Unlocking water management optimization: A data-driven exploration through bibliometric analysis

Abstract

The utilization of optimization models is crucial for the effective management of water resources. These models serve as key tools for promoting sustainable water distribution and conservation. Despite advancements in water management, gaps persist in comprehensively addressing core themes, evolutionary trends, and future research directions. This article aims to bridge this gap by providing a detailed examination of the application of bibliometric tools in the optimization of the water management context. The methodology employed in this study involved data science and text mining procedures. There was exponential growth in publications on the proposed topic, especially after the publication of the Sustainable Development Goals in 2015. The universities that published the most on the subject were The University of Tehran and Wuhan University, and the countries that had the most corresponding authors were China and Iran. During 2013 to 2019, keywords like “irrigation” and “multireservoir systems” were widely utilized in articles. However, particularly after 2019, which also encompasses the global pandemic period, terms such as “rainfall” and “runoff emerged as trending topics. Finally, future research should explore the integration of bibliometric analyses with empirical data and stakeholder perspectives.