An overview of Data Envelopment Analysis applications and methodological approaches in water resources management

Abstract The use of mathematical models, such as D​​ata E​nvelopment Analysis (DEA), has become increasingly frequent in the literature on water resources management. Given the pressures posed by climate change and water scarcity, this review examines how DEA has been applied in studies in this field. Specifically, the review included 99 articles selected through a systematic review process following the PRISMA protocol. These articles were analyzed according to six categories: (i) general information, (ii) application context and sector, (iii) DEA model and orientation, (iv) input–output structure, (v) DEA advanced extensions, (vi) limitations and practical implications reported in the literature. The main findings indicate a predominance of studies at the national level, although the primary scale of application is regional/provincial, with sample size typically ranging from 11 to 30 DMUs. There is a recurring use of variable returns-to-scale models, with an emphasis on economic and productivity inputs and outputs associated with water resources. Extensions focused on performance discrimination and benchmarking stand out, indicating a concern with the analytical and comparative capacity of the applied models. The data are limited in terms of frequency, availability, quality, and granularity. The main practical implications concern public policies related to water governance, including regulatory design and resource allocation. The review reveals a tendency toward analytical reductionism, with limited attention to social dimensions and uncertainty. Drawing on the findings of this review and the corpus analyzed, a ten-step guide is proposed for applying DEA in water resources management.