{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T02:27:17Z","timestamp":1773973637945,"version":"3.50.1"},"reference-count":26,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2024,5,15]],"date-time":"2024-05-15T00:00:00Z","timestamp":1715731200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Limited availability of hydrometeorological data and lack of data sharing practices have added to the challenge of hydrological modelling of large and transboundary catchments. This research evaluates the suitability of latest near real-time global precipitation measurement (GPM)-era satellite precipitation products (SPPs), IMERG-Early, IMERG-Late and GSMaP-NRT, for hydrological and hydrodynamic modelling of the Brahmaputra Basin. The HEC-HMS modelling system was used for the hydrological modelling of the Brahmaputra Basin, using IMERG-Early, IMERG-Late, and GSMaP-NRT. The findings showed good results using GPM SPPs for hydrological modelling of large basins like Brahmaputra, with Nash\u2013Sutcliffe efficiency (NSE) and R2 values in the range of 0.75\u20130.85, and root mean square error (RMSE) between 7000 and 9000 m3 s\u22121, and the average discharge was 20611 m3 s\u22121. Output of the GPM-based hydrological models was then used as input to a 1D hydrodynamic model to assess suitability for flood inundation mapping of the Brahmaputra River. Simulated flood extents were compared with Landsat satellite-captured images of flood extents. In critical areas along the river, the probability of detection (POD) and critical success index (CSI) values were above 0.70 with all the SPPs used in this study. The accuracy of the models was found to increase when simulated using SPPs corrected with ground-based precipitation datasets. It was also found that IMERG-Late performed better than the other two precipitation products as far as hydrological modelling was concerned. However, for flood inundation mapping, all of the three selected products showed equally good results. The conclusion is reached that for sparsely gauged large basins, particularly for trans-boundary ones, GPM-era SPPs can be used for discharge simulation and flood inundation mapping.<\/jats:p>","DOI":"10.3390\/rs16101756","type":"journal-article","created":{"date-parts":[[2024,5,15]],"date-time":"2024-05-15T11:31:52Z","timestamp":1715772712000},"page":"1756","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Evaluation of Near Real-Time Global Precipitation Measurement (GPM) Precipitation Products for Hydrological Modelling and Flood Inundation Mapping of Sparsely Gauged Large Transboundary Basins\u2014A Case Study of the Brahmaputra Basin"],"prefix":"10.3390","volume":"16","author":[{"given":"Muhammad","family":"Jawad","sequence":"first","affiliation":[{"name":"Hydroinformatics and Socio-Technical Innovation Department, IHE Delft Institute for Water Education, 2611 AX Delft, The Netherlands"},{"name":"Hydrology and Atmospheric Sciences Department, The University of Arizona, Tucson, AZ 85721, USA"}]},{"given":"Biswa","family":"Bhattacharya","sequence":"additional","affiliation":[{"name":"Hydroinformatics and Socio-Technical Innovation Department, IHE Delft Institute for Water Education, 2611 AX Delft, The Netherlands"}]},{"given":"Adele","family":"Young","sequence":"additional","affiliation":[{"name":"Coastal and Urban Risk Resilience Department, IHE Delft Institute for Water Education, 2611 AX Delft, The Netherlands"}]},{"given":"Schalk Jan","family":"van Andel","sequence":"additional","affiliation":[{"name":"Hydroinformatics and Socio-Technical Innovation Department, IHE Delft Institute for Water Education, 2611 AX Delft, The Netherlands"}]}],"member":"1968","published-online":{"date-parts":[[2024,5,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Xiang, Y., Chen, J., Li, L., Peng, T., and Yin, Z. 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