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Title: Development of approaches to integrated water resources management
Author: Geng, Guoting
ISNI:       0000 0004 2731 8000
Awarding Body: University of Edinburgh
Current Institution: University of Edinburgh
Date of Award: 2010
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There is a growing need to manage water resources in a sustainable way, particularly in semi arid areas, with dramatic social and economic development as well as rapid population growth. Optimising water allocation in a river basin is an important aspect ensuring equitable and efficient water use. This research develops an optimisation approach (the Integrated Water Resource Optimisation model, IWRO) to optimise the conjunctive use of surface water and groundwater resources in a sustainable manner. The IWRO model is comprised of a surface water optimisation model (SWO) and the Tsinghua groundwater optimisation (TGO) model. These models employ Genetic Algorithms (GAs) to optimise water allocation. Application of a surface water optimisation (SWO) model incorporating a GA is demonstrated initially for a simple test case, through which the GA approach was validated against known solutions. Sensitivity analysis of different operators and parameters related to GAs was also carried out. The validated SWO model was then applied to a more complex system, the Shiyang River Basin in Gansu Province in China, to maximise equitable surface water supplies. On the groundwater side, the GA approach was applied with the existing Tsinghua groundwater model to optimise groundwater supplies with sustainability considerations. The results were compared with those from an existing model (the WEAP model), indicating that the IWRO model is capable of satisfying the objectives of equitable water allocation and groundwater sustainability set for it. In the context of Integrated Water Resources Management (IWRM), account must be taken of a wide range of social and environmental issues. Different scenarios were therefore designed for the Shiyang River Basin management. Various criteria in terms of economic, social, environment and water security were also indentified for further multi-criterion decision making analysis.
Supervisor: Wardlaw, Robin B. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: optimisation ; genetic algorithms ; integrated water resource optimisation ; Integrated Water Resources Management ; multi-criterion decision making