Raja Fara Raja Abd Jalil , Kai Lun Chong , Yuk Feng Huang , Marlinda Binti Abdul Malek , Mohamed Elkollaly , Mohsen Sherif , Ahmed El-Shafie , Ali Najah Ahmed
{"title":"Advancing climate change impact assessment on global hydropower systems: Methodologies, models, and recommendations","authors":"Raja Fara Raja Abd Jalil , Kai Lun Chong , Yuk Feng Huang , Marlinda Binti Abdul Malek , Mohamed Elkollaly , Mohsen Sherif , Ahmed El-Shafie , Ali Najah Ahmed","doi":"10.1016/j.rser.2025.116364","DOIUrl":null,"url":null,"abstract":"<div><div>This review paper provides a comprehensive assessment of the methodologies, models, limitations, and recommendations for assessing the impact of climate change on global hydropower systems. It draws on numerous real-world examples and highlights crucial challenges such as data scarcity, which is exemplified by the limited historical hydrological and meteorological data in many regions. This scarcity of data impacts predictive models and simulations. The review also discusses model uncertainties and emphasizes the need for sophisticated hydrological and climate models. These models should be tested and validated against observed data to ensure reliability and accuracy. To address these challenges, the review advocates for enhanced data collection methods, advanced monitoring systems, and satellite technologies, as demonstrated by real-world examples from regions facing climate-induced risks. It also recommends advanced model sophistication, incorporating complex hydrological processes, climate drivers, and system interactions. This can be achieved through ensemble modeling approaches and machine learning algorithms to capture nonlinear relationships accurately. These advanced techniques enhance the predictive capabilities of models, leading to more robust and actionable strategies for managing hydropower resources under changing climate conditions. Overall, the review aims to improve the accuracy, reliability, and contextual relevance of climate change impact assessments on hydropower. This information can help decision-makers and practitioners to make informed decisions and implement resilient management practices for the essential water-energy nexus faced with a changing climate.</div></div>","PeriodicalId":418,"journal":{"name":"Renewable and Sustainable Energy Reviews","volume":"226 ","pages":"Article 116364"},"PeriodicalIF":16.3000,"publicationDate":"2025-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Renewable and Sustainable Energy Reviews","FirstCategoryId":"1","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1364032125010378","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0
Abstract
This review paper provides a comprehensive assessment of the methodologies, models, limitations, and recommendations for assessing the impact of climate change on global hydropower systems. It draws on numerous real-world examples and highlights crucial challenges such as data scarcity, which is exemplified by the limited historical hydrological and meteorological data in many regions. This scarcity of data impacts predictive models and simulations. The review also discusses model uncertainties and emphasizes the need for sophisticated hydrological and climate models. These models should be tested and validated against observed data to ensure reliability and accuracy. To address these challenges, the review advocates for enhanced data collection methods, advanced monitoring systems, and satellite technologies, as demonstrated by real-world examples from regions facing climate-induced risks. It also recommends advanced model sophistication, incorporating complex hydrological processes, climate drivers, and system interactions. This can be achieved through ensemble modeling approaches and machine learning algorithms to capture nonlinear relationships accurately. These advanced techniques enhance the predictive capabilities of models, leading to more robust and actionable strategies for managing hydropower resources under changing climate conditions. Overall, the review aims to improve the accuracy, reliability, and contextual relevance of climate change impact assessments on hydropower. This information can help decision-makers and practitioners to make informed decisions and implement resilient management practices for the essential water-energy nexus faced with a changing climate.
期刊介绍:
The mission of Renewable and Sustainable Energy Reviews is to disseminate the most compelling and pertinent critical insights in renewable and sustainable energy, fostering collaboration among the research community, private sector, and policy and decision makers. The journal aims to exchange challenges, solutions, innovative concepts, and technologies, contributing to sustainable development, the transition to a low-carbon future, and the attainment of emissions targets outlined by the United Nations Framework Convention on Climate Change.
Renewable and Sustainable Energy Reviews publishes a diverse range of content, including review papers, original research, case studies, and analyses of new technologies, all featuring a substantial review component such as critique, comparison, or analysis. Introducing a distinctive paper type, Expert Insights, the journal presents commissioned mini-reviews authored by field leaders, addressing topics of significant interest. Case studies undergo consideration only if they showcase the work's applicability to other regions or contribute valuable insights to the broader field of renewable and sustainable energy. Notably, a bibliographic or literature review lacking critical analysis is deemed unsuitable for publication.