D422Lot1.SMHI.5.1.1B: Detailed workflows of each case ... · HYPE model setup: By using all...

C3S_422_Lot1_SMHI – D5.1.1B |

Copernicus Climate Change Service

D422Lot1.SMHI.5.1.1B:

Detailed workflows of each case-study

on how to use the CDS for CII

production and climate adaptation

Full Technical Report:

Climate Change Impacts to Water

Safety in the Greater Mekong region

Bui Du Duong, PhD

National Center for Water Resources Planning and Investigation (NAWAPI),

Ministry of Natural Resources and Environment (MONRE) of Vietnam

REF.: C3S_422_Lot1_SMHI D5.1.1B

C3S_422_Lot1_SMHI – D5.1.1B |


Summary

Srepok is a transboundary river basin and it is a major tributary in the Greater

Mekong River basin. The region is extremely vulnerable to adverse effects of

changing climate that result in droughts. Furthermore, considering the poor living

condition of local communities and the difficulties in reaching common

agreements in water management among national and international

stakeholders, assessing climate change impacts on the region through a drought

model is necessary for a better management of the river’s water.

Interactions with stakeholders through a survey show that many have a similar

perspective with the same views and requirements on water resources and

climate change information. They also reflect the proportion of users who are

working in water resources related fields. Most of them show concerns about

raising awareness or getting informed on climate indicators, especially with water

pollution, seawater intrusion, drought, etc.

The impacts of droughts in local, national and regional scale are severe and poor

local management can increase the outcomes, especially considering the future

scenario in a climate change prospective. The effect of using the climate service

covers an important role in technology and global open data in order to reduce

burden on local related infrastructures (e.g. reservoirs, gauged stations) while

facilitating access to information. Meanwhile, it allows decision makers to

understand and predict the likelihood of hazards, vulnerability of the system and

adopt the required measures.

Increasing access to open data sources including daily precipitation,

evapotranspiration, temperature, topography Digital elevation model (DEM), C3S

future scenarios, and multi-basin modelling tools helps the study bring useful

Essential Climate Variables (ECVs) and Climate Impact Indicators (CIIs) towards

drought risk reduction in the Greater Mekong region. The study results also show

that there are increasing demands on water resource and climate change

information from not only academic researchers and governmental decision

makers, but also from private interests. This study, together with the NAWAPI

interactive web-site, can help bridge the gap between institutes who provide

climate impact data on one side, and water managers and policy makers on the

other side, as well as providing users such as citizens, university students and

entrepreneurs a space to discover information for their purposes.


C3S_422_Lot1_SMHI – D5.1.1B |

Contents

1- Case study description ........................................................................................................ 4

1.1 Issue to be addressed ......................................................................................................... 4

1.2 Decision support to client .................................................................................................. 4

1.3 Temporal and spatial scale ............................................................................................... 4

1.4 Knowledge brokering ........................................................................................................... 4

2- Potential adaptation measures ........................................................................................ 5

2.1 Lessons learnt ........................................................................................................................ 5

2.2 Importance and relevance of adaptation .................................................................... 5

2.3 Pros and cons or cost-benefit analysis of climate adaptation ............................. 5

2.4 Policy aspects ......................................................................................................................... 5

3- Contact ...................................................................................................................................... 6

3.1 Purveyors ................................................................................................................................. 6

3.2 Clients/users ........................................................................................................................... 6

4- Data production and results ............................................................................................. 6

4.1 Step 1: Data collection and model setup .................................................................... 7

4.2 Step 2: Model calibration and validation ..................................................................... 9

4.3 Step 3: Model simulation and analysis ....................................................................... 10

4.4 Step 4: Climate Impact Indicators related to drought risks .............................. 11

5- Conclusion of full technical report ................................................................................ 21

References ......................................................................................................................................... 23


C3S_422_Lot1_SMHI – D5.1.1B | 4

1- Case study description

1.1 Issue to be addressed

Disaster events pose increasing threats to sustainable development in the

Greater Mekong region, including Srepok river basin. Nevertheless, lack of

consistent and coherent data does not allow policy makers to set adaptation plan

to climate change. Therefore, we aim to provide projected climate and

hydrological data and information, focusing on drought risks in a showcased

Srepok river basin to ensure its sustainable development and disaster resilience.

1.2 Decision support to client

The analysis is expected to provide information on how the frequency of

droughts has happened and increase/decrease in the future. The clients are local

functional departments, especially Mekong River Commission (MRC) and

Vietnamese Disaster Management Center (DMC), who are decision-makers. They

could base their decisions on these results to apply appropriate measures and

prepare adaptation, and mitigation plans in the near future. Accordingly, it is

expected that MRC and DMC could avoid huge economic losses and minimize

impacts on local people.

1.3 Temporal and spatial scale

The Srepok River basin with 86 sub-basins is explored. To facilitate both near

future and far future assessments, we provide the indicators for different time

ranges: reference period (1980-2015) and the expected future changes including

early century (2016-2040), mid-century (2041-2070) and end-century (2071-

2099).

1.4 Knowledge brokering

NAWAPI, as a governmental agency, has close operational relation with all local

functional departments, especially with MRC and Vietnamese Disaster

Management Center (DMC). NAWAPI and MRC have a long history of

collaboration in the management of the Greater Mekong River basin, where

NAWAPI operates in the national boundaries, while MRC is in charge of the entire

basin from an international prospective.

NAWAPI often collaborates with DMC providing forecasting information.

Furthermore, MONRE (Ministry of Natural Resources and Environment) delegates

both NAWAPI and the DMC in order to handle several national issues, supporting

their cooperation.


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2- Potential adaptation measures

2.1 Lessons learnt

The cooperation among the major institutions involved in the region has proven

itself a key tool in the management of water allocation and river basin

sustainable development. On one hand, a rapid information sharing between

NAWAPI and DMC plays an essential role in case of droughts, reducing the

dramatic outcomes of disaster events. On the other hand, a constant

communication between NAWAPI and MRC allows improving the cooperation

between Vietnam and Cambodia. Therefore, collecting data should be a priority

in the institution’s agenda in order to make more informed decisions.

2.2 Importance and relevance of adaptation

The impacts of droughts in local, national and regional scale are severe and a

bad management of the site increase the outcomes, especially considering the

future scenario in a climate change prospective. The effect of using the climate

service covers an important role in technology and global open data in order to

reduce burden on local infrastructures (reservoirs, gauged stations) while

facilitate access to information. Meanwhile, it allows decision makers to

understand and predict the likelihood of hazards, vulnerability of the system and

adopt the required measures.

2.3 Pros and cons or cost-benefit analysis of climate adaptation

Cost benefit analysis of climate adaptation is not available yet, but from previous

experiences, costs would be numerous if the adaptation measures are not

placed. Indeed, a weak preparation in prevention and protection from droughts

due to climate change would result in significant damages to infrastructure,

environment and human lives. A better understanding of these phenomena

ensures a more efficient management and a reduction in costs and risks.

2.4 Policy aspects

The Law on Water Resources is available at

http://www.wepa-db.net/policies/law/vietnam/lwr.htm.

The Law on natural disaster prevention and control is available at

https://www.preventionweb.net/english/policies/v.php?id=42335&cid=190.

http://www.wepa-db.net/policies/law/vietnam/lwr.htm

http://www.wepa-db.net/policies/law/vietnam/lwr.htm

https://www.preventionweb.net/english/policies/v.php?id=42335&cid=190


C3S_422_Lot1_SMHI – D5.1.1B | 6

3- Contact

3.1 Purveyors

Duong Du BUI, PhD, Director of Water Resources Monitoring Department,

National Center for Water Resources Planning and Investigation (NAWAPI),

Ministry of Natural Resources and Environment (MONRE) of Vietnam.

3.2 Clients/users

Mekong River Commission, National Disaster Management Authority, Center for

Water Res Forecasting and Warning and Local functional departments (natural

environment; agriculture and rural development)

4- Data production and results

Bias adjusted Essential Climate Variables (air temperature and precipitation on

daily time scale) for the historical period were used. This was combined with

monthly change factors from GCMs for future periods and for both RCPs 4.5 and

8.5 developed within the C3S_422_Lot1_SMHI contract, available in the CDS.

Data available from national databases (topography, soil type, river discharge,

evapotranspiration, population density, water demand, infrastructures and

management rule, drought and flood indicators) were collected. Calibration,

validation and accuracy assessment of the hydrological model were performed,

using the data from national databases. Hydrological simulations were performed

using as forcing the bias adjusted ECV to calculate CII for future periods. The

following analysis was performed: comparisons of ECVs and model output

(surface runoff and outflow; soil moisture deficit and potential

evapotranspiration) for historical period. Then CIIs related to drought risk were

calculated and drought risk was assessed based on the result analysis for

historical and future periods. Finally the results were communicated to

representatives of the national hydrology departments of member countries of

the Mekong River basin, especially Vietnam, Lao, and Cambodia.

http://www.nawapi.gov.vn/

http://monre.gov.vn/


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4.1 Step 1: Data collection and model setup

Data collection: To setup the hydrological model for modeling, a diversity of

data was collected Here we used the HYPE hydrological model. Data collection

included:

- Hydro-meteorological data: Precipitation, air temperature and river

discharge.

- Geographical data: Digital Elevation model, sub-basin area, soil type, land

use, hydrographical network

- Lake information: Depths, regulation rules, rating curve, water level

HYPE model setup: By using all collected data, the HYPE model was set up step

by step.

- Geographical and hydraulic network:

A 30×30 m DEM (Figure 1) which derived from open data of the U.S. Geological

Survey (USGS) was used. The HYPE model was set up for the whole of Srepok

(∼18,500 km2), including parts of Gia Lai, Dak Lak, Dak Nong and Lam Dong

with water discharging to Cambodia, with a total number of 86 sub-basins. Sub-

basin areas ranged between <30 km2 and >400 km2 (the latter including the

large lakes) with an average of 218 km2. (median = 170 km2).

The hydraulic network in the basin is dense (Figure 1) and there are lakes as

results of hydropower production, storing water. Lake depths were taken from

the No. 1201/QĐ - TTg dated 23 May 2014 on the issuance of operational

procedures associated reservoirs of Srepok river basin QĐ-Nr.12 (2014). Since

depth information is only available for few lakes, regression equations were

constructed and used for 5 lakes when estimating lake depth, with surface area

as the most important variable.


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Figure 1: DEM and drainage networks of the Srepok basin

- Land Use/Land Cover (LULC) and Soils

Srepok is mainly covered by forests (Figure 2), although there is a mountain

range in the southwest with plateaus. Forestry land is concentrated in the

southern part of Srepok, where most of the inhabitants live and the climate is

milder. This area has a population of 3 million inhabitants. Due to the region’s

forest, lakes are steady and the dominant soil type is basalt. The annual average

temperature is 23°C, with little variation between seasons, latitudes and

altitudes.

Figure 2: Summary of dominant LULC of Srepok


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- The Hydro-metrological data

The hydrological information of daily river discharge (Q) was obtained and

inputted to the HYPE from four on-site stream stations among five stations

located in the basin (Table 4). The location of the used station is marked (red

triangles) in the figure 1. The collection data time is from 2000 – 2009. Daily

rainfall data were recorded by 13 terrestrial rain gauges (Blue circles - figure 1) ,

and the daily maximum, minimum and averaged temperature of 9 Global

Forecast System (GFD) stations (blue square – figure 1) stations are used for the

inputs with the same period of 10 years.

The annual average temperature of the region is 23oC, with only slight variations

between seasons, latitudes and altitudes. The annual mean precipitation varies

from 1600 to 2700 mm. The dynamic forcing was obtained from daily

precipitation and temperature data sets for each sub-basin.

4.2 Step 2: Model calibration and validation

By using the collected data to fill up all HYPE model’s input requirement, the

calibration and validation were implemented in two periods: 2000-2005 and

2006-2009. Based on the comparison between simulated and observation value,

the HYPE parameters which are best fit with this Srepok area can be found. In

this process, we used the 13 ground rain gauges for calibration the discharge at

four stations of Giang Son, Cau 14, Ban Don and Duc Xuyen for the 2000-2005

periods.

In order to evaluate the calibration and to fix the calibrated values, we’ve

estimated the goodness of fit between simulated and observed Q based on the

values of RMSE, NSE, R2 and KGE. From Figure 3, it can be seen that Duc Xuyen

station was the weakest point of the model where all the coefficients showed the

low accuracy such as NSE, R2 and KGE under 0.5. In contrast, Ban Don and

Giang Son presented the most reliable parts of the model with highest values of

NSE, R2 and KGE. Although the accuracy assessment showed the model accuracy

was not homogeneous entire the watershed, the overall errors demonstrated the

model performance was acceptable.


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Figure 3. Daily and monthly HYPE discharge compared to in-situ measured data

in the model validation for the 2006-2009 periods at Giang Son, Cau 14, Ban

Don and Duc Xuyen stations

4.3 Step 3: Model simulation and analysis

The GCM data we have used in this study are provided within the

C3S_422_Lot1_SMHI contract and available in the Climate Data Store. The

calculations are based on daily time series of four Essential Climate Variables

(ECVs), namely mean, minimum and maximum near-surface air temperature,


C3S_422_Lot1_SMHI – D5.1.1B | 11

and precipitation. The ECVs are provided as downscaled and bias adjusted GCM

data using HydroGFD2.0 (Hydrological Global Forcing Data) as reference data.

HydroGFD is a merged data set of historical precipitation and temperature from

meteorological reanalysis and global observations (Berg et al., 2018). The spatial

resolution of the ECVs is 0.5 degree (about 50 km) on a regular global grid.

We defined a reference period and future periods for anomaly analysis for river

discharge as an implication for droughts or floods under climate change. To

estimate future climate conditions, we used the corresponding monthly change

values of the ECVs to modify the daily HydroGFD dataset used as input to HYPE.

Change values obtained for specific future time periods were thus used to create

representative datasets for HYPE modelling of these representative future

periods.

Emission Scenario

Scenarios for the evolution of greenhouse gas emissions are provided by

Representative Concentration Pathways (RCPs). The climate-modelling

community has developed four RCPs. In this study, we used two scenarios: low-

emission scenario RCP4.5 and high-emission scenario RCP8.5 to characterize

future climate change conditions. Ensemble monthly change factors from global

downscaled climate projections of precipitation, average, minimum and

maximum temperature from 18 GCM models ('ACCESS1-0', ‘ACCESS1-3’, ‘IPSL-

CM5B-LR’, HadGEM2-ES’, ‘HadGEM2-CC’, ‘BCC-CSM1.1(m)’, ‘EC-EARTH’ 'bcc-

csm1-1', 'BNU-ESM', 'CNRM-CM5', 'GFDL-CM3', 'GFDL-ESM2G', 'GFDL-ESM2M',

'inm-cm4', 'IPSL-CM5A-LR', 'IPSL-CM5A-MR', 'MPI-ESM-LR', 'MPI-ESM-MR',

'NorESM1-M') for different future periods.

Historical and future time periods

Any climate scenario must adopt a reference baseline period from which to

calculate changes in climate. The reference period usually represents present-

day climate. The projections are calculated relative to the baseline. In this study

three future periods have been chosen, in order to visualize the evolution of the

changes in the water availability over several decades. The following reference

period (baseline) and future periods were considered:

Reference period (historical): 1981-2015

Future periods: Upcoming: 2016-2040; Mid Century:2041-2070; Late Century:

2071-2099

4.4 Step 4: Climate Impact Indicators related to drought risks

The term "drought" has different meanings depending on how a water deficiency

affects them. Droughts have been classified into different types such as


C3S_422_Lot1_SMHI – D5.1.1B | 12

meteorological drought (lack of precipitation) and agricultural drought (lack of

soil moisture), but this also depends on how land use is classified. In another

aspect, urban areas need streamflow or groundwater for domestic water supply

plants, which can cause a deficit in soil moisture, leading to drought. Drought

impact can therefore be a function of drought risks and land use.

For the analyses done here, we define drought as a function of streamflow deficit

and adopt a threshold for streamflow deficit that we use as a general indicator

for drought. For the results presented below, drought is defined as those

occurrences where the mean streamflow deficit exceeds -50 m3s-1.

a. Historical simulations

This step provides an assessment over precipitation, soil moisture, streamflow

and groundwater anomalies over the baseline period of 1981-2015. This helps

decision makers to adopt the required measures in order to reduce the drought

risk in the area (Du et al., 2018).

Figure 4 illustrates the variation of the HydroGFD precipitation over the Srepok

river basin from 2001 to 2015. Values for the dry season months (December –

April) are shown in red. In the dry season of 2001, although the precipitation is

bigger than in 2004, the deficit in soil moisture, streamflow and groundwater is

less for almost all sub-basins (Figures 4 and 5). This can be explained by the

small rain for previous wet season. In 2010, it witnesses a small amount of

precipitation deficit, whereas soil moisture and streamflow saw an increase for a

few basins and less deficit in others

Figure 4: Change of the precipitation and soil moisture during dry season of Srepok river basin

from 2001 to 2010. The rectangles highlight three periods that were analysed in more detail.


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Figure 5 Change of the streamflow and groundwater during dry season of Srepok river basin from

2001 to 2010. The rectangles highlight three periods that were analysed in more detail.

Details from the three specific years of 2001, 2010 and 2004 are presented in

more detail in figures 6 – 11 to show how drought characteristics can be

analysed. The drought impact maps in figures 7, 9 and 11 show varying levels of

drought during the historic period. Drought is defined here as those occurrences

where the mean streamflow deficit is -50 m3s-1 or more. According to this

definition, there was no drought 2001, there was drought in parts of the Srepok

basin during 2010 and drought covered most of the basin during 2004.


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Figure 6: Maps of Precipitation Deficit and Soil Moisture Deficit in Srepok River Basin in 2001

Figure 7: Maps of Streamflow Deficit and Drought Impact in Srepok River Basin in 2001


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Figure 8: Maps of Streamflow Deficit and Soil Moisture Deficit in Srepok River Basin in 2010

Figure 9: Maps of Streamflow Deficit and Drought Impact in Srepok River Basin in 2010


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Figure 10: Maps of Streamflow Deficit and Soil Moisture Deficit in Srepok River Basin in 2004

Figure 11: Maps of Streamflow Deficit and Drought Impact in Srepok River Basin in 2004.


C3S_422_Lot1_SMHI – D5.1.1B | 17

b. Future simulations under climate change

This section presents projected hydrological anomalies as they were derived from

the hydrological model. As mentioned in section 4.3, we used the ensemble

mean of monthly change values from the 18 GCM climate projections in

combination with the HydroGFD time series as forcing. Precipitation and mean

temperature for two emission scenarios RCP 4.5 and RCP 8.5 were used. The

anomalies are calculated as relative change (in percent) with respect to the

baseline period for three future periods: early-century 2016-2040, mid-century

2041-2070 and late-century 2071-2099.

Drought impact is a function of drought risks and land use. Since land use is unknown in future, we only show streamflow anomalies. We assume that

negative anomalies are an indication of future drought risk and positive values indicate increasing flood risk in the respective future periods.

For the early-century (2016-2040), drought is generally shown to be more frequent as most of the Srepok basin shows negative streamflow anomalies

(Figure 12). The eastern areas in particular indicate trends toward more extreme drought with more pronounced negative anomalies.

Figure 12: Streamflow anomalies compared to historical reference period in RCP 4.5 scenario: (a)

Early-Century: 2016-2040; (b) Mid-Century period: 2041-2070; (c) Late-Century: 2071-2099.

For the mid-century period of 2041-2070 compared to the historical reference

period in the RCP 4.5 scenario, drought also tends to be more frequent than in

past. However, the severity is lower than shown for the early century and the

southwest area shows little change.

The late-century period of 2071-2099 shows more severe drought risk conditions

than either of the two earlier periods. As with the early century results, the

eastern areas indicate trends toward more extreme drought..


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Regarding streamflow anomalies for the RCP 8.5 scenario, the early-century

period shows the greatest drought risk, also more pronounced in eastern areas

of the basin, but the most severe is in the north (figure 13).

Figure 13: Streamflow anomalies compared to historical reference period in RCP 8.5 scenario. (d).

Early-Century: 2016-2040; (e) Mid-Century period: 2041-2070; (f) Late-Century: 2071-2099.

In the mid-century period the climate tends to be relatively normal compared

with past conditions. Some drought is indicated in the northern area whereas the

southwestern area indicates the potential for more flooding.

For the late-century period, conditions appear quite similar to the mid-century

period, with the exception that the southwestern areas show even more

tendency for wetter conditions.

Comparing the RCP 4.5 scenario to RCP 8.5, the climate change impacts on

streamflow appear more severe for RCP 4.5. In particular, RCP 4.5 indicates a

greater occurrence of increased drought risk. This was not expected and

warrants additional analysis. The fact that ensemble mean changes from the 18

GCMs were used may be a contributing factor. It would be worthwhile to

investigate in more detail the range of differences in monthly change factors

between the different GCM projection results. The results shown here may simply

be an indication that the precipitation changes from the GCM projections react

quite differently to increasing temperatures for this region.


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4.5. Step 5: Stakeholder communication and dissemination

The Stakeholder communication and dissemination took place through various

capacity building workshop and meetings organized throughout the project

(Figures 14 and 15). It saw the participation of the representatives of the

national hydrology departments of member countries of the Mekong River basin,

especially Vietnam, Lao, and Cambodia. The main objective of these workshops

was to share and get feedback from clients on the new hydrological products of

water information developed as part of the project implementation. Aspects

discussed during this workshop include:

Presentation of the project objectives and identification of sectoral

information needs by clients.

Exchanges of the case study results of hydrological modeling and climate

change impacts assessment with regional peers and clients;

Presentation of the interactive atlas and story map.

Figure 14: Capacity building workshop at NAWAPI on HYPE modeling

Figure 15: Presentation session of the

interactive atlas and client consultation on sectoral information needs

A part of case study is designed to collect information related to the demand of

information on climate change and water resources and other related indicators

in Vietnam which will be supported for policy decision of government as well as

for specific purposes from individuals to private sectors such as researchers,

entrepreneurs, etc. (Figure 16). Respondents focus on data in each level are

distinguished and among these national scale data is the most concern (Figure

17). As recommended information that could provide, reports are the main

materials that respondents want to have, followed by mapping, models (Figure

18).


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Figure 16: Purpose of using climate and hydrological data

Figure 17: Demographic information of respondents

Figure 18: Survey results on users request on water resources and climate

change information in Viet Nam


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Respondents represent the similar perspective group who has the same views

and demand on water resource and climate change information. They also reflect

the proportion of users who are work in and our water resources related fields.

Most of them concern about raising awareness or get informed the Climate

indicators, especially with water pollution, seawater intrusion, drought, etc. The

study results also indicate that not only academic researchers, governmental

decision makers have strong demand on water resource and climate change

information but also private requirements are very huge (Figure 18).

With the views of contributing to proof-of-concept and identifying target users

accompanied with specific demand for a Vietnam service website, the study helps

bring climate data useful in water-management decisions. It is a NAWAPI

interactive web-site (Figure 19) aims to bridge the gap between institutes who

provide climate-impact data on one side, and water managers and policy makers

on the other side as well as providing normal users as citizens, university

students, entrepreneurs a space to discover information for their private

purposes.

Figure 19: Development of WebGIS portal for sharing data and information from

the case study

5- Conclusion of full technical report The goal of this case study is using a global climate service to support drought

risk assessment in Srepok catchment, a part of Mekong basin. After calibration

and validation of HYPE model for periods 2000-2005 and 2006-2009, essential


C3S_422_Lot1_SMHI – D5.1.1B | 22

climate variables (in this case air temperature and precipitation) for historical

and future periods, available in the C3S Climate Data Store were collected, and

used as input to the impact models for simulating historical drought risk through

a number of deficit maps (precipitation, soil moisture, groundwater, streamflow).

The assessment of future drought was also made using ensemble global daily

downscaled climate projections for two emission scenarios RCP 4.5 and RCP 8.5

for three upcoming periods: (a) 2016-2040; (b) mid-century period: 2041-2070;

(c) end-century: 2071-2099.

This suggests that the C3S climate service is potentially applicable for general

local decision support related to drought assessment. The case study also

demonstrates that global data provided by C3S can be a cost-effective methods

supporting quick decision making in basin scale, particularly in un- or poorly

gauged basin. Open access to global climate data and model projections through

the CDS is helpful to improve resilience and adaptation to climate change.

This study support formulation of local policies that manage drought and allocate

water fairly among water user groups and local residents. These decisions have

large impacts on the local life and business activities. The methods and added

values of C3S for the Srepok River basin can be useful for similar studies in other

regions, including the Greater Mekong.

The cooperation among the major institutions involved in the region has proven

itself a key tool in the management of water allocation and river basin

sustainable development. A rapid information sharing between local, national

(NAWAPI, DMC) and regional (MRC) plays an essential role in case of droughts,

reducing the dramatic outcomes of disaster events. Therefore, producing data

and making them accessible should be a priority in order to make more informed

decisions.


C3S_422_Lot1_SMHI – D5.1.1B | 23

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Assessment of Freshwater Resources to Environmental Change: Mekong River Basin.

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Berg, P., Donnelly, C. and Gustafsson, D., 2018. Near-real-time adjusted reanalysis forcing

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https://lta.cr.usgs.gov/HYDRO1K

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