Awash River Research Articles

Modeling Surface Water–Groundwater Interactions: Evidence from Borkena Catchment, Awash River Basin, Ethiopia

The availability of sufficient water resources is critical for sustainable social and economic development globally. However, recurrent drought has been a precursor to inadequate water supply in the case of Borkena Catchment, Awash River Basin, Ethiopia. To support the conjunctive use and management of surface water and groundwater in Borkena Catchment, an integrated model was developed using the SWAT–MODFLOW model. The model was designed to operate on a monthly time scale. The change in the water balance obtained from the SWAT–MODFLOW model provides a quantitative means to assess the effect of the climate variability and changes, as well as the impact of human activities, on water resources. To advance the understanding at the regional and local scales, surface water–groundwater interactions in the Borkena Catchment geochemical information and piezometer maps were integrated. The results show that the groundwater recharge in the study area is approximately 122 mm/a. The surface water–groundwater interaction results show that the areas around Harbu and Dessie are characterized as losing rivers, while the areas around Kemisse-Chefa and the highlands of Kutaber, where the Borkena River originates, are characterized as gaining rivers. A geochemical analysis indicated that there is an inter-basin groundwater transfer from the Abbay to the Awash basin. The integrated model generated key temporal and spatial information that is useful for the sustainable conjunctive management of surface and groundwater in Borkena Catchment for climate resilience in the face of climate variability and increasing demand.

Drought characterization and severity analysis using GRACE-TWS and MODIS datasets: a case study from the Awash River Basin (ARB), Ethiopia

Abstract Drought is the utmost highly devastating phenomenon in Ethiopia because of societies that are reliant on rainfall-dependent agriculture; thus, it is crucial to characterize drought at the basin scale using new developments in remote sensing products and recently proposed drought indices. This study aimed to quantify drought in the Awash River Basin (ARB) using drought indices of the Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), Evaporative Demand Drought Index (EDDI), Evaporative Stress Index (ESI), and Water Storage Deficit Index (WSDI). The Mann–Kendall test analysis of annual and seasonal terrestrial water storage (TWS) showed a significant increase from 2002 to 2017 that is beneficial for developmental activities in the ARB. GRACE showed a record high extreme drought that persisted for 15 months was noticed from 2005/01 to 2006/03 with a total water storage deficit of −411.8 mm with a peak shortage of −46.24 mm in 2005/03, representing severe terrestrial water shortage in the ARB. This GRACE-TWS-based quantified extreme water shortage in 2005/30 can be used as a threshold for adaptation. Overall, this study provides a reliable outcome that will be vital for the establishment of climate change adaptation pathways in the future for viable water resources management to minimize the disastrous impacts of drought in the AR.

Green, blue and economic water productivity: a water footprint perspective from the Upper Awash Basin, Central Ethiopia

Abstract The rise in global freshwater consumption, inefficient water use and population growth are the main drivers of water scarcity and food insecurity. This study analyzed the green, blue and economic water productivity (GWP, BWP and EWP, respectively) of the rainfed (teff, maize and sorghum) and irrigated (sugarcane) crops along with green water scarcity (GWS) in the Upper Awash Basin using water footprints (WFs) approaches. Teff has the lowest average GWP (∼0.3 kg/m3) and the highest average WF (4205 m3/ton) between 2000 and 2010 with an average EWP of ∼0.3 USD/m3 which is higher than those of other rainfed cereal crops (maize and sorghum). The highest GWS of maize was recorded in Metehara (269 mm/growing period) and the lowest in Debrezeit (70 mm/growing period) with an intermediate value of 90 and 117 mm in Wonji and Melkassa, respectively. All the rainfed crops have lower EWP (less than 0.3 USD/m3) compared with the irrigated sugarcane in the basin. This study demonstrates that increasing the value per unit of green/blue water through increasing yield per unit of supply and switching from high to low WFs crops has significant implications for addressing the water scarcity problem by setting a WP benchmark in the basin.

Identification and Prioritization of Sub-watersheds to Soil Erosion and Sediment Yield Susceptibility Using RUSLE, Remote Sensing, and GIS (Case Study: Abbay—Awash Basin in Wollo Area, Ethiopia)

Identification and Prioritization of Sub-watersheds to Soil Erosion and Sediment Yield Susceptibility Using RUSLE, Remote Sensing, and GIS (Case Study: Abbay—Awash Basin in Wollo Area, Ethiopia)

Analysis of the impacts of land use land cover change on streamflow and surface water availability in Awash Basin, Ethiopia

The current study analyzed the impact of Land Use Land Cover (LULC) change on streamflow and surface water availability in the Akaki catchment of the Awash Basin, Ethiopia. Soil and Water Assessment Tool (SWAT) and Climatic Water Balance (CWB) models were used. The SWAT model calibrated and validated the daily streamflow. The results indicated that from 1993 to 2016, built-up and barren land areas increased by 5.3% and 3.4%, respectively. The SWAT model over-simulated the peak flows and best simulated the medium and low flows. Based on the calibrated daily streamflow, the runoff was 236.01 mm and 272.59 mm under the 1993 and 2016 LULC scenarios. The total water yield of the catchment was 366.7 mm and 382.01 mm for the 1993 and 2016 LULC scenarios, respectively. The seasonal CWB of the catchment depicted decreasing trend except for the Tsedey (SON) season. Based on the current study’s findings, since LULC change enhanced surface runoff and total water yield in the catchment, proactive flood management is recommended to reduce the impact of the flood hazard on life and property.

Scenario-Based LULC Dynamics Projection Using the CA–Markov Model on Upper Awash Basin (UAB), Ethiopia

Understanding the spatiotemporal changes in land use and land cover (LULC) in the watershed is crucial for maintaining the sustainability of land resources. This study intents to understand the historical (1972–2015) and future (2030–2060) spatiotemporal distribution of LULC changes in the Upper Awash Basin (UAB). The supervised Maximum Likelihood Classifier technique (MLC) was implemented for historical LULC classification. The Cellular Automata-Markov (CA–Markov) model was employed to project two scenarios of LULC, ‘business-as-usual’ (BAU) and ‘governance’ (Gov). Results from the historical LULC of the study area show that urban and cropland areas increased from 52.53 km2 (0.45%) to 354.14 km2 (3.01%) and 6040.75 km2 (51.25%) to 8472.45 km2 (71.97%), respectively. Whereas grassland, shrubland, and water bodies shrunk from 2052.08 km2 (17.41%) to 447.63 km2 (3.80%), 2462.99 km2 (20.89%) to 1399.49 km2 (11.89%) and 204.87 km2 (1.74%) to 152.44 km2 (1.29%), respectively, from 1972 to 2015. The historical LULC results indicated that the forest area was highly vulnerable and occupied by urban and cropland areas. The projected LULC under the BAU scenario shows substantial cropland and urban area expansion, increasing from 8472.45 km2 (71.97%) in 2015 to 9159.21 km2 (77.71%) in 2060 and 354.14 km2 (3.1%) in 2015, 1196.78 km2 (10.15%) in 2060, respectively, at the expense of vegetation cover. These results provide insight intothe LULC changes in the area, thus requiring urgent attention by watershed managers, policymakers, and stakeholders to provide sustainable practices for the UAB. Meanwhile, the Gov scenario indicates an increase in vegetable covers and a decrease in cropland, encouraging sustainable development compared to the BAU scenario.

Downscaling and validating SMAP soil moisture using a machine learning algorithm over the Awash River basin, Ethiopia.

Microwave remote sensing instrument like Soil Moisture Active Passive ranging from 1 cm to 1 m has provided spatial soil moisture information over the entire globe. However, Soil Moisture Active Passive satellite soil moisture products have a coarse spatial resolution (36km x 36km), limiting its application at the basin scale. This research, subsequently plans to; (1) Evaluate the capability of SAR for the retrieval of surface roughness variables in the Awash River basin; (2) Measure the performance of Random Forest (RF) regression model to downscale SMAP satellite soil moisture over the Awash River basin; (3) validate downscaled soil moisture data with In-situ measurements in the river basin. Random Forest (RF) based downscaling approach was applied to downscale satellite-based soil moisture product (36km x 36km) to fine resolution (1km x 1km). Fine spatial resolution (1km) soil moisture data for the Awash River basin was generated. The downscaled soil moisture product also has a strong spatial correlation with the original one, allowing it to deliver more soil moisture information than the original one. In-situ soil moisture and downscaled soil moisture had a 0.69 Pearson correlation value, compared to a 0.53 correlation between the original and In-situ soil moisture. In-situ soil moisture measurements were obtained from the Middle and Upper Awash sub-basins for validation purposes. In the case of Upper Awash, downscaled soil moisture shows a variation of 0.07 cm3 /cm3, -0.036 cm3 /cm3, and 0.112 cm3 /cm3 with Root Mean Square Error, Bias error, and Unbiased Root Mean Square Error respectively. Following that, the accuracy of downscaled soil moisture against the Middle Awash Sub-basin reveals a variance of 0.1320 cm3 /cm3, -0.033 cm3 /cm3, and 0.148 cm3 /cm3 with Root Mean Square Error, Bias error, and Unbiased Root Mean Square Error respectively. Future studies should take into account the temporal domain of Soil Moisture Active Passive satellite soil moisture product downscaling over the study region.

Exploratory regression modeling for flood susceptibility mapping in the GIS environment

Understanding the temporal and spatial patterns of flood in the Awash River basin, which is located in Ethiopia’s Afar region, is crucial. The Awash basin was picked because it is continuously in danger both spatially and temporally. The likelihood of flooding was assessed using eight independent variables: elevation, slope, rainfall, drainage density, land use, soil type, wetness index, and lineament density. Each constituent was assigned a weight based on its susceptibility to the danger, which was classified into four classifications. Exploratory regression analysis showed that the existing land use is the main factor influencing flood susceptibility. For the GIS domain, a total of 31 models were built using exploratory regression. Model number 31 was found to be the best fit model, having the highest Adjusted R2 value of 0.8 and the lowest Akaike’s Information criterion value of 1536.8. The spatial autocorrelation tool’s Z score and p-value for the standard residuals are, respectively, 0.7 and 0.4, indicating that they were neither clustered nor scattered. The geographic breadth of flood susceptibility and risk is thoroughly examined in this paper, as is the significance of spatial planning in the Awash basin.

The role of landscape management practices to address natural resource degradation and human vulnerability in Awash River basin, Ethiopia

Landscape management practices (LMP) support addressing the vulnerability of small-scale producers (SSPs) through providing a means of sustaining and strengthening community livelihoods and building their resilience and the environment. However, addressing the vulnerability of SSPs through the implementation of LMP requires meaningful community engagement and assessing the benefits and costs from the perspective of local communities. This study was conducted in two watersheds, Maybar-Felana and Gelana, in the Awash River basin, Ethiopia. The study assessed the links between natural resource degradation and the vulnerability of SSPs, local communities' opinion on the benefits and costs of LMP and the implications of implementing LMP for addressing vulnerability. It gathered and analyzed data through key informant interviews (KII), focus group discussions (FGDs) and GIS and remote sensing techniques. Diverse LMP such as afforestation/reforestation, exclosures, terrace and bunds and crop- and soil-based soil amendments were adopted in the studied watersheds. These practices contributed to the improvement of natural resources such as forests and the services they provide. Over the last 21 years (2000−2021), forest cover increased by 11.5 and 42.5% in Maybar-Felana and Gelana watersheds, respectively, while shrublands increased by 41.1% in Maybar-Felana. In line with this, the SSPs identified multiple benefits of LMP including the restoration of degraded vegetation, reducing runoff and soil loss, improving access to water for multiple uses and increasing agricultural productivity. The adopted LMP contributed to reducing livelihood vulnerability through reducing incidents of weather extremes such as flood and drought, improving food and water security, enhancing resource availability, and building livelihood assets. The SSPs also identified multiple economic and social costs of LMP, suggesting that addressing the economic and social costs through balancing short-term economic losses with long-term environmental benefits of interventions is crucial to sustaining the LMP and the benefits they provide.

Land use/Land cover Classification of Modjo River Catchment, Upper Awash Basin, Central Ethiopia

Land use/Land cover Classification of Modjo River Catchment, Upper Awash Basin, Central Ethiopia

Cholera outbreak investigation report in Mille woreda, Afar region, Ethiopia, 2019

Introduction: Cholera has remained as one of the important public health problems in Asia and Africa causing substantial morbidity and mortality. Although the burden is greatest in low-income populations with poor access to safe water, and sanitation, cholera is also an important health problem globally. Cholera occurs both as a short outbreak and protracted epidemic/pandemic and when uncontrolled; is devastating to communities and to their prospects for development. To respond quickly and control the outbreak, investigation is crucial; identify risk factors that cause the outbreak, and suggest prevention and control measures. Objective: To identify risk factors and etiology of diarrheal disease outbreak and suggest prevention and control measures in Mille woreda, Afar region Ethiopia, May- June, 2018. Method: Descriptive followed by unmatched case-control study with 1:2 ratio were conducted from May-June 2018. A total of 68 patients and 136 controls were enrolled. A structured interviewer-administered questionnaire was used and medical records and line lists review. Simple random sampling was used to select controls and the first 68 cases. Data were analyzed by SPSS and presented using odd ratio, and tables. Environmental and patient samples were collected for culture and rapid diagnostic test. Result: The investigation identified 229 cholera patients, including 22 rapid diagnostic test confirmed patients and seven culture confirmed patients (attack rate: 8.31%, 229/27,562). Index patient were imported from epi-linked woreda. Diglena geraro kebele were the Epicenter of the outbreak. Epicure trend shows common source infection. Using bifurcation of Awash River for drinking, use untreated/ uncoiled water, poor hand washing practices, and close contact with cholera sick person were found to be associated with cholera. Conclusion: This outbreak was caused by vibrio cholera 01 secondary to drinking water from a bifurcation of Awash River and using untreated water. Contact with diseased person, and use untreated/ uncoiled water was associated with being patients. In order to reduce the risk of cholera, safe drinking water or water treatment chemicals needs to be provided to communities.

Examining the impacts of climate variabilities and land use change on hydrological responses of Awash River basin, Ethiopia

Environment and climate changes have been posing pressure on the quality and quantity of water resources. The research examined the hydrological response of upper Awash River basin under the influences of environmental and climate changes. The climate change results up to 77.5% and 100.5% increament in annual and wet season monthly river flow, respectively when using projected climate data of RCP4.5. Whereas, the land use change alterss river flow in a one digit percentile increment/ decrement. It was observed that effects of both climate and land use changes will likely to increase the river flow and possibly cause flooding in the upper Awash River basin. The land use change impact can be alleviated by implementing appropriate land use management practices. The climate change mitigation needs long term process; as a result climate change adaptation mechanisms are recommended for the short term while employing climate mitigation options in the long run.

Understanding the role of catchment and climate characteristics in the propagation of meteorological to hydrological drought

Hydrological and meteorological droughts are complex hazards that cover a wide spatiotemporal spectrum and can affect the economic, environmental, and social sectors. However, it is challenging to characterize hydrometeorological drought and its propagation from precipitation deficits to soil moisture, discharge, and groundwater deficits and to ascertain to what extent catchment characteristics may affect drought features. This research explores the link between hydrometeorological drought characteristics and catchment characteristics. It investigates their propagation from meteorological to hydrological drought conditions in nine selected catchments from the Awash basin in Ethiopia using standardized indices of precipitation (SPI), soil moisture deficits (SPEI), streamflow (SRI), and base flow (SBI). The study results indicate that the propagation of meteorological to agricultural and hydrological droughts increases with increasing aggregation time scale and has a proportionally higher probability of propagation for moderate, severe, and extreme droughts. Across all catchments, the average lag time between hydrological and meteorological drought magnitude occurrence is 4–6 months, with lag times likely to increase by 7–8 months at a higher aggregation time scale. Meteorological drought has a 0.5 higher probability of occurrence than hydrological drought in a given period. In contrast, it has a lower (0.3) probability of the surface deficit becoming a groundwater deficit. At a 3-month cumulative time scale, the probability of propagating meteorological drought using the SPI to hydrological drought using the SRI is higher than that of propagating hydrological drought using the SBI. Therefore, the results suggest that while the propagation of meteorological droughts (SPI and SPEI) to hydrological droughts (SRI and SBI) slightly increases with aggregation time, the time taken for precipitation to become apparent in hydrological variables increases. The results confirmed that the probability of meteorological drought leading to hydrological drought progression is critical and needs to be considered in water resource management and planning.

Blending high-resolution satellite rainfall estimates over urban catchment using Bayesian Model Averaging approach

Study regionAkaki is a headwater catchment of Awash River Basin that hosts the capital city of Ethiopia, Addis Ababa. The area encompasses several agglomerated towns, water supply, and hydropower reservoirs and is characterized by a chain of mountains and floodplains. Due to basin rainfall, and the expansion of urbanized areas, the catchment is frequently affected by flooding. Study focusThis study evaluates dynamic Bayesian Model Averaging (BMA) approach to improve rainfall estimation over the catchment by blending four high-resolution satellite rainfall estimate (SRE) products. Using daily data (2003–2019) observed at thirteen stations as a reference, seven statistical metrics served to assess the point and spatial scale accuracy of the rainfall estimates. New hydrological insightsMain findings from this study are: (i) the blended product outperformed the individual SRE products by notably improving correlation with in-situ observed rainfall, and reducing the error of the estimated rainfall, (ii) the blended and individual SRE products performed better in the highlands than the lowlands of the catchment, and (iii) the amount of daily rainfall during the main-rainy season was mostly overestimated by the individual SRE products but was fairly estimated by the blended product. This study showed the nonexistence of surpassing individual SRE products and emphasized the blending of several products for gaining optimal results from each product.

Sediment yield modeling in Awash Melkasa dam watershed, upper Awash River basin, Ethiopia

Sediment yield modeling in Awash Melkasa dam watershed, upper Awash River basin, Ethiopia

Impact of climate change on hydrological response of Mojo river catchment, Awash river basin, Ethiopia

Climate change is a change in the state of climate identified by a change in temperature and precipitation that affect the hydrology of basins. This study has investigated the effects of climate change on the stream flow of Mojo River Catchment using (CORDEX)-Africa data outputs under RCP4.5 and RCP8.5 scenarios. Three-time horizons: near period (2006–2031), mid-period (2031–2055), and far period (2056–2080) were used. The SWAT model was used to simulate runoff. From the MIROC-MIROC5 Model result, the mean annual precipitation is increasing under RCP4.5 and decreasing under RCP 8.5. Similarly, the mean annual temperature shows an increasing trend for both scenarios. The mean annual streamflow shows a decreasing trend in the near and mid-future under both scenarios and only increases (by 6.31 m3/s) in the far future under RCP8.5. For MPI-M-MPI-ESM-LR, the mean annual precipitation shows a decreasing trend under RCP 4.5 and increasing under RCP 8.5, but the mean annual temperature becomes increasing for both scenarios. However, streamflow shows an increase under both scenarios in the all-time horizons and decreases (by 6.68 m3/s) under RCP 8.5 in the near and mid-future. The result of this study indicates that climate change affects streamflow. Therefore, different water-based design operations should incorporate climate change scenarios.

Evaluation of WRF model rainfall forecast using citizen science in a data-scarce urban catchment: Addis Ababa, Ethiopia

Study regionThe Akaki catchment is found in the Upper Awash River Basin in Ethiopia. Study focusUnderstanding the accuracy of rainfall forecasts in the data-scarce urban catchment has a multitude of benefits given the increased urban flood risk caused by climate change and urbanization. In this study, accuracy of the weather research and forecasting (WRF) model rainfall forecast was evaluated using citizen science data. Categorical and continuous accuracy evaluation metrics were used beside gauge representativeness effect. New hydrological insights for the regionThe rainfall forecasts performance accuracy is high for 1–3-days lead-time but deteriorates for 4–5-days lead-time. The WRF model captured the temporal dynamics and the rainfall amount according to the estimated KGE values. The model has relatively higher detection performance for no rain and light rain events (< 6 mm/day), but it has lower performance for moderate and heavy rain events (> 6 mm/day). Use of data from a single rain gauge misrepresents the accuracy level of the rainfall forecast in the study area. The gauge representativeness error contributed a variance of 28.08–83.33 % to the variance of WRF-gauge rainfall difference. Thus, the use of citizen science rainfall monitoring program is an essential alternative source of information where in-situ rainfall monitoring is limited that can be used to understand the “true” accuracy of WRF rainfall forecasts.

Understanding Future Climate in the Upper Awash Basin (UASB) with Selected Climate Model Outputs under CMIP6

Climate change makes the climate system of a given region unpredictable and increases the risk of water-related problems. GCMs (global climate models) help in understanding future climate conditions over a given region. In this study, 12 GCMs from the CMIP6 (coupled model intercomparison project six) were evaluated and ranked based on their abilities to describe the historical observed series. The ensemble mean of bias-adjusted best five models of average annual precipitation showed an increment with an uncertainty range of (2.0–11.9) and change in the mean of 6.4% for SSP2-4.5 and (6.1–16.1) 10.6% for SSP5-8.5 in 2040–2069 relative to the historical period. Similarly, for 2070–2099, increments of (2.2–15.0) 7.9% and (11.8–29.4) 19.7% were predicted for the two scenarios, respectively. The average annual maximum temperature series showed increments of (1.3–2.0) 1.6 °C for SSP2-4.5 and (1.7–2.3) 2.0 °C for SSP5-8.5 in 2040–2069. At the same time, increments of (1.7–2.3) 2.0 °C and (2.8–3.2) 3.0 °C were predicted for 2070–2099. Furthermore, it was predicted that the average annual minimum temperature series will have increments of (1.6–2.3) 2.0 °C and (2.2–2.9) 2.5 °C for 2040–2069 and (2.1–2.7) 2.4 °C and (3.7–4.2) 4.0 °C for 2070–2099 for the two scenarios, respectively. An increase in precipitation with increased land degradation in the sub-basin results in a higher risk of flood events in the future. Improved soil and water conservation practices may minimize the adverse impacts of future climate change on the loss of agricultural productivity.

Temporal and spatial characteristics of drought, future changes and possible drivers over Upper Awash Basin, Ethiopia, using SPI and SPEI

Temporal and spatial characteristics of drought, future changes and possible drivers over Upper Awash Basin, Ethiopia, using SPI and SPEI

Groundwater potential mapping using integrations of remote sensing and analytical hierarchy process methods in Ataye-watershed, Middle Awash Basin, Ethiopia

Groundwater potential mapping using integrations of remote sensing and analytical hierarchy process methods in Ataye-watershed, Middle Awash Basin, Ethiopia