Climate Change Impact on Water Resources of Phakal Lake using

SWAT model

Sri Lakshmi Sesha Vani JResearch Scholar

NIT Warangal

Introduction

• Climate change and its variability cause significant impacts on water

resources of the region.

• The uncertainties in precipitation and increasing temperature in the• The uncertainties in precipitation and increasing temperature in the

semi-arid regions are posing a serious stress on the water resources.

• Minor Irrigation tanks play a significant role in managing water

resources in semi-arid regions.

• Tank irrigation has a great significance in semi-arid regions, as the

small scale farmers depend mainly on these resources.

• Tank irrigation is significant in arid and semi-arid regions due to

the contribution to water resources development, agricultural

production, livelihood security and environmental sustainability.

• This study was carried out for Phakal watershed, which is situated in

the Krishna River Basin, India.

• This part of the basin is very important as the catchment provides• This part of the basin is very important as the catchment provides

water for Phakal lake – a medium irrigation project.

• So it is crucial to study and evaluate the potential impacts of climate

change on the hydrology and water resources availability.

• The assessment of future climate change impacts on Phakal lake has

been carried out using the Soil and Water Assessment Tool (SWAT).

Climate Data

Climate model data

Observed climate data

Geospatial data

DEM,LU/LC, SOIL MAP

MethodologyHydrological

Data

CWC Gauge Data

SWAT-CUP(Sufi-2)

Bias Correction Swat Model

Generation of Stream flow for future scenarios

Fig. 1 Methodology followed in the present research study

Calibration & Validation

Climate Change Impact Assessment

Study Area• Normal annual rainfall is about 1048mm

• Warangal District has an area of 12,846 km²

• Location: North Latitude 17019' and 180 36'

East Longitude 780 49' and 800 43‘

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Fig 2 Study Area – Warangal district (Undivided)

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Fig. 3 Phakal Watershed

Climate Data

• Observed climate data provided by Indian

Meteorological Department (IMD), Pune.

• Indian Meteorological Department has provided the

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• Indian Meteorological Department has provided the

rainfall data for the whole of India considering a grid

with a cell size of 0.5°×0.5°.

• Climate model data –RCM available with grid cell size

0.5°×0.5°.

• Source: CORDEX (RCP 4.5 )

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Fig.4 Climate model and IMD grid points of Warangal district

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ExperimentName

RCM Description Driving GCMContributingInstitute

CCAM(ACCESS) Commonwealth

Scientific andACCESS1.0

Table 1: List of RCMs used in the studySource: http://cccr.tropmet.res.in/home/ftp_data.jsp

Scientific andIndustrial ResearchOrganisation(CSIRO), Conformal-CubicAtmospheric Model(CCAM; McGregorand Dix, 2001)

CSIRO Marine andAtmosphericResearch,Melbourne,Australia

CCAM(CNRM) CNRM-CM5

CCAM(CCSM) CCSM4

CCAM(MPI) MPI-ESM-LR

Geospatial Data

• Digital Elevation Model – SRTM

• Landuse landcover map (LULC) -USGS

• Soil Map -FAO

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• Soil Map -FAO

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Fig 5 Digital Elevation Model

Fig 6 Landuse Landcover map

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Fig. 7 Soil map of Warangal district

Hydrological Modelling• Soil and Water Assessment Tool (SWAT) is selected for hydrological

modelling.

• SWAT model run by using Observed weather data obtained from

Indian Meteorological Department (IMD) from 1975-2005.

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Indian Meteorological Department (IMD) from 1975-2005.

• SWAT model is run for Konduru watershed which is downstream of

the study area due to the lack of gauge station at the Phakal lake.

• SWAT model calibration and validation is carried out for monthly

simulated stream flow using observed stream flow data from the

Purushothamagudem gauging station present in Konduru

watershed.

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Fig. 8 Watersheds of Warangal district

Fig. 9 Hydrological Modelling of Konduru Watershed

Calibration and Validation of Konduru Watershed using SWAT- CUP• Observed data available at Purushothamgudem

• Data available for the period of 1988 to 2005

• SUFI-2 is used calibration and validation of the Model

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• SUFI-2 is used calibration and validation of the Model

Table 2 Calibration and validation results of Konduru watershed

Objective functions Calibration Validation

R2 0.7 0.39

NSE 0.67 0.35

Sensitivity Analysis

Parameter Name Description Best Parameter Value

MinimumValue

MaximumValue

V__ALPHA_BNK.rte Base flow alpha bank factor for bank storage (days)

0.045 0.000 1.000

V__CH_K2.rte Effective channel hydraulic conductivity, mm/hr

14.141 5.00 22.00

R__CN2.mgt Curve Number -0.000852 -0.007 0.007A__OV_N.hru Manning’s N 0.191 0.18 0.2

A__REVAPMN.gw Threshold depth for revaporation to occur, mm

265.37 0.00 500

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Table -3 The most sensitive parameters and their best parameter values and intervals

occur, mm

V__ESCO.bsn Soil evaporation compensation factor

0.812 0.8 1.0

V__CH_N2.rte Manning’s N 0.183 0.15 2.0R__SOL_K (...).sol Saturated hydraulic conductivity -0.594 -0.6 -0.57

V__GW_DELAY.gw Ground water delay, days 42.445 42 60A__GWQMN.gw Threshold depth for ground water

flow to occur, mm1385.84 1350 1390

V__GW_REVAP.gw Ground water revaporation coefficient

1.857 1.8 1.9

V__EPCO.bsn Plant uptake compensation factor 0.69 0.00 1.00

V__ALPHA_BF.gw Base flow recession factor, days 0.138 0.00 1.0

R__SOL_AWC (...).sol Available water capacity, m/m 0.338 0.33 0.4

R__SOL_BD (...).sol Moist bulk density(Mg/ m3)

-0.023 -0.04 -0.1

Fig. 10 Global Sensitivity Analysis

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Fig. 11 Calibration of Konduru Watershed

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Fig. 12 Validation of Konduru Watershed

Simulation of Konduru Watershed Water resources

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Fig. 13 Average Monthly flow Variations of Konduru Watershed between observed, IMD and Historic

Simulation of Phakal Watershed Water resources

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Fig. 14 Average Monthly flow Variations of Phakal Watershed for different climate models for 2006-2040

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Fig. 15 Average Monthly flow Variations of Phakal Watershed for different climate models for 2041-2070

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Fig. 16 Average Monthly flow Variations of Phakal Watershed for different climate models for 2071-2099

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Fig 16: Monthly flow variation of the stream flow and rainfall for all scenarios for 2006-2040

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Fig 18: Monthly flow variation of the stream flow and rainfall for all scenarios for 2071-2099

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Summary and Conclusions

• The study reveals that SWAT model works well in semi-arid regions

like Warangal district.

• The calibration and validation of the SWAT model indicate good

results

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results

• The climate model (CCSM4) predict very well on overall and even the

rainfall is increased by 4.5% overall still the stream flow generated by

model decreed by 31% percent this indicates model error.

• For the beginning of the century (2006-2040) rainfall is decreased by

58.3% but stream flow is decreases by 72.5%.

• For the mid-century (2041-2070) rainfall is decreased by 13.4%

but the stream flow is decreased by 37.4%.

• For the end century (2071-2099) rainfall is decreased by 14.4%,

the stream flow is decreased by 23%

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• As the results of this study reveal, surface runoff amounts are

going to be affected by the impact of climate change.

• The rainfall and stream flow follows decreeing trend in the

Warangal district.

• In light of this, it is necessary to revise the water budget of Tanks in

Warangal District to consider these changes in the budget.

• It is necessary for Telangana Government to think about policies and

strategies to help the District to adapt for impacts of climate change

and to plan the water resources of the district.

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and to plan the water resources of the district.

• Tanks revival is one of the major works needed by district to take

care about impact of climate change on water resources.

Future Work

• SWAT Model should be run using the Phakal Tank daily

water level data.

• SWAT Model run using RCP 8.5 scenario.• SWAT Model run using RCP 8.5 scenario.

• Further, various regionalization approaches should be

considered for calibration and validation.

• Development of Adaptation Tool with the water budgets

available at the study area for present and future

conditions.

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