Awash River Basin Research Articles

Interannual comparison of historical floods through flood detection using multi-temporal Sentinel-1 SAR images, Awash River Basin, Ethiopia

Interannual comparison of historical floods through flood detection using multi-temporal Sentinel-1 SAR images, Awash River Basin, Ethiopia

Identification and mapping of surface irrigation potential in the data-scarce Jewuha watershed, Middle Awash River Basin, Ethiopia

Abstract This study was conducted to identify and map the surface irrigation potential in the data-scarce Jewuha watershed of the Awash Basin, Ethiopia. The suitability of the land, based on the soil characteristics and slope, was first assessed by the parametric evaluation technique. The overall suitability of the land was then evaluated considering additional factors including land use land cover, proximity to a water source and road using weighted overlay analysis through the analytic hierarchical process (AHP). Water diversion sites as the source of water supply points were selected based on theoretical site selection criteria with the help of a geographic information system (GIS) and physical observation. The surface water available at the diversion sites was estimated using the Soil and Water Assessment Tool (SWAT) model combined with the spatial proximity regionalization technique. The land suitability analysis revealed that 16.7% (11,359 ha) of the study area is suitable for surface irrigation. Five diversion sites were identified as sources of water supply and the total flows at these sites were 12.92 Mm3. It was found that only 27.3% (3,098 ha) of the suitable land, 5% of the total area of the watershed, can be effectively developed by surface irrigation.

Optimizing soil erosion estimates of RUSLE model by analyzing land use/cover dynamics in upper Awash River Basin, Central Ethiopia

The Revised Universal Soil Loss Equation (RUSLE) is the most widely used erosion model for decision making on conservation priority. However, interpreting estimates of the mean annual soil loss alone could not accurately depict the spatial variation of soil erosion severity due to its inherent mathematical errors. This study aims to optimize the model’s outputs through detailed analysis of land use/cover dynamics in Upper Awash River Basin, central Ethiopia (7815.1 km2). The analysis include annual rate of change, net gain or loss, and conversion pathways. Results of the estimated mean annual soil loss in the basin varies between 4.1 t/ha/y and 5.1 t/ha/y during three consecutive decades (1990-2000, 2000-2010, and 2010-2020). The cultivated land cover exhibits slight erosion severity (< 5 t/ha/y), while contributing up to 59% the total annual soil loss (3198.8 Mt/ha). Although the net loss of cultivated land cover outweighing the gain during these decades, it progressively encroaches forests (142.2 km2), shrubs (780.8 km2), and grasslands (274.5 km2). Such net loss of protective land covers will inevitably increase the soil erosion risk. Findings from the study would be useful, enabling conservation practitioners to understand the overall severity of soil erosion and make informed decisions.

Evaluating the effects of geochemical and anthropogenic factors on the concentration and treatability of heavy metals in Awash River and Lake Beseka, Ethiopia: arsenic and molybdenum issues

In the Awash River basin (Ethiopia), massive urbanization and industrialization, driven by rapid development and human settlement, are detrimental to the environment and human health as pollutants such as heavy metals (HMs) find their way into water bodies without proper treatment. The purpose of this study was to assess the HMs content and pollution sources within the basin. In this context, a total of 205 samples were collected from 21 surface water sampling stations. Heavy metal concentrations were measured using the Perkin Elmer NexION 350 ICP-MS with inductively coupled plasma. Findings demonstrate that high levels of HMs, such as Al, Mn, Mo, As, V, Fe, and Ba were exhibited with the value of 1257 μg/L, 626.8 μg/L, 116.7 μg/L, 61.2 μg/L, 100.5 μg/L, 1082.7 μg/L, and 211.7 μg/L, respectively. Among 20 HMs analyzed, 20% of the parameters within the study area were above the WHO limit for drinking water; Al (157 μg/L), V (100.5 μg/L), Fe (1082.7 μg/L), Mn (626.8 μg/L), and Mo (103.8 μg/L) were exhibited at sites along the river system. Likewise, 57% of water samples showed high values of As at many stations down the river systems. In particular, high HM concentrations seen in the upper Awash are primarily controlled by anthropogenic activities such as untreated industrial, agricultural, and domestic discharges, while the high HM concentrations in the middle Awash samples were likely due to the influence from the Lake Beseka that has high HM concentrations due to geological process. In conclusion, securing potable water for the rapidly increasing population in Addis Ababa and in the watersheds of Awash is unsafe to sustain the environment and the human health.

Flash drought evaluation using evaporative stress and evaporative demand drought indices: a case study from Awash River Basin (ARB), Ethiopia

Drought is one of the most devastating phenomena that affect the livelihood of most communities in Ethiopia as they have low adaptive capacity. Recent advancements in remote sensing and drought investigations have made it possible to identify a new type of flash drought that has rapid intensification with a short duration (i.e., less than 1 month unlike conventional droughts). This study intends to identify flash drought in the Awash River Basin (ARB) based on Moderate Resolution Imaging Spectroradiometer (MODIS) data of actual evapotranspiration and potential evapotranspiration using Evaporative Demand Drought Index (EDDI) and Evaporative Stress Index (ESI) indices. The flash drought result exhibited that agricultural lands, grasslands, vegetation areas, and irrigational croplands along the river were vulnerable to flash drought in the ARB. Using ESI, the area of ARB that experienced flash drought in 2002, 2008, 2009, 2012, and 2015 were 23%, 40%, 20%, 40%, and 24%, respectively. These intense flash drought areas can be used as drought monitoring sites. The flash drought extent of EDDI is more compared to ESI because of ESI’s dependency on vegetation coverages and soil moisture. The lowland downstream part of the ARB is highly prone to flash drought, particularly in the major rainy season (MRS) and the last two months of the minor rainy season (mRS). EDDI can discern the onset of flash drought better compared to ESI, but both can be used as a drought early warning mechanisms to minimize agricultural losses and drought-associated risks in the basin.

Potential fish yield and biology of some fish in Lake Hertale, Afar regional state, Ethiopia

The Afar region is characterized by an arid and semi-arid climate with erratic rainfall and is prone to frequent droughts despite being endowed with fresh and saline water bodies along the Awash River Basin. Lake Hertale is one of those fresh water bodies located in the middle of the Awash River Valley. The lake's fishery is presumed not to have been exploited before. The study attempted to describe some physico-chemical parameters, fish species composition, estimate production potential which are relevant to develop a lake fishery with the prospect of contributing to food and nutrition security. The nutrient and chlorphyl-a measurements indicated eutrophic state but with apparently comparative low primary biomass. Conductivity, dissolved oxygen and temperature were within the optimal range for warm water species along with slightly alkaline pH. It was found that Lake Hertale is home to four important fish species, namely, Nile Tilapia (Oreochromis niloticus), barbs (Lebobarbus intermidus), African catfish (Clarias gariepinus) and Common carp (Cyprinus carpio), Nile crocodiles, several species of birds and hippopotamus. Labeobarbus constituted 56%, followed by Nile tilapia with 31% of the total population. The African Catfish constituted only 9% of the catch. The mean lengths of African Catfish and Labeobarbus were 47.2 and 38 cm respectively. The mean lengths of Nile tilapia and Common carp were 22.8 and 21.7 cm respectively. The fish production potential of the lake was estimated from 94.3 to 238 tons per year, with an average production of 145.7 tons per year. The estimate production potential can support up to 21 to 28 fishers, with an average number of 25 fishermen to sustainably utilize the lake's fishery potential. Lake Hertale and other adjacent lakes in the Afar region of Ethiopia can complement to the fight against hunger and malnutrition. Besides, through appropriate fishery development intervention, it is possible to create employment for the predominantly pastoralist Afar community.

Modeling rainfall-runoff estimation and assessing water harvesting zone for irrigation practices in Keleta watershed, Awash river basin, Ethiopia

The world’s water demand is increasing twice as quickly as the world’s population. Contrarily, the greatest problem facing humanity in the twenty-first century is the supply of food. During dry seasons, when water collecting is a crucial survival strategy, the communities in the study area experience water deficit for agricultural production. In this study, socioeconomic and biophysical parameters were considered to evaluate the water harvesting zone for irrigation practices. With the aid of this technology, water harvesting sites can be found in acceptable sites, and water resource management can be improved to address water shortages during the dry season when crops are at key stages of growth and filling. The integrated geographical information system/Remote Sensing (GIS/RS), Soil Water Assessment Tool (SWAT), fuzzy logic, and analytic hierarchy process (AHP) model were used to carry this out. Rainfall, drainage density, surface runoff, percentage of clay content, land use land cover, slope, lithology, lineament, and Euclidian distance to settlement and road were the criteria utilized to choose the Rainwater Harvesting (RWH) sites. The run-off was estimated using the SWAT model, weights for each influential component were determined using AHP, the input factor was standardized using fuzzy membership, and factors were combined using gamma fuzzy (ℽ= 0.9) overlay weighting. The model’s statistical performance was demonstrated by R2 values of 0.79 and NSE values of 0.77 for monthly calibration periods and R2 values of 0.81 and NSE values of 0.75 for monthly validation periods. The study area’s Rainwater Harvesting potential suitability classes covered very highly suitable (16.91%), extremely suitable (27.6%), moderately suitable (20.23%), low suitable (13.1%), and not suitable (6.43%), and restrictions (15.73%). The study’s findings could help decision-makers identify more lucrative and long-lasting irrigation investment options in the Keleta watershed and make better decisions regarding the development of irrigation projects there.

Super ensemble based streamflow simulation using multi-source remote sensing and ground gauged rainfall data fusion

Traditional data-driven streamflow predictions usually apply a single model with inconsistent performance in different variability conditions. These days model ensembles or merging the benefits of different models without losing the general character of the data are becoming a trend in hydrology. This study compared three super ensemble learners with eight base models. Twelve years of monthly rolled daily time series data in three river catchments of Ethiopia (Borkena watershed: Awash river basin), (Gummera watershed: Abay river basin), and (Sore watershed: Baro Akobo river basin) is used for single-step daily streamflow simulation using previous thirty-day input timesteps. Five input scenarios are applied: three vegetation indices, three remote sensing-based precipitation products, ground-gauged rainfall, all fused inputs, and selected inputs with the Recursive Feature Elimination (RFE) algorithm. The time series is then divided into training and testing datasets with a ratio of 80:20. The performance of the proposed models was evaluated using the Root Mean Squared Error (RMSE), coefficient of determination (R2), Mean Absolute Error (MAE), and Median Absolute Error (MEDAE). Finally, the result is presented with the corresponding five input scenarios. The catchment's and input scenario's average performance indicated that the three super ensemble learners outperformed the eight base models with relatively stable performance. The top-ranked WASE model exceeded the linear regression baseline by 13.3%. XGB, CNN-GRU, and LSTM proved the highest performance of the base models. This study also revealed that LSTM's key downside is its performance drop in the absence of feature selection criteria. In comparison, XGB showed its superior performance after controlling redundant inputs internally. Moreover, this study uniquely highlights the potential of remote sensing-based vegetation indices in the science of data-driven streamflow modelling for non-gauged catchments with no meteorological time series.

Simulation of stream flows and climate trend detections using WEAP model in awash river basin

Simulation of stream flows and climate trend detections using WEAP model in awash river basin

Spatio-temporal variability and potential health risks assessment of heavy metals in the surface water of Awash basin, Ethiopia

Increasing urbanization and industrialization are impacting on water quality globally. In the Awash River basin, Ethiopia, these drivers are impacting on water quality with further impacts created due to changes in water management releasing geogenic contaminants. The resulting water quality has potential to cause significant ecological and human health impacts. The physicochemical and heavy metals saptio-temporal variability and their associated risks to human health and ecology were assessed across twenty sampling stations in the Awash River basin. Over twenty-two physicochemical and ten heavy metals parameters were analyzed using different instruments including inductively coupled plasma mass spectrometer (ICP-MS). Elevated levels of heavy metals (As, V, Mo, Mn, and Fe) were detected in the surface water, surpassing the drinking water quality standards set by the World Health Organization (WHO). Seasonal variation was evident with peak concentration of As, Ni, Hg, and Cr were recorded in the dry season. A water quality index, hazard quotient, hazard index, heavy metal pollution index and heavy metal evaluation index were formulated to assess the potential risks to both human health and the environment. The highest values of heavy metal pollution index (HPI) above the threshold (>100) were observed in stations at Lake Beseka with HPI values ranged from 105 to 177. Similarly, the highest values of the heavy metals evaluation index (HEI) were observed in stations situated at cluster 3. The evaluation of health risk that is not related to cancer through hazard quotient demonstrated that in the case of both dermal and ingestion contact, cluster C3 > C1 > C4 > C2 and C3 > C4 > C2 > C1 were observed in children and adults, respectively. Overall, measures to reduce potential pollution risks must be taken in accordance with the standards in the river basin. Nevertheless, further research on the toxicity of heavy metals that pose risks to human health is also necessary.

Flood Hazard Zoning of Upper Awash River Basin, Ethiopia, Using the Analytical Hierarchy Process (AHP) as Compared to Sensitivity Analysis.

Floods and droughts have been two of the most devastating consequences of the climate crisis affecting billions of people in the world. However, unlike the other natural hazards, flooding is manageable through appropriate flood management mechanisms. This study emphasizes on developing a flood hazard zone for the Upper Awash River Basin (UARB), Ethiopia. Six relevant climate, physiographic, and biophysical factors were considered. Then, a flood hazard map was developed employing the analytic hierarchy process (AHP) method and further validated using sensitivity analysis and collected flood marks. The results revealed that drainage density, rainfall, and elevation have higher significance, while land use and soil permeability have a low impact in the process of flood generation. The map showed vulnerable areas at different levels and can serve as a valuable input for the decision makers to consider in the process of implementing emergency plans as well as long-term flood mitigation options.

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.

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.

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.

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.