Semaria Moga Lencha

Rapid urbanization and population growth are increasing municipal solid waste (MSW) generation in Ethiopian cities, yet locally specific data remain limited for effective planning and policy implementation. This study assessed MSW generation rates, composition, physicochemical properties, and future quantities in Hawassa City to support sustainable management and Ethiopia’s Solid Waste Management and Disposal Proclamation of 2025. Direct measurements were conducted over seven days for 384 households stratified by socioeconomic status (127 high-, 140 middle-, and 117 low-income), together with selected commercial, institutional, and street-sweeping sources. An independent truck-volume estimate of waste delivered to the disposal facility was obtained, physical composition determined, and selected physicochemical parameters analysed. Multiple linear regression (MLR) examined associations between household characteristics and per-capita generation, while geometric projections estimated future MSW quantities to 2045. The overall household per capita generation rate was 0.42 kg person ⁻¹ d ⁻¹ , with clear socioeconomic differentiation: 0.59, 0.38, and 0.28 kg person ⁻¹ d ⁻¹ for high-, middle-, and low-income households, respectively. The truck-volume method yielded a comparable city-wide rate of ∼0.40 kg person ⁻¹ d ⁻¹ . The MLR model was statistically significant ( R ² = 0.744) and confirmed a positive association with income status and a negative association with household size. Organic materials dominated the waste stream (60%), followed by plastics (20%). Food-waste fractions showed high moisture and lower estimated calorific values, while non-food fractions were drier and higher in energy potential. Population is projected to rise from 576 880 in 2026–1285 683 in 2045, increasing total MSW generation from 291 to 648 t d ⁻¹ under a constant per capita rate. Under a near total landfilling scenario the existing ∼6 ha disposal site is already overflowing and would reach theoretical capacity within ∼10 months at 2026 rates. These findings provide updated evidence for source separation, organic and recyclable recovery, collection planning and residual disposal infrastructure in Hawassa, and offer a practical basis for implementing the 2025 Proclamation.

Land use and land cover (LULC) change is a major driver of ecosystem service shifts, hydrological processes, and biodiversity loss in Ethiopia’s Rift Valley. This study investigates historical LULC dynamics in the Gidabo watershed (2000–2024) and simulates future trajectories to 2080 using a hybrid modeling framework that integrates agent-based modeling, cellular automata, and multi-criteria evaluation. The model explicitly links human decision-making, spatial suitability, and policy scenarios, enabling dynamic representation of human–environment interactions. LULC classification achieved strong accuracy (80.83%–86.22%, Kappa 0.76–0.82), confirming the reliability of the ABCSMM framework. Results reveal a clear transition from tree-based systems toward agriculture and settlements, with agroforestry declining by nearly 50%, while farmland and built-up areas expanded substantially. Forest cover showed a non-linear pattern, increasing initially before declining under growing land pressure. These changes reflect the combined influence of accessibility, population growth and economic conditions. Future projections indicate non-linear land-use trajectories driven by interactions between agent behavior and spatial constraints. Farmland expands in the medium term before declining, while forest cover shows partial recovery under reduced pressure. Agent-based simulations highlight the role of household economics: financially stable conditions promote cropland expansion, whereas economic stress increases the likelihood of land degradation. Scenario analysis demonstrates that policy choices strongly shape land-use outcomes. Ecological protection scenarios enhance forest and grassland coverage while limiting urban expansion, whereas development-oriented scenarios accelerate the growth of farmland, agroforestry, and built-up areas. Overall, the findings show that LULC dynamics in the Gidabo watershed are governed by the interaction of socioeconomic drivers, environmental suitability, and policy interventions. The integrated modeling framework provides a useful tool for evaluating alternative land-use strategies and supports the design of policies that balance agricultural development, urban growth, and ecosystem conservation.

In Ethiopia, groundwater is critical to ensuring sustainable water security, underpinning domestic needs, agricultural irrigation, and socio-economic progress. This is especially evident in areas where surface water resources are scarce or subject to significant seasonal variability. The groundwater potential zones in the Gelda Watershed were assessed and delineated using an integrated approach that combined Geographic Information System (GIS), Remote Sensing (RS), and the Analytic Hierarchy Process (AHP). Eight key thematic factors influencing groundwater potential rainfall, lineament density, drainage density, slope, Land Use Land Cover (LULC), Geology, lithology and soil were derived from satellite imagery (Landsat 8, SRTM DEM), CHIRPS rainfall data, geological, soil maps and hydrogeological records. Factor weights were assigned via pairwise comparison matrices in AHP (Consistency Ratio of 0.043 < 0.1), and layers were standardized and combined using weighted overlay analysis to generate a Groundwater Potential Index (GWPI) map. The map was classified into five zones: very high (2.3%), high (10.2%), moderate (53.6%), low (33.1%), and very low (0.8%). Validation against 80 borehole and spring data points showed strong spatial agreement, with 81% of high-yield sites falling in high to very high zones. Receiver Operating Characteristic (ROC) analysis yielded an Area Under the Curve (AUC) of 0.907, indicating excellent model predictive performance. These findings confirm the robustness of the GIS–RS–AHP framework as a cost-effective, reliable tool for groundwater exploration, borehole siting, and sustainable resource management in data-scarce volcanic highland regions like the Gelda Watershed.

Land use and land cover change (LULC) is known worldwide as a key factor of environmental modification that significantly affects natural resources. The aim of this study was to evaluate the dynamics of land use and land cover in the Matenchose watershed from the years 1991, 2003, and 2020, and future prediction of land use changes for 2050. Landsat TM for 1991, ETM+ for 2003, and Landsat-8 OLI were used for LULC classification for 2020. A supervised image sorting method exhausting a maximum likelihood classification system was used, with the application using ERDAS Imagine software. Depending on the classified LULC, the future LULC 2050 was predicted using CA-Markov and Land Change Models by considering the different drivers of LULC dynamics. The 1991 LULC data showed that the watershed was predominantly covered by grassland (35%), and the 2003 and 2020 LULC data showed that the watershed was predominantly covered by cultivated land (36% and 52%, respectively). The predicted results showed that cultivated land and settlement increased by 6.36% and 6.53%, respectively, while forestland and grassland decreased by 63.76% and 22.325, respectively, from 2020 to 2050. Conversion of other LULC categories to cultivated land was most detrimental to the increase in soil erosion, while forest and grassland were paramount in reducing soil loss. The concept that population expansion and relocation have led to an increase in agricultural land and forested areas was further reinforced by the findings of key informant interviews. This study result might help appropriate decision making and improve land use policies in land management options.

Increasing pollutant emissions in the Lake Hawassa watershed (LHW) has led to a severe water quality deterioration. Allocation and quantification of responsible pollutant fluxes are suffering from scarce data. In this study, a combination of various models with monitoring data has been applied to determine the fluxes for Chemical Oxygen Demand (COD), Biochemical Oxygen Demand (BOD₅), Total Dissolved Solid (TDS), Total Nitrogen (TN), Nitrate and Nitrite-nitrogen (NOx-N), Total Phosphorous (TP) and phosphate (PO₄-P). Water, wastewater and stormwater samples were collected and analyzed at eight monitoring stations from rivers and point sources and six monitoring stations of stormwater samples. The flow simulated with soil and water assessment tool (SWAT) could be very well calibrated and validated with gauge data. This flow from SWAT model, measured flow during monitoring and pollutant concentrations were used in FLUX32 to estimate pollutant fluxes of main rivers and point sources in LHW. The formulas provided by Ethiopian Roads Authority and Gumbel’s theory of rainfall frequency analysis was employed to determine the 2-years return period rainfall depth for the City of Hawassa. The integration of HEC-GeoHMS and SCS-CN with the catchment area enabled to determine stormwater pollution load of Hawassa City. The estimated pollutant flux at each monitoring stations showed that the pollutant contribution from the point and nonpoint sources prevailing in the study area, where the maximum fluxes were observed at Tikur-Wuha sub-catchments. This station was located downstream of the two point sources and received flow from the upper streams where agricultural use is predominant. Furthermore, Hawassa city has been identified as a key pollutant load driver, owing to increased impacts from clearly identified point sources and stormwater pollutant flux from major outfalls. Agricultural activities, on the other hand, covers a large portion of the catchment and contributes significant amount to the overall load that reaches the lake. Thus, mitigation measures that are focused on pollutant flux reduction to the lake Hawassa have to target on the urban and agricultural activities.

The magnitude of pollution in Lake Hawassa has been exacerbated by population growth and economic development in the city of Hawassa, which is hydrologically closed and retains pollutants entering it. This study was therefore aimed at examining seasonal and spatial variations in the water quality of Lake Hawassa Watershed (LHW) and identifying possible sources of pollution using multivariate statistical techniques. Water and effluent samples from LHW were collected monthly for analysis of 19 physicochemical parameters during dry and wet seasons at 19 monitoring stations. Multivariate statistical techniques (MVST) were used to investigate the influences of an anthropogenic intervention on the physicochemical characteristics of water quality at monitoring stations. Through cluster analysis (CA), all 19 monitoring stations were spatially grouped into two statistically significant clusters for the dry and wet seasons based on pollution index, which were designated as moderately polluted (MP) and highly polluted (HP). According to the study results, rivers and Lake Hawassa were moderately polluted (MP), while point sources (industry, hospitals and hotels) were found to be highly polluted (HP). Discriminant analysis (DA) was used to identify the most critical parameters to study the spatial variations, and seven significant parameters were extracted (electrical conductivity (EC), dissolved oxygen (DO), chemical oxygen demand (COD), total nitrogen (TN), total phosphorous (TP), sodium ion (Na⁺), and potassium ion (K⁺) with the spatial variance to distinguish the pollution condition of the groups obtained using CA. Principal component analysis (PCA) was used to qualitatively determine the potential sources contributing to LHW pollution. In addition, three factors determining pollution levels during the dry and wet season were identified to explain 70.5% and 72.5% of the total variance, respectively. Various sources of pollution are prevalent in the LHW, including urban runoff, industrial discharges, diffused sources from agricultural land use, and livestock. A correlation matrix with seasonal variations was prepared for both seasons using physicochemical parameters. In conclusion, effective management of point and non-point source pollution is imperative to improve domestic, industrial, livestock, and agricultural runoff to reduce pollutants entering the Lake. In this regard, proper municipal and industrial wastewater treatment should be complemented, especially, by stringent management that requires a comprehensive application of technologies such as fertilizer management, ecological ditches, constructed wetlands, and buffer strips. Furthermore, application of indigenous aeration practices such as the use of drop structures at critical locations would help improve water quality in the lake watershed.

The rapid growth of urbanization, industrialization and poor wastewater management practices have led to an intense water quality impediment in Lake Hawassa Watershed. This study has intended to engage the different water quality indices to categorize the suitability of the water quality of Lake Hawassa Watershed for anthropogenic uses and identify the trophic state of Lake Hawassa. Analysis of physicochemical water quality parameters at selected sites and periods was conducted throughout May 2020 to January 2021 to assess the present status of the Lake Watershed. In total, 19 monitoring sites and 21 physicochemical parameters were selected and analyzed in a laboratory. The Canadian council of ministries of the environment (CCME WQI) and weighted arithmetic (WA WQI) water quality indices have been used to cluster the water quality of Lake Hawassa Watershed and the Carlson trophic state index (TSI) has been employed to identify the trophic state of Lake Hawassa. The water quality is generally categorized as unsuitable for drinking, aquatic life and recreational purposes and it is excellent to unsuitable for irrigation depending on the sampling location and the applied indices. Specifically, in WA WQI, rivers were excellent for agricultural uses and Lake Hawassa was good for agricultural uses. However, the CCME WQI findings showed rivers were good for irrigation but lake Hawassa was marginal for agricultural use. Point sources were impaired for all envisioned purposes. The overall category of Lake Hawassa falls under a eutrophic state since the average TSI was 65.4 and the lake is phosphorous-deficient, having TN:TP of 31.1. The monitored point sources indicate that the city of Hawassa and its numerous industrial discharges are key polluters, requiring a fast and consequent set-up of an efficient wastewater infrastructure, accompanied by a rigorous monitoring of large point sources (e.g., industry, hospitals and hotels). In spite of the various efforts, the recovery of Lake Hawassa may take a long time as it is hydrologically closed. Therefore, to ensure safe drinking water supply, a central supply system according to World Health organization (WHO) standards also for the fringe inhabitants still using lake water is imperative. Introducing riparian buffer zones of vegetation and grasses can support the direct pollution alleviation measures and is helpful to reduce the dispersed pollution coming from the population using latrines. Additionally, integrating aeration systems like pumping atmospheric air into the bottom of the lake using solar energy panels or diffusers are effective mitigation measures that will improve the water quality of the lake. In parallel, the implementation and efficiency control of measures requires coordinated environmental monitoring with dedicated development targets.