A comprehensive optimum integrated water resources management approach for multidisciplinary water resources management problems.

A holistic Integrated Water Resources Management (IWRM) model can be difficult to implement and the associated high-dimension optimization problems' complexity often forces the decision makers to downscale such problems. These challenges however have motivated this research to develop a comprehensive Optimum IWRM approach (OP-IWRM) using a many-objective optimization algorithm to solve complex and large-scale problems. The approach employs the social, economic, and environmental objectives; ground and surface water resources; and water infrastructure for river basin management to: (1) improve the relevant revenues, (2) enhance community welfare, and (3) pave the road for the decision makers to set better investment policy. The results demonstrate comprehensive improvement of all considered targets. The decision makers may reconsider implementing complex integrated water resources management of large-scale regions. The OP-IWRM may extend for country-scale approach as a pathway towards a national sustainable development plan. The large-scale Diyala river basin, Iraq, was adopted to evaluate the approach using seventeen objectives and more than 1500 decision variables.

Optimum socio-environmental flows approach for reservoir operation strategy using many-objectives evolutionary optimization algorithm.

Water resource system complexity, high-dimension modelling difficulty and computational efficiency challenges often limit decision makers' strategies to combine environmental flow objectives (e.g. water quality, ecosystem) with social flow objectives (e.g. hydropower, water supply and agriculture). Hence, a novel Optimum Social-Environmental Flows (OSEF) with Auto-Adaptive Constraints (AAC) approach introduced as a river basin management decision support tool. The OSEF-AAC approach integrates Socio-Environmental (SE) objectives with convergence booster support to soften any computational challenges. Nine SE objectives and 396 decision variables modelled for Iraq's Diyala river basin. The approach's effectiveness evaluated using two non-environmental models and two inflows' scenarios. The advantage of OSEF-AAC approved, and other decision support alternatives highlighted that could enhance river basin SE sectors' revenues, as river basin economic benefits will improve as well. However, advanced land use and water exploitation policy would need adoption to secure the basin's SE sectors.

Reservoir operation using a robust evolutionary optimization algorithm.

In this research, a significant improvement in reservoir operation was achieved using a state-of-the-art evolutionary algorithm named Borg MOEA. A real-world multipurpose dam was used to test the algorithm's performance, and the target of the reservoir operation policy was to fulfil downstream water demands in drought condition while maintaining a sustainable quantity of water in the reservoir for the next year. The reservoir's performance was improved by increasing the maximum reservoir storage by 14.83 million m3. Furthermore, sustainable water storage in the reservoir was achieved for the next year, for the simulated low flow condition considered, while the total annual imbalance between the monthly reservoir releases and water demands was reduced by 64.7%. The algorithm converged quickly and reliably, and consistently good results were obtained. The methodology and results will be useful to decision makers and water managers for setting the policy to manage the reservoir efficiently and sustainably.