Analysis of effects on validation of

spatiotemporal changes in cropping

at agriculture-dominant watershed

Jiwon Lee, Donghyuk Kum, Bomchul Kim,

Seong Joon Kim, John Tenhunen,

Kyoung Jae Lim

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What is the Hydrologic models ?

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SWAT

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Limitation of SWAT model

The objectives of this study

Weather 2009

Landuse 2009

Parameters in Year 2009

Weather 2010

Validation Calibration

Landuse 2010

Parameters in Year 2010

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Calibration

Study Area

Soyanggang-dam Watershed

Mandae watershed 6

Input data of this study DEM

Soil

L09 L10

Ag.mgt Slope & Slope length Point Source

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Ag. Land L09(%) L10(%)

Pumpkin 5.69 9.88

Cabbage 7.75 5.21

Corn 2.63 0.99

Orchard 4.68 8.60

Pepper 0.98 0.04

Potato 12.25 11.73

Rice 46.37 46.39

Radish 11.58 7.39

Soybean 8.08 9.76

SUM 100 100 AREA(km2) 18.45 17.15

Comparison of landuse 2009/2010

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Spatial changes in cropping

L09 L10

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Please remember this Terms

Obs10

W10 L10

W09

Obs09

L09 Weather 2009 Landuse 2009

Weather 2010 Landuse 2010

Observed Data 2009, 2010

Methodologies

L10

W10

Scenario3

Obs10

W09

Scenario1

Obs09

W10

Scenario2

Obs10

L09 Parameters Scenario 1

Parameters Scenario 3

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However, there might be differences in parameters if parameters derived under

different weather data were used for other weather condition.

Results of Scenario 1

StreamFlow NSE = 0.662

SS NSE = 0.688

Calibration

W09

Scenario1

Obs09

L09

Result of Scenario 2

StreamFlow NSE = 0.246

SS NSE = -8.007

Validation

W10

Scenario2

Obs10

L09

Result of Scenario 3

StreamFlow NSE = 0.493

SS NSE = 0.534

Calibration

L10

W10

Scenario3

Obs10

Scenario2 vs. Scenario3

-35%

1.3%

56.7%

28%

14.9%

30.8%

-16.8%

478%

-6.4%

20%

-22.5%

-12%

291.4% -36%

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vs. L09

W10

Parameters

Scenario1

L10

W10

Parameters

Scenario3

Scenario2 Scenario3

vs. L09

W10

Parameters

Scenario1

L10

W10

Parameters

Scenario3

Scenario2 Scenario3

Scenario2 vs. Scenario3

Scenario2 1.931 (CMS)

Scenario3 1.998 (CMS)

Scenario2 1,117.1 (mg/l)

Scenario3 332.7 (mg/l)

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L10

W10

Scenario3

W09

Scenario1

W10

Scenario2

L09

Parameters used in this study

File Parameter Scenario1 Calibration

Scenario2

Validation

Scenario3 Calibration

.BSN SPCON 0.001 0.001 0.0002

W09 Precip 1,258 mm

W10 Precip 970 mm

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Some parameters should be changed with changes in other parameters throughout the simulation period.

In the current SWAT, the SPCON parameter should be dynamically

changed during the model run depending on hydrologic condition.

New Scenario 4

L10

W10

Scenario3

W10

Scenario4

L09

Parameters used In Scenario3

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Scenario3 vs. Scenario4

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R2 = 0.993

R2 = 0.917

Do you have any idea why the sediment loads at the main outlet are similar although there are

differences in estimated sediment for each subbasins ?

Scenario3 vs. Scenario4

Outlet

L10

W10

Parameters

Scenario3

Scenario3 Scenario4

W10

L09

Parameters

Scenario3

vs.

This comparison shows effects of land use change are not negligible.

We can infer that the SWAT model evaluations should be performed at several

outlet as well as main outlet.

Scenario2 vs. Scenario4

Outlet

L09

W10

Parameters

Scenario1

Scenario2 Scenario4

W10

L09

Parameters

Scenario3

vs.

Model parameters should be dynamically changed depending on other conditions in

the watershed.

We strongly recommend SWAT model should be calibrated for several locations (outlets) as well as main outlet in the watershed

However, some model parameters depending on various field/weather condition should be dynamically changed for better estimation of what has been occurring at the watershed through calibration / validation period.

If changes in land use (cropping) and weather are not negligible, what is your strategy to evaluate model performance?

(any good idea/comments ?)

Conclusions

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E-mail:wogija@naver.com

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