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Application of WetSpa to DMIP 2 project, USA

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Alireza Safari Alireza Safari Department of Hydrology and Hydraulic Department of Hydrology and Hydraulic Engineering ( Engineering ( HYDR HYDR) Vrije Universiteit Brussel ( Vrije Universiteit Brussel ( VUB VUB) Pleinlaan 2, 1050 Brussels, Belgium Pleinlaan 2, 1050 Brussels, Belgium Application of WetSpa WetSpa to DMIP 2 project, USA
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Page 1: Application of WetSpa to DMIP 2 project, USA

Alireza SafariAlireza SafariDepartment of Hydrology and Hydraulic Department of Hydrology and Hydraulic Engineering (Engineering (HYDRHYDR))Vrije Universiteit Brussel (Vrije Universiteit Brussel (VUBVUB))Pleinlaan 2, 1050 Brussels, BelgiumPleinlaan 2, 1050 Brussels, Belgium

Application of WetSpaWetSpa to DMIP 2 project, USA

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Pag.04/13/23 2Application of WetSpa to DMIP 2

A distributed model for water and energy transfer between soil, plants and atmosphere (WetSpa)

A physics-based hydrological model to simulate rainfall-runoff processes

Hydrological processes considered in the model include:

Precipitation, snowmelt, interception, depression, surface runoff, infiltration, evapotranspiration,

percolation, interflow, groundwater flow, etc.

Inputs to the Model: 3 basic input maps (DEM, Landuse, and Soil type), weather station locations and time

series

WetSpa is a product of over 12 years of HYDRmodel development

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Performance criteria

1. Water balance bias:

2. Nash-Sutcliffe (1970):

3. Modified correlation index (1975):

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Pag.

Auto Calibration

04/13/23 7Application of WetSpa to DMIP 2

• Parameter Estimation (PEST) Software

• Model Independent Parameter Estimator: Minimize the bias between observed and simulated flows by many runs as needed

• PEST:works well in terms of saving time and efforts

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Model calibration and testing

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Model calibration and testing

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Model calibration and testing

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Model calibration and testing

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Testing the calibrated model for two years 1998 and 2004

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Comparison of observed and simulated hydrographs (Calibrated run)Year 1998

Model bias % Rmod % Nash % Nash-Lowflow % Nash-highflow %

11.3 74.3 71.3 37.4 85.4

Peak discharge (m3/s) Observed simulated

Peak value 729 824Peak_Error % - 13

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Comparison of observed and simulated hydrographs (Un-Calibrated run)

Year 1998

Model bias % Rmod % Nash % Nash-Lowflow % Nash-highflow %

-0.6 88.0 81.5 11.5 92.4

Peak discharge (m3/s) Observed simulated

Peak value 729 659Peak_Error % - -10

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Comparison of observed and simulated hydrographs (Calibrated run)Year 2004

Model bias % Rmod % Nash % Nash-Lowflow % Nash-highflow %

-5.5 83.4 89.5 60.0 92.6

Peak discharge (m3/s) Observed simulated

Peak value 874 627Peak_Error % - -28

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Comparison of observed and simulated hydrographs (Un-Calibrated run)

Year 2004

Model bias % Rmod % Nash % Nash-Lowflow % Nash-highflow %

-23.1 51.3 70.3 47.2 68.7

Peak discharge (m3/s) Observed simulated

Peak value 874 399Peak_Error % - -54

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Conclusion

• WetSpa is well suited to DMIP2

• The calibration results reveal that the WetSpa when forced with hourly radar based rainfall data, is able to reproduce well the observed hourly streamflow at the outlet of each study watershed.

• WETSPA is able to reproduce adequately the hourly flows .

• the control years of 1998 and 2004 show that the calibrated WetSpa is a stable model to predict periods regardless of length of the simulation periods.

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