Overview of Drought Indicators and their Application in the Context of a

Drought Early Warning and Information System

Mark Svoboda, Climatologist/Monitoring Program Area Leader

National Drought Mitigation Center

NOAA’s Drought Risk Management Research Center

University of Nebraska-Lincoln

NENA Regional Water/Drought Platform Stakeholders Workshop

Cairo, Egypt, October 27-29, 2015

The Cycle of Disaster Management

Provide a template for action that countries can use in the development of a national drought management policy and drought preparedness/mitigation plans

The process is structured in 10 steps that can be adapted by countries to reflect their institutional, infrastructure, legal, socio-economic and environmental context

Case studies from Brazil, Mexico, Morocco and the USA and will be continuously updated based on the experiences gained in the guidelines’ application

The guidelines respond to a need for action oriented drought policies

IDMP Guidelines

Drought Plan Components

Monitoring and early warning Integrate and distill information

Assess, communicate, and trigger action

Foundation of a drought mitigation plan

Vulnerability assessment Who and what is at risk and why?

Mitigation and response actions Actions/programs that reduce risk and impacts and enhance recovery

Most processes and plans in the past have primarily focused on monitoring and response...

The Importance of Drought Early Warning and Information

Systems (DEWIS)

Allows for early drought detection Improves response (proactive) Data and tools for decision support “Triggers” actions within a drought plan A critical mitigation action Foundation of a drought plan

Components of a Drought Early Warning and Information System

(DEWIS)

Monitoring AND Forecasting Access to timely data (including impacts)and “value added” information Synthesis/analysis of data used to “trigger” set actions within a drought plan Tools for decision makers Efficient dissemination/communication (WWW, media, extension, etc.) Drought risk assessment and planning Education and Awareness

Types of Drought:

Meteorological

Agricultural

Hydrological

Socioeconomic

There are indicators and indices for all of these types of drought

There is no one definition of drought

Thus, there is typically no “one size fits all” drought index or indicator

Spatial Extent

Definitions: Indicators, Indices and Triggers

Indicators: Variables or parameters used to describe drought conditions. (NOTE: Indices are Indicators as well)

Examples: precipitation, temperature, streamflow, groundwater, reservoir levels, snowpack, soil moisture, drought indices, etc.

Indices: Typically a computed numerical representation of a drought’s severity/intensity using climatic, hydrologic, or remotely sensed inputs.

Definitions: Indicators, Indices and Triggers

Triggers: Specific values of an indicator/indice that initiate and/or terminate each level of a drought plan, and associated management responses.

Who is accountable to do what and when? Ties back to the plan!

Examples: 6-mo SPI below the 5th percentile for two consecutive months Level 4 Drought

OR…

3-mo SPI above the 30th percentile for three consecutive months No Drought

What Questions Do Drought Indicators/Indices Help Answer?

How does the drought compare historically?

How often does a drought of this magnitude happen? (frequency/return periods)

When was the last time a drought like this happened? (analogs)

What did the spatial footprint of the last drought look like? (areal extent via maps)

Expand drought planning horizons? Add paleo (tree rings) data in the future?

Importance of Drought Indices

Simplify complex relationships and provide a good communication tool for diverse audiences/users

Quantitative assessment of anomalous climatic conditions

Intensity

Duration

Spatial extent

Historical reference (probability of recurrence)

Planning and design applications

Considerations for Choosing Indicators / Triggers

Proper and Timely Detection of Drought

Spatial and Temporal Sensitivity

Supplies and Demands

Drought In / Drought Out

Composite and/or Multiple Indicators

Data availability/stability, period of record, and validity

Ease of Implementation

Validation….do they match the impacts/reality of the situation on the ground?

Approaches to Drought Assessment

Single index or indicator (parameter) Multiple indices or indicators

Assessed stand-alone

Composite (or “hybrid”) Indicator Blended approach

http://www.droughtmanagement.info/

The purpose of this handbook is to identify some of the most commonly used physically-based drought indicators/indices that are being applied across drought-prone regions with the goal of advancing monitoring, early warning and information delivery systems in support of risk-based drought management policies and preparedness plans.

Monitoring Drought: A Handbook

of Indicators and Indices

The guide is intended to be used by the general drought practitioner (e.g. Meteorological/Hydrological service, Ministry level, resource managers and other decision makers at various levels) and was intended to serve as a potential starting point to determine which indicators/indices are available and being put into practice around the world.

Monitoring Drought: A Handbook

of Indicators and Indices

The indicators and indices covered are aimed at the physical nature of drought and do not cover overlap issues such as climate change, vulnerability assessment, risk, aridity, desertification or water scarcity, all of which play a role in how drought needs to be monitored and addressed.

Monitoring Drought: A Handbook of

Indicators and Indices

The indicator/index types are grouped into the following classifications: which directly correspond to the meteorological, agricultural and hydrological drought types: 1) temperature and/or precipitation; 2) soil moisture; 3) hydrological; 4) satellite and vegetation; and 5) composite, modeled or experimental

Monitoring Drought: A Handbook of

Indicators and Indices

For the “ease of use” classification, a “traffic light” approach for each indicator/index was adopted where:

Green: Indices are considered to be green if one or more of the following criteria apply:

Code or program to run the index is readily and freely available

Does not require daily data

Does allow for missing data

Output of the index is already being produced operationally and is made available on the web

Monitoring Drought: A Handbook of

Indicators and Indices

Note: While a “green” ease of use classification may imply that the indicator/indice may be the easiest to obtain or use, it does not mean it is the best index/indicator for any given region or locale. This decision as to which indicator(s)/indices to use has to be determined by the user and depends on the given application(s).

Monitoring Drought: A Handbook of

Indicators and Indices

Yellow: Indices are considered to be yellow if one or more of the following criteria apply:

Multiple variables or inputs needed for calculations

Code or program to run the index is not available in a public domain

May only need a single input or variable, but no code is available

The complexity of the calculations needed to produce the index is minimal

Monitoring Drought: A Handbook of

Indicators and Indices

Red: Indices are considered to be red if one or more of the following criteria apply:

Would need to develop code to calculate the index based upon the methodology in the literature

The index or derivative products are not readily available

An obscure index which is not widely used, but may be applicable to some

Any index which contains modeled input or is part of the calculations

Monitoring Drought: A Handbook

of Indicators and Indices

Meteorological Based Page

Ease of

Use Inputs

Required Additional Information

Aridity Anomaly Index (AAI) Green P,T, PET, ET Operationally available for India

Deciles Green P

Ease of calculation and examples from Australia useful

Keetch-Byram Drought Index (KBDI) Green P,T

KBDI calculations are based upon the climate of the area of interest

Percent of Normal Precipitation Green P Simple calculations

Standardized Precipitation Index (SPI) Green P

The WMO highlighted the SPI as a starting point for meteorological drought monitoring

Weighted Anomaly Standardized Precipitation (WASP) Green P,T

Uses gridded data in monitoring drought in tropical regions

Aridity Index (AI) Yellow P, T Can also be used in climate classifications

China Z Index (CZI) Yellow P

Intended to improve upon what the SPI provides

Crop Moisture index (CMI) Yellow P,T Weekly values are needed

Drought Area Index (DAI) Yellow P

Gives an indication of how the monsoon season perform

Drought Reconnaissance Index (DRI) Yellow P, T

Monthly temperature and precipitation needed

Effective Drought Index (EDI) Yellow P

Program is available through direct contact with originator

Hydro-Thermal Coefficient (HTC) Yellow T,P

Ease in calculations and several examples in Russia

NOAA Drought Index (NDI) Yellow P

Best used in agricultural applications

Palmer Drought Severity Index (PDSI) Yellow P,T, AWC

Not green due to complexity of calculations and the need for serially complete data

Palmer Z Index Yellow P,T, AWC One of the many outputs of the Palmer Drought Severity Index calculations

Rainfall Anomaly Index (RAI) Yellow P Serially complete data required

Self-Calibrated Palmer Drought Severity Index (sc-PDSI) Yellow P,T, AWC

Not green due to complexity of calculations and serially complete data needed

Standardized

Anomaly Index (SAI)

Yello

w P

Point data used to describe regional

conditions

Standardized

Precipitation

Evapotranspiration

Index (SPEI)

Yello

w P, T

Serially complete data required, output

similar to the SPI but with a

temperature component

Agricultural

Reference Index for

Drought (ARID) Red P,T, Mod

Regionally produced in the

southeastern United States and not

tested widely outside of the region

Crop Specific

Drought Index

(CSDI) Red

P,T,Td,W,

Rad,AWC,

Mod,crop

data

Quality data of many variables needed,

making its use a challenge

Reclamation

Drought Index (RDI) Red P,T,S,R, SF

Similar to the SWSI, but contains a

temperature component

Soil Moisture Based

Ease

of

Use

Inputs

Needed Additional Information

Soil Moisture

Anomaly (SMA)

Yello

w P,T, AWC

Intended to improve upon the water

balance of the PDSI

Evapotranspiration

Deficit Index (ETDI) Red Mod

Complex calculations with multiple

inputs needed

Soil Moisture

Deficit Index (SMDI) Red Mod

Weekly calculations at different soil

depths, complicated to calculate

Soil Water Storage

(SWS) Red

AWC,RD,S

T,SWD

Due to variation in both soil and crop

types, interpolation over large areas is

challenging

Hydrological Based

Ease

of

Use

Inputs

Needed Additional Information

Index Name: Aridity Anomaly Index (AAI)

Ease of use: Green

Origins: Developed in India by the India Meteorological Department (IMD).

Characteristics: A real time drought index in which the water balance is considered. The Aridity Index

(AI) is computed for each week or bi-weekly period. For each period, the actual aridity for the period is

compared to the normal aridity for that period. Negative values indicate a surplus of moisture while

positive values indicate moisture stress.

Input parameters: Actual evapotranspiration and calculated potential evapotranspiration, which would

require temperature, wind, and solar radiation values.

Applications: Agricultural drought, especially in the tropics where defined wet and dry seasons are part

of the climate regime. Both the winter and summer cropping seasons can be assessed with this method.

Strengths: Specific to agriculture, the calculations are simple and the description of drought (mild,

moderate, severe) is based on the departure from normal. Will respond quickly with a weekly time step.

Weaknesses: Not applicable to long-term or multi-seasonal events.

Resources: http://www.imdpune.gov.in/research/drought/drought.html

References:

Indicator Summaries…

1) Typically, No single indicator/index is used solely in determining appropriate actions

2) Instead, different thresholds from different combinations of inputs is the best way to approach monitoring and triggers using a variety of indices and indicators

3) Decision making (or “triggers”) based on quantitative values are supported favorably and are better understood

Critical Observations:

Lessons Learned

Monitoring is the foundation of risk management planning

Trigger for who does what and when!

One can not manage what is not monitored….and you can’t monitor what you don’t measure!

Mark Svoboda msvoboda2@unl.edu

402-472-8238

http:/drought.unl.edu

Questions?

Photo Credit: Daniel Griffin