Water is vital for life and various biophysical processes, yet despite covering over 71% of Earth's surface, it remains a scarce resource due to uneven distribution and management challenges. Water scarcity is a growing global issue, and in Jimma town, Ethiopia, the mismatch between water supply and demand is especially severe. This is exacerbated by rapid population growth and urban expansion, which stress the town's already limited water resources. This study assesses the impacts of climate change and land use changes on Jimma's water supply and demand using the Water Evaluation and Planning (WEAP) model. The research employs a scenario-based approach, considering five scenarios: current conditions, climate change, land use changes, combined impacts, and population growth. Results show that Jimma faces significant water shortages in November, December, January, and February, with additional shortages in April and May. Supply coverage is especially low in February (92%) and fluctuates in August and September due to prioritization of demand. Projections suggest that water demand could rise to 4.5 gigaliters by 2030, with unmet demand reaching 1.6 GL. The combined effects of climate change and land use changes may worsen these shortages, underscoring the urgent need for effective water management to ensure long-term sustainability.

  • Scenario analysis is a valuable tool for developing strategies to achieve sustainable water management in response to the growing challenges posed by population growth and climate change.

  • The study examines the current water demand and explores strategies to enhance the efficiency and performance of the water supply system.

Water is a limited and vulnerable resource essential for sustaining life, socio-economic development, and environmental health (Silva-Novoa Sánchez et al. 2022). Despite covering most of the Earth's surface, water remains a scarce resource indispensable for all forms of life. It is essential to sustain agriculture, industry, ecosystems, and human communities (Scanlon et al. 2023). However, water scarcity is indeed a serious challenge, often resulting in conflicts and a higher demand from society where there are not enough resources in order to ensure such basic needs (Shemer et al. 2023). The global water cycle is accelerating due to climate and land use changes, a trend expected to increase in the future (Newell 2023; Tilahun et al. 2023). Rising global temperatures due to climate change can accelerate evaporation rates, increasing atmospheric moisture, while land use changes, such as deforestation and urbanization, can alter water infiltration and runoff patterns across the landscape. Such acceleration exacerbates water scarcity, directly impacting food production, community livelihoods, and ecosystem health (Godde et al. 2021). Ethiopia, known as the ‘water tower of East Africa’, frequently faces water shortages for drinking, irrigation, and other essential uses due to suboptimal water resource utilization and management practices (Tefera 2017). In Jimma town, the growing pressures due to population growth, climate change, and land use changes have significantly impacted water accessibility and demand (Muche et al. 2023). As Ethiopia's population continues to grow, accompanied by expanding urbanization, industrialization, and agricultural activities, water demand has surged.

The rapidly urbanizing region of southwestern Ethiopia is experiencing substantial changes in land use, driven by agricultural expansion, urban development, and deforestation. These changes, along with fluctuating climate patterns, have changed the hydrological cycle, affecting both the quantity and quality of water available for various uses. Tefera et al. (2023) indicate that changes in precipitation and temperature have resulted in decreased river flows and altered seasonal water availability, which are crucial for effective water management. Increased variability in rainfall patterns, rising temperatures, and more frequent extreme weather events are further worsening the water supply challenges, making it imperative to adopt an integrated approach to water resource management. Similarly, Mummed & Seleshi (2024) emphasize the significant implications of climate variability for water resource planning in Ethiopia, particularly in regions such as Jimma. Land use/land cover change (LULCC) are also essential factors that influence water supply and demand. Urban and industrial expansion, deforestation, and agricultural intensification can significantly change hydrological processes by affecting water infiltration, runoff, and evapotranspiration (Abebe et al. 2019; Demissie 2022). Liu et al. (2019) revealed that urbanization increases impervious surfaces, which in turn leads to more surface runoff and less groundwater recharge. Cheng et al. (2019) demonstrated that deforestation and the conversion of agricultural land lead to decreased water retention and increased soil erosion, which negatively impacts both water quality and availability. In Jimma, rapid population growth and changes in land use are intensifying water stress. Jimma town faces increasing challenges in ensuring adequate, accessible, and safe water supply to meet growing population demands, which is vital for development. In the town, a significant gap exists between water demand and supply, as the current water infrastructure faces considerable challenges. Managed by the Jimma town municipality, the water supply system serves a rapidly growing population but struggles to meet the rising demand, especially during peak periods and in more remote areas. Reports indicate that the town's water supply capacity is approximately 28,000 m3/day, which falls short of the population's needs. This shortfall is exacerbated by an expanding urban population, irregular rainfall patterns, and underdeveloped water infrastructure (World Bank 2011). The impact of climate and land use changes on water resources is becoming increasingly apparent, particularly in this town where integrated assessments of water supply and demand are crucial. This escalating demand, compounded by the effects of climate change, has intensified the stress on existing water resources, leading to substantial challenges in water supply management and sustainability.

To tackle these challenges, the WEAP tool offers a comprehensive approach to Integrated Water Resources Management (IWRM). The WEAP system offers a robust framework for analyzing the complex interaction between water supply and demand in the context of changing environmental and socio-economic conditions (Ayt Ougougdal et al. 2020; Dlamini et al. 2023). WEAP facilitates the simulation of water supply and demand under various scenarios, integrating data on climate, land use, water demand, and supply to provide a comprehensive analysis of water systems (Yao et al. 2021). Recent studies highlight the effectiveness of the WEAP model in simulating water resources amidst evolving environmental and societal situations. Opere et al. (2022) used WEAP to assess the impact of climate change on water resources, demonstrating the tool's effectiveness in capturing water supply and demand dynamics. Similarly, Tena et al. (2019) used WEAP to model the impacts of land use changes on water availability, highlighting its ability to simulate complex environmental interactions. Mengistu et al. (2021) investigated the long-term impacts of climate change on the Upper Blue Nile (Abay) River Basin using a regional climate model. Their analysis primarily focused on the hydrological changes in the basin driven by climate factors. However, climate change alone does not fully explain the complexities of water stress, particularly in areas experiencing rapid urbanization. Our research aims to integrate multiple factors such as population growth, land use changes due to urban expansion, and the long-term effects of climate change to provide a comprehensive evaluation of urban water demand and supply in Jimma town. This multi-faceted approach represents a significant innovation in our study, as water stress arises from the interaction of several drivers rather than just climate variability. Also, the importance of a scenario-based approach to water resource modeling has been emphasized by Al Khoury et al. (2023), who demonstrated that considering multiple drivers leads to a more accurate understanding of water demand and supply dynamics. Similarly, Abadi et al. (2024) highlighted the necessity of factoring in land use changes, irrigation growth, and climate change in water resource modeling to address future water challenges effectively. Our study integrates these essential drivers by employing a comprehensive framework that considers the demographic, environmental, and climatic factors affecting urban water availability.

This study aims to model the impact of climate and land use changes on water supply and demand in Jimma, Ethiopia, using the WEAP tool. To achieve this objective, the study comprehensively assessed the Gilgel Gibe River's water resources, projected future water demand under various development scenarios, and evaluated the potential impacts of these changes on both the river's ecosystem and Jimma town's water supply. By integrating climate projections with land use scenarios, this research seeks to offer insights into how these factors influence water resources in the area. The study addresses existing gaps in knowledge and provides valuable information for policymakers, planners, and stakeholders involved in water resource management, contributing to more effective strategies for managing water scarcity and promoting sustainable development in Jimma and similar regions. Also, the findings of this study provide valuable insights for water resource managers and stakeholders to develop adaptive strategies for ensuring a reliable and resilient water supply in the face of environmental and socio-economic changes.

The study area

Jimma is located in the southwestern part of Ethiopia and is prominent for its abundant natural resources, including water bodies, fertile lands, and diverse ecosystems. Jimma is the seat of the Jimma Administrative Zone and lies approximately 350 km southwest of Addis Ababa. It is located between latitudes 7°39′ and 7°42′ N and longitudes 36°47′ and 36°54′ E. The area's elevation varies from 1,100 to 3,341 m.a.s.l. The area is characterized by a tropical climate with substantial rainfall, dense forests, and an abundance of rivers and streams, making it a critical area for water resource management (Mitiku et al. 2024). One of the most significant watercourses in the area is the Gilgel Gibe River, which flows through Jimma and serves as a vital water source for both urban and rural communities. This river supports a range of activities, including domestic water use, irrigation for agriculture, and industrial operations. Additionally, the Gilgel Gibe Hydropower Plant, which is built on the course of the river, contributes by supplying energy to the region and the entire nation. The river's basin, which encompasses various tributaries and associated wetlands, substantially contributes to the region's water supply system. The area experiences a tropical monsoon climate, characterized by a long rainy season from June to September and a shorter dry season from November to February. The annual rainfall in the region averages around 1,500–2,000 mm, with the heaviest precipitation occurring during the summer months (Gashaw et al. 2023). The annual temperature varies between 14 and 34 °C throughout the year, contributing to the region's high agricultural productivity. The geological structure of the region is composed of diverse Tertiary volcanic formations and more recent Quaternary sediments (Mathewos et al. 2024). The area predominantly features two main soil types: reddish-brown residual soils and alluvial soils, which range from brownish-gray to grayish-white clay. Jimma town, with its growing population, has seen a steady increase in water demand. The demand is primarily driven by domestic needs, including drinking water, sanitation, and industrial use. With an estimated population of over 239,022 people, the water demand is expected to rise further due to urban expansion and economic development (CSA 2007) (Figure 1).
Figure 1

Location map of the study area.

Figure 1

Location map of the study area.

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Data collection

In this study, a comprehensive set of data was collected to analyze water demand and supply using the WEAP model. The dataset includes hydrometeorological data such as relative humidity, wind speed, solar radiation, temperature, rainfall, and streamflow, along with information on water demand, land cover, soil type, surface water, and reservoir data. Additionally, population and household-level consumption data, as well as climate scenarios, were incorporated into the analysis. Domestic and non-domestic water demand data were sourced from the Jimma town water supply and sewerage service enterprise (JTWSSSE), and hydrology datasets from repositories such as the Global Runoff Data Centre https://grdc.bafg.de/GRDC/EN/01_GRDC/13_dtbse/database_node.html). The data covered the aggregate water consumption from 2015 to 2023, as indicated on water bills across four demand sites or town branches. Surface water was identified as the primary source of water, with Gilgel Gibe and Boye serving as the main supply sources. The water distribution network comprises four subsystems that are linked to the main reservoirs at Jiren Kella. These subsystems are Boye, Ginjo, Hospital, and Aba Jifar. Specifically, the Aba Jifar subsystem is connected to the Ginjo supporter pumping station, which pumps water to a reservoir situated near the Aba Jifar Palace. This setup supplies water to the Jiren area and the neighborhood around Mosque 40. The study used daily and monthly data from the Gilgel Gibe and Jimma rainfall stations, as well as temperature pan records from Gibe and Boye obtained from the Google Earth Engine from 1993 to 2023. Furthermore, monthly inflow, storage capacity, and water supply data in million metric cubes for the same period were obtained from the JTWSSSE. The preferred water supply method was identified as one where a demand site (DS) is connected to multiple supply sources. Water supply data from 2015 to 2023 were gathered from the JTWSSSE for two primary reservoirs (Jiren Kella and Ginjo), five wells (including two from Kitto wells: Plywood and AADu), and three springs (St. Gabriel, Jiren, and Legahare). Additionally, several wells are supplied to individual users, such as the Jimma Hotel and Jimma College of Agriculture. The primary water source for the town is the Gilgel Gibe River, utilizing a weir intake structure built in 1994/95. This system was initially designed to serve a projected population of 123,000 over a 10-year period, which has already expired. However, estimates indicate that the Gilgel Gibe River's flow is sufficient to meet Jimma's water demand until 2035, assuming 50% of the minimum or drought flow is reserved for downstream needs (MoWE 2023). The water treatment plant, spanning over 10,000 m2, has a capacity of 34,000 m3/day. Currently, the average annual water production is 8.6 million m3, with 6.9 million m3 available for consumption (Table 1).

Table 1

Water supply capacity of Jimma town reservoirs

IDDescriptionStatusSupplied fromCapacity (m3)Elevation (m)Bed level (m)Min. water level (m)Max. water level (m)
01 Jiren Kella Main Reservoir New O-PS_01 4,000 1,723 1,890 1,892 1,896.65 
02 Ginjo Reservoir and Booster Station Existing PR-01 500 1,712 1,840 1,842 1,844.30 
03 Hospital Reservoir Existing J-G12 2,500 1,801 1,779 1,937 1,942 
04 Gabriel Reservoir Existing J-B062 2,500 1,780 1,779 1,781 1,786 
05 Aba Jifar Reservoir New O-PB-02 200 2.024 2,020 2,022 2,024 
Total    9,750     
IDDescriptionStatusSupplied fromCapacity (m3)Elevation (m)Bed level (m)Min. water level (m)Max. water level (m)
01 Jiren Kella Main Reservoir New O-PS_01 4,000 1,723 1,890 1,892 1,896.65 
02 Ginjo Reservoir and Booster Station Existing PR-01 500 1,712 1,840 1,842 1,844.30 
03 Hospital Reservoir Existing J-G12 2,500 1,801 1,779 1,937 1,942 
04 Gabriel Reservoir Existing J-B062 2,500 1,780 1,779 1,781 1,786 
05 Aba Jifar Reservoir New O-PB-02 200 2.024 2,020 2,022 2,024 
Total    9,750     

The bed level of a reservoir refers to the elevation of its bottom or the lowest point at which water can be retained. Above this level, the minimum water level marks the lowest point from which water can be effectively stored or extracted. Conversely, the maximum water level represents the highest point that water can reach before overflowing or spilling.

Methods

WEAP model

To assess the impacts of climate and land use change on water supply and demand within Jimma town, this study employed the WEAP model, which was developed by the Stockholm Environment Institute. WEAP is a widely recognized tool for IWRM. Its capacity to simulate water demand, supply, flow, and storage makes it particularly suitable for proactive planning. With applications at both national and international scales, the WEAP provides a flexible framework for policy analysis and robust management of water-related data (Saleem et al. 2021; Hadri et al. 2022). In the WEAP model applied to the analysis of Jimma town's water demand and supply, the modeling scenario is structured into three distinct stages: (i) the base year (or current year), which serves as the foundation for the model; (ii) a reference scenario, generated from current data, which forecasts potential system developments under existing conditions; and (iii) ‘what-if’ scenarios, designed to modify the reference scenario, allowing for the evaluation of changes in technology and regulations on the system's performance. This scenario addresses a wide range of questions, including ‘what-if’ and the potential impacts of future climate pattern changes and population growth. The WEAP scenario is grounded in assumptions regarding how water resources are expected to be influenced by climate change, population growth, and changes in land use. Water modeling and scenario analysis are highly effective approaches for evaluating and planning water systems. The efficient and sustainable management of water resources is crucial for addressing challenges related to access to clean water, particularly for low-income residents and school children in Jimma town. These methods also play a vital role in ensuring that the town's population has a sufficient and dependable water supply over the long term.

Water supply: effective management of water supply involves balancing multiple interconnected factors, including land cover, soil types, water sources (such as groundwater, streams, rivers, and reservoirs), water quality, and demands from various sectors (agriculture, domestic use, livestock, and industry) (RaziSadath et al. 2023). This balance also requires consideration of water withdrawals, economic assessments, and other essential factors. To evaluate the impact of climate change on the equilibrium between water supply and demand within the WEAP model, the study utilizes average precipitation data for reservoir catchment areas spanning from 2015 to 2023.

Water demand: the primary challenge in designing and managing a water demand network (WDN) lies in accurately estimating the quantity of required water, which is influenced by dynamic and variable factors. These include population growth, variable climate, land use changes, the number of service connections, and evolving customer lifestyles (Jalal 2008; Beker & Kansal 2024). Modeling water demand within a WDN is complex due to fluctuating variables that necessitate adaptive strategies (Figure 2). The WEAP model incorporates population data from Jimma town to assess water demand (for Gilgel Gibe) (Timotewos et al. 2023).
Figure 2

Water demand–supply balance and interventions.

Figure 2

Water demand–supply balance and interventions.

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The above diagram illustrates the relationship between water demand and influencing factors, population growth, water supply sources, and strategic interventions and its depiction of their interactions. The left side, symbolized by a water droplet, represents demand, while the triangular structure conceptually balances supply and demand. Three arrows represent key factors: population growth (increasing demand), water supply sources (which contribute to meeting demand), and interventions (optimizing supply or regulating demand).

Stochastic demand forecasting: this method addresses the unpredictable nature of water demand across different times and locations (Saleem et al. 2021). It relies on historical consumption patterns for various user categories (residential, industrial, and commercial) and anticipates changes over the forecast period. The model prioritizes high-demand needs first and then addresses lower-priority demands, ensuring all categories are adequately met (Tayyebi et al. 2023). The priority structure includes both residential (households) and non-residential (industrial, commercial, and construction) water needs.

Key assumptions: these user-defined variables are crucial for evaluating water supply and demand systems (Mugatsia 2010). Important considerations include population growth, usage patterns, resource availability, infrastructure capacity, water losses, and conservation efforts.

Per capita consumption: this metric indicates the number of individuals served by each water service and is expected to evolve (Jorgensen et al. 2014; Esraa et al. 2023). The study uses this metric to project both current and future proportions of individuals being and/or to be served in each demand category by considering various influencing factors.

Adjusted domestic water demand: the study refines domestic water demand estimates by incorporating climatic and socio-economic factors, thereby providing a more accurate average demand (Merheb & Abdallah 2022).

Climatic adjustment factor: climate change is anticipated to affect water resource systems at both global, regional and local levels (Sheikha-BagemGhaleh et al. 2023). Adjustments for consumption levels account for regional climate conditions, with lower demands in cooler regions and higher demands in areas experiencing extreme temperatures. Even if the most severe climate change impacts are not realized, water supplies will remain vulnerable. This factor aids in evaluating water management strategies and promoting coordinated measures among all water users. In the WEAP model, water demand for a given DS is calculated by summing the demands of all its bottom-level branches (Br). A bottom-level branch is defined as one that has no subdivisions beneath it (SEI 2011; Al-Shutayri & Al-Juaidi 2019). The total water demand at any DS is determined by the formula:
(1)
For a particular DS, the water demand can also be calculated using population data:
(2)
The total activity level for a bottom-level branch is calculated as the cumulative product of the activity levels from that branch up through its hierarchy to the DS branch, represented by:
(3)
where Br represents the bottom-level branch, Br′ is its parent branch, and Br′′ is its grandparent branch, illustrating the hierarchical structure of the calculation. The WEAP software calculates water demand by aggregating the demands from all bottom-level branches. The annual water demand for a DS is expressed as:
(4)
The total activity level for any given bottom-level branch (Br) is estimated using the following formula:
(5)

In this hierarchy, Br denotes the lowest-level branch, while Br′ and Br″ represent the parent and grandparent branches, respectively. This methodology is extracted from the WEAP software (WEAP 2017), and it provides a robust framework for simulating and analyzing water demand and supply scenarios.

Data sources for scenario development

This study utilizes a varied range of data sources to develop comprehensive scenarios. Historical climate data records from 1992 to 2024 were obtained from the Ethiopian Meteorological Institute. Additionally, high-resolution (0.05°) climate data from the Climate Hazards Group InfraRed Precipitation with Station Data for the same period were accessed (https://www.chc.ucsb.edu/data/chirps). These datasets provided baseline information on key climatic variables, including temperature, solar radiation, relative humidity, wind speed, and precipitation trends. For Land Use/Land Cover (LULC) classification and mapping, satellite imagery and Geographic Information System (GIS)-based land cover datasets were employed. Specifically, 30-m resolution Landsat data from the Thematic Mapper (1993), Enhanced Thematic Mapper Plus (ETM + , 2001 and 2009), and Landsat Operational Land Imager (2017 and 2023) were downloaded from https://earthexplorer.usgs.gov/ and processed using Google Earth Engine (https://earthengine.google.com/). These datasets were instrumental in assessing historical land use changes over time. Socio-economic data, including local census information and population growth statistics, were sourced from the Jimma Census Bureau and the Central Statistical Agency (CSA) of Ethiopia (2007). These datasets were vital for understanding urban expansion patterns and demographic trends (Figure 3). To ensure consistency and accuracy, the imagery was preprocessed using preprocessing techniques such as atmospheric correction, cloud masking, and geometric correction. Supervised classification methods Maximum Likelihood Classifier were used to classify LULC into several classes. In addition, this study combines climate change and LULCC into the WEAP model for Jimma town, significantly improving its ability to predict future water resource challenges. Previous research often concentrated on individual factors, such as Gedefaw & Denghua (2023), who utilized the SWAT model to evaluate the effects of climate variability on surface water runoff and groundwater recharge, or Ngondo et al. (2022), who examined the impacts of LULCC on streamflow without considering climate change scenarios. This research fills those gaps by integrating both factors within a multi-scenario framework. This combination enhances predictive accuracy by reflecting the real-world interactions between climate conditions and land use changes, leading to more dependable estimates of future water availability and demand. Furthermore, the study improves scenario analysis by exploring various climate projections and urbanization-driven LULCC, equipping decision-makers with tools to evaluate adaptation strategies. By thoroughly examining the combined effects of climate change and LULCC, this approach provides valuable insights for urban water resource management, especially in tackling issues like rising water demand and diminished groundwater recharge due to rapid urban growth. Finally, this comprehensive methodology elevates the WEAP model beyond traditional single-variable analyses, ensuring a more precise depiction of future water stress conditions.
Figure 3

Methodological flowchart for the WEAP Model (Source: Adapted from own production, 2025).

Figure 3

Methodological flowchart for the WEAP Model (Source: Adapted from own production, 2025).

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Scenario analysis

The study employs the WEAP modeling tool to analyze the impacts of various scenarios on water supply and demand in Jimma. This includes assessing both the variables influencing water supply and demand, in addition to the broader context of impacting factors. Key variables include climate change, LULCC, population growth, and their combined impacts on Jimma town's demand and supply. Using a multi-scenario framework is essential for distinguishing climate-induced and human-driven impacts on streamflow. This framework evaluates the combined effects of climate change, land use dynamics, and population growth on urban water demand and supply (Shahid et al. 2018).

  • Scenario 1: reference scenario

The reference scenario serves as the baseline for comparison, reflecting current water supply and demand conditions without any alterations due to external factors (Al Sabeh et al. 2024). It incorporates the existing climate, land use patterns, water management practices, and population data as of the present day. This scenario provides a status quo perspective, establishing a benchmark against which the impacts of the other scenarios can be measured.

  • Scenario 2: climate change scenario

In this scenario, the analysis focuses on the projected impacts of climate change on Jimma's water supply and demand. Climate variables, such as temperature, precipitation patterns, and evapotranspiration rates, are adjusted based on climate models and projections for the area (Goyburo et al. 2023). The scenario examines how shifts in climate parameters, including increased temperatures, altered rainfall patterns, and prolonged dry periods, affect the availability of water resources and the demand for water in agriculture, domestic use, and other sectors.

  • Scenario 3: LULCC scenario

This scenario investigates the effects of changes in LULC on water supply and demand in Jimma. It explores how urban expansion, deforestation, agricultural land conversion, and other changes influence the hydrological cycle, including surface runoff, infiltration, and groundwater recharge (Hanifehlou et al. 2022). The scenario assesses the consequences of increased impervious surfaces, reduced vegetation cover, and altered land management practices on water availability and sustainability.

  • Scenario 4: combined impact scenario

The combined impact scenario integrates the effects of both climate change and LULC changes on water supply and demand. This comprehensive analysis considers the synergistic and potentially compounding effects of simultaneous changes in climate conditions and land use patterns (Abungba et al. 2022). It aims to capture the complex interactions between these factors and their collective impact on the hydrological system, providing insights into the cumulative stress on water resources under multiple pressures.

  • Scenario 5: population growth scenario

This scenario examines the impact of population growth on water supply and demand in Jimma. It models future population projections and evaluates the additional pressure on water resources as a result of increased domestic, industrial, and agricultural water demands (Saketa 2022). The scenario explores how growing population levels, coupled with existing water management challenges, could lead to intensified competition for limited water supplies, potentially exacerbating water scarcity issues. Each scenario provides valuable insights into the specific and combined impacts of various drivers of change on Jimma's water resources. These scenario analysis methods can inform decision-makers and stakeholders in developing adaptive strategies and sustainable water management practices to address the challenges posed by climate change, land use alterations, and population growth in the region.

Seasonal water deficit modeling method

Analyzing seasonal water deficits within the WEAP model enhances the assessment of water resources by addressing significant seasonal variations in supply and demand. This is particularly important in areas like Jimma town, which experience prominent climatic fluctuations and changes in land use. Unlike traditional annual water balance evaluations, this research focuses on seasonal deficits by dividing the hydrological year into wet and dry seasons. It also considers sector-specific demand changes based on historical data, population growth, and land use data. Water deficits are calculated as the difference between total demand and available supply, with surface water runoff modeled according to seasonal precipitation and infiltration rates. Scenario-based modeling, which takes into account climate change and urbanization, indicates that shortages during the dry season are expected to worsen due to decreased precipitation, increased evapotranspiration, and reduced groundwater recharge (Bo et al. 2021). This approach improves methodological contributions by enhancing predictive accuracy, facilitating dynamic scenario analysis, and guiding sustainable water management practices. The water deficit calculation equation is as follows:
(6)

Calibration and validation

Calibrating hydrological models, particularly in data-scarce catchments, presents substantial challenges. To address these issues, several methods have been developed to extend the application of watershed models (Sidle 2021). First, the regionalization approach involves calibrating model parameters in gauged catchments and then applying these parameters to similar, ungauged catchments. This method groups catchments with similar characteristics such as physiography, geology, soils, climate, and vegetation to predict hydrologic variables in ungauged areas (Moges et al. 2020). Second, the spatial proximity approach assumes that neighboring catchments with similar physical and climatic attributes will exhibit comparable hydrological responses. This approach is particularly useful for estimating hydrological variables in ungauged catchments. Third, calibration with regression methods establishes empirical relationships between catchment descriptors (physical and climatic characteristics) and model parameters calibrated from observed data in gauged catchments. This method uses regression equations to predict parameters for ungauged watersheds based on their physical attributes (Mengistu & Assefa 2019). The regionalization approach categorizes catchments into similar regions to evaluate whether areas within the same region exhibit comparable hydrological responses. By transferring model parameters from gauged catchments to ungauged ones within the same regional classification, this method enhances the assessment of hydrological variables in data-limited areas.

Basic assumptions

The WEAP model's basic assumptions are built on key demographic and consumption parameters, including the total population, per capita daily water consumption, annual water usage per capita, growth rates, and water loss percentages in the distribution network. The model is set up with 2015 as the base year. For the base year of 2015, Jimma town's total population is considered to be 200,000 individuals. The per capita daily water consumption rate is set at 50 liters per person per day, in alignment with the Growth and Transformation Plan II of Ethiopia, which outlines the standards for urban water consumption (MoWE 2016). This translates to an annual water consumption of approximately 18.25 m3/capita/year. The model incorporates a population growth rate of 2.7%, reflecting the expected annual increase in the town's population over the simulation period. This growth rate is crucial for projecting future water demand as the population expands. Additionally, the model accounts for inefficiencies within the water distribution network by including a water loss assumption of 15%. This figure represents the percentage of water lost due to leakages, theft, or other inefficiencies in the system, which directly impacts the overall water supply available for consumption. These assumptions form the foundation for the scenario analyses conducted in the WEAP model, enabling the simulation of various future water supply and demand scenarios under changing demographic and infrastructural conditions (Assefa 2023).

WEAP model setup

In the setup phase of the WEAP model, all elements of the water resource system under study and the parameters for analysis are defined (Adgolign et al. 2016; Farrokhzadeh et al. 2020). The model includes four main types of system components: (1) demand sites, which represent areas where water is consumed; (2) local supply sources, encompassing reservoirs, groundwater, and other local water supplies; (3) wastewater treatment facilities, which manage and treat used water before it is discharged or reused; and (4) rivers and their nodes, which represent the interconnected water resources and river-based uses within a unified river network managed through a river simulation framework (Figure 4). This study used the Water Evaluation and Planning (WEAP) model to simulate water demand and supply, configuring demand sites (domestic, agricultural, and industrial) based on local data and simulating supply sources (rivers, reservoirs, and groundwater) and infrastructure (dams and pipelines). WEAP's hydrological module used climatic data to resemble processes such as runoff and trends of water loss, while its allocation system prioritized supply based on demands and environmental flows. Scenario analysis examined the effects of population growth, climate change, and policy, using external data such as climate model outputs and socio-economic predictions. Finally, WEAP's graphical tools made it easier to visualize and analyze data, which aligned with accepted procedures for accurate water resource management analysis.
Figure 4

A schematic representation of the WEAP model applied to the Gilgel Gibe River basin.

Figure 4

A schematic representation of the WEAP model applied to the Gilgel Gibe River basin.

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Model validation

This study employed cross-validation to validate the model through iterative training and testing across multiple dataset subsets, thus assessing its generalizability to independent data. Cross-validation serves to evaluate a model's predictive capability for unseen data, offering insights into its performance on new datasets. Data from 1993 to 2016 were designated for training, and data from 2017 to 2022 for testing, using an 80/20 split while preserving class proportions with the createDataPartition function (DeSimone & Ransom 2021; Kuhn et al. 2024). This procedure was repeated multiple times, yielding a series of well-trained models with distinct performance metrics. Finally, metrics were averaged across iterations to refine model parameters, enhancing robustness and predictive accuracy. This approach ensured a reliable model with improved capability for generalization to unseen data.

Evaluation of model performance

In evaluating the effect of climate and land use changes on water supply and demand in Jimma town using the WEAP modeling tool, the model's performance was assessed during both the calibration and validation phases. Several standard methods were employed to compare the simulated pressure and flow data with the observed data, in line with the approach of Hajibabaei et al. (2019). Specifically, four key statistical indices were used: root mean square error (RMSE), mean absolute error (MAE), correlation coefficient (R2), and Nash–Sutcliffe efficiency (NSE). These metrics were chosen to identify the model that offered the highest predictive accuracy and the least error. The RMSE and MAE are widely used for model performance evaluation. Both metrics measure the degree of error between the simulated and observed values, where an RMSE or MAE of 0 indicates a perfect fit, while higher values indicate increasing error. An RMSE between 0.2 and 0.5 typically indicates a model capable of providing reasonably accurate predictions. The R2 value, which quantifies the strength of the linear relationship between the observed and simulated data, ranges from −1 (negative correlation) to 1 (excellent fit). A value of R2 greater than 0.5 is generally considered acceptable, with higher values reflecting less variance in error. Similarly, the NSE further assesses the model's ability to predict outcomes accurately, with values closer to 1 representing better model performance. These criteria, adapted from Koo et al. (2021), Makridakis et al. (2018), and Ou et al. (2023), were applied to evaluate the model's reliability comprehensively. The values of RMSE, MAE, R2, and NSE are computed using the following equations:
(7)
where X denotes the observed values, Y represents the simulated values, and n is the total number of data points or observations.
(8)
where X and Y denote the observed and predicted values, respectively, n represents the number of observations, and the absolute difference ∣XY∣ is calculated for each comparison.
(9)
(10)

In this context, n refers to the total number of observations, yi represents the actual value for the ith observation, and signifies the predicted value for the corresponding observation.

Assessment of water demand and supply dynamics

The WEAP model analysis for Jimma town reveals that the town experiences a water deficit during January, February, November, and December, with additional shortages in domestic and agricultural water demands occurring in April and May. In February, the water supply coverage was approximately 92%, while in August and September, the demand coverage reached 68 and 92%, respectively, influenced by demand prioritization. For agricultural needs, water coverage was at 100% in July and August, as there was no demand recorded for those months. The streamflow analysis shows a decrease following the withdrawal of Jimma town's water supply, which is further reduced after agricultural withdrawals. However, downstream areas exhibit increased streamflow due to the return flow from Jimma town and the Gilgel Gibe River, followed by another decrease due to agricultural water discharge. Assessing Jimma's water resources is critical for improving water efficiency, particularly in areas experiencing severe scarcity. This study utilizes the WEAP model to examine the impact of various socio-economic factors on water demand by simulating multiple scenarios that incorporate key assumptions reflecting different conditions. In the base year of 2015, Jimma's total water demand was approximately 2.07 gigaliters (GL) or 2,070,000 m3, with an unmet demand of 96,000 m3, indicating a shortfall of about 4.6% of the total demand. This means that domestic water demand was satisfied by 95.4% in 2018. Monthly water demand varied significantly, with higher demands observed in March (560,000 m3), April (550,000 m3), and February (390,000 m3), and lower demands in August and September (190,000 m3). This variability reflects seasonal changes in water consumption, with substantial shortages during the dry months of February, March, and April. The study emphasizes the importance of collecting long-term monthly and daily data to enhance future WEAP modeling accuracy.

Scenario evaluation

Base-case scenario

To project the future conditions of Jimma's municipal water system, the WEAP model was run under a reference scenario that assumes no additional water supply infrastructure or demand management strategies. This scenario considers a population growth rate of 2.7%, predicting the town's population to reach approximately 310,384 by 2030. Given that water demand is directly correlated with population growth, it is expected to increase from 2.07 GL in 2018 to about 4.5 GL by 2030, a growth of 117.4%, driven largely by the growing population. Meanwhile, the unmet water demand, initially at 0.096 GL in 2018, is projected to rise sharply to 1.6 GL by 2030, a staggering 1,567% increase. This substantial unmet demand highlights the critical need for strategic interventions to mitigate an impending water shortage. Currently, the primary source of water supply for Jimma town is the Gilgel Gibe River, located approximately 40 km away. The river supplies between 30,000 and 50,000 m3 of water daily. In addition to the river, Jimma's water supply system includes six service reservoirs. The reservoirs, particularly associated with the Gilgel Gibe hydropower projects, play a vital role in regulating water flow and maintaining a steady supply for domestic consumption. The Gilgel Gibe I Reservoir, supporting the Gilgel Gibe I hydroelectric project, has a large capacity of approximately 184 million cubic meters, ensuring it can store and release water for both energy generation and domestic use. The total effective water production from the Gilgel Gibe River is estimated to be around 850 million m3 annually. Daily, this equates to approximately 2,330 cubic meters. However, this can vary based on seasonal factors and management practices. About 60% of the water produced is allocated for domestic purposes, including drinking water for Jimma's residents. Despite these supplies, there remains a significant shortfall in meeting the town's water demand. The daily deficit between water supply and demand is estimated at 24,563 m3, or about 38% of the total water demand, underscoring the urgent need for sustainable water management solutions.

Figure 5 indicates that the head flow of the catchment river remains at 20 during specific months, particularly January and February, across all study years. This behavior is primarily due to intermittent flow from tributaries during the dry months, influenced by seasonal variations in precipitation and upstream water abstractions. The reduced flow during these periods suggests that the river's flow is intermittent, with a marked decrease in water volume owing to lower rainfall in the early months of the year. These seasonal variations in headwater streams are strongly linked to regional climate patterns and agricultural water demands during the dry season. In contrast, the main river exhibits a clear seasonal trend, with peak flows occurring around mid-year. This trend is attributed to the seasonal hydrological dynamics of the Gilgel Gibe River, where peak flows are typically seen during the wet season due to increased rainfall and water runoff. The seasonal peaks are a result of cumulative runoff from the surrounding catchment area, driven by rainfall and other climatic factors that vary throughout the year. The absence of flow in the catchment river during certain months, particularly January and February, suggests that the river is subject to seasonal drying due to reduced precipitation and increased evaporation during the dry season. The analysis was conducted using annually segmented data to determine variations in water flow across different years and months, thereby capturing the river's seasonal dynamics. For this purpose, two distinct periods were selected to represent dry and wet seasons: January and July for 2020–2021, February and August for 2022–2024, and February and September for 2025–2028. For the period 2029–2030, April was selected as the dry month, while October was chosen as a month with moderate rainfall. These observed variations in head flow underscore the significant roles played by hydrological and climatic factors such as precipitation, evapotranspiration, and water abstraction practices in shaping the river's seasonal behavior. Moreover, the absence of statistical measures such as mean, median, standard deviation, and correlation coefficients limits the ability to perform a detailed quantitative analysis.
Figure 5

Projected monthly water supply trend and forecast (2020–2030).

Figure 5

Projected monthly water supply trend and forecast (2020–2030).

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Scenario 1: climate change scenario

This scenario evaluates the impact of climate change on water demand, assuming alterations in temperature, precipitation patterns, and evaporation rates. Under this scenario, water demand is projected to increase due to higher temperatures, which drive up water consumption for cooling and irrigation. The expected increase in water demand from 2.07 GL in 2018 to about 4.7 GL by 2030 emphasizes the critical need for adaptive strategies, such as enhancing water use efficiency and investing in climate-resilient water infrastructure. The unmet demand could rise to 2.63 GL by 2030, highlighting the compounded effects of climate change on water scarcity.

Figure 6 reveals substantial fluctuations in precipitation in the study period with values ranging from 200 to 240 mm between 2000 and 2004 and a significant increase to 500 mm from 2013 to 2015. Maximum wind speeds peaked at 3.5 m/s1 in 1994, 2003, 2012, and 2023, while minimum wind speeds ranged between 0 and 0.6 m/s1, particularly in 1994, 1998, and 2016. Relative humidity exhibited a broad range, varying from 40 to 90 g/m3 between 1993 and 2023. The maximum temperature consistently exceeded 32 °C in several years, notably in 2000, 2003, 2004, 2005, 2016, and 2023. Meanwhile, minimum temperatures fluctuated between 5 and 14 °C over the same period. Solar radiation levels also varied from 6 to 7.5 kJ/m2 annually from 1993 to 2023. This analysis considers key factors such as temperature increases, changes in precipitation patterns, and extreme weather events, which influence water availability and consumption patterns. The scenarios modeled include moderate and severe climate change projections, highlighting the potential challenges in balancing water resources. The figure underscores the increasing gap between water demand and supply under worsening climate conditions, emphasizing the need for adaptive water management strategies to mitigate future water scarcity. In addition, this result indicated that water demand in Jimma town is greatly affected by climatic factors, which influence both direct usage and indirect aspects such as evapotranspiration and groundwater recharge. Temperature plays a significant role, as higher temperatures lead to increased domestic water use for drinking, cooling, and hygiene purposes. Precipitation patterns are also essential when rainfall decreases, and water availability drops, resulting in a greater dependance on alternative sources. Relative humidity impacts evaporation rates, with lower humidity causing more water loss and higher irrigation needs. Wind speed boosts evapotranspiration, raising agricultural water requirements, while solar radiation further heightens water loss driven by temperature. These climate variables collectively influence water availability and use trends in Jimma. These insights are crucial for informing policy decisions and resource allocation to ensure sustainable water use in the face of climate variability (Figure 6).
Figure 6

Climate trends and time series analysis of water demand and supply (1993–2023). (a = precipitation; b = windspeed max c = windspeed min; d = solar radiation; e = relative humidity; f = temperature max; and g = temperature min).

Figure 6

Climate trends and time series analysis of water demand and supply (1993–2023). (a = precipitation; b = windspeed max c = windspeed min; d = solar radiation; e = relative humidity; f = temperature max; and g = temperature min).

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Scenario 2: LULC change scenario

Land use changes in Jimma town, examined through remote sensing and GIS techniques, show a transition from natural landscapes to urban and agricultural zones. This scenario examines the influence of LULCC on water demand, focusing on the expansion of urban areas and agricultural activities. The scenario assumes that increased urbanization and agricultural expansion will elevate water demand due to greater domestic and irrigation needs. There has been a notable increase in impervious surfaces and a decline in vegetative cover. This urban growth leads to higher domestic and industrial water usage, while the expansion of agricultural land, particularly for cash crops, raises the demand for irrigation. By 2030, water demand is projected to rise from 2.07 GL in 2018 to 4.8 GL, indicating the significant impact of land use changes. Unmet demand could reach 2.3 GL, suggesting that land use planning and sustainable development are crucial for managing water resources effectively. Furthermore, the conversion of wetlands reduces natural water storage, disrupting the hydrological balance. These alterations, along with the loss of vegetation, can change microclimates, affecting precipitation and evapotranspiration. When combined with climate change, these elements worsen water scarcity, resulting in increased runoff, decreased groundwater recharge, and increased water demand.

The analysis of LULC dynamics in Jimma town and its surrounding areas from 1993 to 2024 revealed significant changes affecting the region's water demand and supply. Built-up areas have expanded dramatically from 6.15 km2 (4.08%) in 1993 to 36.28 km2 (24.08%) by 2024, reflecting rapid urbanization and increased infrastructure development. Farmland also shows a notable increase, growing from 45.49 km2 (30.19%) in 1993 to a peak of 85.76 km2 (56.92%) in 2017 before slightly declining to 60.92 km2 (40.42%) by 2024. Conversely, forest cover has decreased significantly, dropping from 60.82 km2 (40.36%) in 1993 to 20.83 km2 (13.83%) in 2017, with a slight recovery to 43.69 km2 (28.99%) by 2024, indicating deforestation and subsequent reforestation efforts. Shrubland and grassland areas have also diminished, while wetlands and waterbodies experienced substantial reductions, particularly wetlands, which decreased sharply from 22.43 km2 (14.88%) in 2001 to 0.39 km2 (0.26%) in 2017, highlighting the impact of land use changes on these critical ecosystems (Table 2). These changes in LULC classes, particularly the increase in built-up and farmland areas coupled with the reduction in forests, wetlands, and waterbodies, are likely to exacerbate water demand due to increased population and agricultural activities, while simultaneously reducing water supply through loss of natural water retention and recharge areas (Figure 7). This poses significant challenges for sustainable water management in Jimma town.
Table 2

Land cover transformation and urban expansion in Jimma, 1993–2024

LULC classYear 1993
2001
2009
2017
2024
Area
(km2)
Area
(%)
Area
(km2)
Area
(%)
Area
(km2)
Area
(%)
Area
(km2)
Area
(%)
Area
(km2)
Area
(%)
Built-up area 6.15 4.08 10.63 7.05 23.54 15.62 26.93 17.87 36.28 24.08 
Farmland 45.49 30.19 58.49 38.81 52.95 35.14 85.76 56.92 60.92 40.42 
Forest 60.82 40.36 28.82 19.12 51.63 34.26 20.83 13.83 43.69 28.99 
Grassland 0.09 0.06 11.88 7.88 0.07 0.04 1.76 1.17 0.27 0.18 
Shrubland 23.36 15.50 15.70 10.42 12.13 8.05 12.22 8.11 1.63 1.08 
Waterbody 13.89 9.22 2.76 1.83 10.23 6.79 2.77 1.84 0.27 0.18 
Wetland 0.89 0.59 22.43 14.88 0.15 0.10 0.39 0.26 7.64 5.07 
Total 150.70 100.00 150.70 100.00 150.70 100.00 150.67 100.00 150.70 100.00 
LULC classYear 1993
2001
2009
2017
2024
Area
(km2)
Area
(%)
Area
(km2)
Area
(%)
Area
(km2)
Area
(%)
Area
(km2)
Area
(%)
Area
(km2)
Area
(%)
Built-up area 6.15 4.08 10.63 7.05 23.54 15.62 26.93 17.87 36.28 24.08 
Farmland 45.49 30.19 58.49 38.81 52.95 35.14 85.76 56.92 60.92 40.42 
Forest 60.82 40.36 28.82 19.12 51.63 34.26 20.83 13.83 43.69 28.99 
Grassland 0.09 0.06 11.88 7.88 0.07 0.04 1.76 1.17 0.27 0.18 
Shrubland 23.36 15.50 15.70 10.42 12.13 8.05 12.22 8.11 1.63 1.08 
Waterbody 13.89 9.22 2.76 1.83 10.23 6.79 2.77 1.84 0.27 0.18 
Wetland 0.89 0.59 22.43 14.88 0.15 0.10 0.39 0.26 7.64 5.07 
Total 150.70 100.00 150.70 100.00 150.70 100.00 150.67 100.00 150.70 100.00 
Figure 7

Temporal pattern of land use /land cover change of Jimma town.

Figure 7

Temporal pattern of land use /land cover change of Jimma town.

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Scenario 3: combined impact scenario

The analysis reveals that water demand in Jimma town is projected to rise significantly, from 2.07 GL in 2018 to approximately 5.0 GL by 2030 under the combined impact scenario. The synergistic effects of climate variability, such as temperature and precipitation change and rapid land use changes, including urban expansion and deforestation, drive this sharp increase. As the population grows and urban areas expand, the demand for domestic, agricultural, and industrial water use will intensify, putting additional strain on the existing water supply system. The scenario also projects that unmet water demand could escalate to 2.5 GL by 2030, highlighting a substantial gap between available water resources and the town's growing needs. This shortfall is exacerbated by reduced rainfall, increased evapotranspiration due to climate change, and the conversion of natural landscapes to urban and agricultural areas, affecting groundwater recharge and surface water availability. These findings underscore the urgent need for integrated water management strategies that address both climate resilience and land use planning. To mitigate the anticipated water shortages, it is crucial to implement adaptive measures such as enhancing water storage capacity by constructing new reservoirs and expanding existing ones to capture and store excess water during periods of high rainfall. Promoting sustainable land use practices, such as implementing policies that prevent deforestation and encourage reforestation, can improve groundwater recharge and reduce surface runoff. Additionally, improving water use efficiency through the adoption of water-saving technologies and practices in domestic, agricultural, and industrial sectors can help to reduce overall water demand. Developing climate-resilient infrastructure that can withstand extreme weather events and variability is also essential to ensure a reliable water supply under changing climatic conditions. This scenario highlights the interconnectedness of climate and land use factors in shaping future water availability. It calls for a proactive and integrated approach to water resource management, combining technological, policy, and community-based solutions to sustainably meet the water needs of Jimma town in the face of growing challenges.

The highest water supply occurs in July, closely followed by June and August, coinciding with the wettest months of the year in the region (Figure 8). This peak period is characterized by increased water usage for irrigation and other purposes. Water demand exhibits a distinct seasonal pattern, with higher consumption during the warmer months and lower demand in cooler periods. This variation is likely influenced by agricultural activities, weather conditions, and consumer behavior. By comparing actual demand and supply measures to this reference, one can evaluate the system's performance and identify areas for improvement
Figure 8

Monthly water demand and supply.

Figure 8

Monthly water demand and supply.

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Scenario 4: population growth scenario

Accurate population forecasting is crucial for determining the current and future water demand of Jimma town. In this study, the geometric growth method was employed to predict the population over a 10-year period from 2020 to 2030. The formula used for the projection was:
(11)
where Pn is the projected population, Po is the initial population, G is the growth rate, and n is the number of years.

The result of Table 3 indicates a significant increase in population over the decade, which poses challenges for sustainable water management. Starting with a projected population of 234,115 in 2020, Jimma is expected to experience a steady growth in its population, reaching 310,384 by 2030. Each year shows a consistent upward trend, with the population increasing by approximately 5,000–8,000 individuals annually. For instance, the population is projected to grow from 239,022 in 2021 to 250,900 in 2022, marking an increase of 11,878 people in just 1 year. This trend continues, with the population expected to reach 278,679 by 2026 and 302,036 by 2029. The most significant growth occurs between 2029 and 2030, where the population is anticipated to jump to 310,384, indicating a surge of over 8,000 individuals in that single year. Furthermore, under an accelerated growth scenario with an annual rate of 2.7%, Jimma's population is projected to reach 315,000 by 2030, significantly intensifying water demand. This rapid population growth is largely driven by migration from rural and suburban areas to the town in search of employment opportunities, education, healthcare, and improved living conditions. The pressure on Jimma's water supply system is intensifying. Under this scenario, water demand is forecasted to rise from 2.07 GL in 2018 to 4.0 GL by 2030, an increase of 0.5 GL compared to the reference scenario. This reflects the direct influence of rapid population growth on water demand and underscores the critical need for effective water resource management and new technologies to address future deficits. The unmet demand is anticipated to grow to 2.1 GL by 2030, which is 0.5 GL higher than the reference scenario, underscoring the need for proactive measures. However, this influx of people is placing immense pressure on the town's water supply system, which is already struggling to meet current demands. As the population increases and urbanization progresses, the need for water rises for various uses, including residential, commercial, industrial, and agricultural purposes. Furthermore, urbanization creates more impervious surfaces, which diminishes groundwater recharge and worsens water shortages. Continuous monitoring and adaptive management are vital to ensure that Jimma's water supply can sustainably meet future demands. The existing water infrastructure is inadequate to support the increasing population, leading to concerns about water scarcity and sustainability. As the population continues to expand, local authorities must address these challenges by enhancing water management strategies and investing in infrastructure improvements to ensure that the growing population has access to sufficient water resources. To tackle these issues, it is crucial to incorporate trends in population and urbanization into demand forecasting models, encourage sustainable water practices such as rainwater harvesting, and invest in technologies that use water more efficiently.

Table 3

Projected population growth in Jimma town

YearProjected population
2020 234,115 
2021 239,022 
2022 250,900 
2023 257,574 
2024 264,374 
2025 271,406 
2026 278,679 
2027 286,198 
2028 293,979 
2029 302,036 
2030 310,384 
YearProjected population
2020 234,115 
2021 239,022 
2022 250,900 
2023 257,574 
2024 264,374 
2025 271,406 
2026 278,679 
2027 286,198 
2028 293,979 
2029 302,036 
2030 310,384 

Figure 9 shows the annual activity levels for various categories of activities, including showers, toilets, washing, and others, over a decade, revealing several key observations. The other category consistently represents the largest share of water consumption throughout the period, indicating that activities such as cooking, cleaning, or gardening, which are not explicitly classified as showers, toilets, or washing, significantly contribute to overall water use. Additionally, there is a general upward trend in activity levels, suggesting a growing demand for water driven by population growth, urbanization, and changing lifestyle. Although the other category remains predominant, there are noticeable fluctuations in the activity levels of other categories. For instance, the showers category may see increased activity due to improved access to indoor plumbing and better sanitation facilities. The figure also provides projections up to 2030, offering valuable insights for anticipating future water demand and facilitating effective planning.
Figure 9

Projected distribution of water use per capita.

Figure 9

Projected distribution of water use per capita.

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Figure 10(a) shows the segmentation of the average daily water consumption of Jimma town into the following basic components: domestic, public and commercial, industrial, livestock, fire and water that is not accounted for, and also total average daily demand. The major range of water usage is domestic demand which accounts for roughly 8.60 million m3/day and is followed by unaccounted-for water consumption which comes to roughly 3.42 million m3/day and public/commercial consumption, which is equal to 2.58 million m3/day. Industrial as well as fire demands comprise approximately 1.03 million m3/day each. However, livestock demand is the lowest and stands at about 0.43 million m3/day. In aggregate, all these categories resulted in an average daily water consumption of 17.09 million m3/day illustrating the grave losses attributable to domestic needs and unaccounted-for consumption, which constitutes a sizable portion of total usage.
Figure 10

(a) Current water demand in Jimma town (JTWSSA 2024). (b) Sectoral water costs per capita in Jimma town.

Figure 10

(a) Current water demand in Jimma town (JTWSSA 2024). (b) Sectoral water costs per capita in Jimma town.

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Figure 10(b) illustrates capital costs over time across various sectors, revealing several key statistical observations. The Catchment sector consistently accounts for the largest share of capital costs throughout the projected period, indicating significant investments in water infrastructure such as dams, reservoirs, and treatment plants. Overall capital costs are on an upward trend, suggesting increasing investment in water resource development, likely driven by factors such as population growth, urbanization, and the need for improved water quality and supply reliability. While the Catchment sector remains predominant, there are fluctuations in the capital costs allocated to other sectors. For instance, the Demand sector may see increased investment in areas like water distribution networks, metering systems, and consumer connections. The figure also provides projections of capital costs up to 2030, which can be utilized to forecast future investment requirements and inform strategic planning. Furthermore, water demand forecasts for Jimma town in 2030 are subject to uncertainty due to factors such as population growth, climate variability, land use changes, and economic development. Unpredictable population expansion and urbanization can have a considerable impact on water demand, while climate fluctuation influences supply. To address these uncertainties, IWRM can foster cross-sector collaboration and sustainable water use. Forecasts can be improved by using data-driven models that incorporate climatic, demographic, and land use projections. Regular monitoring, adaptive management, and infrastructure investments in water storage and distribution are essential for fulfilling future demand.

Household water use dynamics in Jimma town

In Jimma town, the characteristics of household water consumption revealed significant challenges due to an unreliable water supply system. Many residents are compelled to purchase water from decentralized sources, such as truck tankers, to meet their daily needs. The inconsistent water delivery across different residential areas exacerbates this situation. Research indicates that approximately 30% of the households receive water only once a week, while 14% have access to water 1–2 times weekly. A larger proportion, about 40%, of the households receive water 2–3 times per week, and only 10% experience delivery 3–4 times per week. Remarkably, 6% of the households benefit from water delivery more than five times weekly. Despite such variations, it is noteworthy that 56% of the households manage to access water at least four times weekly, in stark contrast to the 30% who receive water no more than three times per week. These findings underscore the pressing need for improvements in the water supply infrastructure to ensure equitable and reliable access to water for all residents, as highlighted in studies focused on urban water management and sustainability. Addressing the water supply challenges is essential for enhancing the quality of life and promoting public health in Jimma town.

Evaluation of the model calibration and validation

The statistical analysis of the correlation between the observed and simulated water demand during calibration and validation for Jimma town shows a high degree of accuracy, with R2 values of 0.95 and 0.97, respectively. These results fall within acceptable limits, indicating that the calibration and validation processes for measured and simulated water demand have been conducted according to the required standards of the coefficient of determination. Similarly, a high correlation was observed during the calibration and validation phases for the average daily water supply, with R2 values of 0.93 and 0.94, respectively. This strong agreement between measured and simulated water supply values suggests that the model accurately represents the water distribution dynamics in the town (Table 4).

Table 4

Model performance analysis

ParameterCalibration (R2)Validation (R2)RMSEMAENSE
Water demand 0.95 0.97 0.65 0.40 0.82 
Water supply (averaged) 0.93 0.94 0.62 0.45 0.68 
Tank storage levels 0.88 0.90 0.52 0.42 0.75 
ParameterCalibration (R2)Validation (R2)RMSEMAENSE
Water demand 0.95 0.97 0.65 0.40 0.82 
Water supply (averaged) 0.93 0.94 0.62 0.45 0.68 
Tank storage levels 0.88 0.90 0.52 0.42 0.75 

The training and validation loss curves, illustrated in Figure 11, provide a visual representation of the model's learning process. Initially, both the training loss and validation loss exhibit significant fluctuations, reflecting the model's adjustments to the data. However, as training progresses, these losses gradually converge toward similar values, indicating stabilization in performance. Notably, the absence of a substantial gap between the training and validation loss suggests that the model is effectively capturing the underlying patterns in the data without overfitting. This convergence is a positive sign, affirming the model's reliability and robustness across different evaluation metrics.
Figure 11

Training and validation loss curve.

Figure 11

Training and validation loss curve.

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Moreover, the correlation coefficients for the calibration and validation of tank storage levels recorded R2 values of 0.88 and 0.90, respectively, as shown in Table 4 and Figure 12. In this study, the model performance for Jimma town indicated a strong agreement between observed and simulated values during both the calibration and validation phases. The metrics for pressure, flow, and storage levels were RMSE, MAE, R2, and ENS of 0.65, 0.40, 0.96, and 0.82 for calibration and 0.62, 0.45, 0.96, and 0.68 for validation, and for storage levels, 0.52, 0.42, 0.85, and 0.75, respectively. Overall, the model performance assessment demonstrates a high level of correlation and agreement between the observed and simulated water demand, supply, and storage levels for Jimma town's water distribution network. This confirms that the WEAP modeling tool provides a reliable representation of the town's water supply and demand dynamics.
Figure 12

Model performance metrics.

Figure 12

Model performance metrics.

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Figure 13's correlation matrix reveals several important associations among climate variables. In particular, relative humidity and precipitation exhibit a strong positive correlation, indicating that higher relative humidity typically aligns with increased precipitation. A moderate positive correlation is observed between maximum and minimum temperature and solar radiation, suggesting that warmer temperatures are often accompanied by higher solar radiation levels. Interestingly, minimum temperature shows an even stronger positive correlation with solar radiation, implying that higher solar radiation may coincide with lower minimum temperatures. Conversely, relative humidity and maximum temperature demonstrate a moderate negative correlation, suggesting that higher humidity levels are associated with lower maximum temperatures. Similarly, precipitation and maximum temperature have a moderate negative correlation, indicating that higher precipitation is generally linked to lower maximum temperatures. Additionally, a weak correlation between maximum and minimum wind speed suggests a limited relationship between these two variables. Weak correlations are also noted between wind speed and precipitation, indicating minimal direct association. This correlation matrix provides critical insights into the interdependencies among climate variables, aiding in the understanding of local climate dynamics, improving predictive accuracy, and supporting data-driven decision-making.
Figure 13

Correlation matrix analysis of climate data.

Figure 13

Correlation matrix analysis of climate data.

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In analyzing water demand and supply data, comparing predicted values with true training values is crucial for evaluating model performance. This comparison not only quantifies the model's accuracy but also significantly contributes to the optimization process during training. Numerous studies, including those by Chen et al. (2020) and Deng et al. (2022), highlight that true training values are essential for calculating the loss function, which acts as feedback guiding the model's learning. By minimizing the difference between its predictions and the true training values, the model improves its performance on the training dataset, effectively aligning itself with the underlying data patterns. The predicted values for both training and validation sets represent the outcomes the model is designed to estimate accurately. As illustrated in Figures 14 and 15, a consistent match between the true training values and the predicted training values indicates that the model has effectively captured the dynamics of the training dataset. Likewise, the validation true values, when compared with the predicted validation values, show a strong fit, highlighting the model's ability to generalize to unseen data. This dual comparison reveals commendable accuracy, demonstrated by the close alignment between observed and simulated data, a result consistent with findings reported in existing literature (Wang et al. 2023). Such a relationship suggests that the model not only excels at predicting values based on training data but also maintains high predictive accuracy on validation data, reinforcing its usefulness for future climate-related forecasting efforts. Moreover, this study examines the combined effects of key climate factors, such as temperature changes, rainfall patterns, and seasonal variations, on the water supply and demand in Jimma town amid climate change and rapid population growth. The analysis reveals that rising temperatures lead to increased evaporation and a higher demand for water in agricultural, domestic, and industrial sectors. At the same time, unstable precipitation patterns and unpredictable rainfall further stress the water resources and deteriorate water scarcity issues. Moreover, the fast-growing population in Jimma town raises water consumption rates, adding more pressure to the already limited water supply. The WEAP modeling tool effectively simulates these complex interactions, providing insights into the estimated water demand–supply imbalances and highlighting the necessity for sustainable water management strategies to address both the impacts of climate change and population growth. Furthermore, the findings of this study provide important insights for policymakers at both local and regional levels. On a local scale, the results can guide water conservation efforts, urban planning approaches, and infrastructure investments aimed at addressing expected water shortages. At the regional level, incorporating scenario-based analyses into water management policies can foster more adaptive and resilient strategies that take into account the interconnected impacts of climate change, urban growth, and land use changes.
Figure 14

Comparison between predictions and true value.

Figure 14

Comparison between predictions and true value.

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Figure 15

Calibration model of observed and simulated data of water demand and supply.

Figure 15

Calibration model of observed and simulated data of water demand and supply.

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This study provides a comprehensive analysis of Jimma town's water resource base and the rising water demand and evaluates five distinct water management scenarios to address future needs. The findings emphasize that Jimma town's rapidly growing population and climate and land use changes expected to significantly increase the water demand. The observation is consistent with similar research, which documents how urban expansion and environmental changes exacerbated water scarcity issues. Similarly, Jimma's projected population growth rate of 2.7% shall result in a population size of about 310,384 by 2030. Given the direct correlation between population size growth and water demand, we expect Jimma's water demand to rise from 2.07 GL in 2018 to approximately 4.5 GL by 2030, a 117.4% increase. The results indicated that, without proactive measures such as upgrading the current water infrastructure and expanding storage capacity, Jimma shall likely face severe water shortages by 2030. For instance, Zeng et al. (2017) demonstrated that urban growth and climate variability substantially affect water demand and availability, mirroring our findings for Jimma. Studies by various scholars have demonstrated the effectiveness and usability of the WEAP model in diverse contexts for water demand and supply analysis, reporting highly satisfactory results (Andah et al. 2003; McCartney & Arranz 2007). Recognized as a valuable tool for integrated water resource planning, WEAP has proven its utility for evaluating water needs and availability. This study affirms these findings, as the model outputs effectively highlight water demand and supply dynamics. However, one limitation is WEAP's relatively basic integrated surface water modeling capabilities. Given that Jimma town's water supply largely depends on surface water, more refined groundwater data are needed for comprehensive analysis. Enhancing surface water modeling through remote sensing integration could address this, although it might compromise WEAP's user-friendliness. Despite its constraints, WEAP remains accessible and straightforward to use, thanks to extensive tutorials (Sieber 2006). The primary limitation lies in the model's simplified surface water options. Nevertheless, WEAP's strength in quantitatively assessing surface water resources, optimizing water allocation under scarcity via a demand-priority approach (Juízo & Líden 2008), and its extensibility to incorporate additional data over time (Van Loon & Droogers 2006) are evident in this study. WEAP also offers integrated modeling tools for generating inflows when external hydrological data are unavailable, and its free accessibility to institutions in developing countries further enhances its appeal.

Using the WEAP model, our study assessed various scenarios to manage water demand effectively. Our scenario analysis also reveals that unmet water demand, initially at 0.096 GL in 2018, will increase drastically to 1.6 GL by 2030, representing a 1,567% increase. The Gilgel Gibe River, the primary surface water source for Jimma, currently supplies between 30,000 and 50,000 m3 of water daily. While this provides a vital lifeline for the town, it is insufficient to meet future demand without intervention. This approach aligns with methodologies employed by Yang et al. (2020), who used integrated water management models to evaluate different strategies under varying climate conditions. Our analysis particularly focused on the Gibe River's role in water availability and demand, providing insights into how climate and land use changes could impact future water resources. This aspect is crucial, reflecting broader trends noted in water resource studies such as those by Zhang et al. (2023), which highlight significant shifts in water availability due to environmental changes and demand pressures.

The scenarios we evaluated indicate that without intervention, Jimma is likely to experience severe water shortages. This finding underscores the urgent need for proactive measures, such as upgrading reservoir capacities and constructing new storage facilities, to ensure long-term water security. Our recommendations are supported by similar studies, including Nivesh et al. (2023), which advocate for enhancing water infrastructure to cope with increased demand and impacts of climate change.

Overall, our study highlights the critical need for wise water resource management in Jimma town. By drawing on insights from related research and applying them to the context of Jimma town, we provide a valuable framework for addressing water scarcity challenges. The study underscores the importance of expanding and upgrading water infrastructure and implementing sustainable practices to adapt to evolving climate conditions and demographic changes. This comprehensive analysis contributes valuable insights into the complexities of water resource management and emphasizes the need for strategic planning to secure sustainable water resources for Jimma's future. This study concludes that, with these benefits, WEAP is highly recommended for IWRM. To address the projected water deficits, the study proposes several adaptive strategies, including the adoption of water-saving practices, the use of efficient irrigation technologies, and the development of alternative water sources such as rainwater harvesting and managed aquifer recharge. Furthermore, the implementation of IWRM strategies is essential for coordinating water use across various sectors. This study emphasizes the importance of coordinated governance through IWRM, which encourages cross-sectoral collaboration between agriculture, urban growth, and environmental protection. IWRM frameworks can address water deficits and improve climate resilience by leveraging data-driven models and multi-stakeholder involvement. The adaptation of such strategies to local circumstances ensures that water management policies are successful and sustainable. Furthermore, capacity-building and awareness-raising programs for local governments are vital for implementing and maintaining these policies. These efforts, which align with global frameworks such as the Sustainable Development Goals, can help to increase water security and resilience at the local and national levels.

Comparison with other works

The study of water demand and supply in Jimma town provides crucial insights into the issues of urban water management in a fast-increasing population. These findings can be contextualized and compared to previous research undertaken in the East African sub-region, where many cities confront similar challenges such as population growth, urbanization, and climate variability (Table 5).

Table 5

Comparison result with other works

StudyLocationMethodologyKey findingsStatistical valuesKey recommendations
Tefera et al. (2023)  Addis Ababa, Ethiopia Hydrological Modeling, Scenario Analysis The study found that under different climate scenarios, Addis Ababa faces significant water deficits, with demand surpassing supply by 2040. Increased urbanization and population growth exacerbate the situation. Water deficit: 15–20% by 2040 Implementing water efficiency measures, enhancing water supply infrastructure, improving demand management practices 
Tena et al. (2019)  Chongwe River Catchment, Zambia Hydrological Modeling and Water Resources Assessment of Chongwe River Catchment using WEAP Model The study found that increased agricultural and domestic water demand, combined with climate change impacts, will reduce water availability by 30% by 2050. Water availability reduction: 30% by 2050 Implementation of sustainable water management strategies, improving storage and distribution efficiency. 
Mwangi et al. (2020)  Kenya (National Study) Hydrological Model, Climate Change Scenarios, Population Growth Climate change will lead to 15–25% reduction in water availability across various urban centers, particularly affecting urban water supplies. 15–25% decrease in water availability by 2050 Sustainable water management, urban resilience strategies 
Macharia et al. (2021)  Sub-Saharan Africa Water Demand Forecasting, Energy Use Analysis The study projects a sharp rise in water demand, with a corresponding increase in energy demand for water supply by 2050. Climate variability and rapid urbanization are key factors driving the increasing water stress Energy demand increase: 40% by 2050, Water demand rise: 35% Enhancing energy efficiency in water supply systems, investment in alternative water sources 
This study Gilgel Gibe River basin Evaluating the Effect of Climate Change and Fast Population Growth on Water Supply and Demand in Jimma Town, Ethiopia, Using WEAP Modeling Tool Urban water demand could rise substantially by 2030, potentially reaching 4.5 GL under the base-case scenario, with unmet demand increasing to 1.6 GL Urban demand: 8.60 million m3 unaccounted-for water consumption: 3.42 million m3/day and public/commercial consumption: 2.58 million m3/day. Industrial as well as fire demands 1.03 million m3/day each Increase the adoption of water-saving practices, the use of efficient irrigation technologies, and the development of alternative water sources such as rainwater harvesting and managed aquifer recharge 
StudyLocationMethodologyKey findingsStatistical valuesKey recommendations
Tefera et al. (2023)  Addis Ababa, Ethiopia Hydrological Modeling, Scenario Analysis The study found that under different climate scenarios, Addis Ababa faces significant water deficits, with demand surpassing supply by 2040. Increased urbanization and population growth exacerbate the situation. Water deficit: 15–20% by 2040 Implementing water efficiency measures, enhancing water supply infrastructure, improving demand management practices 
Tena et al. (2019)  Chongwe River Catchment, Zambia Hydrological Modeling and Water Resources Assessment of Chongwe River Catchment using WEAP Model The study found that increased agricultural and domestic water demand, combined with climate change impacts, will reduce water availability by 30% by 2050. Water availability reduction: 30% by 2050 Implementation of sustainable water management strategies, improving storage and distribution efficiency. 
Mwangi et al. (2020)  Kenya (National Study) Hydrological Model, Climate Change Scenarios, Population Growth Climate change will lead to 15–25% reduction in water availability across various urban centers, particularly affecting urban water supplies. 15–25% decrease in water availability by 2050 Sustainable water management, urban resilience strategies 
Macharia et al. (2021)  Sub-Saharan Africa Water Demand Forecasting, Energy Use Analysis The study projects a sharp rise in water demand, with a corresponding increase in energy demand for water supply by 2050. Climate variability and rapid urbanization are key factors driving the increasing water stress Energy demand increase: 40% by 2050, Water demand rise: 35% Enhancing energy efficiency in water supply systems, investment in alternative water sources 
This study Gilgel Gibe River basin Evaluating the Effect of Climate Change and Fast Population Growth on Water Supply and Demand in Jimma Town, Ethiopia, Using WEAP Modeling Tool Urban water demand could rise substantially by 2030, potentially reaching 4.5 GL under the base-case scenario, with unmet demand increasing to 1.6 GL Urban demand: 8.60 million m3 unaccounted-for water consumption: 3.42 million m3/day and public/commercial consumption: 2.58 million m3/day. Industrial as well as fire demands 1.03 million m3/day each Increase the adoption of water-saving practices, the use of efficient irrigation technologies, and the development of alternative water sources such as rainwater harvesting and managed aquifer recharge 

Quantifying future unmet water demand under multiple development pathways: assessing scenario reliability of socio-economic and policy implications in Jimma town

The reliability of assumptions in scenario-based projections is crucial for water resource modeling, as these projections underpin urban planning, policy formulation, and sustainable development. In this study, the WEAP model was employed to assess future water demand and supply in Jimma town under various climate and land use scenarios. These projections rely heavily on assumptions about socio-economic drivers and policy changes, which influence the water demand and supply balance.

Population growth and urban expansion implications: population growth is a key socio-economic driver of water demand. The study based its projections on historical growth rates and national projections, assuming a steady increase in Jimma's population. However, urbanization rates can vary significantly, influenced by migration patterns, economic opportunities, and infrastructure development. Studies, such as Chiquito Gesualdo et al. (2021), underline the uncertainty associated with population growth projections, suggesting the need for sensitivity analyses to capture potential variations in urbanization. In Ethiopia, urbanization is one of the fastest in Sub-Saharan Africa, with projections indicating that the urban population will reach 40% by 2050 (World Bank n.d.). This urbanization causes unmet water demand and supply for Jimma town. Similarly, Konar & Marston (2020) explored urbanization's impacts on water supply in the Colorado River Basin and highlighted the significant effect of urbanization and policy on future water availability. By considering these uncertainties, the current study enhances the predictive capacity of water resource models.

Economic development and water consumption patterns: economic growth influences domestic, industrial, and agricultural water demand. The study suggests that water demand increases proportionally with economic expansion. However, research such as Chapagain et al. (2022) challenges this linear relationship, suggesting that water consumption patterns do not always scale directly with economic growth due to technological advances and efficiency improvements. Additionally, Gohari et al. (2017) incorporated economic growth scenarios in evaluating water scarcity in Iran, stressing the importance of adaptive water management strategies. Accounting for these factors and including elasticity variables, such as per capita income growth, could further refine future projections.

Land use change and policy change: land use changes due to urbanization and agricultural expansion affect groundwater recharge and surface runoff, thus influencing water availability. This study includes over a year of land use changes, and validation was conducted using remote sensing data and GIS-based change detection to improve accuracy. The LULC results indicate significant land use changes in the area, driven by population growth. Zhou et al. (2022) applied such methods in assessing water sustainability in China, which could provide a reference for refining land use assumptions in Jimma. Additionally, land tenure and governance issues, as discussed by Wubneh (2018), exacerbate land use challenges in Ethiopia, further affecting water resources. Policy changes, such as improved water conservation strategies, reforestation, and zoning regulations, can significantly alter land use and influence long-term water availability.

Water management policies and institutional factors: Government policies on water pricing, infrastructure investment, and conservation measures have a profound impact on future water demand and supply (Dagnachew et al. 2024; Ethiopian Water Resources Management Policy 2001). While the study assumes the continuation of existing policies, it does not explore potential future policy shifts. Notable policies such as Ethiopia's IWRM and the Ethiopian Water Policy (2001) emphasize efficient water use but face challenges in implementation, such as institutional weaknesses and insufficient funding (Timotewos & Barjenbruch 2024). Pichon (2019) examined the disparities between rural and urban water access under Ethiopia's water policies, revealing implementation gaps. Incorporating policy reforms, such as stricter conservation measures or investments in alternative water sources, as demonstrated by Almulhim & Abubakar (2023) in Saudi Arabia, is important for future water management. Finally, this study offers a solid foundation for assessing water resource challenges in Jimma town. By refining assumptions regarding socio-economic and policy variables and incorporating sensitivity analyses and alternative scenarios, the model's reliability and predictive accuracy can be strengthened. These improvements would not only enhance the study's methodological contribution but also provide valuable insights for policymakers and water resource managers, aiding in the development of sustainable urban water management strategies for Jimma town.

Limitations and future directions

Several limitations were discovered when applying the WEAP model to Jimma town. A major challenge was the scarcity of data, especially the absence of high-resolution, long-term hydrological and meteorological records, which hindered the calibration and validation of the model. The lack of adequate climate and hydrological data can compromise the accuracy of water availability simulations, as noted in earlier studies (Lévite et al. 2003; Joyce et al. 2011). Another challenge was forecasting future land use and socio-economic conditions, which introduced uncertainty into the model outputs. The predictions of water demand in WEAP are limited because they rely on factors such as population growth, urban expansion, and economic development. Assaf & Saadeh (2008) discovered that variations in socio-economic variables significantly affected water demand predictions, highlighting the need for sensitivity tests to evaluate the robustness of different scenarios. The limited availability of groundwater data affected the accuracy of groundwater resource simulations. WEAP relies on estimates of groundwater recharge and extraction data to model the interactions between surface and subsurface water. However, the lack of sufficient hydrogeological data in Jimma hindered the precision of groundwater models, a concern noted in similar studies (Döll et al. 2003). Additionally, computational limitations and model assumptions created further challenges. The WEAP model is built on specific assumptions regarding water allocation priorities, infrastructure efficiency, and conservation strategies, which may not fully reflect the complexities of actual water management systems. Amin et al. (2018) emphasized that although WEAP offers a structured framework for scenario analysis, the reliability of the results largely depends on the quality of the input data and the assumptions made about parameters. To overcome these limitations, it is essential to enhance data collection efforts, integrate high-resolution climatic and hydrological models, and conduct sensitivity assessments to minimize uncertainty in socio-economic projections. Future research aimed at improving the reliability of WEAP-based water management strategies should prioritize increasing data availability, refining groundwater modeling techniques, and incorporating more thorough evaluations of climate impacts.

The study represents a pioneering application of the WEAP model to address the complex water demand and supply issues faced by Jimma town in the Gilgel Gibe River basin. The Gilgel Gibe River hydrological condition is crucial for sustaining local communities and ecosystems, but the situation is increasingly affected by stressors such as climate change, land use changes, and population growth. The pressure on water resources has heightened the demand for water resources in Jimma, underscoring the need for effective management strategies. The research results offer valuable insights into the water resource dynamics of Jimma town, serving as a crucial tool for policymakers and water resource managers. The findings highlight that Jimma town is likely to experience significant water shortages in the future, primarily due to rapid population growth, climate change, and unfavorable land use changes. According to the WEAP model projections, water demand could exceed 4.5 GL by 2030 in the base-case scenario, with unmet demand potentially reaching 1.6 GL. Scenarios involving increased population growth and combined impacts of climate and land use changes could exacerbate the shortage, indicating a pressing need for comprehensive water management interventions. To address these challenges, it is recommended that Jimma town implement sustainable water management practices, including rainwater harvesting, upgrading infrastructure, reducing water leakage, and enhancing public awareness about efficient water use. Additionally, expanding water storage capacity and exploring alternative water sources will be crucial to securing water availability for the growing population. This study provides essential information for developing robust strategies for future water resource management in Jimma town, guiding efforts to mitigate water scarcity and build resilience against environmental challenges.

I sincerely acknowledge the Jimma Town Water Supply and Sewerage Service Enterprise (JTWSSSE) for providing essential water demand and supply data. I am also grateful to the Ethiopian Space Science and Geospatial Institute for supplying the necessary geospatial data that supported this study. Additionally, I extend my appreciation to the Ethiopian Meteorological Institute for providing climate data crucial to this research.

A.K.B conceived the study, collected and processed the data, developed remote sensing models, conducted statistical analyses, drafted the manuscript, and ensured data integrity. Dr M.W provided expert guidance and supervision throughout the research process. S.N. reviewed, refined, and edited the manuscript.

Data cannot be made publicly available; readers should contact the corresponding author for details.

The authors declare there is no conflict.

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