Assessing the performance of the Satellite-Based Precipitation Products (SPP) in the data-sparse Himalayan terrain
Located on the south-facing slope of the Himalayas, Nepal receives intense, long-lasting precipitation during the Asian summer monsoon, making Nepal one of the most susceptible countries to flood and landslide hazards in the region. However, sparse gauging and irregular measurement constrain the vul...
| Autores principales: | , , , , , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
MDPI
2022
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/125123 |
| _version_ | 1855540102761021440 |
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| author | Kumar, S. Amarnath, Giriraj Ghosh, Surajit Park, E. Baghel, T. Wang, J. Pramanik, M. Belbase, D. |
| author_browse | Amarnath, Giriraj Baghel, T. Belbase, D. Ghosh, Surajit Kumar, S. Park, E. Pramanik, M. Wang, J. |
| author_facet | Kumar, S. Amarnath, Giriraj Ghosh, Surajit Park, E. Baghel, T. Wang, J. Pramanik, M. Belbase, D. |
| author_sort | Kumar, S. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Located on the south-facing slope of the Himalayas, Nepal receives intense, long-lasting precipitation during the Asian summer monsoon, making Nepal one of the most susceptible countries to flood and landslide hazards in the region. However, sparse gauging and irregular measurement constrain the vulnerability assessments of floods and landslides, which rely highly on the accuracy of precipitation. Therefore, this study evaluates the performance of Satellite-based Precipitation Products (SPPs) in the Himalayas region by comparing different datasets and identifying the best alternative of gauge-based precipitation for hydro-meteorological applications. We compared eight SPPs using statistical metrics and then used the Multi-Criteria Decision-Making (MCDM) technique to rank them. Secondly, we assessed the hydrological utility of SPPs by simulating them through the GR4J hydrological model. We found a high POD (0.60–0.80) for all SPPs except CHIRPS and PERSIANN; however, a high CC (0.20–0.40) only for CHIRPS, IMERG_Final, and CMORPH. Based on MCDM, CMORPH and IMERG_Final rank first and second. While SPPs could not simulate daily discharge (NSE < 0.28), they performed better for monthly streamflow (NSE > 0.54). Overall, this study recommends CMORPH and IMERG_Final and improves the understanding of data quality to better manage hydrological disasters in the data-sparse Himalayas. This study framework can also be used in other Himalayan regions to systematically rank and identify the most suitable datasets for hydro-meteorological applications. |
| format | Journal Article |
| id | CGSpace125123 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | MDPI |
| publisherStr | MDPI |
| record_format | dspace |
| spelling | CGSpace1251232025-12-08T10:29:22Z Assessing the performance of the Satellite-Based Precipitation Products (SPP) in the data-sparse Himalayan terrain Kumar, S. Amarnath, Giriraj Ghosh, Surajit Park, E. Baghel, T. Wang, J. Pramanik, M. Belbase, D. satellite observation precipitation river basins hydrological modelling datasets hydrometeorology indicators discharge rain temperature Located on the south-facing slope of the Himalayas, Nepal receives intense, long-lasting precipitation during the Asian summer monsoon, making Nepal one of the most susceptible countries to flood and landslide hazards in the region. However, sparse gauging and irregular measurement constrain the vulnerability assessments of floods and landslides, which rely highly on the accuracy of precipitation. Therefore, this study evaluates the performance of Satellite-based Precipitation Products (SPPs) in the Himalayas region by comparing different datasets and identifying the best alternative of gauge-based precipitation for hydro-meteorological applications. We compared eight SPPs using statistical metrics and then used the Multi-Criteria Decision-Making (MCDM) technique to rank them. Secondly, we assessed the hydrological utility of SPPs by simulating them through the GR4J hydrological model. We found a high POD (0.60–0.80) for all SPPs except CHIRPS and PERSIANN; however, a high CC (0.20–0.40) only for CHIRPS, IMERG_Final, and CMORPH. Based on MCDM, CMORPH and IMERG_Final rank first and second. While SPPs could not simulate daily discharge (NSE < 0.28), they performed better for monthly streamflow (NSE > 0.54). Overall, this study recommends CMORPH and IMERG_Final and improves the understanding of data quality to better manage hydrological disasters in the data-sparse Himalayas. This study framework can also be used in other Himalayan regions to systematically rank and identify the most suitable datasets for hydro-meteorological applications. 2022-09-26 2022-10-20T07:21:08Z 2022-10-20T07:21:08Z Journal Article https://hdl.handle.net/10568/125123 en Open Access MDPI Kumar, S.; Amarnath, Giriraj; Ghosh, Surajit; Park, E.; Baghel, T.; Wang, J.; Pramanik, M.; Belbase, D. 2022. Assessing the performance of the Satellite-Based Precipitation Products (SPP) in the data-sparse Himalayan terrain. Remote Sensing, 14(19):4810. (Special issue: Remote Sensing Monitoring of Natural Disasters and Human Impacts in Asian Rivers) [doi: https://doi.org/10.3390/rs14194810] |
| spellingShingle | satellite observation precipitation river basins hydrological modelling datasets hydrometeorology indicators discharge rain temperature Kumar, S. Amarnath, Giriraj Ghosh, Surajit Park, E. Baghel, T. Wang, J. Pramanik, M. Belbase, D. Assessing the performance of the Satellite-Based Precipitation Products (SPP) in the data-sparse Himalayan terrain |
| title | Assessing the performance of the Satellite-Based Precipitation Products (SPP) in the data-sparse Himalayan terrain |
| title_full | Assessing the performance of the Satellite-Based Precipitation Products (SPP) in the data-sparse Himalayan terrain |
| title_fullStr | Assessing the performance of the Satellite-Based Precipitation Products (SPP) in the data-sparse Himalayan terrain |
| title_full_unstemmed | Assessing the performance of the Satellite-Based Precipitation Products (SPP) in the data-sparse Himalayan terrain |
| title_short | Assessing the performance of the Satellite-Based Precipitation Products (SPP) in the data-sparse Himalayan terrain |
| title_sort | assessing the performance of the satellite based precipitation products spp in the data sparse himalayan terrain |
| topic | satellite observation precipitation river basins hydrological modelling datasets hydrometeorology indicators discharge rain temperature |
| url | https://hdl.handle.net/10568/125123 |
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