Title | ||
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Evaluation and Hydrological Application of Four Gridded Precipitation Datasets over a Large Southeastern Tibetan Plateau Basin |
Abstract | ||
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Reliable precipitation is crucial for hydrological studies over Tibetan Plateau (TP) basins with sparsely distributed rainfall gauges. In this study, four widely used precipitation products, including the Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation of the water resources (APHRODITE), the High Asia Reanalysis (HAR), and the satellite-based precipitation estimates from Global Precipitation Measurement (GPM) and Tropical Rainfall Measurement Mission (TRMM), were comprehensively evaluated by combining statistical analysis and hydrological simulation over the Upper Brahmaputra (UB) River Basin of TP during 2001-2013. In respect to the statistical assessment, the overall performances of GPM and HAR are comparable to each other, and both are superior to the other two datasets. For hydrological assessment, both daily and monthly GPM-based streamflow simulations perform the best not only at the UB outlet with very good results, but they also illustrate satisfactory results at Yangcun and Lhasa hydrological stations within the UB. Runoff simulation using HAR only performs well at the UB outlet, whereas it shows poor results at both Yangcun and Lhasa stations. The simulated results based on APHRODITE and TRMM show poor performances at UB. Generally, the GPM shows an encouraging potential for hydro-meteorological investigation over UB, although with some bias in flood simulation. |
Year | DOI | Venue |
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2022 | 10.3390/rs14122936 | REMOTE SENSING |
Keywords | DocType | Volume |
gridded precipitation dataset, VIC-glacier model, Tibetan Plateau, streamflow | Journal | 14 |
Issue | ISSN | Citations |
12 | 2072-4292 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
---|---|---|---|
Yueguan Zhang | 1 | 0 | 0.34 |
Qin Ju | 2 | 0 | 0.68 |
Leilei Zhang | 3 | 0 | 0.34 |
Xu, C. | 4 | 19 | 5.36 |
Xide Lai | 5 | 0 | 0.34 |