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Urban water resource management for sustainable environment planning using artificial intelligence techniques
Institution:5. School of Economics and Management, Qinghai Nationalities University, Xining 810007, Qinghai, China;1. Faculty of Natural Resources, University of Tehran, Karaj, Iran;2. Amirkabir University Foundation''s Nexus and HSE Center, Tehran, Iran;3. Environmental Geography Group, Institute for Environmental Studies, Vrije Universiteit Amsterdam, De Boelelaan 1087, 1081 HV, Amsterdam, the Netherlands;4. Swiss Federal Institute for Forest Snow and Landscape Research, WSL Zürcherstrasse 111, CH-8903, Birmensdorf, Switzerland;1. Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Sciences, Northwest University, Xi''an 710127, China;2. State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation, Chinese Academy of Sciences, Yangling 712100, China;3. University of Chinese Academy of Sciences, Beijing 100049, China;1. Bureau of Hydrology, ChangJiang Water Resources Commission, Wuhan, 430010, China;2. School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan, 430074, China
Abstract:In the current era, water is a significant resource for socio-economic growth and the protection of healthy environments. Properly controlled water resources are considered a vital part of development, which reduces poverty and equity. Conventional Water system Management maximizes the existing water flows available to satisfy all competing demands, including on-site water and groundwater. Therefore, Climatic change would intensify the specific challenges in water resource management by contributing to uncertainty. Sustainable water resources management is an essential process for ensuring the earth's life and the future. Nonlinear effects, stochastic dynamics, and hydraulic constraints are challenging in ecological planning for sustainable water development. In this paper, Adaptive Intelligent Dynamic Water Resource Planning (AIDWRP) has been proposed to sustain the urban areas' water environment. Here, an adaptive intelligent approach is a subset of the Artificial Intelligence (AI) technique in which environmental planning for sustainable water development has been modeled effectively. Artificial intelligence modeling improves water efficiency by transforming information into a leaner process, improving decision-making based on data-driven by combining numeric AI tools and human intellectual skills. In AIDWRP, Markov Decision Process (MDP) discusses the dynamic water resource management issue with annual use and released locational constraints that develop sensitivity-driven methods to optimize several efficient environmental planning and management policies. Consequently, there is a specific relief from the engagement of supply and demand for water resources, and substantial improvements in local economic efficiency have been simulated with numerical outcomes.
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