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{"title":"Evaluation and hydrological application of precipitation estimates derived from PERSIANN-CDR, TRMM 3B42V7, and NCEP-CFSR over humid regions in China","authors":"Qian Zhu, Weidong Xuan, Li Liu, Yue-Ping Xu","doi":"10.1002/hyp.10846","DOIUrl":null,"url":null,"abstract":"<p>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 © 2016 John Wiley & Sons, Ltd.</p>","PeriodicalId":13189,"journal":{"name":"Hydrological Processes","volume":"30 17","pages":"3061-3083"},"PeriodicalIF":3.2000,"publicationDate":"2016-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/hyp.10846","citationCount":"111","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Hydrological Processes","FirstCategoryId":"89","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/hyp.10846","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Environmental Science","Score":null,"Total":0}
引用次数: 111
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Abstract
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 © 2016 John Wiley & Sons, Ltd.
PERSIANN-CDR、TRMM 3B42V7和NCEP-CFSR对中国湿润地区降水估算的评价及水文应用
基于卫星和再分析的降水定量估计对于水文预测或预报和可靠的水资源管理具有吸引力,特别是对于没有测量的地区。本文利用中国两个湿润地区的7个统计指标,对三种广泛使用的全球高分辨率降水产品[基于人工神经网络的遥感降水估算-气候数据记录(PERSIANN-CDR)、热带降雨测量任务3B42 Version 7 (TRMM 3B42V7)和国家环境预测-气候预报系统再分析中心(NCEP-CFSR)]进行了评估。此外,研究还探讨了这三种降水产品是否可以可靠地作为半分布式水文模型水土评估工具(Soil and Water Assessment Tool)的输入来模拟河流。结果表明:TRMM 3B42V7降水估算结果的误差和偏差最小,月尺度上相关性最高,PERSIANN-CDR和NCEP-CFSR次之;然而,在日常尺度上,TRMM 3B42V7在误差、偏差和相关性方面的优势并没有得到保证。在两个湿润地区,PERSIANN-CDR和3B42V7分别在日和月尺度上表现出令人鼓舞的流量预测潜力,而NCEP-CFSR在水文应用中的表现因流域而异。在3种降水产品中,3B42V7驱动的模拟在捕获日实测流量方面效果最好,而persiann - cdr驱动的模拟低估了大流量,NCEP-CFSR驱动的大流量模拟大多被显著高估。在极端事件分析方面,PERSIANN-CDR往往低估了极端降水,也低估了与之相适应的极端径流模拟。与PERSIANN-CDR相比,NCEP-CFSR的表现正好相反。TRMM 3B42V7在极值上的性能模式不确定,存在过低估计和过高估计并存的情况。版权所有©2016 John Wiley &儿子,有限公司
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