文章摘要
李伶杰,刘勇,彭志鑫,王银堂,王磊之,苏鑫.卫星与再分析降水产品在无测站区域的精度评价与多源融合[J].水利学报,2025,56(12):1620-1632
卫星与再分析降水产品在无测站区域的精度评价与多源融合
Accuracy assessment and multi-source fusion of satellite and reanalysis precipitation products for ungauged region
投稿时间:2025-02-15  修订日期:2025-12-24
DOI:10.13243/j.cnki.slxb.20250087
中文关键词: 无测站区域  三元搭配  精度评价  多源融合  湖泊水域
英文关键词: ungauged region  triple collocation  accuracy assessment  multi-source fusion  lake orrea
基金项目:国家重点研发计划项目(2022YFC3202802);国家自然科学基金项目(52009081)
作者单位E-mail
李伶杰 南京水利科学研究院, 水灾害防御全国重点实验室, 江苏 南京 210029
长江保护与绿色发展研究院, 江苏 南京 210098 
 
刘勇 南京水利科学研究院, 水灾害防御全国重点实验室, 江苏 南京 210029 yongliu@nhri.cn 
彭志鑫 南京水利科学研究院, 水灾害防御全国重点实验室, 江苏 南京 210029  
王银堂 南京水利科学研究院, 水灾害防御全国重点实验室, 江苏 南京 210029
长江保护与绿色发展研究院, 江苏 南京 210098 
 
王磊之 南京水利科学研究院, 水灾害防御全国重点实验室, 江苏 南京 210029  
苏鑫 南京水利科学研究院, 水灾害防御全国重点实验室, 江苏 南京 210029  
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中文摘要:
      卫星和再分析降水产品可为无测站区域提供降水监测信息源,由于缺乏地面观测,降水产品的精度评价和多源融合仍面临挑战。三元搭配(TC)是不依赖地面观测信息的经典方法,但它仅适用于连续变量,无法降低有雨无雨分类误差。本文融合分类型三元搭配(CTC)与TC,提出适用于无测站区域的卫星与再分析降水产品精度评价与多源融合集成方法CTC-TC。以无固定测站的湖泊为例,开展了鄱阳湖与洞庭湖区域实证研究。结果表明,在精度评价方面,所提方法正确排序了各降水产品分辨有雨无雨的能力,较精准输出了卫星产品的相关系数和均方根误差。在多源融合方面,集成再分析降水ERA5-Land+土壤含水量估算降水SM2RAIN-ASCAT+卫星反演降水GSMaP-MVK的融合数据精度最高,临界成功指数CSI和克林-古普塔效率系数KGE’分别高于0.60和0.49,接近或超过最佳的单一降水产品。与贝叶斯模型平均融合方法相比,CTC-TC提升CSIKGE’均值的幅度分别超过31.2%和6.3%。CTC-TC丰富了卫星与再分析降水产品精度评价与多源融合的方法体系,在无测站区域具有应用潜力。
英文摘要:
      Satellite and reanalysis precipitation products can provide critical spatial information for ungauged regions However,due to the absence of ground observations,the accuracy assessment and multi-source fusion of precipitation products still face challenges. Triple collocation(TC)is a classical method that does not rely on ground obgervation data,but it is only opplicable to continuous variables and cannot reduce classification errors between rain and no-rain events. This study proposes a novel CTC-TC framework by integrating categorical triple collocation(CTC) with TC, enabling comprehensive accuracy assessment and multi-source fusion of precipitation products for ungauged regions. Using the Poyang Lake and Dongting Lake basins as study areas,a systematic investigation was conducted on five representative precipitation products. Results demonstrate that the CTC-TC framework successfully ranked the rainfall detection capabilities of evaluated products and accurately estimating correlation coefficients and root mean square errors for satellite-based products. For multi-source fusion,the integration of ERA5-Land, SM2RAIN-ASCAT,and GSMaP-MVK achieved optimal accuracy in multi-source precipitation fusion,demonstrating Critical Success Index(CSI)and modified Kling-Gupta Efficiency(KGE’)values of 0.60 and 0.49,respectively. These metrics match or exceed the performance of the best parent product. Compared to Bayesian Model Averaging,CTC-TC improved mean CSI and KGE’values by over 31.2% and 6.3%,respectively. The proposed CTC-TC framework enriches the methodology for accuracy assessment and multi-source fusion of precipitation products,demonstrating great potential for application in ungauged regions.
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