Nile River Basin Research Articles

Reconstructed centennial precipitation-driven water storage anomalies in the Nile River Basin using RecNet and their suitability for studying ENSO and IOD impacts

While the Gravity Recovery And Climate Experiment (GRACE) and its Follow-On (GFO) missions have offered valuable observations for monitoring total water storage anomalies (TWSA), their short record constrains our ability to study the complete range and long-term variability of TWSA in the Nile River Basin (NRB). Previous studies reconstructing TWSA in this region either relied on specific hydrological models or did not consider spatial correlations among the TWSA grids. Here, we employ RecNet, a deep learning model capable of providing independent TWSA observations without relying on hydrological models while considering spatial correlations, to reconstruct precipitation-driven TWSA in the NRB from 1923 to 2022. The reconstructed data are validated by comparisons with the Global Land Data Assimilation System (GLDAS), the WaterGAP Global Hydrology Model (WGHM), the water balance budget, long-term runoff data, and GRACE-REC (i.e., a global reconstruction dataset freely available online). Subsequently, the suitability of the reconstructed data for studying El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) impacts within the NRB is assessed. Dividing the NRB into four sub-regions, i.e., the Lake Victoria Basin (LVB), the Bahr el Jebel and Bahr el Ghazal basins (BJBG), Ethiopian Highlands region (EH), and the Lower Nile River Basin (LNRB), it is shown that RecNet successfully reconstructs precipitation-driven TWSA over BJBG and EH, achieving correlation coefficient (CC), normalized root mean square error (NRMSE), and Nash–Sutcliffeefficiency (NSE) of 0.94/0.11/0.88 and 0.96/0.09/0.91 during the testing period, respectively. Additionally, RecNet’s reconstruction shows better agreement with GLDAS and WGHM than GRACE-REC, correlating well with runoff and the water balance budget in these regions. The relatively poor performance in the LVB and LNRB regions could be attributed to the substantial influence of Lake Victoria and the arid climate, respectively. Correlation analysis and wavelet coherence analysis identify significant coherence between ENSO/IOD and the reconstructed TWSA in BJBG and EH, with CC values of −0.68/0.34 and −0.82/0.56, respectively. This study provides centennial reconstructed TWSA data that could be useful in climate change/variability studies and water resource management within the NRB.

Deep Learning Ensemble for Flood Probability Analysis

Predicting flood events is complex due to uncertainties from limited gauge data, high data and computational demands of traditional physical models, and challenges in spatial and temporal scaling. This research innovatively uses only three remotely sensed and computed factors: rainfall, runoff and temperature. We also employ three deep learning models—Feedforward Neural Network (FNN), Convolutional Neural Network (CNN), and Long Short-Term Memory (LSTM)—along with a deep neural network ensemble (DNNE) using synthetic data to predict future flood probabilities, utilizing the Savitzky–Golay filter for smoothing. Using a hydrometeorological dataset from 1993–2022 for the Nile River basin, six flood predictors were derived. The FNN and LSTM models exhibited high accuracy and stable loss, indicating minimal overfitting, while the CNN showed slight overfitting. Performance metrics revealed that FNN achieved 99.63% accuracy and 0.999886 ROC AUC, CNN had 95.42% accuracy and 0.893218 ROC AUC, and LSTM excelled with 99.82% accuracy and 0.999967 ROC AUC. The DNNE outperformed individual models in reliability and consistency. Runoff and rainfall were the most influential predictors, while temperature had minimal impact.

Policy Options for Achieving Sustainable Development Goals (SDGs) in the MENA Region through the Effective Implementation of Multilateral Environmental Agreements

The Middle East and North Africa (MENA) region faces a complex set of challenges, including political instability, economic disparities, and environmental degradation. Achieving the Sustainable Development Goals (SDGs) in this region is paramount to ensuring a sustainable and prosperous future for its diverse populations. Multilateral Environmental Agreements (MEAs) play a crucial role in addressing environmental issues, which are intertwined with many of the SDGs. This paper explored policy options that can help the MENA region make significant strides towards achieving the SDGs through the effective implementation of MEAs. To achieve this, the MENA region will be required to strengthen regional cooperation through the development and implementation of regional agreements that are tailored towards shared environmental issues, such as trans-boundary water management in the Nile River basin or tackling air pollution in the Gulf Cooperation Council (GCC) countries. Strategies for the adoption of policies on the region’s prevalent issues such as drought and desertification, renewable energy transition, biodiversity conservation, climate change mitigation and adaptation will have to be negotiated, developed, strengthened, and implemented. The paper utilised a content analysis research approach in analysing selected international and regional MEAs. The paper highlights the challenges with the implementation of both international and regional MEAs, with a view to raising awareness on the shortcomings and challenges of implementation of these very important environmental treaties. Achieving the SDGs in the MENA region through the implementation of MEAs requires a coordinated effort amongst nations, international organisations, and civil society. By prioritising regional cooperation, sustainable resource management, renewable energy adoption, biodiversity conservation, climate action, waste management and education, the MENA region can make significant progress towards a more sustainable and prosperous future. These policy options offer a roadmap to address pressing environmental challenges whilst simultaneously advancing the broader agenda of sustainable development.

Description of Pegethrix niliensis sp. nov., a Novel Cyanobacterium from the Nile River Basin, Egypt: A Polyphasic Analysis and Comparative Study of Related Genera in the Oculatellales Order.

In this paper, we examine the filamentous cyanobacterial strain NILCB16 and describe it as a new species within the genus Pegethrix. The original population was sampled from a mat growing in an irrigation canal in the Nile River, Egypt. Initially classified under Plectonema or Planktolyngbya, the strain is a potential producer of the toxins microcystin and β-N-Methylamino-L-Alanine (BMAA). Additionally, we reviewed the taxonomic relationships between the Oculatellales genera. To describe the new species, we conducted a polyphasic study, encompassing 16S rRNA gene phylogenetic analyses performed using both Maximum Likelihood and Bayesian methods, sequence identity (p-distance) analysis, 16S-23S ITS secondary structures, and morphological and habitat comparisons. The phylogenetic analysis revealed that strain NILCB16 clustered within the Pegethrix clade with strong phylogenetic support, but in a distinct position from other species in the genus. The strain shared a maximum 16S rRNA gene identity of 97.3% with P. qiandaoensis and 96.1% with the type species, P. bostrychoides. Morphologically, NILCB16 can be differentiated from other species in the genus by its lack of false branching. Our phylogenetic analyses also show that Pegethrix, Cartusia, Elainella, and Maricoleus are clustered with strong phylogenetic support. They exhibit high 16S rRNA gene identity and are morphologically indistinguishable, suggesting they could potentially be merged into a single genus in the future.

Assessment of monthly to daily streamflow disaggregation methods: A case study of the Nile River Basin

Study regionThe Nile River Basin Study focusThe lack of observed streamflow data at a short time scale poses a critical challenge for calibrating and validating hydrologic models. Therefore, many disaggregation methods were developed, resulting in various relative performances without a clear indication of the optimal choice. This study aims to iteratively assess eight monthly to daily streamflow disaggregation methods at 21 major subbasin outlets in the Nile River Basin (NRB) to identify the best-performing ones. These methods include one proportionality method and seven interpolation methods, i.e., linear, 2nd-order spline, 3rd-order spline, Piecewise Cubic Hermite Interpolating Polynomial (Pchip), Modified Akima (MAkima), mean preserved 2nd-order spline, and mean preserved 3rd-order spline. We assessed these methods using three metrics and visual investigations. New hydrologic insights for the regionThe results showed that the interpolation methods performed well, better than the proportionality method. However, their performances decreased at stations with high daily streamflow fluctuations. The interpolation methods’ performances were similar in mimicking the daily values but significantly different in preserving the mass balance. The mean preserving 3rd-order interpolation method (Lai 22) was the best in preserving the mass balance and capturing the low, moderate and high flows and, therefore, selected to generate the daily flow data in the NRB. The results of this study can guide a reliable method for obtaining daily streamflow data, which is important for the hydrologic and water management studies in the NRB.

One third of African rivers fail to meet the ’good ambient water quality’ nutrient targets

The ambition of Sustainable Development Goal (SDG) target 6.3 is to improve global water quality by 2030. SDG indicator 6.3.2 monitors progress towards this target by assessing water bodies against ‘good’ ambient water quality criteria, with nutrients (nitrogen and phosphorus) as part of the key metrics. However, large data gaps present a fundamental challenge, especially for Africa on how to assess the progress being made with respect to both the current and desired future situations. Here, a continental water quality model for Africa is presented to simulate river sediment load, Total Nitrogen (TN) and Total Phosphorus (TP) loads and concentrations. Furthermore, critical areas and hotspots of TN and TP pollution are mapped for the period 2017 – 2019, in relation to the United Nations Environment Programme (UNEP) target thresholds used for the assessment of SDG indicator 6.3.2. Utilizing the UNEP’s criteria, which designates a water body as having “good ambient water quality” if 80% or more of its monitored values meet their targets, it is estimated that 44 % and 15 % of African rivers fail to meet the set water quality thresholds for simulated TP and TN, respectively. When synthesizing data for both TP and TN, 34 % of the rivers do not qualify as having “good ambient water quality”. Geographically, the most pronounced nutrient pollution hotspots were in North Africa, Niger River Delta, Nile River basin, Congo River basin and specific zones in Southern Africa. These areas correlate with regions characterized by high inputs of fertilizers, manure and wastewater discharge.

Oxytenanthera abyssinica (A. Rich.) Munro land suitability evaluation in the Kurar watershed, Abay Gorge, Upper Blue Nile River Basin, Ethiopia

O. abyssinica, known in Ethiopia as lowland bamboo, is a solid-stemmed clump-forming bamboo species widely distributed in the western dry regions of Ethiopia. The versatility of the species means that it has enormous potential for land restoration in arid and semi-arid areas, in addition to bringing socio-economic benefits. It also displays remarkable adaptability, allowing it to thrive in the challenging ecological conditions of areas such as the Abay Gorge. The Abay Gorge, situated within the Upper Blue Nile River Basin of Northwestern Ethiopia is characterized by problems associated with soil erosion and land degradation. This study, therefore, aimed to evaluate and recommend a suitable spatial analysis for the adoption and development of lowland bamboo (O. abyssinica). Fifteen primary influencing factors were chosen according to the needs of O. abyssinica, the accessibility of data, and the financial implications associated with data analysis, particularly the expenses related to soil laboratory testing. Eight composite soil samples were taken directly by dividing the watershed into two categories (upper and lower catchment areas). These composite soil samples were analyzed. Data analysis was performed via Analytical Hierarchy Process (AHP) in conjunction with Multi-Criteria Decision-Making (MCDM) analysis and the use of Remote Sensing (RS) and Geographic Information System (GIS). The spatial analysis employed in this study was a weighted sum overlay analysis, which was applied by considering the criteria weight assigned to each factor. The analysis revealed that 21.2 % (666.5 ha) of the total area was highly suitable for the growth and development of O. abyssinica. About 56 % (1753 ha) of the land was moderately and marginally suitable for the desired land utilization type. However, 23 % (723.8 ha) of the study area was unsuitable for O. abyssinica. O. abyssinica has the potential to rehabilitate large parts of challenging areas such as the Abay Gorge due to its naturally invase rhizomes and drought-tolerance. It can also be introduced into agroforestry systems and used as living fences for villages.

Navigating the Nile: Ethiopia's Development Plans and the Future of Water Sharing

This article explores the dynamics of the relationship between Egypt and the countries in the Nile River Basin, with a specific focus on the natural challenges Ethiopia faces in developing water projects. This research employs a descriptive qualitative approach with the aim of identifying Ethiopia's natural conditions and their impact on water infrastructure development. Data sources include secondary literature from official reports, case studies, and statistical data related to Ethiopia's water resources and climate. Data were collected through literature reviews and document analysis. The research findings indicate that Ethiopia faces various challenges such as uneven rainfall distribution, high evaporation rates, difficult topography, and rock types that do not support water storage. Data analysis was conducted using qualitative methods to evaluate the impact of natural conditions on Ethiopia's capacity to develop water projects. In conclusion, Ethiopia, despite being a major contributor to the Nile River's water, faces significant natural barriers that limit its ability to build large and stable water infrastructure.

A Review on Nitrogen Flows and Obstacles to Sustainable Nitrogen Management within the Lake Victoria Basin, East Africa

The Lake Victoria Basin (LVB) is located in the upper reaches of the Nile River Basin and is shared by five East-African countries. The population in the catchment is growing rapidly and the lake is facing several environmental problems. During the past few decades, numerous efforts have been made across the five countries, with the coordination of the Lake Victoria Basin Commission (LVBC) to reduce the loading of reactive nitrogen (Nr) into the lake and Lake Watershed. However, most of the measures envisaged to ensure long-term sustainable N management are not as easily adopted as planned. This paper reports on a review study on N flows and obstacles in achieving sustainable N management in the LVB, with the objectives of improving the understanding of the N cycle and examining the N management practices and policies that can help reduce the loss of Nr in the region. The scientific literature related to a range of N flows, N management obstacles, and options to overcome obstacles has been analyzed using N prospects developed at the global level for their potential applicability across the LVB. The study showed that an unbalanced use of N input is a serious threat to agricultural productivity leading to extreme soil N mining and degradation, with the majority of LVB farms operating within negative N balances and above the safe operating boundary for N in production systems. From the projections in N input as recommended by various stakeholders, there would likely be changes in both current yield and N use efficiency (NUE) values; however, most small-scale farmers will continue to experience low yields, which remains a challenge for food security in the area. These results suggest that scientists as well as those involved in decision-making and policymaking processes should formulate new targets for fertilizer increment to reduce the yield gap for sustainability, focusing on more integrated soil fertility as a package for nutrient management in cropping systems.

Estimation of climate and watershed management-induced potential soil loss using the USLE in Demjer watershed, Blue Nile basin, Ethiopia

ABSTRACT This study aimed to predict future soil loss under different climatic scenarios in the Demjer watershed, Blue Nile River Basin. The soil loss was calculated using USLE. The GCMs derived under the RCP4.5 and RCP8.5 for the period 2020–2049 were used. Three LULC scenarios were considered and the projection of the change in rainfall was estimated under the RCP4.5 and RCP8.5 scenarios. The projected mean annual precipitation increased by 6.42 and 5.95% under the RCP4.5 and RCP8.5 scenarios, respectively. The soil loss rate in the future ranged from 0 to 144.7 t ha−1y−1 and from 0 to 142.4 t ha−1y−1 for RCP4.5 and RCP8.5, respectively. Compared to the base period, the soil loss rates increased by 7.6% (RCP4.5) and 7.4% (RCP8.5). This is attributed to increase in rainfall erosivity. The LULC scenario is a major variable in reducing soil erosion rates in the future. That means, soil loss would reduce up to 33.6% of the present soil loss rate, if all the current cultivated lands with slopes >35% are covered by plantations and if open grazing land controlled. Estimation of future soil loss risk could provide evidence for preparing site-specific conservation plans, thereby enabling sustainable use of land.

Comparison of different machine-learning algorithms for land use land cover mapping in a heterogenous landscape over the Eastern Nile river basin, Ethiopia

Land use/land cover (LULC) information is regarded as one of the most important variables in global change studies. Several LULC classification algorithms are available with different levels of accuracy in LULC mapping under different geographical setups. Furthermore, different remote sensing (RS) based indices and auxiliary data have been reported to have contributed to the accuracy of LULC mapping. Hence, the main aim of this study was to compare the different ML algorithms for the LULC mapping and explicitly assess the potential contribution of different RS-derived indices and auxiliary data on classification accuracy in the Upper Tekeze-Atbarah (UTA) river basin in Ethiopia. The overall classifiers evaluation result revealed that random forest (RF) performed best and followed by K-Nearest Neighbour (KNN), Support Vector Machine (SVM), Artificial Neural Network (ANN), Maximum Likelihood Classification (MLC), and Classification and Regression Tree (CART). Compared to RF, the MLC method showed less accuracy by 16.2% (19.7%) in OA (kappa coefficient) respectively, which showed that the currently emerging ML classifiers contributed to an improvement in LULC mapping. The use of RS-derived indices and DEM as predictors together with the Landsat bands improved the overall accuracy and kappa coefficient by 5.5% and 7% respectively. Furthermore, the discrepancy in the classified LULC map from RF and other classifiers was compared at pixel-level and the result showed a considerable disagreement between the LULC maps. For instance, when the LULC map from RF and KNN are compared, only 80.6% of the area has the same LULC condition. This result reflects the potential discrepancy that could exist in LULC maps from different classifiers. The hydrological simulation under each of the classified map also resulted in a considerable difference in the major water balance components. In a conclusion, given the considerable difference in classifier performance and the potential propagation of errors in LULC maps to further applications such as water resources assessment, it is highly recommended to explicitly evaluate the available classifiers. Users should also harness the power of RS indices and auxiliary datasets for improved LULC mapping.

Drought Dynamics in the Nile River Basin: Meteorological, Agricultural, and Groundwater Drought Propagation

The Nile River Basin (NRB) has experienced a notable rise in drought episodes in recent decades. The propagation of meteorological, agricultural, and groundwater drought dynamics in the NRB was investigated in this study. The following drought indices examined the correlation and propagation among meteorological, agricultural, and groundwater droughts. These are the standardized precipitation evapotranspiration index (SPEI), soil moisture index, Gravity Recovery and Climate Experiment, and GRACE Follow-On (GRACE/GRACE-FO)-derived groundwater drought index (GGDI). These droughts were comprehensively evaluated in the NRB from 2003 to 2022. The cross-wavelet transform approach highlighted the links between droughts. The following are the key findings: (1) In the NRB, the cross-wavelet energy spectrum of wavelet coherence can indicate the internal connection between meteorological versus (vs.) agricultural and agricultural versus (vs.) groundwater drought. The time scale with the most significant correlation coefficient is the drought propagation time. (2) The El Niño–Southern Oscillation (ENSO) correlated with agricultural and groundwater drought much more than the Indian Ocean Dipole (IOD), demonstrating that ENSO has an important impact on drought advancement. (3) The R2 values were 0.68 for GGDI vs. standardized soil moisture index (SSI), 0.71 for Blue Nile Region (BNR) GGDI vs. SSI, and 0.55 for SSI vs. Standardized Precipitation Evapotranspiration Index (SPEI). Similarly, in the Lake Victoria Region (LVR), GGDI vs. SSI was 0.51 and SSI vs. SPEI was 0.55, but in the Bahr-el-Ghazal Region (BER), GGDI vs. SSI was 0.61 and SSI vs. SPEI was 0.27 during the whole research period with varied lag durations ranging from 1 to 6 months. Thus, the propagation of drought (i.e., meteorological, agricultural, and groundwater drought) dynamics has the potential to reshape our understanding of drought evolution, which could lead to early drought forecasting across the NRB and similar climatic regions.

Power Data Access Viewer-Based Meteorological Drought Analysis and Rainfall Variability in the Nile River Basin

Meteorological drought poses a frequent challenge in the Nile River basin, yet its comprehensive evaluation across the basin has been hindered by insufficient recorded rainfall data. Common indices like the standard precipitation index, coefficients of variation, and precipitation concentration index serve as pivotal tools in gauging drought severity. This research aimed to assess the meteorological drought status in the Nile River basin by using the Power Data Access Viewer product rainfall data. Bias correction procedures were implemented to refine the monthly rainfall data for Bahirdar, Markos, Nekemt, and Muger stations, resulting in notable improvements in the coefficient of determination (R2) that were increased from 0.74 to 0.93, 0.72 to 0.89, 0.71 to 0.96, and 0.69 to 0.84, respectively. The average spatial distribution of drought in the Nile basin was classified as extremely wet (3.81%), severely wet (9.01%), moderately wet (7.36%), near normal (9.97%), moderately drought (21.20%), severely drought (17.11%), and extremely drought (31.54%). Approximately 10.33% of the Nile River basin was situated in regions characterized by high rainfall variability, while around 21.17% was located in areas with a notably irregular precipitation concentration index. Overall, this study sheds light on the prevailing meteorological drought patterns in the Nile River basin, emphasizing the significance of understanding and managing these phenomena for the sustainable development of the region.

Impacts of the Grand Ethiopian Renaissance Dam on the Nile River’s downstream reservoirs

The Nile River Basin’s (NRB’s) water resources are vulnerable to hydrologic alteration projects. Construction of the Grand Ethiopian Renaissance Dam (GERD), a hydroelectric power project on the Blue Nile, is expected to improve living standards in Ethiopia and contribute to the country's sustainable development. However, the effects of the GERD on water resources of downstream countries (Sudan and Egypt) have been a source of concern. In this study, eight types of remote sensing data and products were used to assess the impacts of the GERD reservoir’s filling process on Ethiopia’s, Sudan’s, and Egypt’s surface water resources. Specifically, spatiotemporal variability in surface area, volume, rainfall, and water storage for five reservoirs located in Ethiopia (GERD), Sudan (Roseires and Merowe), and Egypt (Lake Nasser and Toshka) for the period 2013–2022 were examined. Results indicate that (1) the GERD reservoir’s three filling phases started in July 2020, July 2021, and August 2022, respectively, (2) at the onset of these three phases, the GERD reservoir covered an area (volume) of 110 ± 7 km2 (1.87 ± 0.07 km3), 233 ± 31 km2 (4.30 ± 0.48 km3), and 544 ± 126 km2 (11.79 ± 2.18 km3), respectively, (3) a reduction in the GERD reservoir’s area (24–49 %) observed at the end of the first two fillings is attributed to enhanced infiltration and evaporation rates at the GERD site, (4) no significant changes were observed in the Roseires and Merowe reservoir’s surface areas, although both Nasser and Toshka reservoirs saw a slight increase in surface area during the investigated period, (5) the observed increase in water storage over the five reservoirs is attributed mainly to increased rainfall rates (6–10 %) and heavy flooding during the GERD filling period, and (6) if the GERD filling continues at the similar rates for an additional four years during drought periods, Egypt's Nile water allocation might be reduced by 35.47 ± 2.29 % (16.57 ± 1.07 km3), which could translate into an agricultural land loss of 33.14 ± 1.81 % each year. This study emphasizes the critical need for Ethiopia, Sudan, and Egypt to work together to effectively and equitably manage the water resources of the NRB.

Effect of watershed characteristics on river flow for the case of two watersheds, Megech and Gumaro, Upper Blue Nile Basin, Ethiopia

Land degradation is a series of problems in Ethiopia’s highlands, particularly in the Upper Blue Nile River Basin reflected in the form of soil erosion and reduce soil fertility from time to time. The effect of watershed characteristics on the river flow of those watersheds was evaluated by distributing a physically based hydrological model known as the soil and water assessment tool model. The model was calibrated for the river flow from 1992 to 2006 and validated for the period from 2007 to 2014. The performance of the model was evaluated based on performance rating criteria, coefficient of determination, and Nash and Sutcliff efficiency on monthly based value, the coefficient of determination (R2) and Nash–Sutcliffe coefficient was greater than 0.6 and 0.5 for all scenarios on both watersheds, respectively. The land-use land-cover change scenario, the climate characteristics, and the slope change scenario was developed, from those analyses, it was found that has been a substantial decrease or increase in forest land, shrubland, grassland, and expansion of agricultural land. The mean annual streamflow of 2010 LULC decreased by 1.44% for 2010 from 2003 LULC and 5.23% for 2018 from 2010. Because of reduced cultivated land from 2010 up to 2018 and increased grassland and plantation in the Megech watershed and 2010 LULC decreased by 0.9% for 2010 from 2003 LULC and 2.04% in 2018 from 2010. This distributed physically based hydrological model has been applied for the evaluation of physical catchment characteristics with significant differences which was Cropland for Megech and Gumaro watersheds which were 67.28% and 61.5%, respectively, for the 2003 LULC, 64.94% Megech, and 58.89% for Gumaro watershed for 2010LULC and 51.95% for Megech and 42.12% for Gumaro watershed, similarly, Eutric Cambisols were covering large areas for both watersheds.

The strategic significance of Ethiopia's hydroelectric energy exports on Horn of Africa regional integration

ABSTRACT This article seeks to explore the compelling strategic impact of Ethiopia's hydroelectric energy exports on the regional integration of the Horn of Africa. The study employed a qualitative research approach that impeccably integrated primary and secondary data sources. The study shades light on the extensive implications of Ethiopia’s energy exports on socio-economic, political, and security dimensions. Economically, these exports foster a sense of mutual reliance among neighboring states, pooling resources for collective development, expanding regional markets, and driving industrialization. Socially, the initiative cultivates invaluable people-to-people relationships among communities with interconnected fates and destinies. From a security standpoint, it actively engages in diplomatic strategies to avert water-related tensions and emphasizes cooperative approaches. Politically, the exportation of hydroelectric energy is poised to significantly redefine the existing power dynamics in the Horn of Africa, sparking transformative collaboration and integration at a regional level. Furthermore, Ethiopia's hydroelectric energy will decisively reshape the competitive landscape related to shared water resources in the Nile River basin. However, the realization of these initiatives hinges on effective reservoir management and responsible hydroelectric energy exports.

Impact-based flood forecasting in the Greater Horn of Africa

Abstract. Every year Africa is hit by extreme floods which, combined with high levels of vulnerability and increasing population exposure, often result in humanitarian crises and population displacement. Impact-based forecasting and early warning for natural hazards is recognized as a step forward in disaster risk reduction, thanks to its focus on people, livelihoods, and assets at risk. Yet, the majority of the African population is not covered by any sort of early warning system. This article describes the setup and the methodological approach of Flood-PROOFS East Africa, an impact-based riverine flood forecasting and early warning system for the Greater Horn of Africa (GHA), with a forecast range of 5 d. The system is based on a modeling cascade relying on distributed hydrological simulations forced by ensemble weather forecasts, link to inundation maps for specific return period, and application of a risk assessment framework to estimate population and assets exposed to upcoming floods. The system is operational and supports the African Union Commission and the Disaster Operation Center of the Intergovernmental Authority on Development (IGAD) in the daily monitoring and early warning from hydro-meteorological disasters in eastern Africa. Results show a first evaluation of the hydrological reanalysis at 78 river gauging stations and a semi-quantitative assessment of the impact forecasts for the catastrophic floods in Sudan and in the Nile River basin in summer 2020. More extensive quantitative evaluation of the system performance is envisaged to provide its users with information on the model reliability in forecasting extreme events and their impacts.

Geochemical Characterization of Sedimentary Materials (Limestone, Gypsum, Coal, and Iron Ore) along the Nile River Basin, South Wollo, Ethiopia

Sedimentary rocks are produced by the weathering of preexisting rocks and the subsequent transportation and deposition of the weathering products. Among the sedimentary rocks, especially limestone is a crucial raw material for cement production. The purpose of this study was to characterize the valuable industrial raw materials, limestone, gypsum, clay, coal, and iron ore, along with the Nile River basin. For sample collection, a random sampling method was applied. Different analytical methods were carried out for complete oxide analysis such as LiBO2 fusion, HF attack, and gravimetric, calorimetric, and atomic absorption spectroscopy (AAS). The percentages of oxides detected in this study are in the range of acceptable values (high content of CaO ranging from 47.3 to 50.4% and less content of SiO2 ranging from 8.72 to 11.24%) for good proposal as a potential raw material for cement production. The most dominant and wide-range coverage of limestone along with the Nile basin, particularly near Arsema Monastery, was found as matured limestone. The petrographic analysis of gypsum, sandstone, and clay samples indicated that all the samples taken from Wegidi revealed that the high percentage of gypsum ranges from 90 to 95%. Sandstone is dominantly preset in Kelala to Jamma road along with Beto River with high content of SiO2 ranging from 61 to 95%. The results of this study indicate that the treated coal samples are relative to high calorific value, fixed carbon, and low ash content. Coal and iron ore from Jamma revealed that high calorific value is 4929.24 and hematite content is 52.2, respectively. The result of this study revealed that a huge amount of limestone reservoir is detected in Borena Wereda, Amhara, Ethiopia.

Assessing Future Precipitation Patterns, Extremes and Variability in Major Nile Basin Cities: An Ensemble Approach with CORDEX CORE Regional Climate Models

Understanding long-term variations in precipitation is crucial for identifying the effects of climate change and addressing hydrological and water management issues. This study examined the trends of the mean and four extreme precipitation indices, which are the max 1-day precipitation amount, the max 5-day precipitation amount, the consecutive wet days, and the consecutive dry days, for historical observations (1971–2000) and two future periods (2041–2060/2081–2100) under RCP2.6 and RCP8.5 emission scenarios over the Nile River Basin (NRB) at 11 major stations. Firstly, the empirical quantile mapping procedure significantly improved the performance of all RCMs, particularly those with lower performance, decreasing inter-model variability and enhanced seasonal precipitation variability. The Mann–Kendall test was used to detect the trends in climate extreme indices. This study reveals that precipitation changes vary across stations, scenarios, and time periods. Addis Ababa and Kigali anticipated a significant increase in precipitation across all periods and scenarios, ranging between 8–15% and 13–27%, respectively, while Cairo and Kinshasa exhibited a significant decrease in precipitation at around 90% and 38%, respectively. Wet (dry) spells were expected to significantly decrease (increase) over most parts of the NRB, especially during the second period (2081–2100). Thereby, the increase (decrease) in dry (wet) spells could have a direct impact on water resource availability in the NRB. This study also highlights that increased greenhouse gas emissions have a greater impact on precipitation patterns. This study’s findings might be useful to decision makers as they create NRB-wide mitigation and adaptation strategies to deal with the effects of climate change.

Climate change and its impact on streamflow in the upper Blue Nile River Basin, Ethiopia

Climate change and its impact on streamflow in the upper Blue Nile River Basin, Ethiopia