{"title":"Water Governance Prediction System Based on Fuzzy Logic","authors":"Samira Nabiafjadi, Maryam Sharifzadeh*, Mostafa Ahmadvand, Hossein Shabanali Fami and Sima Ziaee, ","doi":"10.1021/acsestwater.4c0067010.1021/acsestwater.4c00670","DOIUrl":null,"url":null,"abstract":"<p >In recent years, water governance has emerged as a critical concern, presenting challenges in predicting and assessing effective governance strategies. This paper introduces the water governance prediction system, based on a fuzzy logic controller (FLC), designed to dynamically evaluate the quality of water governance. Termed the water governance performance (WGP) model, it provides a holistic perspective that includes three key components: the water governance regime (WGR), water governance structure (WGS), and contextual factors. To validate the efficacy of the model, a case study was conducted in the Zayandeh-Rud basin in Iran, covering the period from 2006 to 2019. The model’s comprehensive approach and complexity equip water managers with valuable insights for decision-making. The study confirms the model’s efficiency in delivering accurate predictions based on effective data and indicators, highlighting its practical value in water governance assessments.</p>","PeriodicalId":93847,"journal":{"name":"ACS ES&T water","volume":"5 3","pages":"1086–1098 1086–1098"},"PeriodicalIF":4.8000,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS ES&T water","FirstCategoryId":"1085","ListUrlMain":"https://pubs.acs.org/doi/10.1021/acsestwater.4c00670","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
In recent years, water governance has emerged as a critical concern, presenting challenges in predicting and assessing effective governance strategies. This paper introduces the water governance prediction system, based on a fuzzy logic controller (FLC), designed to dynamically evaluate the quality of water governance. Termed the water governance performance (WGP) model, it provides a holistic perspective that includes three key components: the water governance regime (WGR), water governance structure (WGS), and contextual factors. To validate the efficacy of the model, a case study was conducted in the Zayandeh-Rud basin in Iran, covering the period from 2006 to 2019. The model’s comprehensive approach and complexity equip water managers with valuable insights for decision-making. The study confirms the model’s efficiency in delivering accurate predictions based on effective data and indicators, highlighting its practical value in water governance assessments.