{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,16]],"date-time":"2026-09-16T22:19:00Z","timestamp":1789597140956,"version":"build-2803163510"},"reference-count":66,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2021,1,11]],"date-time":"2021-01-11T00:00:00Z","timestamp":1610323200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Strategic Priority Research Program of the Chinese Academy of Sciences, Pan-Third Pole Environment Study for a Green Silk Road","award":["XDA20060303"],"award-info":[{"award-number":["XDA20060303"]}]},{"name":"State\u2019s Key Project of Research and Development Plan","award":["2017YFC0404501"],"award-info":[{"award-number":["2017YFC0404501"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41761144079"],"award-info":[{"award-number":["41761144079"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"International Partnership Program of the Chinese Academy of Sciences","award":["131551KYS B20160002"],"award-info":[{"award-number":["131551KYS B20160002"]}]},{"name":"CAS Interdisplinary Innovation Team","award":["JCTD-2019-20"],"award-info":[{"award-number":["JCTD-2019-20"]}]},{"name":"CAS Research Center for Ecology and Environment of Central Asia","award":["Y934031"],"award-info":[{"award-number":["Y934031"]}]},{"name":"Regional Collaborative Innovation Project of Xinjiang Uygur Autonomous Regions","award":["2020E01010"],"award-info":[{"award-number":["2020E01010"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Hydrological modeling has always been a challenge in the data-scarce watershed, especially in the areas with complex terrain conditions like the inland river basin in Central Asia. Taking Bosten Lake Basin in Northwest China as an example, the accuracy and the hydrological applicability of satellite-based precipitation datasets were evaluated. The gauge-adjusted version of six widely used datasets was adopted; namely, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks\u2013Climate Data Record (CDR), Climate Hazards Group Infrared Precipitation with Stations (CHIRPS), Global Precipitation Measurement Ground Validation National Oceanic and Atmospheric Administration Climate Prediction Center (NOAA CPC) Morphing Technique (CMORPH), Integrated Multi-Satellite Retrievals for GPM (GPM), Global Satellite Mapping of Precipitation (GSMaP), the Tropical Rainfall Measuring Mission (TRMM) and Multi-satellite Precipitation Analysis (TMPA). Seven evaluation indexes were used to compare the station data and satellite datasets, the soil and water assessment tool (SWAT) model, and four indexes were used to evaluate the hydrological performance. The main results were as follows: 1) The GPM and CDR were the best datasets for the daily scale and monthly scale rainfall accuracy evaluations, respectively. 2) The performance of CDR and GPM was more stable than others at different locations in a watershed, and all datasets tended to perform better in the humid regions. 3) All datasets tended to perform better in the summer of a year, while the CDR and CHIRPS performed well in winter compare to other datasets. 4) The raw data of CDR and CMORPH performed better than others in monthly runoff simulations, especially CDR. 5) Integrating the hydrological performance of the uncorrected and corrected data, all datasets have the potential to provide valuable input data in hydrological modeling. This study is expected to provide a reference for the hydrological and meteorological application of satellite precipitation datasets in Central Asia or even the whole temperate zone.<\/jats:p>","DOI":"10.3390\/rs13020221","type":"journal-article","created":{"date-parts":[[2021,1,11]],"date-time":"2021-01-11T11:36:11Z","timestamp":1610364971000},"page":"221","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":47,"title":["Satellite-Based Precipitation Datasets Evaluation Using Gauge Observation and Hydrological Modeling in a Typical Arid Land Watershed of Central Asia"],"prefix":"10.3390","volume":"13","author":[{"given":"Jiabin","family":"Peng","sequence":"first","affiliation":[{"name":"State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China"},{"name":"Key Laboratory of GIS &amp; RS Application, Xinjiang Uygur Autonomous Region, Urumqi 830011, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"Department of Geography, Ghent University, 9000 Ghent, Belgium"},{"name":"Sino-Belgian Joint Laboratory of Geo-Information, Urumqi 830011, China"},{"name":"Sino-Belgian Joint Laboratory of Geo-Information, 9000 Ghent, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6879-4818","authenticated-orcid":false,"given":"Tie","family":"Liu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China"},{"name":"Key Laboratory of GIS &amp; RS Application, Xinjiang Uygur Autonomous Region, Urumqi 830011, China"},{"name":"Sino-Belgian Joint Laboratory of Geo-Information, Urumqi 830011, China"},{"name":"Sino-Belgian Joint Laboratory of Geo-Information, 9000 Ghent, Belgium"},{"name":"CAS Research Center of Ecology and Environment in Central Asia, Urumqi 830011, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yue","family":"Huang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China"},{"name":"Key Laboratory of GIS &amp; RS Application, Xinjiang Uygur Autonomous Region, Urumqi 830011, China"},{"name":"Sino-Belgian Joint Laboratory of Geo-Information, Urumqi 830011, China"},{"name":"Sino-Belgian Joint Laboratory of Geo-Information, 9000 Ghent, Belgium"},{"name":"CAS Research Center of Ecology and Environment in Central Asia, Urumqi 830011, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yunan","family":"Ling","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China"},{"name":"Key Laboratory of GIS &amp; RS Application, Xinjiang Uygur Autonomous Region, Urumqi 830011, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"Department of Geography, Ghent University, 9000 Ghent, Belgium"},{"name":"Sino-Belgian Joint Laboratory of Geo-Information, Urumqi 830011, China"},{"name":"Sino-Belgian Joint Laboratory of Geo-Information, 9000 Ghent, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhengyang","family":"Li","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China"},{"name":"Key Laboratory of GIS &amp; RS Application, Xinjiang Uygur Autonomous Region, Urumqi 830011, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anming","family":"Bao","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China"},{"name":"Key Laboratory of GIS &amp; RS Application, Xinjiang Uygur Autonomous Region, Urumqi 830011, China"},{"name":"Sino-Belgian Joint Laboratory of Geo-Information, Urumqi 830011, China"},{"name":"Sino-Belgian Joint Laboratory of Geo-Information, 9000 Ghent, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xi","family":"Chen","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China"},{"name":"Sino-Belgian Joint Laboratory of Geo-Information, Urumqi 830011, China"},{"name":"Sino-Belgian Joint Laboratory of Geo-Information, 9000 Ghent, Belgium"},{"name":"CAS Research Center of Ecology and Environment in Central Asia, Urumqi 830011, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9387-8127","authenticated-orcid":false,"given":"Alishir","family":"Kurban","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China"},{"name":"Sino-Belgian Joint Laboratory of Geo-Information, Urumqi 830011, China"},{"name":"Sino-Belgian Joint Laboratory of Geo-Information, 9000 Ghent, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8902-3855","authenticated-orcid":false,"given":"Philippe","family":"De Maeyer","sequence":"additional","affiliation":[{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"Department of Geography, Ghent University, 9000 Ghent, Belgium"},{"name":"Sino-Belgian Joint Laboratory of Geo-Information, Urumqi 830011, China"},{"name":"Sino-Belgian Joint Laboratory of Geo-Information, 9000 Ghent, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,1,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1016\/0022-1694(95)02704-S","article-title":"Impact of small-scale spatial rainfall variability on runoff modeling","volume":"173","author":"Goodrich","year":"1995","journal-title":"J. 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