A Review of Precipitation Use Efficiency: Integrative Analysis of Ecological Connotation, Quantification Methods, and Driving Factors
Year: 2026
Type: article
Study design: Systematic Review
Abstract: Precipitation Use Efficiency (PUE) is a key ecological indicator for evaluating how vegetation converts precipitation into biomass or productivity. A thorough analysis of its quantification methods and driving mechanisms is of great significance for improving regional precipitation use efficiency and ensuring agricultural and ecological water security. In this study, we conducted a comprehensive literature search without time restrictions in the Web of Science and China National Knowledge Infrastructure (CNKI) databases, using “Precipitation Use Efficiency” and “PUE” as core keywords. After retrieval, a strict “independent dual-screening plus cross-checking” procedure was adopted with unified inclusion and exclusion criteria to ensure literature quality. Only highly relevant and methodologically rigorous studies were retained, resulting in a final set of 80 eligible publications. Key information was systematically extracted using content analysis, followed by integrated summarization and inductive analysis. This paper systematically illustrates the ecological connotation of PUE, compares diverse quantification and research methods with their applicable conditions, analyzes spatiotemporal differentiation characteristics and multidimensional driving mechanisms, summarizes practical approaches for PUE improvement, and reviews current research limitations. It represents a systematic integration and refinement of the research framework of precipitation use efficiency. The results can provide targeted theoretical support for revealing the driving mechanisms of PUE and promoting the efficient utilization of precipitation resources.
Source: Sustainability
DOI: 10.3390/su18083851
Language: English
Subfield: Water Science and Technology
Field: Environmental Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,896
Award: G1693404716
OpenAlex ID: W7154124257
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