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