4.6 Article

Evaluation and hydrological application of precipitation estimates derived from PERSIANN-CDR, TRMM 3B42V7, and NCEP-CFSR over humid regions in China

期刊

HYDROLOGICAL PROCESSES
卷 30, 期 17, 页码 3061-3083

出版社

WILEY
DOI: 10.1002/hyp.10846

关键词

satellite-based precipitation estimates; reanalysis precipitation estimate; evaluation; hydrological applications; SWAT model

资金

  1. Zhejiang Provincial Natural Science Foundation of China [LR14E090001]
  2. National Natural Science Foundation of China [51379183, 91547106]

向作者/读者索取更多资源

Satellite-based and reanalysis quantitative precipitation estimates are attractive for hydrologic prediction or forecasting and reliable water resources management, especially for ungauged regions. This study evaluates three widely used global high-resolution precipitation products [Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), Tropical Rainfall Measuring Mission 3B42 Version 7 (TRMM 3B42V7), and National Centers for Environment Prediction-Climate Forecast System Reanalysis (NCEP-CFSR)] against gauge observations with seven statistical indices over two humid regions in China. Furthermore, the study investigates whether the three precipitation products can be reliably utilized as inputs in Soil and Water Assessment Tool, a semi-distributed hydrological model, to simulate streamflows. Results show that the precipitation estimates derived from TRMM 3B42V7 outperform the other two products with the smallest errors and bias, and highest correlation at monthly scale, which is followed by PERSIANN-CDR and NCEP-CFSR in this rank. However, the superiority of TRMM 3B42V7 in errors, bias, and correlations is not warranted at daily scale. PERSIANN-CDR and 3B42V7 present encouraging potential for streamflow prediction at daily and monthly scale respectively over the two humid regions, whilst the performance of NCEP-CFSR for hydrological applications varies from basin to basin. Simulations forced with 3B42V7 are the best among the three precipitation products in capturing daily measured streamflows, whilst PERSIANN-CDR-driven simulations underestimate high streamflows and high streamflow simulations driven by NCEP-CFSR mostly are overestimated significantly. In terms of extreme events analysis, PERSIANN-CDR often underestimates the extreme precipitation, so do extreme streamflow simulations forced with it. NCEP-CFSR performs just the reverse, compared with PERSIANN-CDR. The performance pattern of TRMM 3B42V7 on extremes is not certain, with coexisting underestimation and overestimation. Copyright (c) 2016 John Wiley & Sons, Ltd.

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