The Response of the HydroGeoSphere Model to Alternative Spatial Precipitation Simulation Methods
This paper presents the simulation results obtained from a physically based surface-subsurface hydrological model in a 5730 km<sup>2</sup> watershed and the runoff response of the physically based hydrological models for three methods used to generate the spatial precipitation distributi...
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| Format: | Article |
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MDPI AG
2021-07-01
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| Series: | Water |
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| Online Access: | https://www.mdpi.com/2073-4441/13/14/1891 |
| _version_ | 1797525936761995264 |
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| author | Haishen Lü Qimeng Wang Robert Horton Yonghua Zhu |
| author_facet | Haishen Lü Qimeng Wang Robert Horton Yonghua Zhu |
| author_sort | Haishen Lü |
| collection | DOAJ |
| description | This paper presents the simulation results obtained from a physically based surface-subsurface hydrological model in a 5730 km<sup>2</sup> watershed and the runoff response of the physically based hydrological models for three methods used to generate the spatial precipitation distribution: Thiessen polygons (TP), Co-Kriging (CK) interpolation and simulated annealing (SA). The HydroGeoSphere model is employed to simulate the rainfall-runoff process in two watersheds. For a large precipitation event, the simulated patterns using SA appear to be more realistic than those using the TP and CK method. In a large-scale watershed, the results demonstrate that when HydroGeoSphere is forced by TP precipitation data, it fails to reproduce the timing, intensity, or peak streamflow values. On the other hand, when HydroGeoSphere is forced by CK and SA data, the results are consistent with the measured streamflows. In a medium-scale watershed, the HydroGeoSphere results show a similar response compared to the measured streamflow values when driven by all three methods used to estimate the precipitation, although the SA case is slightly better than the other cases. The analytical results could provide a valuable counterpart to existing climate-based drought indices by comparing multiple interpolation methods in simulating land surface runoff. |
| first_indexed | 2024-03-10T09:20:07Z |
| format | Article |
| id | doaj.art-aef1bc3e72404c73a5b8807f82931fe0 |
| institution | Directory Open Access Journal |
| issn | 2073-4441 |
| language | English |
| last_indexed | 2024-03-10T09:20:07Z |
| publishDate | 2021-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Water |
| spelling | doaj.art-aef1bc3e72404c73a5b8807f82931fe02023-11-22T05:15:56ZengMDPI AGWater2073-44412021-07-011314189110.3390/w13141891The Response of the HydroGeoSphere Model to Alternative Spatial Precipitation Simulation MethodsHaishen Lü0Qimeng Wang1Robert Horton2Yonghua Zhu3State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, College of Hydrology and Water Resources, Hohai University, Nanjing 210098, ChinaState Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, College of Hydrology and Water Resources, Hohai University, Nanjing 210098, ChinaDepartment of Agronomy, Iowa State University, Ames, IA 50011, USAState Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, College of Hydrology and Water Resources, Hohai University, Nanjing 210098, ChinaThis paper presents the simulation results obtained from a physically based surface-subsurface hydrological model in a 5730 km<sup>2</sup> watershed and the runoff response of the physically based hydrological models for three methods used to generate the spatial precipitation distribution: Thiessen polygons (TP), Co-Kriging (CK) interpolation and simulated annealing (SA). The HydroGeoSphere model is employed to simulate the rainfall-runoff process in two watersheds. For a large precipitation event, the simulated patterns using SA appear to be more realistic than those using the TP and CK method. In a large-scale watershed, the results demonstrate that when HydroGeoSphere is forced by TP precipitation data, it fails to reproduce the timing, intensity, or peak streamflow values. On the other hand, when HydroGeoSphere is forced by CK and SA data, the results are consistent with the measured streamflows. In a medium-scale watershed, the HydroGeoSphere results show a similar response compared to the measured streamflow values when driven by all three methods used to estimate the precipitation, although the SA case is slightly better than the other cases. The analytical results could provide a valuable counterpart to existing climate-based drought indices by comparing multiple interpolation methods in simulating land surface runoff.https://www.mdpi.com/2073-4441/13/14/1891HydroGeoSphereThiessen polygonCo-Krigingsimulated annealingrainfall-runoff process |
| spellingShingle | Haishen Lü Qimeng Wang Robert Horton Yonghua Zhu The Response of the HydroGeoSphere Model to Alternative Spatial Precipitation Simulation Methods Water HydroGeoSphere Thiessen polygon Co-Kriging simulated annealing rainfall-runoff process |
| title | The Response of the HydroGeoSphere Model to Alternative Spatial Precipitation Simulation Methods |
| title_full | The Response of the HydroGeoSphere Model to Alternative Spatial Precipitation Simulation Methods |
| title_fullStr | The Response of the HydroGeoSphere Model to Alternative Spatial Precipitation Simulation Methods |
| title_full_unstemmed | The Response of the HydroGeoSphere Model to Alternative Spatial Precipitation Simulation Methods |
| title_short | The Response of the HydroGeoSphere Model to Alternative Spatial Precipitation Simulation Methods |
| title_sort | response of the hydrogeosphere model to alternative spatial precipitation simulation methods |
| topic | HydroGeoSphere Thiessen polygon Co-Kriging simulated annealing rainfall-runoff process |
| url | https://www.mdpi.com/2073-4441/13/14/1891 |
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