{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T18:04:56Z","timestamp":1775066696207,"version":"3.50.1"},"reference-count":92,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2018,1,17]],"date-time":"2018-01-17T00:00:00Z","timestamp":1516147200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the National Key R&amp;D Program of China","award":["2016YFA0601601"],"award-info":[{"award-number":["2016YFA0601601"]}]},{"name":"Applied Basic Research Programs of Yunnan Province","award":["2017FB071"],"award-info":[{"award-number":["2017FB071"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Accurate precipitation data at a high spatial resolution are essential for hydrological, meteorological, and ecological research at regional scales. This study presented a geostatistical downscaling-calibration procedure to derive the high spatial resolution maps of precipitation over a mountainous watershed affected by a monsoon climate. Based on the relationships between precipitation and other environmental variables, such as the Normalized Difference Vegetation Index (NDVI) and digital elevation model (DEM), a regression model with a residual correction method was applied to downscale the Tropical Rainfall Measuring Mission (TRMM) 3B43 product from coarse resolution (25 km) to fine resolution (1 km). Two methods, geographical difference analysis (GDA) and geographical ratio analysis (GRA), were used to calibrate the downscaled TRMM precipitation data. Monthly 1 km precipitation data were obtained by disaggregating 1 km annual downscaled and calibrated precipitation data using monthly fractions derived from original TRMM data. The downscaled precipitation datasets were validated against ground observations measured by rain gauges. According to the comparison of different regression models and residual interpolation methods, a geographically-weighted regression kriging (GWRK) method was accepted to conduct the downscaling of TRMM data. The downscaled TRMM precipitation data obtained using GWRK described the spatial patterns of precipitation reasonably well at a spatial resolution of 1 km with more detailed information when compared with the original TRMM precipitation. The results of validation indicated that the GRA method provided results with higher accuracy than that of the GDA method. The final annual and monthly downscaled precipitation not only had significant improvement in spatial resolution, but also agreed well with data from the validation rain gauge stations (i.e., R2 = 0.72, RMSE = 161.0 mm, MAE = 127.5 mm, and Bias = 0.050 for annual downscaled precipitation during 2001 to 2015; and R2 = 0.91, RMSE = 22.2 mm, MAE = 13.5 mm, and Bias = 0.048 for monthly downscaled precipitation during 2001 to 2015). In general, the downscaling-calibration procedure is useful for complex mountainous areas with insufficient ground gauges.<\/jats:p>","DOI":"10.3390\/rs10010119","type":"journal-article","created":{"date-parts":[[2018,1,17]],"date-time":"2018-01-17T12:17:11Z","timestamp":1516191431000},"page":"119","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":54,"title":["Fine-Resolution Precipitation Mapping in a Mountainous Watershed: Geostatistical Downscaling of TRMM Products Based on Environmental Variables"],"prefix":"10.3390","volume":"10","author":[{"given":"Yueyuan","family":"Zhang","sequence":"first","affiliation":[{"name":"Asian International Rivers Center, Yunnan University, Kunming 650091, China"},{"name":"Yunnan Key Laboratory of International Rivers and Transboundary Eco-Security, Yunnan University, Kunming 650091, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3194-3621","authenticated-orcid":false,"given":"Yungang","family":"Li","sequence":"additional","affiliation":[{"name":"Asian International Rivers Center, Yunnan University, Kunming 650091, China"},{"name":"Yunnan Key Laboratory of International Rivers and Transboundary Eco-Security, Yunnan University, Kunming 650091, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5186-594X","authenticated-orcid":false,"given":"Xuan","family":"Ji","sequence":"additional","affiliation":[{"name":"Asian International Rivers Center, Yunnan University, Kunming 650091, China"},{"name":"Yunnan Key Laboratory of International Rivers and Transboundary Eco-Security, Yunnan University, Kunming 650091, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xian","family":"Luo","sequence":"additional","affiliation":[{"name":"Asian International Rivers Center, Yunnan University, Kunming 650091, China"},{"name":"Yunnan Key Laboratory of International Rivers and Transboundary Eco-Security, Yunnan University, Kunming 650091, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xue","family":"Li","sequence":"additional","affiliation":[{"name":"Asian International Rivers Center, Yunnan University, Kunming 650091, China"},{"name":"Yunnan Key Laboratory of International Rivers and Transboundary Eco-Security, Yunnan University, Kunming 650091, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,1,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"853","DOI":"10.1007\/s11431-013-5176-7","article-title":"Accuracy and spatio-temporal variation of high resolution satellite rainfall estimate over the Ganjiang River Basin","volume":"56","author":"Hu","year":"2013","journal-title":"Sci. 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