Evidence map›Paper›PMID 41922501›Full record

ArticleScientific reports2026

Multidimensional evaluation of four high-resolution precipitation products based on REOF zones in the upper and middle Hanjiang River Basin.

Huijuan Bo, Xiaole Huang, Shaokang Yang, Lichuan Luo, Lingyun Guo, Juan Yue, Ni Zhang, Lihua Long, Wei Pan, Chong Wei and 1 more

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Huijuan Bo *Hubei Water Resources Technical College, Wuhan, 430202, People's Republic of China.
Xiaole Huang *Xiangyang Polytechnic, Xiangyang, 441050, People's Republic of China.
Shaokang YangXiantao River Embankment Administration, Xiantao, 433000, People's Republic of China.
Lichuan LuoHubei Water Resources Technical College, Wuhan, 430202, People's Republic of China.
Lingyun GuoHubei Water Resources Technical College, Wuhan, 430202, People's Republic of China.
Juan YueHubei Water Resources Technical College, Wuhan, 430202, People's Republic of China.
Ni ZhangHubei Water Resources Technical College, Wuhan, 430202, People's Republic of China.
Lihua LongHubei Water Resources Technical College, Wuhan, 430202, People's Republic of China.
Wei PanHubei Water Resources Technical College, Wuhan, 430202, People's Republic of China.
Chong WeiEngineering Education Center of Ecological Environment of the Three Gorges Reservoir Area, Ministry of Education, Yichang, 443002, People's Republic of China. chong.wei@ctgu.edu.cn.
Yi ZhangScience and Technology College of Hubei University of Arts and Science, Xiangyang, 441050, People's Republic of China. zy27ok@163.com.

Funding

Hubei Province Construction Science and Technology Plan Project No. JK2024029Hubei Provincial Education Department Research Project No. B2024488Hubei Water Resources Technical College Special Doctoral Research Project HBSYBSZX202404the High-Level Talent Research Startup Fund of Xiangyang Polytechnic No. XYZYZZ202405the National Natural Science Foundation of China No. 42401030
6 · The paper itself

Abstract

The spatiotemporal accuracy of precipitation products is critical for their application in watershed hydrology, meteorology and drought monitoring. This study introduces a novel, multi-scale assessment framework to evaluate the accuracy of four widely used precipitation products [the Global Precipitation Measurement Integrated Multi-Satellite Retrievals (GPM IMERG), the Multi-Source Weighted Ensemble Precipitation (MSWEP), the China Meteorological Forcing Dataset, and the long-term, gauge-based gridded precipitation dataset for the Chinese mainland (CHM_PRE)]. A key innovation is the integration of precipitation zoning, achieved by applying the Rotated Empirical Orthogonal Function method to delineate the upper and middle reaches of the Hanjiang River Basin (UMHRB) into distinct precipitation zones. We then systematically assessed the performance within these zones in terms of daily statistical accuracy, capacity to capture spatiotemporal evolution, and skill in detecting precipitation events and extremes. This study validates the applicability of dividing the study area into five precipitation zones, as determined from observed data (1975–2018). A key finding is CHM_PRE is recommended as the most reliable product across all zones. In terms of precipitation event probability, MSWEP excels at reproducing the probability density distribution across various intensities, whereas CHM_PRE tends to overestimate the frequency of non-precipitation events (< 0.1 mm/d). Critically, a major discrepancy emerges in extreme precipitation detection: although all products show high capability at the watershed scale, their performance deteriorates markedly at the zonal scale. This was most pronounced for MSWEP, whose Kling–Gupta Efficiency for Rx1day dropped to as low as 0.07 in Zone 5 and 0.09 in Zone 3, indicating a failure to effectively capture extremes in these regions. This multi-faceted, zoning-level assessment provides a nuanced understanding of product performance, offering valuable insights for the informed selection of appropriate datasets tailored to specific hydrological and meteorological applications.

Indexed as

Extreme precipitation detectionmultidimensional accuracy evaluationprecipitation event probabilityPrecipitation productsREOF-based precipitation zoning scale

Identifiers

PMID41922501
PMCPMC13183927

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