Blue Nile Research Articles

Spatial analysis of groundwater potential using remote sensing and GIS-based multi-criteria decision analysis method in Fetam-Yisir catchment, Blue Nile Basin, Ethiopia

Spatial analysis of groundwater potential using remote sensing and GIS-based multi-criteria decision analysis method in Fetam-Yisir catchment, Blue Nile Basin, Ethiopia

Trends and climate change analysis for common climate variables in Gelgel Belese Watershed, Upper Blue Nile Basin, Ethiopia

Trends and climate change analysis for common climate variables in Gelgel Belese Watershed, Upper Blue Nile Basin, Ethiopia

Design and Modeling of Hybrid Solar PV/Mini Hydro Micro-grid Systems for Rural Electrification: A Case of Gilgel Abay River, Ethiopia

Design and Modeling of Hybrid Solar PV/Mini Hydro Micro-grid Systems for Rural Electrification: A Case of Gilgel Abay River, Ethiopia

Modelling the Impacts of the Changing Climate on Streamflow in Didesa Catchment, Abay Basin, Ethiopia

The Didesa catchment, which is the second largest subbasin of the Abay basin, significantly contributes to the Blue Nile’s outflow. Understanding the dynamics of water availability under the changing climate in such a basin assists in the proper planning of land use and other development activities. This study presents changes in climatic elements such as rainfall, temperature, and evapotranspiration using observation data and regional climate models (RCMs) under two representative concentration pathways (RCPs) for three future periods. We use a calibrated hydrological model to further assess climate change’s effects on streamflow. We select three RCMs and their ensemble’s mean by evaluating their performance with respect to observations. We apply the modified Mann–Kendall test to detect trends in each dataset. The result shows that annual mean maximum and minimum temperatures increase in the catchment for the 2021–2040, 2041–2070, and 2071–2100 periods as compared to baseline (1989–2018) under both RCP4.5 and RCP8.5 scenarios. Annual mean maximum temperature and potential evapotranspiration experienced a significant decreasing trend during the year from 1989 to 2018. Furthermore, there was an increasing trend in annual rainfall from 1989 to 2018, which could be related to the cooling of sea surface temperature over the equatorial Pacific. We detect an increasing trend in temperature in both scenarios and all periods; however, no clear trend pattern is found in rainfall. The result from hydrological model simulations reveals that the mean monthly streamflow slightly increases in the winter season while it decreases during the main rainy season. Further study of detailed weather systems, which affect the subbasin’s climate, is recommended.

Reliability-weighted approach for streamflow prediction at ungauged catchments

Understanding the hydrological processes and the determination of the frequencies and magnitudes of streamflow are crucial for better oversight of available water resources. A significant obstacle to accurately assessing the water resources of a basin is the accessibility of data for hydrologic modeling. For example, nearly 70% of Ethiopia's Omo-Gibe River basin is ungauged, despite the fact that it is currently undergoing major socioeconomic activity, including the development of cascade hydropower generation. As a result, regionalization remains a critical difficulty in creating solid projections in these ungauged catchments. Thus, this study aimed to provide a dependable technique for accurately determining surface water resources in ungauged catchments. To accomplish this, a new approach called Reliability-weighted (RB) has been introduced to predict runoff in regions with unreliable data. This method combines the advantages of three commonly used parameter transfer methods: global mean, physical similarity, and spatial proximity through weighted averaging. The weights are computed using the reliability-weighted values of each parameter transfer strategy, which are also computed using the donor catchment's hydrological model's reliability value during the calibration and validation periods. The suitability of the proposed scheme was checked in the Omo Gibe and Upper Blue Nile River basins, in Ethiopia. After analyzing parameter transfer techniques using the jackknife algorithm at several target-gauging stations, it was found that the reliability-weighted method outperforms all three regionalization approaches by about 30% for the test catchments. In addition, approximately 85% of the time, the proposed strategy's regionalization performance has a metric Nash-Sutcliffe efficiency greater than 0.50. Alternatively, according to the median Efficiency of the Nash-Sutcliffe model, the newly proposed strategy reduces the spatial and temporal losses by around 0.01 and 0.02, respectively, when compared to the second-best performing option. Furthermore, the performance of the presented approach's runoff prediction at the test gauged catchments was very comparable to the performance of the on-site calibrated model. The newly proposed approach therefore proved to be a useful tool for assessing the potential of available water resources in ungauged catchments. Finally, the uncertainty in runoff prediction at ungauged basins was reduced by combining the strengths of parameters transfer strategies relying on their reliability at test gauging stations.

Watershed Hydrological Responses to Land Cover Changes at Muger Watershed, Upper Blue Nile River Basin, Ethiopia

Changes in land cover (LC) are the major factors influencing the hydrological processes within a watershed. Understanding the impacts of LC on watershed hydrology is crucial for planning and predicting land resource utilization, water resources, and sustaining hydrological balance. This study assesses the hydrological responses of LC changes in the Muger watershed located in the Upper Blue Nile River Basin (UBNRB) from 1986 to 2020. We used the Soil and Water Assessment Tool (SWAT) hydrological model to investigate the effects of LC on the hydrological process. The simulations were driven by several datasets, such as watershed elevations, mean climatology, hydrology and soil datasets, and LC satellite maps for three time periods (i.e., satellite imagery taken in 1986, 2003, and 2020). We found that the key LC changes that affected hydrological parameters in the Muger watershed are changes in cultivation land, forest land, and settlement. The expansion of cultivation land and shrinkage of forest and shrub lands triggered surface runoff and a reduction in groundwater between 1986 and 2003. Additionally, settlement was identified as the primary factor contributing to increases in evapotranspiration (ET) and surface runoff. The LC changes that occurred between 1986 and 2020 reduced the average annual, wet season, and dry season streamflow. Between 2003 and 2020, surface runoff decreased by 3.71% due to the effect of land landscape restoration interventions. The outcome of the study can assist decision-makers and planners in preparing adaptable strategies under changing LC conditions within a watershed.

Evaluating the Impact of Statistical Bias Correction on Climate Change Signal and Extreme Indices in the Jemma Sub-Basin of Blue Nile Basin

This study evaluates the effect of the statistical bias correction techniques of distribution mapping and linear scaling on climate change signals and extreme rainfall indices under different climate change scenarios in the Jemma sub-basin of the Upper Blue Nile Basin. The mean, cumulative distribution function (CDF), mean absolute error (MAE), probability of wet days (Prwet (%)), and 90th percentile (X90 (mm)) of observed rainfall and the regional climate model (RCM) simulations of rainfall with and without statistical bias correction were compared with the historical climate (1981–2005). For future (2071–2100) climate scenarios, the change in climate signal and extreme rainfall indices in the RCM simulations with and without bias correction were also evaluated using different statistical metrics. The result showed that the statistical bias correction techniques effectively adjusted the mean annual and monthly RCM simulations of rainfall to the observed rainfall. However, distribution mapping is effective and better than linear scaling for adjusting the probability of wet days and the 90th percentile of RCM simulations. In future climate scenarios, RCM simulations showed an increase in rainfall. However, the statistically bias-adjusted RCM outputs revealed a decrease in rainfall, which indicated that the statistical bias correction techniques triggered a change in climate signal. Statistical bias correction methods also result in changes in the extreme rainfall indices, such as frequency of wet days (R1mm), number of heavy precipitation days (R10mm), number of very heavy rainfall days (R20mm), and other intensity and frequency indices.

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.

Analyzing the contribution of gully erosion to land degradation in the upper Blue Nile basin, Ethiopia

Soil erosion has become a worldwide problem that threatens the environment and the future of economic and social development. The purpose of this study is to investigate the contribution of steep slopes and gullies to erosion in high precipitation tropical areas of the Ethiopian highlands. A trapezoidal weir was installed at the head and tail of the gully to monitor the discharge and sediment concentration from 2017 to 2020. Sediment yield and runoff are heavily influenced by the amount and timing of precipitation. The coefficients of variation for total sediment loads ranged from 65.1 to 96.1% at the head and 17.1–78.1% at the tail; the lowest coefficients were found in 2018 and the highest in 2020. Furthermore, 85% of the sediment at the tail comes from the gully, according to the four-year sediment budget. Further, a hysteretic analysis of suspended sediment concentration and runoff revealed that hilly sediment sources are limited (clockwise), then sediment can be transported through the gully via bank failures (counterclockwise). Study findings contributed to a classification of runoff patterns and an investigation of suspended sediment dynamics. In the gully tail, sediment yield was higher than in the head, suggesting gully sediment contributed more to sediment yield than large upland catchments. As a result of the study, we have been able to develop practical recommendations for managing gully erosion in the future.

Characterizing groundwater and surface water interaction using geological, environmental tracers (222Rn, EC, δ18O, and δ2H) and baseflow index methods for part of the Upper Awash and the adjacent Blue Nile Basin, Ethiopia

Characterization of groundwater-surface water interaction using a combined approach of geological, environmental tracers (222Rn, EC, δ18O, and δ2H) and baseflow index in a complex geological environment was carried out for part of the Upper Awash and adjacent Blue Nile Basins. In this work, total measurements of 59 water samples were used (52 from different reaches of main Rivers and tributaries, 4 from springs, and 3 from boreholes) for 222Rn analysis in dry and wet seasons, along with recent 8–20 years of daily stream flow records from 11-gauge stations. For sub-surface inference, regional geological structures and lineament density zones were determined using Kriging interpolation techniques. 222Rn values for the river and streams show 2.7–468 Bq/m3 during the rainy season and 17.1–1467 Bq/m3 for the non-rainy season. The credible justification related to moderate to high seasonal 222Rn values (100–400 Bq/m3) in the upstream parts of the two Basins, including areas falling along the surface water divide between the two adjacent Basins, shows a link between groundwater and surface water systems. In the same area, a very high mean annual baseflow index (BFI >0.5) is dominantly associated with high lineament density (0.9 < LD < 3.0), regional faults, and geologic units of highly permeable scoriaceous basalt, rift basalt, and fractured ignimbrite units. Relatively, low 222Rn (<100 Bq/m3) in both seasons and low baseflow index (BFI <0.35) values mainly in the central part of the Upper Awash basin are attributed to existing impervious superficial deposits (alluvial, tuff and ash). This, in turn, shows the poor connection between the groundwater and surface water systems in the central plain part of the Upper Awash Basin and, as also evidenced by the storage of floodwater for an extended time after the end of the rainy season, prove poor connectivity between groundwater and surface water systems. The very high 222Rn (400–1467 Bq/m3) with varied mean annual baseflow index (0.35 < BFI <0.5) at different stations in the extreme southern and southeastern parts of the Upper Awash Basin show Awash River is gaining from the aquifer system through highly fractured basalt and fractured ignimbrite geologic units. Evidence from analysis of measured electrical conductivity and stable isotopes (δ18O, δ2H) generally agree with the observed 222Rn value and baseflow analysis.

Simulation of the rainfall–runoff relationship using an HEC-HMS hydrological model for Dabus Subbasin, Blue Nile Basin, Ethiopia

Abstract Hydrological modeling is important to provide relevant hydrologic information from limited data. In this study, Hydrologic Modeling System (HEC-HMS) was used to simulate the rainfall–runoff relationship for the Dabus subbasin of the Blue Nile Basin. Daily precipitation and stream flow data from 2002 to 2019 were used as key input data for the model, together with soil and land use/land cover data, and a digital elevation model of the study area. Arc-GIS was employed in combination with Arc Hydro and HEC-GeoHMS tools for terrain processing and translating spatial information into model files for HEC-HMS, respectively. Model calibration was done with data from 2002 to 2014, while the validation was done from 2015 to 2019. Nash-Sutcliffe simulation efficiency (NSE), observation standardized ratio (RSR), and coefficient of correlation (R2) were used to assess the performance of the model. With NSE, RSR, and R2 values of 0.784, 0.334, and 0.816 for calibration, and 0.793, 0.323, and 0.875 for validation, the model simulation of stream flows was found in good agreement with the observed values. Therefore, the HEC-HMS model can be utilized to predict stream flows in ungauged catchments in the Dabus subbasin from measured rainfall data for proper water resource planning and management.

ESTIMATION OF CHANGE IN TERRESTRIAL WATER STORAGE FOR ABBAY RIVER BASIN USING OPEN ACCESS SATELLITE DATABASES AND HYDROLOGICAL MODEL

Access to freshwater resources has become more limited. Correspondingly, water monitoring methods in sensitive or critical areas interims of terrestrial water storage are becoming increasingly important. The monitoring of the water storage in this area, using appropriate methods and data sets, is highly effective in preventing possible future water crises. This paper aims to estimate terrestrial water storage of the Abbay river basin with available data and tools where hydro climatological studies are scarce due to limited observation. The data obtained from GLDAS, GRACE and TerraClimate were used for the analysis of terrestrial water storage in the river basin. The result shows that there was a varying trend of terrestrial water storage for the study time. We have observed water shortages during the dry season and surplus water during the wet season. The monitoring of changes in terrestrial water storage is crucial for optimal water resource utilization and our results confirm the major role of such monitoring in decision-making processes and management.

Evaluating climate change impact on the hydrology of Kessie Watershed, Upper Blue Nile Basin, Ethiopia

Climate change affects ecosystems, agriculture, human health, forestry, and water resource availability. This study is mainly aimed at assessing the climate change effect on the water resources of the Kessie Watershed in the Upper Blue Nile Basin, Ethiopia. The updated Coupled Model Intercomparison Project Phase 6 (CMIP-6) data outputs were used. The three climate model outputs: ACESS_ESM1-5, FGOALS_g3, and GFDL_ESM4 with two shared socioeconomic pathways (SSP2-4.5 and SSP5-8.5) scenarios, were used. The climate model output rainfall and temperature data were downscaled to the station level through bias correction. The catchment hydrology was represented by the SWAT—Soil and Water Assessment Tool—through calibration and validation. Future temperatures and rainfall change were evaluated by the Mann–Kendall trend test and Sen’s slope estimator. Future climate change trend analysis and streamflow simulation were done on two time horizons: the 2050s (2041–2070) and the 2080s (2071–2100). The baseline streamflow data (1985–2014) were used as a reference. The global climate model projection data indicated mean annual precipitation and temperatures show a slight increase for the future in both scenarios for all climate model outputs. According to the SSP2-4.5 and SSP5-8.5 scenarios, respectively, mean annual precipitation is expected to increase by 5% and 4.89% in the 2050s and 10.13% and 6.8% in the 2080s based on ACCESS_ESM1-5; 4.7% and 3.8% in the 2050s and 4.3% and 4.84% in the 2080s based on FGOALS_g3; and 4.67% and 3.81% in the 2050s and 4.67% and 3.81% based on GFDL_ESM4 models data. Yearly average maximum temperature may increase by 3.62 °C and 1.87 °C in the 2050s and 3.31 °C and 2.99 °C in the 2080s based on ACCESS ESM1-5, 1.76 °C and 1.25 °C in the 2050s and 3.44 °C and 2.61 °C in the 2080s based on FGOALS-g3, and 2.15 °C and 3.83 °C in the 2050s and 1.37 °C and 2.66 °C in the 2080s based on GFDL-ESM4 model data. Similarly, the mean annual minimum temperature is also expected to increase by 2.73 °C and 1.90 °C in the 2050s and 5.63 °C and 4.52 °C in the 2080s based on ACCESS ESM1-5, 3.04 °C and 2.43 °C in the 2050s and 3.55 °C and 4.36 °C in the 2080s based on FGOALS-g3, and 2.31 °C and 3.29 °C in the 2050s, and 3.16 °C and 3.87 °C in the 2080s based on GFDL-ESM4 model data. The streamflow is also expected to increase. In the 2050s, simulated annual streamflow is expected to increase from 12.1 to 21.8% and 9.8 to 15.4% in SSP2-4.5 and SSP5-8.5, respectively, whereas in the 2080s, the change is expected to increase from 15.14 to 24.08% and 13.08 to 41% in SSP2-4.5 and SSP5-8.5, respectively. Future water resource potential of the case study watershed seems able to support irrigation and other projects.

Groundwater potential assessment in the Blue Nile River catchment, Ethiopia, using geospatial and multi-criteria decision-making techniques

Groundwater supplies have been exploited because of global water shortage. Therefore, effective management of water resources is crucial. Identifying potential groundwater regions in arid and mountainous terrains is challenging for many developing nations because of a lack of financial and human resources. An integrated strategy using remote sensing, geographic information systems, and multi-criteria decision analysis of the hierarchical analytical process was used to identify potential zones for groundwater in the Gulufa Watershed, Blue Nile River Basin, Ethiopia, which covers 1700 km2. Nine groundwater-influencing thematic layers were produced from conventional and satellite data, including lineament density, lithology, slope, geomorphology, soil, land use/land cover, drainage density, rainfall, and elevation. Satty scale values for the thematic layers and their classes were determined based on experts' opinions and literature. Thematic maps were integrated based on their weights and rates to produce a potential zone map using ArcGIS weighted overlay spatial function tool. According to the results, the prospect zone map consists of 383 km2 of very high, 865 km2 of high, 350 km2 of moderate, 58 km2 of low, and 0.3 km2 of poor zones. Validation of the potential zone map using existing boreholes yielded a close agreement, demonstrating the method's accuracy. According to the map removal sensitivity analysis results, the potential zone was more sensitive to lithology than other thematic layers. The map created in the research region can be an essential reference for identifying potential locations for additional groundwater resource exploration, planning, and management.

The Global Perspective of the Dilemma of Cooperation and Complex Relationships between the Upper and Lower Nile Riparian States after 2011

There is a perceived global deficit of fresh water due to rapid population growth and increasing widespread poverty. This will inevitably lead to more complicated cooperation dilemmas between downstream and upstream Nile Basin states. Egypt and Sudan have been pushing for the Nile's water to be globally controlled by the UN Security Council from 2020–2021, after fruitless discussions; so the conflict in the Nile Basin may have far-reaching global implications and seems elusive. Due to suspicion and mistrust among Ethiopia, Sudan, and Egypt over the Grand Ethiopian Renaissance Dam (GERD) on the Blue Nile, the states are unable to prioritize mutual cooperation efforts. Third-country intervention has worsened the ongoing great divide over the GERD. Thus, the main purpose of the present article is to assess, from a global perspective, how upstream and downstream Nile Basin states, in particular Ethiopia, Sudan, and Egypt, cross the threshold of cooperation dilemma and concern and how excessive third-party intervention exacerbates the complex relations between these states. The study conducted an in-depth documentary analysis of secondary sources by using a qualitative research method and examining various documentary sources.

Transboundary Nile basin dynamics: Land use change, drivers, and hydrological impacts under socioeconomic pathways

Landscape transitions in the Nile River basin will likely accelerate over the next decades due to socioeconomic developments and climate change. However, the assessments of land use/land cover (LULC) changes and their impact on the water resources over the Nile basin lacked a transboundary perspective. Here we used coupled basin-scale geospatial-hydrological models to project future LULC changes in the Nile basin and its three tributaries (i.e., White Nile, Blue Nile, and Atbara River), explored their drivers and projected hydrological impacts under different shared socioeconomic pathways (SSPs) during 2020–2060. Compared to 1992–2019, significant increases in the forested area (>50 × 103 km2) are expected to occur in the upstream areas of the White Nile and the Blue Nile in South Sudan and Ethiopia, with larger increases projected under higher emission scenarios. Consequently, it will likely reduce the downstream seasonal river discharge for the White and Blue Nile by up to 8.4% (SSP5) and 8.9% (SSP2), respectively. An increase of 7.4% in the Blue Nile discharge is expected during the flood season if the current urbanization/deforestation rates would prevail in the future. Large decreases (>15 × 103 km2) of unused land are expected in the Atbara River sub-catchment with increases in natural vegetation socioeconomic-related LULC types, leading to a river flow decrease of 15% during the rainy season under the SSPs. The basin-scale LULC changes are projected to decrease the Main Nile flow to Egypt by 3.6% under SSPs and increase by 2.1% if the historical trends prevail. The results highlight a close association between landscape dynamics, socioeconomic growth, and climate change over the Nile basin and suggest adaptive LULC planning and conservation measures.

Proxy modeling approach to evaluate groundwater recharge potentiality zones in the data scarce area of upper Blue Nile Basin, Ethiopia.

Prioritization of groundwater recharge potentiality evaluation is critical for sustainable water resources management. Since recharge is a main source for enhancing groundwater availability. Water scarcity is extremely severe in the upper Blue Nile Basin (i.e., Gunabay watershed). Therefore, this study emphasizes groundwater recharge delineating and mapping 3920.25 km2 in the data-limited area of the upper Blue Basin using proxy modeling (i.e., WetSpass-M model and geodetector model) and tools. The driving/influencing factors are rainfall, temperature, wind speed, evapotranspiration, elevation, slope, land cover, soil, groundwater depth, drainage density, geomorphology, and geology that control the movement of groundwater recharge. However, the first nine factors were used as inputs in the WetSpass-M model to evaluate groundwater recharge. To validate the groundwater recharge availability, water table fluctuation was established based on recorded groundwater levels. Furthermore, the major influencing factors and their interaction have been quantified using geodetector model. Spatiotemporal recharge distribution (in mm) is classified as very low (0-6), low (6-30), moderate (30-51), high (51-83), and very high (83-508) comprising 21%, 20%, 20%, 20%, and 19% of the total area, respectively. Very high groundwater recharge zone has been found in the northwest part of the area. The geodetector results showed that soil (0.841) and temperature (0.287) had larger individual contributions, but the interaction between soil and temperature (0.962) was more significant. It indicates that the interaction between climate and soil has the largest influence on groundwater recharge variability. Generally, the overall approach of this study can be applied to water sectors, policymakers, and decision-makers to overcome future water scarcity.

Sediment yield estimation and evaluating the best management practices in Nashe watershed, Blue Nile Basin, Ethiopia

Sediment yield estimation along with identification of soil erosion mechanisms is essential for developing sophisticated management approaches, assessing, and balancing different management scenarios and prioritizing better soil and water conservation planning and management. At the watershed scale, land management practices are commonly utilized to minimize sediment loads. The goal of this research was to estimate sediment yield and prioritize the spatial dispersion of sediment-producing hotspot areas in the Nashe catchment using the Soil and Water Assessment Tool (SWAT). Moreover, to reduce catchment sediment output, this study also aims to assess the effectiveness of certain management practices. For calibration and validation of the model, monthly stream flow and sediment data were utilized. The model performance indicators show good agreement between measured and simulated stream flow and sediment yields. The study examined four best management practice (BMP) scenarios for the catchment’s designated sub-watersheds: S0 (baseline scenario), S1 (filter strip), S2 (stone/soil bunds), S3 (contouring), and S4 (terracing). According to the SWAT model result, the watershed’s mean yearly sediment output was 25.96 t/ha. yr. under baseline circumstances. The model also revealed areas producing the maximum sediment quantities indicating the model’s effectiveness for implementing and evaluating the sensitivity of sediment yield to various management strategies. At the watershed scale, treating the watershed with various management scenarios S1, S2, S3, and S4 decreased average annual sediment yield by 34.88%, 57.98%, 39.55%, and 54.77%, respectively. The implementations of the soil/stone bund and terracing scenarios resulted in the maximum sediment yield reduction. The findings of this study will help policymakers to make better and well-informed decisions regarding suitable land use activities and best management strategies.

Implications for selecting persistent hot spots of schistosomiasis from community- and school-based surveys in Blue Nile, North Kordofan, and Sennar States, Sudan.

In several schistosomiasis-endemic countries, the prevalence has remained high in some areas owing to reinfection despite repeated mass drug administration (MDA) interventions; these areas are referred to as persistent hot spots. Identifying hotspots is critical for interrupting transmission. This study aimed to determine an effective means of identifying persistent hot spots. First, we investigated the differences between Schistosoma haematobium and Schistosoma mansoni prevalence among school-aged children (SAC) estimated by a community-based survey, for which local key informants purposively selected communities, and a randomly sampled school-based survey. A total of 6,225 individuals residing in 60 villages in 8 districts of North Kordofan, Blue Nile, or Sennar States, Sudan participated in a community-based survey in March 2018. Additionally, the data of 3,959 students attending 71 schools in the same 8 districts were extracted from a nationwide school-based survey conducted in January 2017. The community-based survey identified 3 districts wherein the prevalence of S. haematobium or S. mansoni infection among SAC was significantly higher than that determined by the randomly sampled school survey (e.g., S. haematobium in the Sennar district: 10.8% vs. 1.1%, P&lt;0.001). At the state level, the prevalence of schistosomiasis among SAC, as determined by the community-based survey, was consistently significantly higher than that determined by the school-based survey. Purposeful selection of villages or schools based on a history of MDA, latrine coverage, open defecation, and the prevalence of bloody urine improved the ability for identifying persistent hot spots.

Soil erosion estimation and risk assessment at watershed level: a case study of Neshe Dam Watershed in Blue Nile River basin, Ethiopia

ABSTRACT Accelerated erosion caused by human activities is the major triggering factor for the loss of soil and water resources in Ethiopia. Soil erosion is commonly regarded as a major environmental problem that affects the sustainability of agricultural production and downstream reservoir. To facilitate urgent policy intervention in sustainable land management, evaluating the amount of annual soil loss is inevitable. In this study, the Revised Universal Soil Loss Equation (RUSLE) and Geographic Information System (GIS) are integrated to analyse the amount of soil loss in the Neshe Dam Watershed of Ethiopia. The total amount of soil loss from the watershed (33,376 hectares) is about 1,252,935 tons per year. Furthermore, the potential average annual soil loss for the whole watershed is anticipated at 37.54 t ha−1 yr−1. In terms of sub-watersheds, very high soil loss (56.62 t ha−1 yr−1) was observed in sub-watershed B accounts (for 16.3%) and the least (16.06 t ha−1 yr−1) observed in sub-watershed E accounts (for 23.6%). The study concluded that if proper measures are not taken now, the accelerated erosion in the watershed will jeopardize the sustainability of agricultural production within the watershed and energy generated from the dam in the long term.