soil moisture accounting (SMA) algorithm for runoff generation, the Clark Unit Hydrograph for the transformation of direct runoff, two linear reservoirs to consider interflow and base flow transformation and the kinematic wave for river routing. Potential evapotranspiration is estimated using the Priestley-Taylor method.

Data requirementsTerrain, land use, soil, daily weather data (rainfall, maximum and minimum temperature, relative humidity and wind speed), cropping pattern, reservoirs and any man-made structure with their characteristics.

Model Outputs• Precipitation• Total flow (Water yield) consisting of surface runoff, lateral and base flow

• Potential evapotranspiration (PET)

• Base flow

• Ground water recharge

LimitationsCannot model branching or looping stream networks, cannot model backwater in the stream network, supplemental tool HEC-GeoHMS requires ArcGIS with the Spatial Analyst Extension, model code is not publicly available.

VIC model (Variable Infiltration Capacity model) - Surface Water ModelVIC a semi distributed grid based hydrology model which uses both energy and water balance equations. It shares several basic features with the other land surface models (LSMs) that are commonly coupled to global circulation models (GCMs). The processes like infiltration, runoff, base flow etc are based on various empirical relations. Surface runoff is generated by infiltration excess runoff (Hortonian flow) and saturation excess runoff (Dunne flow). VIC simulates saturation excess runoff by considering soil heterogeneity and precipitation. It consists of 3 layers. Top layer allows quick soil evaporation, middle layer represent dynamic response of soil to rainfall events and lower layer is used to characterise behaviour of soil moisture. Improvised VIC model has included both infiltration excess runoff and saturation excess runoff and also the effects of variability of soil heterogeneity on surface runoff characteristics. It can deal with the dynamics of surface and ground water interactions and calculate ground water table.

32 Fleming, M. and Neary, V.: Continuous Hydrologic Modeling Study with the Hydrologic Mode-ling System, J. Hydrol. Eng., 9, 175–183, 200

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Data requirementsTerrain, land use, soil, daily weather data (rainfall, maximum and minimum temperature, wind speed).

Model Outputs

• Precipitation

• Surface runoff, lateral and base flow

• Potential evapotranspiration (PET)

• Base flow

• Total soil moisture content

LimitationsNot supported for Microsoft Windows operating system, cannot process geospatial data, each grid cell is treated independently except for routing, not applicable for small watersheds.

MIKE water resources products - CommercialThe product suite comprises MIKE HYDRO River for network modelling applications, MIKE FLOOD for surface water flooding, MIKE SHE for integrated catchment hydrology, MIKE HYDRO Basin for water resources planning and MIKE 21C for river hydraulics , sediments and morphology applications.MIKE Basin is a software package developed by Danish Hydrologic Institute, DHI. MIKE Basin uses the ESRI software Arc Editor as a basis. The model is a versatile, GIS-based decision support tool for integrated water resources management and planning. Mike Basin is used for addressing water allocation, conjunctive use, reservoir operation, or water quality issues.

Data requirementsInput data requirement to Mike Basin include:

• Rivers represented by river reaches and nodes

• Catchment area represented by an area

• Reservoirs of 3 different types: lakes, rule curve reservoirs and allocation pool reservoirs

• Water users, including irrigation, represents any user that abstract, consumes and returns surface and/or groundwater.

• Hydrological information

Calibration of the model is based on observed discharge.

MODFLOW - The Ground Water ModelThe modular finite-difference ground-water flow model (MODFLOW) is a package to simulate the ground-water flow using finite difference technique developed

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by McDonald and Harbaugh33 of United States Geological Survey. This package is highly portable and modular. The program was constructed in the early 1980’s and has continually evolved since then with development of many new packages and related programs for ground-water studies. Currently, MODFLOW is the most widely used program in the world for simulating ground-water flow. The popularity of the program is attributed to the following factors: The finite-difference method used by MODFLOW is relatively easy to under-stand and applies to a wide variety of real-world conditions. MODFLOW works on many different computer systems ranging from personal computers to super computers. MODFLOW can be applied as a one-dimensional, two-dimensional, or quasi-or full three-dimensional model. Each simulation feature of MODFLOW has been extensively tested. Data input instructions and theory are well documented. The modular program design of MODFLOW allows for new simulation features to be added with relative ease.

Data requirements

Following is the list of the data required for the MODFLOW.

• number of layers

• model boundaries

• ground water levels

• recharge data

• well abstraction data

• aquifer properties (porosity, specific storage, horizontal and vertical hydraulic conductivity, transmissivity, vertical leakage) (Basic)

• drain elevation and the hydraulic conductance of the interface (drain)

• hydraulic conductance of the river bed, elevation of the river bottom, head in the river (River)

• maximum evapotranspiration (ET) rate

• elevation of ET surface

• ET extinction depth (Evapotranspiration)

• hydraulic conductance of the interface between aquifer cell and the boundary head on the boundary (General- head boundary)

• Recharge flux (Recharge).

The above inputs are the general inputs for the model. The actual requirement and extent of these inputs shall be decided by the conditions at the specific site.

33 McDonald, M.G., and Harbaugh, A.W., 1988, A modular three-dimensional finite-difference ground-water flow model: U.S. Geological Survey Techniques of Water-Resources Investigations book 6, chap. A1, 586 p Harbaugh, A.W., and McDonald, M.G. (1996a). User’s documentation for MODFLOW-96, an update to the U.S. Geological Survey modular finite-difference ground-water flow model, Open-File Report 96-485. U.S. Geological Survey, 56 p

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Model OutputMODFLOW uses the input to construct and solve equations of ground-water flow in the aquifer system. The solution consists of head (ground-water level) at every cell in the aquifer system (except for cells where head was specified as known in the input data sets) at intervals called “time steps”. The head can be printed and (or) saved on a computer storage device for any time step. Water levels from a model layer can be used to construct contour maps for comparison with similar maps drawn from field data. Computed water levels at individual cells can be compared with measured water levels from wells at corresponding locations to determine model error. The process of adjusting the model input values to reduce the model error is referred to as model calibration.

LimitationsUnsaturated aquifers cannot be modelled, absence of inbuilt GUI, cannot simulate multiphase flow.

Water Evaluation and Planning Model (WEAP) - Water System ModelWEAP21 is a software tool that takes an integrated approach to water resources planning. It has been through a series of developments over its 20-year history. WEAP21 attempts to address the gap between water management and watershed hydrology, and the requirements that an effective integrated water resources model be useful, easy to use, affordable and readily available to the broad water resource community. WEAP21 integrates a range of physical hydrologic processes with the management of demands and installed infrastructure in a coherent manner. It allows for multiple scenario analysis, including alternative climate projections and changing anthropogenic stressors, such as land-use variations, changes in municipal and industrial demands, alternative operating rules and points of diversion changes. WEAP21’s strength is in addressing water planning and resource allocation problems and issues and, importantly, it is not designed to be a detailed water operations model that might be used to optimize hydropower based on hydrologic forecasts, for example.The management system in the WEAP21 decision support system (DSS) is described by a user-defined demand priority and supply preference set for each demand site used to construct an optimization routine that allocates available supplies. Demands are defined by the user, but typically include municipal and industrial demand, irrigated portions of sub-catchments and environmental flow requirements. Demand analysis in WEAP21 that is not covered by the evapotranspiration-based irrigation demand follows a disaggregated, end-use-based approach for determining water requirements at each demand node. Economic, demographic and water use information is used to construct alternative scenarios that examine how total and disaggregated consumption of water evolve over time. These demand scenarios are computed in WEAP21 and applied deterministically to a linear-programme-based allocation algorithm. Demand analysis is the starting point for conducting integrated water planning analysis because all supply and resource calculations in WEAP21 are driven by the optimization routine that determines the final delivery to each demand node, based on the priorities specified by the user.

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WEAP is free to developing countries’

Data Requirement

Input data include:

• Configuration of system (can use GIS layers for background)

• Component capacities and operating policies

• Water demand: Spatially explicit demographic, economic, crop water requirements; current and future water demands and pollution generation.

• Economic data: Water use rates, capital costs, discount rate estimates.

• Water supply: Historical inflows at a monthly timestep;

• Groundwater sources. Scenarios:

• Reservoir operating rule modifications

• Pollution changes and reduction goals

• Projections: socioeconomic projections, water supply projections.

Model OutputMass balances, water diversions, sectoral water use; benefit/cost scenario comparisons; pollution generation and pollution loads. Not applicable for detailed design, data needs to be imported into the model, cannot model reservoir water quality, cannot account for stream attenuation.

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Appendix II - Vulnerability Assessment

Table 5: Commonly employed terminology

DRM CIP IPCC AR4 IPCC AR5

Adaptive/Coping Capacity/ (Lack of) Resilience

Coping capacity: The ability of people, organizations and systems, using available skills and resources, to face and manage adverse conditions, emergencies or disasters (UNISDR 2009 34).

(Lack of) resilience: The ability of a system, community or society exposed to hazards to resist, absorb, accommodate to and recover from the effects of a hazard in a timely and efficient manner, including through the preservation and restoration of its essential basic structures and functions (UNIDSR 2009)

The ability of a system to adjust to cli-mate change (including climate var-iability and extremes) to moderate potential dam-ages, to take advantage of opportu-nities, or to cope with the consequences (IPCC 2007)

Coping capacity: The ability of people, institutions, organizations, and systems, using available skills, values, beliefs, resources, and opportunities, to address, manage, and over come adverse conditions in the short to medium term (IPCC 2014).Adaptive capacity: The ability of systems, institutions, humans, and other organisms to adjust to potential damage, to take advantage of opportunities, or to respond to consequences (IPCC201435 )

Exposure People, property, systems, or other elements present in hazard zones that are

The potential loss to an area due to the occurrence of an adverse event (ENISA36 )

The nature and degree to which a system is exposed to significant climatic variations (IPCC 200137).

The presence of people, livelihoods, species or ecosystems, environmental services and resources, infrastructure, or economic, social, or cultural assets in places that could be adversely affected (IPCC2014) (What is exposed?)

34 UNISDR, 2009. Terminology on disaster risk reduction (The United Nations Office for Disaster Risk Reduction). Available at: http://www.unisdr.org/we/inform/terminology35 IPCC, 2014b. Annex II: Glossary [Agard, J., E.L.F. Schipper, J. Birkmann, M. Campos, C. Dubeux, Y. Nojiri, L. Olsson, B. Osman-Elasha, M. Pelling, M.J. Prather, M.G. Rivera-Ferre, O.C. Ruppel, A. Sallenger, K.R. Smith, A.L. St Clair, K.J. Mach, M.D. Mastrandrea, and T.E. Bilir (eds.)], in: Barros, V.R., Field, C.B., Dokken, D.J., Mastrandrea, M.D., Mach, K.J., Bilir, T.E., Chatterjee, M., Ebi, K.L., Estrada, Y.O., Genova, R.C., Girma, B., Kissel, E.S., Levy, A.N., MacCracken, S., Mastrandrea, P.R., White, L.L. (Eds.), Climate Change 2014: impacts, adaptation, and vulnerability. Part B: regional aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom and New York, USA, pp. 1757–1776.36 https://www.enisa.europa.eu/topics/threat-risk-management/risk-management/current-risk/risk-management-inventory/glossary37 IPCC. 2001. Climate Change 2001: The scientific basis. contribution of working group I to the third assessment report of the Intergovernmental Panel on Climate Change. Cambridge, Cambridge University Press, 2001.

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Hazard A dangerous phenomenon, substance, hu-man activity or condition that may cause loss of life, injury or other health im-pacts, property damage, loss of livelihoods and services, social and economic disruption, or environmental damage (UNIS-DR 2009).

Source of potential harm (CIPedia© 2015 38)

N/A The potential occurrence of a natural or hu-man-induced physi-cal event or trend, or physical impact, that may cause loss of life, injury, or other health im-pacts, as well as damage and loss to property, infrastruc-ture, livelihoods, service provision, and environmental resources(IPCC 2014).

Vulnerability The charac-teristics and circumstances of a community, system or asset that make it susceptible to the damaging effects of a hazard (UNISDR 2009). (Who or what is vulnera-ble?))

A characteristic of an element of the CI’s design, implemen-tation, or operation that renders it sus-ceptible to disrup-tion or destruction by a threat and includes dependen-cies on other types of infrastructure (Eu-ropean Commission, COM(2006)787) (Who or what is vulnerable?)

Vulnerability is a function of the character, magnitude, and rate of climate variation to which a system is exposed, its sensitivity, and its adaptive capacity (IPCC 2007) (Who, or what is vulnerable and to what, when and where?).

The propensity or predisposition to be adversely affected.Vulnerability encompasses variety of concepts including sensitivity or susceptibility to harm and lack of capacity to cope and adapt. (Who or what is vulner-able, and to what extent can they cope/recover from/adapt?)

(Source: http://www.resin-cities.eu/fileadmin/user_upload/D1_1_SOTAVulnerability_UNIMAN_2015-11-30.pdf)

DRM: Disaster Risk Management, CI: Critical Infrastructure Protection

38 CIPedia© 2015. A multi-disciplinary glossary. CIPRNet’s VCCC (Virtual Centre of Competence and expertise in CIP). Available at: https://publicwiki-01.fraunhofer.de/CIPedia/index.php/CIPedia%C2%A9_Main_Page

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Normalization of Indicator DataNormalization is done to convert raw data into a normalized form.

• To make the raw data unit free.

• To avoid one variable having an undue influence on the analysis (principal components).

• To get the relative position of each district in respect of the indicators.

• Normalized values always lie between 0 and 1.

Whenever an indicator has positive relationship (vulnerability increases with increase in value of the indicator) with vulnerability normalized value for each of the indicator for each district is computed as:

𝑁𝑁𝑁𝑁 = [X − minimum (X)][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [ maximum (X) − X ][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [X − minimum (X)][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [X − 169.2][270.9 – 169.2]

𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 = [210.4 − 169.2][270.9 – 169.2] = 0.405

𝑁𝑁𝑁𝑁 = [ maximum (X) − X ][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [81.1 − X][81.1 – 36.1]

𝐿𝐿𝑆𝑆𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 = [81.1 – 36.1][81.1 – 36.1] = 1.0

𝑁𝑁𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉 𝐼𝐼𝑉𝑉𝐼𝐼𝑉𝑉𝐼𝐼, 𝑁𝑁𝐼𝐼 = 1𝑉𝑉 [∑(𝐴𝐴𝐴𝐴𝑉𝑉𝑉𝑉𝑉𝑉𝐴𝐴𝑉𝑉 𝐼𝐼𝑉𝑉𝐼𝐼𝑉𝑉𝐼𝐼𝐴𝐴)𝛼𝛼

𝑛𝑛

𝐴𝐴=1]

1 𝛼𝛼⁄

𝑉𝑉�̅�𝑖 = ∑ 𝑤𝑤𝐴𝐴𝐼𝐼𝐴𝐴𝐴𝐴

𝐾𝐾

𝐴𝐴=1(0 < 𝑤𝑤 < 1 𝑉𝑉𝑉𝑉𝐼𝐼 ∑ 𝑤𝑤𝐴𝐴 = 1

𝐾𝐾

𝐴𝐴=1)

𝑤𝑤𝐴𝐴 = 𝑐𝑐√𝐴𝐴𝑉𝑉𝑉𝑉𝐴𝐴(𝐼𝐼𝐴𝐴𝐴𝐴)⁄

𝑐𝑐 = [∑ 1√𝐴𝐴𝑉𝑉𝑉𝑉𝐴𝐴(𝐼𝐼𝐴𝐴𝐴𝐴)⁄

𝑘𝑘

𝐴𝐴=1]

−1

𝑁𝑁𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉 𝐼𝐼𝑉𝑉𝐼𝐼𝑉𝑉𝐼𝐼 = ⌊∑(𝑤𝑤𝐴𝐴 ∗ 𝑁𝑁𝑁𝑁𝐴𝐴)𝑛𝑛

𝐴𝐴=1⌋

Whenever an indicator has negative relationship (vulnerability decreases with increase in value of the indicator) with vulnerability then the normalized value is calculated as:

𝑁𝑁𝑁𝑁 = [X − minimum (X)][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [ maximum (X) − X ][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [X − minimum (X)][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [X − 169.2][270.9 – 169.2]

𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 = [210.4 − 169.2][270.9 – 169.2] = 0.405

𝑁𝑁𝑁𝑁 = [ maximum (X) − X ][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [81.1 − X][81.1 – 36.1]

𝐿𝐿𝑆𝑆𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 = [81.1 – 36.1][81.1 – 36.1] = 1.0

𝑁𝑁𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉 𝐼𝐼𝑉𝑉𝐼𝐼𝑉𝑉𝐼𝐼, 𝑁𝑁𝐼𝐼 = 1𝑉𝑉 [∑(𝐴𝐴𝐴𝐴𝑉𝑉𝑉𝑉𝑉𝑉𝐴𝐴𝑉𝑉 𝐼𝐼𝑉𝑉𝐼𝐼𝑉𝑉𝐼𝐼𝐴𝐴)𝛼𝛼

𝑛𝑛

𝐴𝐴=1]

1 𝛼𝛼⁄

𝑉𝑉�̅�𝑖 = ∑ 𝑤𝑤𝐴𝐴𝐼𝐼𝐴𝐴𝐴𝐴

𝐾𝐾

𝐴𝐴=1(0 < 𝑤𝑤 < 1 𝑉𝑉𝑉𝑉𝐼𝐼 ∑ 𝑤𝑤𝐴𝐴 = 1

𝐾𝐾

𝐴𝐴=1)

𝑤𝑤𝐴𝐴 = 𝑐𝑐√𝐴𝐴𝑉𝑉𝑉𝑉𝐴𝐴(𝐼𝐼𝐴𝐴𝐴𝐴)⁄

𝑐𝑐 = [∑ 1√𝐴𝐴𝑉𝑉𝑉𝑉𝐴𝐴(𝐼𝐼𝐴𝐴𝐴𝐴)⁄

𝑘𝑘

𝐴𝐴=1]

−1

𝑁𝑁𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉 𝐼𝐼𝑉𝑉𝐼𝐼𝑉𝑉𝐼𝐼 = ⌊∑(𝑤𝑤𝐴𝐴 ∗ 𝑁𝑁𝑁𝑁𝐴𝐴)𝑛𝑛

𝐴𝐴=1⌋

This is possible when, for example, higher literacy leads to lower vulnerability. Where,

NV = Normalized value of X, X is an observed value for the districts for a given variable, Max X is the highest value of the variable across the district, Min X is the lowest value of the variable across the district.

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Example of normalisation of indicators using functional relationshipNormalized value for each of the indicator for each district is computed as:

Case 1 : Vulnerability increases with increase in value of the indicator. Example : Indicator STDRF(Standard deviation in annual rainfall39). Higher value of this variable implies in consistency in the rainfall pattern, which in turn would affect water availability, agriculture etc. Normalized value is computed as:

𝑁𝑁𝑁𝑁 = [X − minimum (X)][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [ maximum (X) − X ][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [X − minimum (X)][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [X − 169.2][270.9 – 169.2]

𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 = [210.4 − 169.2][270.9 – 169.2] = 0.405

𝑁𝑁𝑁𝑁 = [ maximum (X) − X ][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [81.1 − X][81.1 – 36.1]

𝐿𝐿𝑆𝑆𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 = [81.1 – 36.1][81.1 – 36.1] = 1.0

𝑁𝑁𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉 𝐼𝐼𝑉𝑉𝐼𝐼𝑉𝑉𝐼𝐼, 𝑁𝑁𝐼𝐼 = 1𝑉𝑉 [∑(𝐴𝐴𝐴𝐴𝑉𝑉𝑉𝑉𝑉𝑉𝐴𝐴𝑉𝑉 𝐼𝐼𝑉𝑉𝐼𝐼𝑉𝑉𝐼𝐼𝐴𝐴)𝛼𝛼

𝑛𝑛

𝐴𝐴=1]

1 𝛼𝛼⁄

𝑉𝑉�̅�𝑖 = ∑ 𝑤𝑤𝐴𝐴𝐼𝐼𝐴𝐴𝐴𝐴

𝐾𝐾

𝐴𝐴=1(0 < 𝑤𝑤 < 1 𝑉𝑉𝑉𝑉𝐼𝐼 ∑ 𝑤𝑤𝐴𝐴 = 1

𝐾𝐾

𝐴𝐴=1)

𝑤𝑤𝐴𝐴 = 𝑐𝑐√𝐴𝐴𝑉𝑉𝑉𝑉𝐴𝐴(𝐼𝐼𝐴𝐴𝐴𝐴)⁄

𝑐𝑐 = [∑ 1√𝐴𝐴𝑉𝑉𝑉𝑉𝐴𝐴(𝐼𝐼𝐴𝐴𝐴𝐴)⁄

𝑘𝑘

𝐴𝐴=1]

−1

𝑁𝑁𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉 𝐼𝐼𝑉𝑉𝐼𝐼𝑉𝑉𝐼𝐼 = ⌊∑(𝑤𝑤𝐴𝐴 ∗ 𝑁𝑁𝑁𝑁𝐴𝐴)𝑛𝑛

𝐴𝐴=1⌋

STRRF is lowest for Katni (169.2 mm) and highest for Harda (270.9 mm). Normalization based on above formula works out to be:

𝑁𝑁𝑁𝑁 = [X − minimum (X)][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [ maximum (X) − X ][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [X − minimum (X)][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [X − 169.2][270.9 – 169.2]

𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 = [210.4 − 169.2][270.9 – 169.2] = 0.405

𝑁𝑁𝑁𝑁 = [ maximum (X) − X ][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [81.1 − X][81.1 – 36.1]

𝐿𝐿𝑆𝑆𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 = [81.1 – 36.1][81.1 – 36.1] = 1.0

𝑁𝑁𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉 𝐼𝐼𝑉𝑉𝐼𝐼𝑉𝑉𝐼𝐼, 𝑁𝑁𝐼𝐼 = 1𝑉𝑉 [∑(𝐴𝐴𝐴𝐴𝑉𝑉𝑉𝑉𝑉𝑉𝐴𝐴𝑉𝑉 𝐼𝐼𝑉𝑉𝐼𝐼𝑉𝑉𝐼𝐼𝐴𝐴)𝛼𝛼

𝑛𝑛

𝐴𝐴=1]

1 𝛼𝛼⁄

𝑉𝑉�̅�𝑖 = ∑ 𝑤𝑤𝐴𝐴𝐼𝐼𝐴𝐴𝐴𝐴

𝐾𝐾

𝐴𝐴=1(0 < 𝑤𝑤 < 1 𝑉𝑉𝑉𝑉𝐼𝐼 ∑ 𝑤𝑤𝐴𝐴 = 1

𝐾𝐾

𝐴𝐴=1)

𝑤𝑤𝐴𝐴 = 𝑐𝑐√𝐴𝐴𝑉𝑉𝑉𝑉𝐴𝐴(𝐼𝐼𝐴𝐴𝐴𝐴)⁄

𝑐𝑐 = [∑ 1√𝐴𝐴𝑉𝑉𝑉𝑉𝐴𝐴(𝐼𝐼𝐴𝐴𝐴𝐴)⁄

𝑘𝑘

𝐴𝐴=1]

−1

𝑁𝑁𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉 𝐼𝐼𝑉𝑉𝐼𝐼𝑉𝑉𝐼𝐼 = ⌊∑(𝑤𝑤𝐴𝐴 ∗ 𝑁𝑁𝑁𝑁𝐴𝐴)𝑛𝑛

𝐴𝐴=1⌋

Normalised STDRF value for Alirajpur is calculated as:

𝑁𝑁𝑁𝑁 = [X − minimum (X)][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [ maximum (X) − X ][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [X − minimum (X)][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [X − 169.2][270.9 – 169.2]

𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 = [210.4 − 169.2][270.9 – 169.2] = 0.405

𝑁𝑁𝑁𝑁 = [ maximum (X) − X ][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [81.1 − X][81.1 – 36.1]

𝐿𝐿𝑆𝑆𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 = [81.1 – 36.1][81.1 – 36.1] = 1.0

𝑁𝑁𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉 𝐼𝐼𝑉𝑉𝐼𝐼𝑉𝑉𝐼𝐼, 𝑁𝑁𝐼𝐼 = 1𝑉𝑉 [∑(𝐴𝐴𝐴𝐴𝑉𝑉𝑉𝑉𝑉𝑉𝐴𝐴𝑉𝑉 𝐼𝐼𝑉𝑉𝐼𝐼𝑉𝑉𝐼𝐼𝐴𝐴)𝛼𝛼

𝑛𝑛

𝐴𝐴=1]

1 𝛼𝛼⁄

𝑉𝑉�̅�𝑖 = ∑ 𝑤𝑤𝐴𝐴𝐼𝐼𝐴𝐴𝐴𝐴

𝐾𝐾

𝐴𝐴=1(0 < 𝑤𝑤 < 1 𝑉𝑉𝑉𝑉𝐼𝐼 ∑ 𝑤𝑤𝐴𝐴 = 1

𝐾𝐾

𝐴𝐴=1)

𝑤𝑤𝐴𝐴 = 𝑐𝑐√𝐴𝐴𝑉𝑉𝑉𝑉𝐴𝐴(𝐼𝐼𝐴𝐴𝐴𝐴)⁄

𝑐𝑐 = [∑ 1√𝐴𝐴𝑉𝑉𝑉𝑉𝐴𝐴(𝐼𝐼𝐴𝐴𝐴𝐴)⁄

𝑘𝑘

𝐴𝐴=1]

−1

𝑁𝑁𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉 𝐼𝐼𝑉𝑉𝐼𝐼𝑉𝑉𝐼𝐼 = ⌊∑(𝑤𝑤𝐴𝐴 ∗ 𝑁𝑁𝑁𝑁𝐴𝐴)𝑛𝑛

𝐴𝐴=1⌋

Excel Formula: =(L3-MIN($L$3:$L$17))/(MAX($L$3:$L$17)- MIN($L$3:$L$17))

Case Vulnerability decreases with increase in value of the indicator. Example: Indicator LR (Literacy Rate). A high value of this variable implies more literates in the district who will have more awareness to cope with climate change. So the vulnerability will be lower with higher literacy rate. For this case normalized value is computed as:

𝑁𝑁𝑁𝑁 = [X − minimum (X)][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [ maximum (X) − X ][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [X − minimum (X)][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [X − 169.2][270.9 – 169.2]

𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 = [210.4 − 169.2][270.9 – 169.2] = 0.405

𝑁𝑁𝑁𝑁 = [ maximum (X) − X ][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [81.1 − X][81.1 – 36.1]

𝐿𝐿𝑆𝑆𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 = [81.1 – 36.1][81.1 – 36.1] = 1.0

𝑁𝑁𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉 𝐼𝐼𝑉𝑉𝐼𝐼𝑉𝑉𝐼𝐼, 𝑁𝑁𝐼𝐼 = 1𝑉𝑉 [∑(𝐴𝐴𝐴𝐴𝑉𝑉𝑉𝑉𝑉𝑉𝐴𝐴𝑉𝑉 𝐼𝐼𝑉𝑉𝐼𝐼𝑉𝑉𝐼𝐼𝐴𝐴)𝛼𝛼

𝑛𝑛

𝐴𝐴=1]

1 𝛼𝛼⁄

𝑉𝑉�̅�𝑖 = ∑ 𝑤𝑤𝐴𝐴𝐼𝐼𝐴𝐴𝐴𝐴

𝐾𝐾

𝐴𝐴=1(0 < 𝑤𝑤 < 1 𝑉𝑉𝑉𝑉𝐼𝐼 ∑ 𝑤𝑤𝐴𝐴 = 1

𝐾𝐾

𝐴𝐴=1)

𝑤𝑤𝐴𝐴 = 𝑐𝑐√𝐴𝐴𝑉𝑉𝑉𝑉𝐴𝐴(𝐼𝐼𝐴𝐴𝐴𝐴)⁄

𝑐𝑐 = [∑ 1√𝐴𝐴𝑉𝑉𝑉𝑉𝐴𝐴(𝐼𝐼𝐴𝐴𝐴𝐴)⁄

𝑘𝑘

𝐴𝐴=1]

−1

𝑁𝑁𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉 𝐼𝐼𝑉𝑉𝐼𝐼𝑉𝑉𝐼𝐼 = ⌊∑(𝑤𝑤𝐴𝐴 ∗ 𝑁𝑁𝑁𝑁𝐴𝐴)𝑛𝑛

𝐴𝐴=1⌋

LR is highest for Jabalpur (81.1%) and highest for Alirajpur (36.1%). Normalization based on above formula works out to be:

𝑁𝑁𝑁𝑁 = [X − minimum (X)][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [ maximum (X) − X ][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [X − minimum (X)][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [X − 169.2][270.9 – 169.2]

𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 = [210.4 − 169.2][270.9 – 169.2] = 0.405

𝑁𝑁𝑁𝑁 = [ maximum (X) − X ][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [81.1 − X][81.1 – 36.1]

𝐿𝐿𝑆𝑆𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 = [81.1 – 36.1][81.1 – 36.1] = 1.0

𝑁𝑁𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉 𝐼𝐼𝑉𝑉𝐼𝐼𝑉𝑉𝐼𝐼, 𝑁𝑁𝐼𝐼 = 1𝑉𝑉 [∑(𝐴𝐴𝐴𝐴𝑉𝑉𝑉𝑉𝑉𝑉𝐴𝐴𝑉𝑉 𝐼𝐼𝑉𝑉𝐼𝐼𝑉𝑉𝐼𝐼𝐴𝐴)𝛼𝛼

𝑛𝑛

𝐴𝐴=1]

1 𝛼𝛼⁄

𝑉𝑉�̅�𝑖 = ∑ 𝑤𝑤𝐴𝐴𝐼𝐼𝐴𝐴𝐴𝐴

𝐾𝐾

𝐴𝐴=1(0 < 𝑤𝑤 < 1 𝑉𝑉𝑉𝑉𝐼𝐼 ∑ 𝑤𝑤𝐴𝐴 = 1

𝐾𝐾

𝐴𝐴=1)

𝑤𝑤𝐴𝐴 = 𝑐𝑐√𝐴𝐴𝑉𝑉𝑉𝑉𝐴𝐴(𝐼𝐼𝐴𝐴𝐴𝐴)⁄

𝑐𝑐 = [∑ 1√𝐴𝐴𝑉𝑉𝑉𝑉𝐴𝐴(𝐼𝐼𝐴𝐴𝐴𝐴)⁄

𝑘𝑘

𝐴𝐴=1]

−1

𝑁𝑁𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉 𝐼𝐼𝑉𝑉𝐼𝐼𝑉𝑉𝐼𝐼 = ⌊∑(𝑤𝑤𝐴𝐴 ∗ 𝑁𝑁𝑁𝑁𝐴𝐴)𝑛𝑛

𝐴𝐴=1⌋

Normalised LR value for Alirajpur is calculated as:

𝑁𝑁𝑁𝑁 = [X − minimum (X)][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [ maximum (X) − X ][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [X − minimum (X)][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [X − 169.2][270.9 – 169.2]

𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 = [210.4 − 169.2][270.9 – 169.2] = 0.405

𝑁𝑁𝑁𝑁 = [ maximum (X) − X ][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [81.1 − X][81.1 – 36.1]

𝐿𝐿𝑆𝑆𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 = [81.1 – 36.1][81.1 – 36.1] = 1.0

𝑁𝑁𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉 𝐼𝐼𝑉𝑉𝐼𝐼𝑉𝑉𝐼𝐼, 𝑁𝑁𝐼𝐼 = 1𝑉𝑉 [∑(𝐴𝐴𝐴𝐴𝑉𝑉𝑉𝑉𝑉𝑉𝐴𝐴𝑉𝑉 𝐼𝐼𝑉𝑉𝐼𝐼𝑉𝑉𝐼𝐼𝐴𝐴)𝛼𝛼

𝑛𝑛

𝐴𝐴=1]

1 𝛼𝛼⁄

𝑉𝑉�̅�𝑖 = ∑ 𝑤𝑤𝐴𝐴𝐼𝐼𝐴𝐴𝐴𝐴

𝐾𝐾

𝐴𝐴=1(0 < 𝑤𝑤 < 1 𝑉𝑉𝑉𝑉𝐼𝐼 ∑ 𝑤𝑤𝐴𝐴 = 1

𝐾𝐾

𝐴𝐴=1)

𝑤𝑤𝐴𝐴 = 𝑐𝑐√𝐴𝐴𝑉𝑉𝑉𝑉𝐴𝐴(𝐼𝐼𝐴𝐴𝐴𝐴)⁄

𝑐𝑐 = [∑ 1√𝐴𝐴𝑉𝑉𝑉𝑉𝐴𝐴(𝐼𝐼𝐴𝐴𝐴𝐴)⁄

𝑘𝑘

𝐴𝐴=1]

−1

𝑁𝑁𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉 𝐼𝐼𝑉𝑉𝐼𝐼𝑉𝑉𝐼𝐼 = ⌊∑(𝑤𝑤𝐴𝐴 ∗ 𝑁𝑁𝑁𝑁𝐴𝐴)𝑛𝑛

𝐴𝐴=1⌋

Thus, normalized scores for each district can be computed.

Excel Formula: ==(MAX($D$3:$D$17)-D3)/(MAX($D$3:$D$17)-MIN($D$3:$D$17))

39 The standard deviation is the average variation from a long-term average; a large standard deviation will have a lot of year-to-year variability which may make planning more difficult.

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Tab

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Calculation of WeightsIn the development of aggregated index problems arise when the weights of each indicator have to be selected.

There is no single agreed methodology to weight individual indicators before aggregating them into a composite indicator. Weights usually have an important impact on the composite indicator value and on the resulting ranking. The method for weighting needs to be made explicit and transparent.

Commonly used methods for weighting include the following:

• Equal weights

o Simple Equal Weights.

o Patnaik and Narain Method.

• Unequal Weights

o Expert/Stakeholder opinion.

o Iyengar and Sudarshan’s method.

o Weights based on statistical models (Principal components analysis).

Method of Equal weights

Simple Equal Weights

In many composite indicators all variables are given the equal weight when there are no statistical or empirical grounds for choosing a different scheme. Equal weighting could imply the recognition of an equal status for all indicators with the intention to make each input variable contribute equally to the value of the composite indicator. All variables are given equal importance while constructing the vulnerability index.

Combining indicators that are highly correlated may introduce an element of double counting into the index.

Patnaik and Narain Method ( Patnaik and Narayanan, 200540)

In the Patnaik and Narayanan method, the possible sources of vulnerability are grouped as demographic, climatic, agricultural, occupational and geographic, etc., and for each source several sub-indicators are identified. The methodology used to calculate the vulnerability index follows the basic approach developed (Anand and Sen, 199441) for the calculation of the human development index (HDI).

40 Patnaik U and Narayanan K. 2005. Vulnerability and Climate Change: An Analysis of the Eastern Coastal Districts of India, Human Security and Climate Change: An International Workshop, Asker.41 Anand, S., and Amartya Sen, 1994, Human Development Index: Methodology and Measurement, Occasional Paper 12, United Nations Development Programme, Human Development Report Office, New York.

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Methodology for calculation of the index :

Step 1 : Calculate a dimension index of the each of the indicators for a district (XI ) by using the formula

(Actual X I - Minimum XI) / (Maximum XI - Minimum XI)

Step 2: Calculate average index for each of the sources of vulnerability viz. Demographic, Climatic, Agricultural and Occupational vulnerability. This is done by taking a simple average of the indicators in each category.

Average Indexi = [Indicator+.......... + Indicator] /j

Where,

j = Number of indicators in each source of vulnerability

Step 3: Aggregate across all the sources of vulnerability by the following formula.

𝑁𝑁𝑁𝑁 = [X − minimum (X)][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [ maximum (X) − X ][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [X − minimum (X)][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [X − 169.2][270.9 – 169.2]

𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 = [210.4 − 169.2][270.9 – 169.2] = 0.405

𝑁𝑁𝑁𝑁 = [ maximum (X) − X ][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [81.1 − X][81.1 – 36.1]

𝐿𝐿𝑆𝑆𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 = [81.1 – 36.1][81.1 – 36.1] = 1.0

𝑁𝑁𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉 𝐼𝐼𝑉𝑉𝐼𝐼𝑉𝑉𝐼𝐼, 𝑁𝑁𝐼𝐼 = 1𝑉𝑉 [∑(𝐴𝐴𝐴𝐴𝑉𝑉𝑉𝑉𝑉𝑉𝐴𝐴𝑉𝑉 𝐼𝐼𝑉𝑉𝐼𝐼𝑉𝑉𝐼𝐼𝐴𝐴)𝛼𝛼

𝑛𝑛

𝐴𝐴=1]

1 𝛼𝛼⁄

𝑉𝑉�̅�𝑖 = ∑ 𝑤𝑤𝐴𝐴𝐼𝐼𝐴𝐴𝐴𝐴

𝐾𝐾

𝐴𝐴=1(0 < 𝑤𝑤 < 1 𝑉𝑉𝑉𝑉𝐼𝐼 ∑ 𝑤𝑤𝐴𝐴 = 1

𝐾𝐾

𝐴𝐴=1)

𝑤𝑤𝐴𝐴 = 𝑐𝑐√𝐴𝐴𝑉𝑉𝑉𝑉𝐴𝐴(𝐼𝐼𝐴𝐴𝐴𝐴)⁄

𝑐𝑐 = [∑ 1√𝐴𝐴𝑉𝑉𝑉𝑉𝐴𝐴(𝐼𝐼𝐴𝐴𝐴𝐴)⁄

𝑘𝑘

𝐴𝐴=1]

−1

𝑁𝑁𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉 𝐼𝐼𝑉𝑉𝐼𝐼𝑉𝑉𝐼𝐼 = ⌊∑(𝑤𝑤𝐴𝐴 ∗ 𝑁𝑁𝑁𝑁𝐴𝐴)𝑛𝑛

𝐴𝐴=1⌋

Where,

ij = average sectoral vulnerability index

n = Number of sources of vulnerability (a= n)

After the values of the index are calculated for all the districts a ranking of the various districts can be carried out to identify the most vulnerable districts in terms of the indicators used for measurement. The vulnerability indices can be calculated for different time periods and can be compared to assess the changes in vulnerabilities over time.

Unequal Weights

Expert/Stakeholder opinion

This is a subjective method and the weights are assigned based on expert opinion.

Iyengar and Sudarshan’s method

Iyengar and Sudarshan (198242) developed a method to work-out a composite index from multivariate data and it was used to rank the districts in terms of their economic performance. This methodology is statistically sound and well suited for the development of composite index of vulnerability to climate change. This method is simple and it does not have the restrictive assumption of linearity in relation to indicators.

For M regions /districts, K indicators of vulnerability and xij, i=1,2 ...M; j= 1, 2...K are the normalized scores. Vulnerability index yi,is calculated as a linear sum of xij.

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𝑁𝑁𝑁𝑁 = [X − minimum (X)][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [ maximum (X) − X ][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [X − minimum (X)][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [X − 169.2][270.9 – 169.2]

𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 = [210.4 − 169.2][270.9 – 169.2] = 0.405

𝑁𝑁𝑁𝑁 = [ maximum (X) − X ][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [81.1 − X][81.1 – 36.1]

𝐿𝐿𝑆𝑆𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 = [81.1 – 36.1][81.1 – 36.1] = 1.0

𝑁𝑁𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉 𝐼𝐼𝑉𝑉𝐼𝐼𝑉𝑉𝐼𝐼, 𝑁𝑁𝐼𝐼 = 1𝑉𝑉 [∑(𝐴𝐴𝐴𝐴𝑉𝑉𝑉𝑉𝑉𝑉𝐴𝐴𝑉𝑉 𝐼𝐼𝑉𝑉𝐼𝐼𝑉𝑉𝐼𝐼𝐴𝐴)𝛼𝛼

𝑛𝑛

𝐴𝐴=1]

1 𝛼𝛼⁄

𝑉𝑉�̅�𝑖 = ∑ 𝑤𝑤𝐴𝐴𝐼𝐼𝐴𝐴𝐴𝐴

𝐾𝐾

𝐴𝐴=1(0 < 𝑤𝑤 < 1 𝑉𝑉𝑉𝑉𝐼𝐼 ∑ 𝑤𝑤𝐴𝐴 = 1

𝐾𝐾

𝐴𝐴=1)

𝑤𝑤𝐴𝐴 = 𝑐𝑐√𝐴𝐴𝑉𝑉𝑉𝑉𝐴𝐴(𝐼𝐼𝐴𝐴𝐴𝐴)⁄

𝑐𝑐 = [∑ 1√𝐴𝐴𝑉𝑉𝑉𝑉𝐴𝐴(𝐼𝐼𝐴𝐴𝐴𝐴)⁄

𝑘𝑘

𝐴𝐴=1]

−1

𝑁𝑁𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉 𝐼𝐼𝑉𝑉𝐼𝐼𝑉𝑉𝐼𝐼 = ⌊∑(𝑤𝑤𝐴𝐴 ∗ 𝑁𝑁𝑁𝑁𝐴𝐴)𝑛𝑛

𝐴𝐴=1⌋

Where, w’s are weights.

In Iyengar and Sudarshan’s method, the weights are assumed to vary inversely as the variance over the regions in the respective indicators of vulnerability. The weights to the standardized values of the indicators using the following formula:

The weight wj is determined by:

𝑁𝑁𝑁𝑁 = [X − minimum (X)][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [ maximum (X) − X ][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [X − minimum (X)][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [X − 169.2][270.9 – 169.2]

𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 = [210.4 − 169.2][270.9 – 169.2] = 0.405

𝑁𝑁𝑁𝑁 = [ maximum (X) − X ][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [81.1 − X][81.1 – 36.1]

𝐿𝐿𝑆𝑆𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 = [81.1 – 36.1][81.1 – 36.1] = 1.0

𝑁𝑁𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉 𝐼𝐼𝑉𝑉𝐼𝐼𝑉𝑉𝐼𝐼, 𝑁𝑁𝐼𝐼 = 1𝑉𝑉 [∑(𝐴𝐴𝐴𝐴𝑉𝑉𝑉𝑉𝑉𝑉𝐴𝐴𝑉𝑉 𝐼𝐼𝑉𝑉𝐼𝐼𝑉𝑉𝐼𝐼𝐴𝐴)𝛼𝛼

𝑛𝑛

𝐴𝐴=1]

1 𝛼𝛼⁄

𝑉𝑉�̅�𝑖 = ∑ 𝑤𝑤𝐴𝐴𝐼𝐼𝐴𝐴𝐴𝐴

𝐾𝐾

𝐴𝐴=1(0 < 𝑤𝑤 < 1 𝑉𝑉𝑉𝑉𝐼𝐼 ∑ 𝑤𝑤𝐴𝐴 = 1

𝐾𝐾

𝐴𝐴=1)

𝑤𝑤𝐴𝐴 = 𝑐𝑐√𝐴𝐴𝑉𝑉𝑉𝑉𝐴𝐴(𝐼𝐼𝐴𝐴𝐴𝐴)⁄

𝑐𝑐 = [∑ 1√𝐴𝐴𝑉𝑉𝑉𝑉𝐴𝐴(𝐼𝐼𝐴𝐴𝐴𝐴)⁄

𝑘𝑘

𝐴𝐴=1]

−1

𝑁𝑁𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉 𝐼𝐼𝑉𝑉𝐼𝐼𝑉𝑉𝐼𝐼 = ⌊∑(𝑤𝑤𝐴𝐴 ∗ 𝑁𝑁𝑁𝑁𝐴𝐴)𝑛𝑛

𝐴𝐴=1⌋

Where,c is a normalizing constant.

𝑁𝑁𝑁𝑁 = [X − minimum (X)][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [ maximum (X) − X ][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [X − minimum (X)][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [X − 169.2][270.9 – 169.2]

𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 = [210.4 − 169.2][270.9 – 169.2] = 0.405

𝑁𝑁𝑁𝑁 = [ maximum (X) − X ][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [81.1 − X][81.1 – 36.1]

𝐿𝐿𝑆𝑆𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 = [81.1 – 36.1][81.1 – 36.1] = 1.0

𝑁𝑁𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉 𝐼𝐼𝑉𝑉𝐼𝐼𝑉𝑉𝐼𝐼, 𝑁𝑁𝐼𝐼 = 1𝑉𝑉 [∑(𝐴𝐴𝐴𝐴𝑉𝑉𝑉𝑉𝑉𝑉𝐴𝐴𝑉𝑉 𝐼𝐼𝑉𝑉𝐼𝐼𝑉𝑉𝐼𝐼𝐴𝐴)𝛼𝛼

𝑛𝑛

𝐴𝐴=1]

1 𝛼𝛼⁄

𝑉𝑉�̅�𝑖 = ∑ 𝑤𝑤𝐴𝐴𝐼𝐼𝐴𝐴𝐴𝐴

𝐾𝐾

𝐴𝐴=1(0 < 𝑤𝑤 < 1 𝑉𝑉𝑉𝑉𝐼𝐼 ∑ 𝑤𝑤𝐴𝐴 = 1

𝐾𝐾

𝐴𝐴=1)

𝑤𝑤𝐴𝐴 = 𝑐𝑐√𝐴𝐴𝑉𝑉𝑉𝑉𝐴𝐴(𝐼𝐼𝐴𝐴𝐴𝐴)⁄

𝑐𝑐 = [∑ 1√𝐴𝐴𝑉𝑉𝑉𝑉𝐴𝐴(𝐼𝐼𝐴𝐴𝐴𝐴)⁄

𝑘𝑘

𝐴𝐴=1]

−1

𝑁𝑁𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉 𝐼𝐼𝑉𝑉𝐼𝐼𝑉𝑉𝐼𝐼 = ⌊∑(𝑤𝑤𝐴𝐴 ∗ 𝑁𝑁𝑁𝑁𝐴𝐴)𝑛𝑛

𝐴𝐴=1⌋ The choice of the weights in this manner would ensure that large variation in any

one of the indicators would not unduly dominate the contribution of the rest of the indicators and distort inter regional comparisons. The vulnerability index so computed lies between 0 and 1, with 1 indicating maximum vulnerability and 0 indicating no vulnerability.

42 Iyengar, N. S. and Sudarshan, P., A method of classifying regions from multivariate data. Econ. Polit. Wkly., 1982, 17 , 2048 – 2052.

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Principal components analysis - Weights based on statistical models

PCA is a multivariate statistical technique used to reduce the number of indicators in a data set into a smaller number of ‘dimensions’. In mathematical terms, from an initial set of n correlated indicators, PCA creates uncorrelated indices or components, where each component is a linear weighted combination of the initial indicators. Indeed, if the original indicators are uncorrelated then the analysis does absolutely nothing. The best results are obtained when the original indicators are very highly correlated, positively or negatively.

Each component is a linear combination of indicators (variables) multiplied by their loadings on that component. Large values of loadings of the variables (i.e. indicators) on the PCs imply that the indicator has a large bearing on the creation of that component. Thus, the most important indicators in each component, that best explain variance; will also be more useful in explaining variability between observations (i.e. districts).

The variance (λi) for each principal component is given by the eigenvalue of the corresponding eigenvector. The components are ordered so that the first component (PC1) explains the largest possible amount of variation in the original data. As the sum of the eigenvalues equals the number of indicators in the initial data set, the proportion of the total variation in the original data set accounted by each principal component is given by (λi)/n. The second component (PC2) is completely uncorrelated with the first component, and explains additional but less variation than the first component, subject to the same constraint. Subsequent components are uncorrelated with previous components; therefore, each component captures an additional dimension in the data, while explaining smaller and smaller proportions of the variation of the original indicators. The higher the degree of correlation among the original indicators in the data, the fewer components required to capture common information.

Steps

For M regions /districts, K indicators of vulnerability, PCA extracts K linear functions, called principal components as follows.

From k original variables: X1, X2,...,Xk, produce k new variables: P1, P2,...,Pk:

P1 = a11X1 + a12X2 + ... + a1kXk

P2 = a21X1 + a22X2 + ... + a2kXk

Pk = ak1X1 + ak2X2 + ... + akkXk

such that Pk’s are uncorrelated, P1 explains as much as possible of original variance in data set, P2 explains as much as possible of remaining variance etc. Pk’s are Principal Components.((a11,a12,...,a1k)) is coefficients of first principal component (1st Eigenvector of correlation/covariance matrix).In practice, only the first few components arc sufficient to account for a substantial proportion of the total variation. The essential steps in the computation of principal components,

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applicable to the constriction of vulnerability indices, are as follows:

• Arrange the data in the form of a matrix, rows representing regions (M) and columns arc indicators (K).

• Normalize the values to take into account functional relationships between indicators and vulnerability.

• Compute the correlation matrix.

• Compute the Eigen values and Eigen vectors of the correlation matrix. Each Eigen value represents a portion of the total variance.

• Arrange the Eigen values in descending order of magnitude. Retain Eigen vectors up to a desired level of significance and leave the remaining insignificant ones. Cumulative proportion of variance is used to determine the amount of variance that the principal components explain and finally retain the principal components that explain an acceptable level of variance. Components with Eigen value greater than 1 have been used to calculate the weights (Kaiser, 199043. In essence this is like saying that, unless a factor extracts at least as much as the equivalent of one original variable, it is dropped.

• Each component is a linear combination of indicators multiplied by their loadings on that component. Large values of loadings of the indicators on the PCs (Principal Components) imply that the variable has a large bearing on the creation of that component.

• The PCA (Principal Component Analysis) is used to compute the factor loadings and weights of the indicators. In order to derive the weights of the variable the matrix of loadings are rotated by Varimax Kaiser Normalization criteria.44 Absolute values of the eigenvectors or the loadings are considered in order to derive the weights. To derive the weights following formula is used:

= Σ|Lij|.Ej where j=1, 2, 3,....n

43 Kaiser, H. F. (1960). The application of electronic computers to factor analysis. Educational and Psychological Measurement, 20, 141-151.44 Varimax rotation is an orthogonal rotation of the factor axes to maximize the variance of the squared loadings of a factor (column) on all the indicators (rows) in a factor matrix, which has the effect of differentiating the original indicators by extracted factor. Each factor will tend to have either large or small loadings of any particular variable. A varimax solution yields results which make it as easy as possible to identify each variable with a single factor. This is the most common rotation option.

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wiis the weights of the variables, Lij is the component loading of the ith variable on the jth component; Ej is the Eigen value of the jth component. Taking the Eigen values and component loadings the weights of the indicators are derived according to the above equation45.

Calculation of Indices

𝑁𝑁𝑁𝑁 = [X − minimum (X)][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [ maximum (X) − X ][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [X − minimum (X)][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [X − 169.2][270.9 – 169.2]

𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 = [210.4 − 169.2][270.9 – 169.2] = 0.405

𝑁𝑁𝑁𝑁 = [ maximum (X) − X ][maximum (X) – minimum (X)]

𝑁𝑁𝑁𝑁 = [81.1 − X][81.1 – 36.1]

𝐿𝐿𝑆𝑆𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 = [81.1 – 36.1][81.1 – 36.1] = 1.0

𝑁𝑁𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉 𝐼𝐼𝑉𝑉𝐼𝐼𝑉𝑉𝐼𝐼, 𝑁𝑁𝐼𝐼 = 1𝑉𝑉 [∑(𝐴𝐴𝐴𝐴𝑉𝑉𝑉𝑉𝑉𝑉𝐴𝐴𝑉𝑉 𝐼𝐼𝑉𝑉𝐼𝐼𝑉𝑉𝐼𝐼𝐴𝐴)𝛼𝛼

𝑛𝑛

𝐴𝐴=1]

1 𝛼𝛼⁄

𝑉𝑉�̅�𝑖 = ∑ 𝑤𝑤𝐴𝐴𝐼𝐼𝐴𝐴𝐴𝐴

𝐾𝐾

𝐴𝐴=1(0 < 𝑤𝑤 < 1 𝑉𝑉𝑉𝑉𝐼𝐼 ∑ 𝑤𝑤𝐴𝐴 = 1

𝐾𝐾

𝐴𝐴=1)

𝑤𝑤𝐴𝐴 = 𝑐𝑐√𝐴𝐴𝑉𝑉𝑉𝑉𝐴𝐴(𝐼𝐼𝐴𝐴𝐴𝐴)⁄

𝑐𝑐 = [∑ 1√𝐴𝐴𝑉𝑉𝑉𝑉𝐴𝐴(𝐼𝐼𝐴𝐴𝐴𝐴)⁄

𝑘𝑘

𝐴𝐴=1]

−1

𝑁𝑁𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉 𝐼𝐼𝑉𝑉𝐼𝐼𝑉𝑉𝐼𝐼 = ⌊∑(𝑤𝑤𝐴𝐴 ∗ 𝑁𝑁𝑁𝑁𝐴𝐴)𝑛𝑛

𝐴𝐴=1⌋

Where, i = 1 ……..n is the number of indicators, w= weights, NV = Normalized value

Higher index value represents high vulnerability while lower index value represents low vulnerability.

Cluster AnalysisCluster analysis or clustering is the task of assigning a set of objects into groups (called clusters) Cluster analysis is a class of statistical techniques that can be applied to data that exhibit “natural” groupings. Cluster analysis sorts through the raw data and groups them into clusters. A cluster is a group of relatively homogeneous cases or observations. Objects in the same cluster are more similar (in some sense or another) to each other than to those in other clusters.Statistics associated with cluster analysis include:

• Agglomeration schedule: An agglomeration schedule gives information on the objects or cases being combined at each stage of a hierarchical clustering process.

• Cluster centroid: The cluster centroid is the mean values of the variables for all the cases or objects in a particular cluster.

• Cluster centres: The cluster centres are the initial starting points in non-hierarchical clustering. Clusters are built around these centres, or seeds.

• Cluster membership: Cluster membership indicates the cluster to which each object or case belongs.

• Distances between cluster centres: indicate how separated the individual pairs of clusters are. Clusters that are widely separated are distinct, and therefore desirable.

45 An Investigation into the Inter-District Disparity in West Bengal, 1991-2005: Ajitava Raychaudhuri, Sushil Kr Haldar

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Derive Projected Vulnerability Category w.r.t. Baseline

The projected vulnerability categories (VC) are derived based on the baseline VC generated by baseline vulnerability calculations. Steps involved include:

1. Normalise indicators for baseline (stand alone).

2. Derive baseline indicator weights using PCA.

3. Generate baseline composite index values using weights derived from step2 and assign VC based on cluster analysis.

4. Normalise indicators for projected period along with baseline.

5. The weights obtained in step2 for baseline (stand alone) are then used to calculate the new baseline and projected index values (normalized values of indicators multiplied by respective indicators weight derived from baseline stand alone).

6. Projected index values are subtracted from revised baseline index value obtained in step5 to generate new index value for projected period.

7. New index value for projected period obtained from step6 is then added to the original stand alone base line index from step3 (to adjust projected index values with respect to the baseline index values for comparison).

8. Adjusted projected index values and baseline index values are categorised into vulnerability categories.

Appendix III Adaptation Planning Exercise

Develop adaptation plans for water, agriculture sector using the vulnerability index, sectoral briefs and adaptation tool kit.

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e-g

ory

Ran

kIn

dex

va

lue

Cat

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ory

Ran

kIn

dex

va

lue

Cat

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ory

Nar

sim

hap

ur1

0.23

3V

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0.24

2V

L3

0.25

4V

L2

0.24

9V

L1

0.20

6V

L

Anu

pp

ur2

0.29

8V

L5

0.35

9V

L3

0.32

1V

L5

0.35

2V

L2

0.30

7V

L

Din

do

ri3

0.34

1V

L7

0.41

3L

60.

373

VL

50.

367

VL

40.

351

VL

Um

aria

30.

341

VL

80.

430

L5

0.37

2V

L7

0.40

7L

40.

349

VL

Har

da

50.

360

VL

30.

328

VL

30.

31V

L5

0.36

3V

L2

0.28

1V

L

Man

dla

60.

385

L9

0.43

1L

70.

412

L7

0.40

5L

60.

394

L

Jab

alp

ur7

0.41

1L

110.

454

L9

0.43

5L

130.

461

L8

0.41

8L

Shah

do

l8

0.43

9L

190.

506

M11

0.46

3L

190.

505

M10

0.45

9L

Rais

en9

0.44

5L

130.

465

L10

0.45

8L

130.

467

L8

0.43

4L

Sing

raul

i10

0.45

4L

110.

46L

90.

444

L11

0.46

1L

70.

417

L

Dam

oh

110.

459

L17

0.49

1M

150.

478

M17

0.49

1M

140.

469

L

Kat

ni12

0.46

2L

250.

531

H17

0.49

1M

250.

530

H12

0.46

3L

Sid

hi13

0.47

6M

160.

493

M12

0.46

6L

160.

492

M7

0.43

L

Seo

ni14

0.48

2M

190.

508

M16

0.49

5M

140.

479

M12

0.46

8L

Seho

re15

0.49

0M

170.

492

M14

0.47

8M

190.

506

M9

0.44

7L

Bal

agha

t16

0.49

1M

220.

516

M18

0.49

6M

150.

480

M18

0.49

7M

Ash

okn

agar

170.

495

M22

0.52

1M

130.

472

M20

0.51

2M

140.

482

M

Vid

isha

180.

504

M25

0.53

7H

180.

503

M23

0.53

4H

170.

501

M

Dat

ia19

0.51

1M

420.

628

H20

0.51

4M

360.

603

H9

0.45

2L

Page 80: Climate change Impacts, Vulnerability and Adaptation ... · Training Module - Climate Change Impacts, Vulnerability and Adaptation Planning in Water 3. on the climate change issues.

Trainin

g M

od

ule - C

limate C

han

ge Im

pacts, V

uln

erability an

d A

dap

tation

Plan

nin

g in

Water

80

RC

P4

.5R

CP

8.5

B

asel

ine

Mid

-Cen

tury

En

d-C

entu

ry

Mid

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tury

En

d-C

entu

ry

Dis

tric

tsR

ank

Ind

ex

valu

eC

ate-

go

ryRa

nkIn

dex

va

lue

Cat

e-g

ory

Ran

kIn

dex

va

lue

Cat

e-g

ory

Ran

kIn

dex

va

lue

Cat

e-g

ory

Ran

kIn

dex

va

lue

Cat

e-g

ory

Pann

a20

0.51

9M

270.

556

H20

0.51

7M

250.

545

H8

0.45

L

Sag

ar21

0.52

2M

270.

553

H25

0.53

8H

260.

551

H22

0.52

9H

Ho

shan

gab

-ad

220.

534

H21

0.52

8M

210.

525

M23

0.53

6H

160.

502

M

Bho

pal

230.

544

H28

0.57

2H

210.

532

H27

0.56

6H

170.

511

M

Tika

mg

arh

240.

552

H38

0.63

5V

H26

0.56

3H

370.

627

H17

0.50

7M

Satn

a25

0.55

6H

350.

610

H24

0.54

8H

340.

606

H16

0.50

2M

Chh

atar

pur

260.

557

H38

0.62

8H

280.

565

H37

0.62

1H

180.

512

M

Chh

ind

war

a27

0.56

0H

270.

558

H23

0.53

9H

220.

534

H20

0.52

7M

Rew

a28

0.56

1H

340.

599

H28

0.56

H34

0.60

2H

140.

49M

Shaj

apur

290.

571

H36

0.60

8H

300.

579

H33

0.59

5H

220.

535

H

Gun

a30

0.57

3H

350.

603

H25

0.54

5H

330.

594

H27

0.55

6H

Rajg

arh

310.

583

H38

0.62

H29

0.57

3H

370.

611

H25

0.55

1H

Shiv

pur

i32

0.58

8H

450.

668

VH

380.

611

H44

0.66

4V

H31

0.58

1H

Bet

ul33

0.59

6H

290.

572

H24

0.54

1H

280.

562

H20

0.52

4M

Sheo

pur

330.

596

H43

0.66

7V

H36

0.61

H42

0.66

2V

H23

0.53

7H

Kha

ndw

a35

0.59

8H

320.

581

H27

0.55

6H

340.

590

H24

0.53

7H

Dew

as36

0.60

2H

320.

580

H33

0.58

1H

340.

589

H25

0.54

4H

Jhab

ua37

0.60

4H

310.

578

H21

0.52

1M

330.

589

H12

0.47

1M

Nee

muc

h38

0.60

9H

460.

666

VH

350.

595

H46

0.66

8V

H30

0.57

H

Gw

alio

r39

0.62

0H

500.

757

VH

440.

660

VH

500.

747

VH

330.

588

H

Ujja

in39

0.62

0H

420.

637

VH

380.

611

H40

0.62

3H

280.

559

H

Page 81: Climate change Impacts, Vulnerability and Adaptation ... · Training Module - Climate Change Impacts, Vulnerability and Adaptation Planning in Water 3. on the climate change issues.

Trainin

g M

od

ule - C

limate C

han

ge Im

pacts, V

uln

erability an

d A

dap

tation

Plan

nin

g in

Water

81

RC

P4

.5R

CP

8.5

B

asel

ine

Mid

-Cen

tury

En

d-C

entu

ry

Mid

-Cen

tury

En

d-C

entu

ry

Dis

tric

tsR

ank

Ind

ex

valu

eC

ate-

go

ryRa

nkIn

dex

va

lue

Cat

e-g

ory

Ran

kIn

dex

va

lue

Cat

e-g

ory

Ran

kIn

dex

va

lue

Cat

e-g

ory

Ran

kIn

dex

va

lue

Cat

e-g

ory

Ratla

m41

0.64

6V

H43

0.66

4V

H39

0.62

6H

410.

649

VH

320.

593

H

Ind

ore

420.

648

VH

390.

621

H32

0.58

9H

380.

619

H25

0.54

5H

Man

dsa

ur43

0.66

9V

H45

0.71

0V

H41

0.66

3V

H44

0.70

2V

H39

0.63

7V

H

Bur

hanp

ur44

0.68

6V

H44

0.69

2V

H41

0.64

9V

H43

0.66

5V

H35

0.60

3H

Kha

rgo

ne45

0.71

1V

H43

0.66

9V

H39

0.63

1H

440.

703

VH

340.

604

H

Mo

rena

450.

711

VH

480.

816

EH44

0.70

6V

H47

0.80

9EH

390.

632

H

Bhi

nd47

0.71

9V

H49

0.82

8EH

480.

746

VH

490.

823

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0.66

2V

H

Alir

ajp

ur48

0.72

0V

H47

0.70

8V

H39

0.62

4H

470.

713

VH

350.

603

H

Dha

r49

0.72

5V

H46

0.68

9V

H42

0.64

6V

H48

0.71

5V

H38

0.61

9H

Bar

wan

i50

0.74

2V

H47

0.70

2V

H44

0.66

1V

H50

0.74

0V

H42

0.64

1V

H

Page 82: Climate change Impacts, Vulnerability and Adaptation ... · Training Module - Climate Change Impacts, Vulnerability and Adaptation Planning in Water 3. on the climate change issues.

Trainin

g M

od

ule - C

limate C

han

ge Im

pacts, V

uln

erability an

d A

dap

tation

Plan

nin

g in

Water

82

Tab

le 9

: Dis

tric

t w

ise

agri

cult

ure

vu

lner

abili

ty In

dex

val

ues

, ran

ks a

nd

vu

lner

abili

ty c

ateg

ory

un

der

cu

rren

t an

d p

roje

cted

clim

ate

scen

ario

s

RC

P4

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CP

8.5

Ba

selin

eM

id-C

entu

ryE

nd

-Cen

tury

M

id-C

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ryE

nd

-Cen

tury

Dis

tric

tsRa

nkIn

dex

va

lue

Cat

e-g

ory

Rank

Ind

ex

valu

eC

ate-

go

ryRa

nkIn

dex

va

lue

Cat

e-g

ory

Rank

Ind

ex

valu

eC

ate-

go

ryRa

nkIn

dex

va

lue

Cat

e-g

ory

Har

da

10.

454

VL

10.

453

VL

00.

426

VL

00.

435

VL

00.

411

VL

Ho

shan

gab

-ad

20.

464

VL

20.

453

VL

10.

431

VL

10.

438

VL

00.

407

VL

Sheo

pur

30.

481

VL

30.

479

VL

20.

465

VL

20.

466

VL

10.

443

VL

Nee

muc

h4

0.48

5V

L4

0.48

6V

L2

0.45

7V

L3

0.47

9V

L1

0.43

8V

L

Jab

alp

ur5

0.50

6L

40.

493

VL

30.

482

VL

40.

49V

L2

0.45

9V

L

Vid

isha

60.

514

L6

0.51

2L

30.

482

VL

40.

495

VL

10.

451

VL

Bho

pal

70.

515

L8

0.51

7L

40.

484

VL

50.

496

VL

10.

451

VL

Gw

alio

r8

0.52

0L

80.

518

L6

0.51

0L

60.

507

L4

0.48

6V

L

Dew

as9

0.52

5L

100.

526

L5

0.50

1L

70.

513

L2

0.47

1V

L

Ind

ore

90.

525

L8

0.52

L5

0.49

8L

60.

511

L2

0.46

8V

L

Ratla

m11

0.52

7L

100.

525

L6

0.50

1L

60.

51L

30.

479

VL

Rais

en12

0.53

2L

100.

522

L6

0.49

8L

70.

51L

30.

47V

L

Man

dsa

ur13

0.53

3L

120.

532

L7

0.50

7L

100.

522

L4

0.48

2V

L

Ujja

in14

0.53

4L

150.

535

L7

0.51

0L

100.

519

L3

0.47

7V

L

Tika

mg

arh

150.

535

L14

0.53

4L

90.

515

L11

0.52

0L

60.

489

VL

Seho

re16

0.53

7L

170.

54L

90.

511

L11

0.52

L4

0.47

9V

L

Shaj

apur

170.

545

L17

0.54

6L

100.

518

L13

0.52

8L

50.

487

VL

Page 83: Climate change Impacts, Vulnerability and Adaptation ... · Training Module - Climate Change Impacts, Vulnerability and Adaptation Planning in Water 3. on the climate change issues.

Trainin

g M

od

ule - C

limate C

han

ge Im

pacts, V

uln

erability an

d A

dap

tation

Plan

nin

g in

Water

83

RC

P4

.5R

CP

8.5

Ba

selin

eM

id-C

entu

ryE

nd

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tury

M

id-C

entu

ryE

nd

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tury

Dis

tric

tsRa

nkIn

dex

va

lue

Cat

e-g

ory

Rank

Ind

ex

valu

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go

ryRa

nkIn

dex

va

lue

Cat

e-g

ory

Rank

Ind

ex

valu

eC

ate-

go

ryRa

nkIn

dex

va

lue

Cat

e-g

ory

Dat

ia18

0.54

6L

190.

548

L17

0.54

3L

150.

534

L10

0.51

5L

Dha

r18

0.54

6L

140.

532

L9

0.51

3L

120.

525

L6

0.49

6V

L

Bhi

nd20

0.54

7L

210.

549

L19

0.54

5L

180.

540

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0.51

6L

Bur

hanp

ur21

0.54

8L

200.

546

L14

0.52

5L

180.

538

L18

0.54

L

Alir

ajp

ur22

0.55

1L

190.

542

L12

0.51

9L

150.

532

L13

0.52

4L

Rajg

arh

230.

558

L23

0.55

8L

140.

525

L18

0.53

8L

80.

498

L

Chh

ind

war

a24

0.56

1L

220.

552

L18

0.53

8L

210.

549

L14

0.52

5L

Shiv

pur

i25

0.57

3M

250.

573

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0.55

6L

220.

556

L15

0.53

2L

Kha

rgo

ne26

0.57

5M

250.

565

L19

0.54

3L

230.

559

L16

0.53

4L

Kha

ndw

a27

0.57

6M

260.

570

M21

0.54

9L

240.

561

L18

0.54

0L

Gun

a28

0.57

8M

280.

581

M23

0.55

3L

240.

558

L13

0.52

3L

Nar

sim

hap

ur29

0.58

5M

270.

571

M22

0.54

9L

250.

564

L14

0.52

4L

Chh

atar

pur

300.

586

M29

0.57

7M

250.

561

L27

0.56

8M

160.

527

L

Bar

wan

i31

0.58

9M

280.

575

M24

0.55

7L

280.

575

M23

0.54

9L

Ash

okn

agar

320.

594

M32

0.59

3M

270.

565

L27

0.56

7L

200.

541

L

Bet

ul33

0.59

9M

310.

585

M27

0.56

5L

280.

571

M23

0.54

8L

Seo

ni34

0.61

6H

320.

602

M30

0.58

9M

320.

600

M29

0.58

5M

Jhab

ua35

0.62

5H

330.

615

H31

0.59

6M

320.

604

M28

0.57

9M

Sag

ar36

0.62

7H

340.

614

H31

0.59

4M

330.

604

M25

0.56

4L

Mo

rena

370.

628

H36

0.61

9H

340.

606

M34

0.60

6M

300.

586

M

Dam

oh

380.

634

H36

0.62

0H

330.

602

M35

0.61

0H

280.

572

M

Rew

a39

0.64

5H

390.

639

H35

0.61

5H

370.

628

H31

0.58

9M

Page 84: Climate change Impacts, Vulnerability and Adaptation ... · Training Module - Climate Change Impacts, Vulnerability and Adaptation Planning in Water 3. on the climate change issues.

Trainin

g M

od

ule - C

limate C

han

ge Im

pacts, V

uln

erability an

d A

dap

tation

Plan

nin

g in

Water

84

RC

P4

.5R

CP

8.5

Ba

selin

eM

id-C

entu

ryE

nd

-Cen

tury

M

id-C

entu

ryE

nd

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tury

Dis

tric

tsRa

nkIn

dex

va

lue

Cat

e-g

ory

Rank

Ind

ex

valu

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go

ryRa

nkIn

dex

va

lue

Cat

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ory

Rank

Ind

ex

valu

eC

ate-

go

ryRa

nkIn

dex

va

lue

Cat

e-g

ory

Pann

a40

0.64

6H

390.

636

H36

0.61

7H

380.

627

H31

0.58

3M

Satn

a41

0.64

7H

400.

638

H37

0.61

6H

380.

625

H32

0.58

6M

Kat

ni42

0.66

1V

H41

0.65

3H

390.

635

H40

0.64

7H

340.

603

M

Sid

hi43

0.66

5V

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0.66

5V

H39

0.63

H41

0.64

9H

350.

607

M

Shah

do

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0.67

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0.67

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0.64

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430.

665

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380.

622

H

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raul

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0.67

4V

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0.67

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0.64

3H

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Um

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460.

675

VH

460.

674

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430.

653

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0.67

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450.

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, VH

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