APPLICATION OF SWAT MODEL TO THE STUDY AREA

CHAPTER 5

APPLICATION OF SWAT MODEL TO

THE STUDY AREA

5.1 Introduction

The Meenachil river basin suffers from water shortage during the six

non-monsoon months of the year. The available land and water resources are to

be effectively utilised to improve the livelihood and socio-economic conditions of

the people living in the river basin. The land-water system of the area is adversely

affected by the rapid growth of population and changes in the LU/LC. The need for

hydrological investigations in the Meenachil river basin has been recognised with an

aim to suggest improved catchment management programs for the conservation of

soil and water resources in the area. The lack of decision support tools and limitation

of hydrologic data significantly hindered the research activities in the area. In this

chapter, the performance and feasibility of the SWAT 2012 model for prediction of

flow in the Meenachil river basin of the humid tropics in south-west India has been

tested and validated.

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Chapter 5. APPLICATION OF SWAT MODEL TO THE STUDY

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5.2 Model data inputs

The SWAT is a comprehensive model requiring a diversity of information.

The first step in setting up a SWAT river basin simulation is to partition the basin

into sub units. The first level of sub division is the sub basin. The sub basin

delineation is defined by surface topography so that the entire area within a sub basin

flows to the sub basin outlet. The land area in a sub basin is divided into Hydrologic

Response Units (HRUs). These portions of a sub watershed possess unique land

use/management/soil attributes. The number of HRUs in a sub basin is determined

by a threshold value for land use and soil delineation in the sub basin. The use

of HRUs generally simplifies a simulation run because all similar soil and land use

areas are lumped into a single response unit. The ArcGIS platform provides the user

with a complete set of GIS tools for developing, running and editing hydrologic and

management inputs and finally calibrating the model. The spatially distributed data

required for ArcSWAT include the Digital Elevation Model (DEM), soil and land

use data, either as shape files or grid data. The weather and measured streamflow

data are also required as input for the calibration and prediction purposes.

5.2.1 Digital elevation model

The DEM for the study area prepared to use with SWAT2012 is given

in Figure 3.4. This DEM is used to delineate the river basin using automated

delineation tool in SWAT. The entire river basin was divided into 17 sub basins

(Figure 5.1), each of which was again divided into several HRUs. A total of 307

HRUs were created.

5.2.2 Climate data

The climate data required are precipitation, maximum and minimum

air temperature, wind speed, relative humidity and solar radiation. Values for these

parameters may be read from the records of observed data or these may be generated.

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Figure 5.1: SWAT delineated river basin map

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The weather generator input file contains the statistical data needed to generate

representative daily climate data for the sub basins. Climate data will be generated

for two instances - when user specifies that simulated weather will be used or when

measured data is missing. In the present study, a weather generator input file was

created from the data record for 42 years from the weather station at Puthupally

as given in Appendix 1. Daily observed data for precipitation from the four rain

gauge stations - Kottayam, Erattupetta, Teekoy and Kozha were used for input

data preparation. Daily observed data on maximum and minimum temperature,

wind speed and relative humidity collected from Puthupally station were used for

the climate input data preparation.

5.2.3 Streamflow data

Daily streamflow values for Peroor and Cheripad collected from the Hy-

drology Division of Water Resources Department of Kerala State were used for

preparing the observed data file for use in the calibration process.

5.2.4 Land use data

Land use maps prepared from the satellite image for the year 1990 (Fig-

ure 3.15) was used for the calibration period. The SWAT land cover was appropri-

ately selected from the in-built SWAT database for each land cover in the map and

reclassified as given in Figure 5.2.

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Figure 5.2: SWAT reclassified land use map

5.2.5 Soil data

The digitised soil map was used in SWAT and the soil properties for

different layers were fed as the input data for the soils in the user soils database

of SWAT, as given in Appendix 2. Major soils of the study area are Muthur,

Arpookara, Kooropada, Lakkattoor, Koduman, Nellappara and Mavady series as

shown in Figure 3.19. The Soil map was linked to the appropriate soil type from

the soil data base and reclassified as showin in Figure 5.3.

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Figure 5.3: SWAT reclassified soil map

5.3 Model application

In order to apply SWAT model to the Meenachil river basin, the major

steps involved are: 1) data preparation, 2) river basin and sub basin delineation, 3)

HRU definition, 4) sensitivity analysis, and 5) model calibration and validation. The

precipitation and temperature data files were created for the observed data in the

format specified in SWAT. The spatial data sets required were projected to the same

projection, WGS 1984 UTM ZONE 43N using ArcGIS 10.0. The DEM was used

to delineate the watershed and to analyse the drainage pattern of the land surface

terrain. The spatial data on LU/LC were reclassified into SWAT land cover/plant

types. User defined soil types were added to the soil database and the spatial soil

data were linked to the appropriate types. The multiple HRU definition suggested

by the ArcSWAT User’s Manual - 20 percent land use, 10 percent soil and 20 percent

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slope threshold - was applied in the study. The parameter sensitivity analysis was

done for the whole river basin. Eighteen hydrologic parameters pertinent to water

flow (SWAT2005 User’s Guide, 2007) were tested for sensitivity for the simulation

of streamflow in the study area. The top ranked three parameters were used for

calibrating the model.

The data for the period 1990 to 2000 were used for calibrating the model

for the observed flows at Peroor and Cheripad. An independent precipitation, tem-

perature, wind speed, relative humidity and streamflow data set (1987-2004) were

prepared. Periods from 1987 to 1989 were taken as “warm-up”period for calibration.

The warm-up period allows the model to get the hydrologic cycle fully operational.

For the study area, an increasing trend in the area under rubber plantation and a

decreasing trend in the area under mixed crop cultivation is observed. Hence, while

simulating streamflow using SWAT model, land use update files has been incorpo-

rated. Since the gap from 1973 to 1990 is high to properly interpolate the land

cover variation, simulation of the model was done for the period from 1990 to 2004.

The land cover map for the year 1990 (Figure 5.2) was used with the SWAT model.

SWAT allows a maximum of ten files for updating the land use. A spatial linear

interpolation was applied for updating the land use. Also, the area under rubber

plantation is found to be progressing downstream. Table 5.1 gives the area variation

made on creating the land use update files. Seven land use update files were created

considering a linear variation between the available year-span. The final land use

map prepared after incorporating the LU/LC change in the model is given in Figure

5.4.

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Table 5.1: Year wise area conversion made for land use update

Year Sub basins changed Land use New Land use

1992 3,4,5 AGRL RUBR

1995 7,8,9 AGRL RUBR

1999 2,6,10,11,13,14 AGRL RUBR

2004 2,6,7 RICE URMD

2004 15,16 RICE URMD

2004 12 AGRL RUBR

2004 5,14 AGRL URBN

Figure 5.4: SWAT final land use/land cover map

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5.4 SWAT-CUP5 software

SWAT CUP5 software was used for the calibration of the model. Sequen-

tial Uncertainity Fitting (SUFI2) algorithm was used for calibration. The model was

calibrated for the three top ranked parameters - alpha bf (base flow alpha factor in

days), gw revap (ground water revap coefficient) and rchrg dp (deep aquifer perco-

lation factor).

5.5 Evaluation of model performance

Simulated data from the SWAT model can be compared statistically to

observed data to evaluate the predictive capability of the model.

5.6 Uncalibrated model results

The uncalibrated model results were obtained from a SWAT simulation

using the default SWAT settings for parameter values before any calibration was

performed. The uncalibrated simulation was performed for the period 1987-2000,

with 1987-1989 as warm-up period. The R2 values for correlation between simulated

and observed streamflow were relatively high (0.73 and 0.84) for the two stations,

indicating a strong linear relationship between simulated and observed flows. Also,

the NSE values were greater than 0.5, which shows that the model is suitable for

this particular river basin. But the PBIAS for Peroor was -51.4% (ie., > ±25 %),

which indicates an over-prediction. Considering this, the need for calibration of the

model was recognised.

5.7 Model calibration

For calibrating the model, a preliminary sensitivity analysis was per-

formed on all the flow parameters based on the available climatic and hydrologic

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input data for the period from 1987 to 2000. The first three ranked parameters

were selected for calibration purpose. Guidance for identifying input parameters for

manual calibration provided by Feyereisen et al. (2007) based on the study con-

ducted by Van Liew et al. (2007) has been followed in this study for calibrating

the streamflow from the two gauging sites in the Meenachil river basin. Looking to

the uncalibrated model result, the two parameters, base flow recession constant (al-

pha bf) and groundwater ”revap” coefficient (gw revap), were adjusted for the entire

area, since the base flow is high for the simulated flows. The parameter rchrg dp is

found to be the most sensitive parameter. So the model was calibrated with these

three parameters for the observed streamflow values at Cheripad and Peroor. The

study area of Meenachil river basin lies in the highland and midland regions. For

the highland station at Cheripad the un-calibrated model results give -2.0% PBIAS.

Hence, the parameter rchrg dp was calibrated for sub basins in the midland region

alone to arrive at the best value for predicting the accurate streamflow. The SUFI2

algorithm in SWAT CUP was used for calibration. The calibrated values for the

parameters are given in Table 5.2.

Table 5.2: SWAT flow sensitive parameters and fitted values after calibrationusing SUFI2

Sl.no.Sensitivity Lower and Final fitted

Parameter descriptionparameters upper bounds values

1 alpha bf 0− 1 0.8 Baseflow alpha factor (days)

2 gw revap 0.02 - 0.2 0.19 Ground water revap

coefficient

3 rchrg dp 0 - 1 0.98 (for Deep aquifer percolation

midland) fraction

sub basins)

Comparison between the observed and calibrated streamflow values for

eleven years of simulation indicated that there is a good agreement between the

observed and simulated flows with higher values of Nash-Sutcliffe efficiency and

lower values of RSR. The calibrated model predictive performance statistics for

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monthly flows are summarised in Table 5.3. Table 5.4 gives the calibration statistics

for individual years.

Table 5.3: Streamflow calibration results for Cheripad and Peroor

Station NSE R2 RSR d PBIAS(%)

Cheripad 0.87 0.89 0.36 0.96 0.7

Peroor 0.82 0.85 0.43 0.94 −0.4

Table 5.4: Streamflow calibration statistics for each year

YearCheripad Peroor

NSE R2 d NSE R2 d

1990 0.81 0.93 0.93 0.89 0.93 0.97

1991 0.90 0.96 0.97 0.96 0.97 0.98

1992 0.90 0.91 0.97 0.92 0.97 0.98

1993 0.95 0.98 0.99 0.85 0.95 0.97

1994 0.79 0.97 0.92 - - -

1995 0.91 0.96 0.97 - - -

1996 0.97 0.98 0.99 0.81 0.94 0.93

1997 0.87 0.91 0.97 0.82 0.92 0.93

1998 0.60 0.62 0.88 0.74 0.93 0.90

1999 - - - 0.74 0.93 0.90

2000 0.86 0.90 0.96 0.71 0.77 0.90

5.8 Model validation

The streamflow for 2001 - 2004 from the stations at Peroor and Cheripad

were used for validating the predictive capability of the SWAT model with respect

to Meenachil river basin. The comparison statistics for observed and simulated

monthly streamflow for the validation period are shown in Table 5.5. Table 5.6

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gives the statistics for individual years. Figures 5.5 to 5.6 give the time series of

observed and simulated monthly streamflow during the calibration and validation

period.

The other graphical forms of model evaluation - double mass and scat-

ter plot = are given in Figures 5.7 - 5.10. It can be seen from the plot that the

model underpredicts high values and overpredicts lower values. However, the overall

statistics shows that the model is very good for predicting monthly streamflow in

the Meenachil river basin. This calibrated model was then used for computing the

impacts on hydrology due to land use/land cover change in the river basin.

Table 5.5: Streamflow validation statistics (2001-2004)

Station NSE R2 RSR d PBIAS(%)

Cheripad 0.79 0.84 0.46 0.92 4.60

Peroor 0.71 0.76 0.49 0.89 - 6.90

Table 5.6: Streamflow validation statistics for each year

YearCheripad Peroor

NSE R2 d NSE R2 d

2001 0.67 0.94 0.96 0.67 0.85 0.85

2002 0.61 0.67 0.86 0.64 0.76 0.90

2003 0.67 0.79 0.88 0.83 0.90 0.95

2004 0.61 0.90 0.84 0.78 0.79 0.94

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Figure 5.5: Observed and simulated flow at Peroor (1990-2004)

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Figure 5.6: Observed and simulated flow at Cheripad (1990-2004)

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Figure 5.7: Scatter plot of observed and simulated streamflow - Cheripad

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Figure 5.8: Scatter plot of observed and simulated streamflow - Peroor

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Figure 5.9: Double mass curve for observed and simulated streamflow -Cheripad

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Figure 5.10: Double mass curve for observed and simulated streamflow -Peroor

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The average water balance components of the basin, as obtained by the

model simulation, is represented in Figure 5.11.

Figure 5.11: Average annual basin values - SWAT model results

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APPLICATION OF SWAT MODEL TO THE STUDY AREA