Bi-criteria evaluation of the MIKE SHE model for a forested watershed on the South Carolina coastal plain
Hydrological models are important tools for effective management, conservation and restoration of forested wetlands. The objective of this study was to test a distributed hydrological model, MIKE SHE, by using bi-criteria (i.e., two measurable variables, streamflow and water table depth) to describe...
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| Veröffentlicht in: | Hydrology and earth system sciences Jg. 14; H. 6; S. 1033 - 1046 |
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| Sprache: | Englisch |
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Katlenburg-Lindau
Copernicus GmbH
24.06.2010
Copernicus Publications |
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| ISSN: | 1607-7938, 1027-5606, 1607-7938 |
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| Abstract | Hydrological models are important tools for effective management, conservation and restoration of forested wetlands. The objective of this study was to test a distributed hydrological model, MIKE SHE, by using bi-criteria (i.e., two measurable variables, streamflow and water table depth) to describe the hydrological processes in a forested watershed that is characteristic of the lower Atlantic Coastal Plain. Simulations were compared against observations of both streamflow and water table depth measured on a first-order watershed (WS80) on the Santee Experimental Forest in South Carolina, USA. Model performance was evaluated using coefficient of determination (R2) and Nash-Sutcliffe's model efficiency (E). The E and root mean squared error (RMSE) were chosen as objective functions for sensitivity analysis of parameters. The model calibration and validation results demonstrated that the streamflow and water table depth were sensitive to most of the model input parameters, especially to surface detention storage, drainage depth, soil hydraulic properties, plant rooting depth, and surface roughness. Furthermore, the bi-criteria approach used for distributed model calibration and validation was shown to be better than the single-criterion in obtaining optimum model input parameters, especially for those parameters that were only sensitive to some specific conditions. Model calibration using the bi-criteria approach should be advantageous for constructing the uncertainty bounds of model inputs to simulate the hydrology for this type of forested watersheds. R2 varied from 0.60–0.99 for daily and monthly streamflow, and from 0.52–0.91 for daily water table depth. E changed from 0.53–0.96 for calibration and 0.51–0.98 for validation of daily and monthly streamflow, while E varied from 0.50–0.90 for calibration and 0.66–0.80 for validation of daily water table depth. This study showed that MIKE SHE could be a good candidate for simulating streamflow and water table depth in coastal plain watersheds. |
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| AbstractList | Hydrological models are important tools for effective management, conservation and restoration of forested wetlands. The objective of this study was to test a distributed hydrological model, MIKE SHE, by using bi-criteria (i.e., two measurable variables, streamflow and water table depth) to describe the hydrological processes in a forested watershed that is characteristic of the lower Atlantic Coastal Plain. Simulations were compared against observations of both streamflow and water table depth measured on a first-order watershed (WS80) on the Santee Experimental Forest in South Carolina, USA. Model performance was evaluated using coefficient of determination (R2 ) and Nash-Sutcliffe's model efficiency (E). The E and root mean squared error (RMSE) were chosen as objective functions for sensitivity analysis of parameters. The model calibration and validation results demonstrated that the streamflow and water table depth were sensitive to most of the model input parameters, especially to surface detention storage, drainage depth, soil hydraulic properties, plant rooting depth, and surface roughness. Furthermore, the bi-criteria approach used for distributed model calibration and validation was shown to be better than the single-criterion in obtaining optimum model input parameters, especially for those parameters that were only sensitive to some specific conditions. Model calibration using the bi-criteria approach should be advantageous for constructing the uncertainty bounds of model inputs to simulate the hydrology for this type of forested watersheds. R2 varied from 0.60-0.99 for daily and monthly streamflow, and from 0.52-0.91 for daily water table depth. E changed from 0.53-0.96 for calibration and 0.51-0.98 for validation of daily and monthly streamflow, while E varied from 0.50-0.90 for calibration and 0.66-0.80 for validation of daily water table depth. This study showed that MIKE SHE could be a good candidate for simulating streamflow and water table depth in coastal plain watersheds. Hydrological models are important tools for effective management, conservation and restoration of forested wetlands. The objective of this study was to test a distributed hydrological model, MIKE SHE, by using bi-criteria (i.e., two measurable variables, streamflow and water table depth) to describe the hydrological processes in a forested watershed that is characteristic of the lower Atlantic Coastal Plain. Simulations were compared against observations of both streamflow and water table depth measured on a first-order watershed (WS80) on the Santee Experimental Forest in South Carolina, USA. Model performance was evaluated using coefficient of determination ( R 2 ) and Nash-Sutcliffe's model efficiency ( E ). The E and root mean squared error (RMSE) were chosen as objective functions for sensitivity analysis of parameters. The model calibration and validation results demonstrated that the streamflow and water table depth were sensitive to most of the model input parameters, especially to surface detention storage, drainage depth, soil hydraulic properties, plant rooting depth, and surface roughness. Furthermore, the bi-criteria approach used for distributed model calibration and validation was shown to be better than the single-criterion in obtaining optimum model input parameters, especially for those parameters that were only sensitive to some specific conditions. Model calibration using the bi-criteria approach should be advantageous for constructing the uncertainty bounds of model inputs to simulate the hydrology for this type of forested watersheds. R 2 varied from 0.60–0.99 for daily and monthly streamflow, and from 0.52–0.91 for daily water table depth. E changed from 0.53–0.96 for calibration and 0.51–0.98 for validation of daily and monthly streamflow, while E varied from 0.50–0.90 for calibration and 0.66–0.80 for validation of daily water table depth. This study showed that MIKE SHE could be a good candidate for simulating streamflow and water table depth in coastal plain watersheds. Hydrological models are important tools for effective management, conservation and restoration of forested wetlands. The objective of this study was to test a distributed hydrological model, MIKE SHE, by using bi-criteria (i.e., two measurable variables, streamflow and water table depth) to describe the hydrological processes in a forested watershed that is characteristic of the lower Atlantic Coastal Plain. Simulations were compared against observations of both streamflow and water table depth measured on a first-order watershed (WS80) on the Santee Experimental Forest in South Carolina, USA. Model performance was evaluated using coefficient of determination (R super(2)) and Nash-Sutcliffe's model efficiency (E). The E and root mean squared error (RMSE) were chosen as objective functions for sensitivity analysis of parameters. The model calibration and validation results demonstrated that the streamflow and water table depth were sensitive to most of the model input parameters, especially to surface detention storage, drainage depth, soil hydraulic properties, plant rooting depth, and surface roughness. Furthermore, the bi-criteria approach used for distributed model calibration and validation was shown to be better than the single-criterion in obtaining optimum model input parameters, especially for those parameters that were only sensitive to some specific conditions. Model calibration using the bi-criteria approach should be advantageous for constructing the uncertainty bounds of model inputs to simulate the hydrology for this type of forested watersheds. R super(2) varied from 0.60-0.99 for daily and monthly streamflow, and from 0.52-0.91 for daily water table depth. E changed from 0.53-0.96 for calibration and 0.51-0.98 for validation of daily and monthly streamflow, while E varied from 0.50-0.90 for calibration and 0.66-0.80 for validation of daily water table depth. This study showed that MIKE SHE could be a good candidate for simulating streamflow and water table depth in coastal plain watersheds. |
| Author | Li, C. Sun, G. Trettin, C. Li, H. Dai, Z. Amatya, D. |
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| Title | Bi-criteria evaluation of the MIKE SHE model for a forested watershed on the South Carolina coastal plain |
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