Optimization of Water Resource System for Productivity: Assessment, Evaluation, and Allocation in Rift Valley Basin, Ethiopia

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Date

2025-02

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Addis Ababa University

Abstract

Developing an optimized water allocation model that includes a comprehensive assessment of water demand and resources, as well as system performance evaluation, to enhance water productivity and sustainability in the basin is the main objective of this study. Because it addresses the challenges of inconsistent water availability data, evaluates the water resource system’s performance, and proposes solutions for optimized economic efficiency and environmental sustainability. This study examines the optimization of water resource systems in the Rift Valley Lakes Basin (RVLB) of Ethiopia, with a focus on enhancing water productivity, economic efficiency, and environmental sustainability. The research addresses critical challenges such as water scarcity, inefficient resource use, climate variability, and environmental degradation, which collectively threaten the socio-economic development and ecological health of the basin. The study also employs advanced tools such as the Water Evaluation and Planning (WEAP) model and multispectral remote sensing to assess the basin's water resources and demand. A comprehensive hydrological analysis reveals that while the RVLB receives substantial rainfall annually, the majority is lost through evaporation, leaving limited surface and groundwater resources for abstraction. Irrigated agriculture, which consumes the largest share of water, is characterized by inefficiencies due to traditional irrigation practices and inadequate infrastructure. A detailed mapping of irrigated areas using Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) techniques highlights discrepancies in reported data and demonstrates the value of remote sensing for accurate resource management. The water demand analysis projects a significant increase in demand by 2050 due to population growth and expanded irrigation, underscoring the urgent need for strategic interventions. The research evaluates the water resource system's performance through indicators such as reliability, resilience, and vulnerability, revealing gaps in the current system. To address these challenges, a multi-objective optimization model based on the NSGA-II approach is developed. This model balances competing objectives such as economic returns, equity, and sustainability, providing decision-makers with actionable insights into efficient water allocation strategies. Key recommendations include the development of integrated water resource management (IWRM) policies, investments in modern irrigation and storage infrastructure, and the enhancement of data collection and monitoring systems using GIS and remote sensing technologies. Additionally, stakeholder engagement, climate-resilient planning, and environmental protection measures are emphasized. Strategic interventions must align with projected demands while ensuring equitable and sustainable resource use. This study contributes significantly to water resource management by providing a holistic framework for optimizing allocation and enhancing productivity. Its findings and recommendations serve as a roadmap for policymakers, stakeholders, and researchers, offering solutions to safeguard the RVLB's water resources and promote sustainable development. The major findings are: • The current irrigated area of the RVLB is 108,000 ha, estimated using multispectral satellite imagery and ground truth verification and the potential irrigable area is 230,400 ha. • The basin receives 50.03 BCM of mean annual precipitation, with 83% (41.32 BCM) lost to evaporation. And the available surface water for abstraction includes 358 MCM from lakes and 6,534 MCM from streamflow, totalling 6,892 MCM. • The total current water demand is 1,796.34 MCM, with irrigation taking the largest share (58%), followed by livestock (13%). Agricultural water demand accounts for 71% of total demand. Seasonal water deficits occur, especially in January (329 MCM demand vs. 216 MCM supply) and December (304 MCM demand vs. 250 MCM supply). The projected demand for 2035 ranges from 1,628.23 MCM to 3,146.89 MCM, depending on different scenarios. • Water productivity varies from 0.7 kg/m³ to 1.58 kg/m³, with an average of 1.13 kg/m³. • A multi-objective optimization model (NSGA-II) was developed to balance economic efficiency, equity, and environmental sustainability. Pareto front solutions: If the goal is to minimize f1 (maximizing economic return), solution S1 can be chosen, as it is preference degree for f1 is 0.995, while for f2 (maximizing equity) it is only 0.005. Similarly, if the aim is to maximize f2, S20 is ideal, with a preference degree of 0.992 for f2 and just 0.008 for f1. For decision-makers who value both objectives equally, S10 is recommended, as it is preference degree for f1 (0.566) is closest to that for f2 (0.434) among all non-inferior solutions.

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Keywords

Allocation · Optimization · Eiciency · Equity · Sustainability · Multi-objective · Water resource · Rift Valley, Lakes Basin, analysis, evaluation, image, irrigated, mapping

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