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Remote Sens. 2016, 8(4), 311; doi:10.3390/rs8040311

A Rainfall Model Based on a Geographically Weighted Regression Algorithm for Rainfall Estimations over the Arid Qaidam Basin in China

1,†,* and 2,†,*
1
Institute of Geographic Science and Natural Resources Research, Chinese Academy of Science, Beijing 100101, China
2
Environmental Quality Comprehensive Assessment Department, China National Environmental Monitoring Center, Beijing 100012, China
These authors contributed equally to this work.
*
Authors to whom correspondence should be addressed.
Academic Editors: Magaly Koch, Richard Gloaguen and Prasad S. Thenkabail
Received: 22 October 2015 / Revised: 20 March 2016 / Accepted: 31 March 2016 / Published: 8 April 2016
View Full-Text   |   Download PDF [8547 KB, uploaded 8 April 2016]   |  

Abstract

Accurate rainfall estimations based on ground-based rainfall observations and satellite-based rainfall measurements are essential for hydrological and environmental modeling in the Qaidam Basin of China. We evaluated the accuracy of daily and monthly scale Tropical Rainfall Measuring Mission (TRMM) rainfall products in the Qaidam Basin. A Geographically Weighted Regression (GWR) was used to estimate the spatial distribution of the TRMM product error using altitude and geographical latitude and longitude as independent variables. Finally, a rainfall model was developed by combining ground-based and satellite-based rainfall measurements, and the model precision was validated with a cross-validation method based on rainfall gauge measurements. The TRMM precipitation observations may contain errors compared with the ground-measured precipitation, and the error for daily data was higher than that for monthly data. A time series of TRMM rainfall measurements at the same location showed errors at certain time intervals. The ground-based and satellite-based rainfall GWR model improved the error in the TRMM rainfall products. This rainfall estimation model with a 1-km spatial resolution is applicable in the Qaidam Basin in which there is a sparse network of rainfall gauges, and is significant for spatial investigations of hydrology and climate change. View Full-Text
Keywords: rainfall estimation; GWR; TRMM; Qaidam Basin rainfall estimation; GWR; TRMM; Qaidam Basin
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Lv, A.; Zhou, L. A Rainfall Model Based on a Geographically Weighted Regression Algorithm for Rainfall Estimations over the Arid Qaidam Basin in China. Remote Sens. 2016, 8, 311.

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