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Correspondence to Author: Shenglian Guo and Fi-John Chang. 

Universidad Viña del Mar, Escuela de Ciencias, Viña del Mar,Chile

Abstract:

Global attention has been drawn to the effects of climate change on the management of water supplies as well as the rise in catastrophic natural catastrophes in recent decades. Effective management of water resources and the prevention of natural disasters depend on precise and dependable hydrological forecasts. Accurate forecasting is extremely difficult due to the infamously nonlinear hydrological processes, but developing accurate forecast models and dependable management systems calls for sophisticated methodologies. Artificial intelligence (AI) is one of the newest methods for modeling complicated systems. AI has the amazing capacity to effectively extract important information from vast volumes of data in order to solve complicated issues, and it can mimic how people learn. By utilizing the most recent cutting-edge methods, like artificial intelligence, the fourteen research papers included in this Special Issue greatly aid in the assessment of operational hydrologic forecasting uncertainty under shifting environmental conditions and the advancement of water resources management. The fourteen contributions fall into four main research areas: (1) hydrological forecasting using machine learning techniques; (2) assessing and analyzing uncertainty in hydrological modeling in dynamic environments; (3) artificial intelligence techniques for optimizing multi-objective reservoir operation; and (4) hazard mitigation adaptation strategies for extreme hydrological events. In addition to advancing the field of water sciences, the articles in this issue can help decision-makers manage water resources in a more efficient and sustainable manner.

Keywords:Water resources management, multi-objective reservoir operation, hydrologic forecasting, artificial intelligence, machine learning, uncertainty, and risk.

Citation:

Dr.Shenglian Guo, Developments In Water Resources Management And Hydrologic Forecasting. Journal Of Water Science 2025.