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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 21, issue 2
Hydrol. Earth Syst. Sci., 21, 999-1015, 2017
https://doi.org/10.5194/hess-21-999-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Hydrol. Earth Syst. Sci., 21, 999-1015, 2017
https://doi.org/10.5194/hess-21-999-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 16 Feb 2017

Research article | 16 Feb 2017

Remapping annual precipitation in mountainous areas based on vegetation patterns: a case study in the Nu River basin

Xing Zhou, Guang-Heng Ni, Chen Shen, and Ting Sun Xing Zhou et al.
  • State Key Laboratory of Hydro-Science and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China

Abstract. Accurate high-resolution estimates of precipitation are vital to improving the understanding of basin-scale hydrology in mountainous areas. The traditional interpolation methods or satellite-based remote sensing products are known to have limitations in capturing the spatial variability of precipitation in mountainous areas. In this study, we develop a fusion framework to improve the annual precipitation estimation in mountainous areas by jointly utilizing the satellite-based precipitation, gauge measured precipitation, and vegetation index. The development consists of vegetation data merging, vegetation response establishment, and precipitation remapping. The framework is then applied to the mountainous areas of the Nu River basin for precipitation estimation. The results demonstrate the reliability of the framework in reproducing the high-resolution precipitation regime and capturing its high spatial variability in the Nu River basin. In addition, the framework can significantly reduce the errors in precipitation estimates as compared with the inverse distance weighted (IDW) method and the TRMM (Tropical Rainfall Measuring Mission) precipitation product.

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We develop a fusion framework to improve precipitation estimation by jointly utilizing the gauge precipitation and vegetation index and then applying them to mountainous areas of the Nu River basin. The results demonstrate the reliability of the framework in reproducing the high-resolution precipitation regime and capturing its high spatial variability in the Nu River basin. The framework can significantly reduce the errors in precipitation estimates as compared with the IDW and TRMM methods.
We develop a fusion framework to improve precipitation estimation by jointly utilizing the gauge...
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