Application of SWAT for the

modelling of sediment yield at Pong

reservoir, India

A. R. Senthil kumar

Tanmoyee Bhattacharya

Suhas D Khobragade

Manohar Arora

National Institute of Hydrology

Roorkee-247667, India

Many large reservoirs for spatial and

temporal distribution of water

High sediment inflow resulting from

unpredicted activities (land use

changes) reduces the performance of

the reservoir during the designed life

time

Average sediment inflow 200 percent

more than inflow assumed during the

design

Ichari diversion dam on Tons river got

silted up to crest level in just two years

Nizam Sagar Reservoir in Andhra

Pradesh lost 60 percent capacity

Estimation of sediment yield from

watershed is very important for

ascertaining the useful life of reservoir

for meeting its intended purposes

Sediment process in a watershed is

highly random and depends upon the

characteristics of basin and river

Study area

Catchment of Beas up to Pong Dam

Catchment area

12,562 sqkm

Water Spread area of the reservoir

260 sqkm

Study objectives

Simulate the discharge and sediment

yield at Nadaun Bridge (Pond

Reservoir)

Methodology

ArcSWAT 2012.10.2.2 for simulating the

discharge and Sediment yield

Conceptual, time continuous and physically

based simulation model to model discharge and

sediment yiled and water quality

Weather, soil properties, topography,

vegetation and land management practices

Data Intensive

Data requirements

DEM of the catchment

LULC of the catchment

Soil Map

Rainfall

Observed discharge and sediment yield

Simulation of discharge and sediment yield at

Jwala Mukhi (Nadaun Bridge)

Data such as Land Use Land Cover, DEM, Soil

Map, Aspect Map generated from NASA,

National Bureau of Soil Survey and Land Use

Planning (NBSSLUP) and NRSC

Grid based data such as daily rainfall, minimum

and maximum temperatures obtained from Indian

Meteorological Department (IMD) and European

Centre for Medium-Range Weather Forecasts

(ECMWF) (ERA Interim data)

Parameters of ARCSWAT for discharge and

sediment yield calibrated manually (trial and

error method)

Calibration data – 1993 to 1996 (Daily data)

Validation data – 1999 to 2002 (Daily data)

Progress during April 2016 to April 2017

DIGITAL ELEVATION MODEL OF THE

CATCHMENT UP TO NADAUN BRIDGE

ASPECT MAP OF THE CATCHMENT UP TO

NADAUN BRIDGE

LULC MAP OF THE CATCHMENT UP TO

NADAUN BRIDGE

SOIL MAP OF THE CATCHMENT UPTO

NADAUN BRIDGE

Conversion of classified LULC map(LISS-III) into

SWAT LULC classes:

FRSD-Deciduous Forest(SWAT)-Degraded Forest

Snow-Snow

FRSE-Evergreen Forest(SWAT)-Deep Forest

SWRN-Bare rock(SWAT)-Current Fallow

PAST-Pasture/Hay(SWAT)-Sparse vegetation

WATR (SWAT)-Water

AGRR-Row crops(SWAT)-Agriculture

ARCSWAT

Typic Udorthents-1-Sandy(FAO)

Typic Dystrudepts-2-Loamy(FAO)

Lithic Cryorthents-24-Loamy Skeletal(FAO)

Rock Outcrop-100-Rock Outcrops(FAO)

Glacier and Rock Outcrop-104-Glaciers and

Rock Outcrops(FAO)

CONVERSION OF NBSSLUP SOIL

CLASSIFICATION TO FAO SOIL

CLASSIFICATION

0

10

20

30

40

50

60

70

80

90

100

Rai

nfa

ll(m

m)

Date

RAINFALL (INTERIM ERA)

0

20

40

60

80

100

120

140

1-Jan-90 1-Jan-91 1-Jan-92 1-Jan-93 1-Jan-94 1-Jan-95 1-Jan-96

Rai

nfa

ll(m

m)

Date

RAINFALL (IMD)

MAXIMUM AND MINIMUM

TEMPERATURE (INTERIM ERA)

0

5

10

15

20

25

30

35

40

45

Tem

per

ature

(°C

)

Date

Maximum Temperature

Minimum Temperature

MAXIMUM AND MINIMUM

TEMPERATURE (IMD)

0

20

40

60

80

100

120 01-J

an-0

0

04-F

eb-0

0

09-M

ar-

00

12-A

pr-

00

16-M

ay-0

0

19-J

un-0

0

23-J

ul-

00

26-A

ug-0

0

29-S

ep-0

0

02-N

ov-0

0

06-D

ec-0

0

09-J

an-0

1

12-F

eb-0

1

18-M

ar-

01

21-A

pr-

01

25-M

ay-0

1

28-J

un-0

1

01-A

ug-0

1

04-S

ep-0

1

08-O

ct-

01

11-N

ov-0

1

15-D

ec-0

1

18-J

an-0

2

21-F

eb-0

2

27-M

ar-

02

30-A

pr-

02

03-J

un-0

2

07-J

ul-

02

10-A

ug-0

2

13-S

ep-0

2

17-O

ct-

02

Rain

fall (

mm

)

RAINFALL (INTERIM ERA)

-10

-5

0

5

10

15

20

25

30

35

01-Jan-99 01-Jan-00 01-Jan-01 01-Jan-02

Tem

pera

ture

(°

C)

Maximum Temperature

Minimum Temperature

MAXIMUM AND MINIMUM

TEMPERATURE (INTERIM ERA)

Parameters Description

CN2.mgt SCS runoff curve number for moisture

condition II

ALPHA_BF.gw Base flow alpha factor

GW_DELAY.gw Groundwater delay time

GWQMN.gw Threshold depth of water in shallow

aquifer required for return flow

SFTMP.bsn

Snowfall temperature

TIMP.bsn Snowmelt temperature lag factor

SNOWCOVMX.bsn Threshold depth of snow above which

there is 100% cover

SOL_AWC.sol Soil available water storage capacity

SOL_BD.sol Soil bulk density

SOL_Z.sol Depth from soil surface to bottom of layer

PARAMETERS SELECTED FOR

STREAMFLOW CALIBRATION

Parameters Description

SOL_K.sol Soil hydraulic conductivity

REVAPMN.gw Threshold depth of water in shallow aquifer

for ‘revap’ or percolation to the deep

aquifer to occur

GW_REVAP.gw Groundwater ‘revaporation’ coefficient

RCHRG_DP.gw Deep aquifer percolation fraction

ESCO.hru Soil evaporation compensation factor

EPCO.hru Plant uptake compensation factor

SURLAG.bsn Surface runoff lag coefficient

SLSUBBSN.hru Average slope length

OV_N.hru

Manning’s n value for overland flow

CANMX.hru Maximum canopy storage

PARAMETERS SELECTED FOR

STREAMFLOW CALIBRATION

Parameters Description

USLE_K USLE equation soil erodibility (K) factor

USLE_P USLE equation support conservation practice

factor

SPCON Linear parameter for calculating the maximum

amount of sediment that can be reentrained

during channel sediment routing

PRF Peak rate adjustment factor for sediment routing

in the main channel

SPEXP Exponent parameter for calculating sediment

reentrained in channel sediment routing

ADJ_PKR Peak rate adjustment factor for sediment routing

in sub basin (tributary channels)

PARAMETERS SELECTED FOR

SEDIMENT YIELD CALIBRATION

Parameters Initial value Fitted value

Minimum value Maximum value

CN2.mgt 35 98 70

ALPHA_BF.gw 0 1 0.42

GW_DELAY.gw 30 450 50.54

GWQMN.gw 0 200 145.32

SFTMP.bsn -20 20 4.56

TIMP.bsn 0 1 0.36

SNOWCOVMX.bsn 0 500 214.84

SOL_AWC.sol 0 1 0.25

SOL_BD.sol

0.9 2.5 1.52

SOL_Z.sol -0.8 8.0 1.40

ARCSWAT CALIBRATION OF PARAMETERS

FOR STREAMFLOW

Parameters Initial value Fitted value

Minimum value Maximum value

SOL_K.sol 1 10 1.31

REVAPMN.gw 0 20 10.23

GW_REVAP.gw 0.02 0.2 0.05

RCHRG_DP.gw 0 1 0.60

ESCO.hru 0 1 0.56

EPCO.hru 0 1 0.45

SURLAG.bsn 0.05 24 10.05

SLSUBBSN.hru 10 150 30.56

OV_N.hru

0.01 30 12

CANMX.hru 0 100 59.56

ARCSWAT CALIBRATION OF PARAMETERS

FOR STREAMFLOW

ARCSWAT CALIBRATION PARAMETERS

FOR SEDIMENT YIELD

Parameters Initial value Fitted value

Minimum

value

Maximum

value

USLE_K 0 0.65 0.17

USLE_P 0 1 1

SPCON 0.0001 0.01 0.0001

PRF 0 2 1

SPEXP 1 1.5 1

ADJ_PKR 0.5 2 1

0

50

100

150

200

250

300

350

400

Jan

-93

Mar

-93

May

-93

Jul-

93

Sep

-93

Nov-9

3

Jan

-94

Mar

-94

May

-94

Jul-

94

Sep

-94

No

v-9

4

Jan

-95

Mar

-95

May

-95

Jul-

95

Sep

-95

Nov-9

5

Jan-9

6

Mar

-96

May

-96

Jul-

96

Sep

-96

Nov-9

6

Dis

char

ge

(m3/s

)

Date

observed (m3/s)

Simulated(m3/s)

ARCSWAT - CALIBRATION (4YR)

RESULTS OF DISCHARGE

R² = 0.928

0

50

100

150

200

250

300

350

400

0 50 100 150 200 250 300 350 400

Sim

ula

ted

Dis

char

ge

(m3/s

)

Observed Discharge (m3/s)

SIMULATED DISCHARGE Vs OBSERVED

DISCHARGE (CALIBRATION)

0

50

100

150

200

250

300

350

Jan

-99

Mar

-99

May

-99

Jul-

99

Sep

-99

Nov-9

9

Jan

-00

Mar

-00

May

-00

Jul-

00

Sep

-00

Nov-0

0

Jan

-01

Mar

-01

May

-01

Jul-

01

Sep

-01

Nov-0

1

Jan

-02

Mar

-02

May

-02

Jul-

02

Sep

-02

Nov-0

2

Dis

char

ge

(m3

/s)

Date

Observed (m3/s)

Simulated (m3/s)

ARCSWAT - VALIDATION (4 YR) RESULTS

OF DISCHARGE

R² = 0.9607

0

50

100

150

200

250

300

350

0 50 100 150 200 250 300 350

Sim

ula

ted

(m

3/s

)

Observed (m3/s)

SIMULATED DISCHARGE Vs OBSERVED

DISCHARGE (VALIDATION)

0

1

2

3

4

5

6

7

8

9

Jan

-93

Mar

-93

May

-93

Jul-

93

Sep

-93

Nov-9

3

Jan

-94

Mar

-94

May

-94

Jul-

94

Sep

-94

Nov-9

4

Jan

-95

Mar

-95

May

-95

Jul-

95

Sep

-95

Nov-9

5

Jan

-96

Mar

-96

May

-96

Jul-

96

Sep

-96

Nov-9

6

Sed

imen

t yie

ld (

t/h

a)

Date

Observed(t/ha)

Simulated(t/ha)

ARCSWAT – CALIBRATION (4YR)

RESULTS OF SEDIMENT YIELD

R² = 0.9521

0

1

2

3

4

5

6

7

8

9

10

0 2 4 6 8 10

Sim

ula

ted

(t/h

a)

Observed(t/ha)

SIMULATED SEDIMENT YIELD Vs

OBSERVED SEDIMENT YIELD

(CALIBRATION)

0

2

4

6

8

10

12

14

Jan

-99

Mar

-99

May

-99

Jul-

99

Sep

-99

Nov-9

9

Jan

-00

Mar

-00

May

-00

Jul-

00

Sep

-00

Nov-0

0

Jan

-01

Mar

-01

May

-01

Jul-

01

Sep

-01

Nov-0

1

Jan

-02

Mar

-02

May

-02

Jul-

02

Sep

-02

Nov-0

2

Sim

ula

ted

(t/

ha)

Observed (t/ha)

Observed(t/ha)

Simulated(t/ha)

ARCSWAT - VALIDATION (4 YR) RESULTS

OF SEDIMENT YIELD

R² = 0.9232

0

2

4

6

8

10

12

14

0 2 4 6 8 10 12 14

Sim

ula

ted

(t/

ha)

Observed (t/ha)

SIMULATED SEDIMENT YIELD Vs

OBSERVED SEDIMENT YIELD

(VALIDATION)

CONCLUSIONS

The coefficient of determination for

simulation of sediment yield during

calibration and validation are

0.95 and 0.92 respectively

The results clearly demonstrate

the capability of SWAT for

simulating the sediment yield

at Pong reservoir.

Thank you