{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,28]],"date-time":"2026-03-28T07:23:41Z","timestamp":1774682621559,"version":"3.50.1"},"reference-count":90,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2023,1,5]],"date-time":"2023-01-05T00:00:00Z","timestamp":1672876800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"The Belt and Road Special Foundation of the State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering","award":["2021491411"],"award-info":[{"award-number":["2021491411"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Understanding the pixel-scale hydrology and the spatiotemporal distribution of regional precipitation requires high precision and high-resolution precipitation data. Satellite-based precipitation products have coarse spatial resolutions (~10 km\u201375 km), rendering them incapable of translating high-resolution precipitation variability induced by dynamic interactions between climatic forcing, ground cover, and altitude variations. This study investigates the performance of a downscaled-calibration procedure to generate fine-scale (1 km \u00d7 1 km) gridded precipitation estimates from the coarser resolution of TRMM data (~25 km) in the Indus Basin. The mixed geographically weighted regression (MGWR) and random forest (RF) models were utilized to spatially downscale the TRMM precipitation data using high-resolution (1 km \u00d7 1 km) explanatory variables. Downscaled precipitation estimates were combined with APHRODITE rain gauge-based data using the calibration procedure (geographical ratio analysis (GRA)). Results indicated that the MGWR model performed better on fit and accuracy than the RF model to predict the precipitation. Annual TRMM estimates after downscaling and calibration not only translate the spatial heterogeneity of precipitation but also improved the agreement with rain gauge observations with a reduction in RMSE and bias of ~88 mm\/year and 27%, respectively. Significant improvement was also observed in monthly (and daily) precipitation estimates with a higher reduction in RMSE and bias of ~30 mm mm\/month (0.92 mm\/day) and 10.57% (3.93%), respectively, after downscaling and calibration procedures. In general, the higher reduction in bias values after downscaling and calibration procedures was noted across the downstream low elevation zones (e.g., zone 1 correspond to elevation changes from 0 to 500 m). The low performance of precipitation products across the elevation zone 3 (&gt;1000 m) might be associated with the fact that satellite observations at high-altitude regions with glacier coverage are most likely subjected to higher uncertainties. The high-resolution grided precipitation data generated by the MGWR-based proposed framework can facilitate the characterization of distributed hydrology in the Indus Basin. The method may have strong adoptability in the other catchments of the world, with varying climates and topography conditions.<\/jats:p>","DOI":"10.3390\/rs15020318","type":"journal-article","created":{"date-parts":[[2023,1,5]],"date-time":"2023-01-05T04:12:56Z","timestamp":1672891976000},"page":"318","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Combining APHRODITE Rain Gauges-Based Precipitation with Downscaled-TRMM Data to Translate High-Resolution Precipitation Estimates in the Indus Basin"],"prefix":"10.3390","volume":"15","author":[{"given":"Rabeea","family":"Noor","sequence":"first","affiliation":[{"name":"Department of Agricultural Engineering, Bahauddin Zakariya University, Multan 60800, Pakistan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0726-1807","authenticated-orcid":false,"given":"Arfan","family":"Arshad","sequence":"additional","affiliation":[{"name":"Department of Biosystems and Agricultural Engineering, Oklahoma State University, Stillwater, OK 74078, USA"},{"name":"Department of Irrigation and Drainage, Faculty of Agricultural Engineering and Technology, University of Agriculture Faisalabad, Faisalabad 38000, Pakistan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2152-6672","authenticated-orcid":false,"given":"Muhammad","family":"Shafeeque","sequence":"additional","affiliation":[{"name":"Climate Lab, Institute of Geography, University of Bremen, 28359 Bremen, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1220-2876","authenticated-orcid":false,"given":"Jinping","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Surveying and Geo-Informatics, North China University of Water Resources and Electric Power, Zhengzhou 450046, China"},{"name":"Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China"},{"name":"Hydraulics and Geotechnics Section, KU Leuven, Kasteelpark Arenberg 40, BE-3001 Leuven, Belgium"}]},{"given":"Azhar","family":"Baig","sequence":"additional","affiliation":[{"name":"Department of Agricultural Engineering, Bahauddin Zakariya University, Multan 60800, Pakistan"},{"name":"Department of Bioresource Engineering, McGill University, 21111 Lakeshore, Ste Anne de Bellevue, QC H9X 3V9, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6377-6610","authenticated-orcid":false,"given":"Shoaib","family":"Ali","sequence":"additional","affiliation":[{"name":"School of Water Conservancy & Civil Engineering, Northeast Agricultural University, Harbin 150030, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0820-488X","authenticated-orcid":false,"given":"Aarish","family":"Maqsood","sequence":"additional","affiliation":[{"name":"Department of Agricultural Engineering, Bahauddin Zakariya University, Multan 60800, Pakistan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0468-5962","authenticated-orcid":false,"given":"Quoc Bao","family":"Pham","sequence":"additional","affiliation":[{"name":"Faculty of Natural Sciences, Institute of Earth Sciences, University of Silesia in Katowice, B\u0119dzi\u0144ska Street 60, 41-200 Sosnowiec, Poland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7295-0361","authenticated-orcid":false,"given":"Adil","family":"Dilawar","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"University of Chinese Academy of Sciences (UCAS), Beijing 100049, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8157-3999","authenticated-orcid":false,"given":"Shahbaz Nasir","family":"Khan","sequence":"additional","affiliation":[{"name":"Department of Structures and Environmental Engineering, University of Agriculture Faisalabad, Faisalabad 38000, Pakistan"}]},{"given":"Duong Tran","family":"Anh","sequence":"additional","affiliation":[{"name":"Laboratory of Environmental Sciences and Climate Change, Institute for Computational Science and Artificial Intelligence, Van Lang University, Ho Chi Minh City 700000, Vietnam"},{"name":"Faculty of Environment, Van Lang University, Ho Chi Minh City 700000, Vietnam"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5506-9502","authenticated-orcid":false,"given":"Ahmed","family":"Elbeltagi","sequence":"additional","affiliation":[{"name":"Agricultural Engineering Department, Faculty of Agriculture, Mansoura University, Mansoura 35516, Egypt"}]}],"member":"1968","published-online":{"date-parts":[[2023,1,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"127389","DOI":"10.1016\/j.jhydrol.2021.127389","article-title":"Performance of satellite-based and reanalysis precipitation products under multi-temporal scales and extreme weather in mainland China","volume":"605","author":"Zhang","year":"2021","journal-title":"J. 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