PICO
PICO: Mon, 28 Apr | PICO spot A
Clean water availability is crucial for ensuring sufficient water of appropriate quality to meet both human and ecosystem needs. Recent research underscores the significance of water quality as a critical factor limiting water availability for sectoral uses. Water quality is a cornerstone of the Sustainable Development Agenda, intersecting with nearly all Sustainable Development Goals (SDGs). Specifically, SDG Target 6.3 outlines an ambitious vision: “By 2030, improve water quality by reducing pollution, eliminating dumping, and minimizing the release of hazardous chemicals and materials; halving the proportion of untreated wastewater; and substantially increasing recycling and safe reuse globally.”
To monitor progress toward this target, SDG Indicator 6.3.2 serves as a key metric, tracking the percentage of water bodies that achieve “good” ambient water quality. This designation refers to levels of dissolved oxygen, salinity, nutrients (total nitrogen – TN and total phosphorus – TP), and acidity that do not compromise ecosystem or human health. However, significant data gaps pose a major challenge, particularly in Africa, where assessing both current conditions and future trajectories remains difficult, hindering efforts to fully understand the severity and extent of water quality deterioration across the continent.
The emergence of large-scale water quality models offers a potential solution to this challenge. These models provide extensive geographic coverage and sufficient spatial resolution to simulate water quality gradients along river networks. For instance, a continental-scale water quality model for Africa was developed to simulate TN and TP loads and concentrations at a daily time step. Using this model, critical areas and hotspots of TN and TP pollution were identified for the period 2017–2019, based on United Nations Environment Programme (UNEP) thresholds for assessing SDG Indicator 6.3.2. According to UNEP’s criteria, a water body is classified as having “good ambient water quality” if at least 80% of monitored values meet the specified thresholds. The model estimates that 44% of African rivers fail to meet the threshold for TP, while 15% fail to meet the threshold for TN. When both TN and TP are considered together, 34% of rivers do not qualify as having “good ambient water quality.” Geospatial analysis highlights pronounced nutrient pollution hotspots in North Africa, the Niger River Delta, the Nile River Basin, the Congo River Basin, and specific areas in Southern Africa. These regions are strongly associated with high inputs of fertilizers, manure, and wastewater discharge.
These findings, along with the generated data augment the UN Environment Global Environment Monitoring System for Freshwater (GEMStat) database, offering a tool to monitor SDG target 6.3 progress in Africa and project potential outcomes by 2030, especially in areas where little or no information are available on whether water quality is suitable to support sustainable development, despite its fundamental importance. For instance, by highlighting areas that do not qualify as having “good ambient water quality,” these results provide insights for African national policy and decision makers to prioritize remediation efforts, develop targeted policies, interventions, and regulatory frameworks to improve water quality.
How to cite: Nkwasa, A.: Perspectives on African water resources with a focus on ambient river water quality, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5203, https://doi.org/10.5194/egusphere-egu25-5203, 2025.
Future climate changes will alter the geographic locations that are environmentally suitable for malaria transmission. The primary driver for these shifts is often considered to be the thermal constraints and dependencies of both the Anopheles mosquitoes that act as malaria vectors and of the Plasmodium spp. malaria parasites themselves. The availability of surface water for vector breeding sites is also a critical requirement for malaria transmission; without surface water bodies, there would be no malaria. However, continental scale analyses typically lack any representation of hydrology, instead relying on simple rainfall thresholds that are a poor proxy for water body availability.
Here we incorporate more robust estimates of breeding site availability into estimates of areas of malaria suitability across Africa. We go beyond the use of a single hydrological model by presenting a multi-model, multi-scenario ensemble of global hydrological models and global climate models, weighted based on model performance when applied to preindustrial (i.e., pre-intervention) conditions. We then use this ensemble to estimate changes in malaria transmission season length across Africa.
Including hydrology results in a much more complex pattern of malaria suitability across Africa and identifies river corridors as foci of endemic malaria. This is particularly important given the concentration of human populations around such river corridors. Models predict a net decrease in areas environmentally suitable for malaria transmission from 2025 as the climate warms and dries, though the geographical locations of suitability shift. Notable decreases in length of transmission season are observed across West Africa. Conversely, increases are observed in the Ethiopian highlands, in Lesotho and also along waterways through South Africa, particularly the Orange River. Compared with models that use rainfall as a proxy for water body availability, future malaria suitability changes cover a smaller area, but are associated with greater changes in season length. Hydrologically-informed estimates are also more sensitive to the choice of emissions scenario.
Despite the net decrease in suitable areas, the projected growth in human population means that the number of people living in malaria suitable areas will increase by over 80 million to 2100. Including hydrology emphasises this increase: the number of people estimated to live in a potentially malaria endemic area (with a transmission season of over nine months) by 2100 will be over four times greater than estimated by rainfall driven models. However, we note that malaria is a complex disease and driven by more than climate alone.
How to cite: Smith, M., Willis, T., Mroz, E., James, W., Klaar, M., Gosling, S., and Thomas, C.: Hydrologically-informed estimates of future malaria suitability in Africa, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2899, https://doi.org/10.5194/egusphere-egu25-2899, 2025.
Precipitation and hydrological processes are important drivers of water quality, as they regulate the transport of nitrogen, as well as other substances, through various flow paths, including surface runoff, subsurface and groundwater flow. Climate change, in combination with land use and management changes, will likely affect nitrogen concentrations in rivers and streams, with potential consequences for aquatic ecology and the suitability of water for drinking, agricultural and industrial use. Understanding drivers of nitrogen concentrations can help to improve our ability to predict the impact of future changes on water quality. This study presents an overview of the current knowledge on nitrogen and drivers of spatiotemporal patterns in African rivers and streams and identifies avenues for future research.
Data on nitrogen concentrations were extracted from 243 peer-reviewed studies conducted in sub-Saharan Africa, covering 32 out of 48 countries. Differences were observed between sites characterised by different land use types, with urban sites having highest median total nitrogen and nitrate concentrations (3.9 and 1.2 mg N L−1, respectively), most likely resulting from wastewater discharge. Seasonality influences nitrogen concentrations, showing higher or lower concentrations during the wet season indicating increased inputs or dilution processes, respectively, depending on the nitrogen compound and land use type. These findings highlight the importance of having a thorough understanding of nitrogen transport and transformation processes. Yet, compared to other continents, only few studies investigated these processes in African rivers and stream. Furthermore, only very few long-term (> 8 years) studies are available, impeding the analysis of trends in nitrogen concentrations alongside changes in climate and land cover. To strengthen the knowledge base and improve our ability to predict climate and land use change impacts on water quality, long-term monitoring as well as in-depth research on the underlying processes are required, also covering those parts of Africa, which are currently understudied.
How to cite: Jacobs, S. and Breuer, L.: Spatiotemporal patterns in nitrogen concentrations in African rivers, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5537, https://doi.org/10.5194/egusphere-egu25-5537, 2025.
Despite their crucial role in water management and hydropower generation, African dams are often overlooked in global dam research. This study examines the geographic distribution and characteristics of large dams in Africa, resulting in a newly compiled database of 1047 large dams with a collective storage volume of 948.7 km³, representing 29% of the continent’s annual discharge. Considering the critical impact of sediment retention on downstream rivers and coastal systems, we estimated the total sediment retention by these large dams. To do this, we applied Brune’s (1953) widely used relationship between trapping efficiency (TE) and the ratio of a reservoir’s storage capacity (C) to its average annual water inflow (I). Storage capacity data were sourced from our database, while a 1 km-gridded runoff dataset provided the average annual water inflow. We then linked the calculated trapping efficiencies with sediment yield data for Africa, and we accounted for the sediment cascade and interdependencies between dam catchments. For 616 dams, representing 98% of the total storage volume, sufficient data allowed us to estimate total sediment retention at 459.9 Megaton per year (Mt yr⁻¹). Significant reductions in land-to-sea sediment fluxes were observed for the Mediterranean Sea (197.6 Mt yr⁻¹), Indian Ocean (74.5 Mt yr⁻¹) and Gulf of Guinea (56.6 Mt yr⁻¹), with additional reductions to the North Atlantic Ocean (42.0 Mt yr⁻¹), South Atlantic Ocean (27.6 Mt yr⁻¹), and within endorheic basins (61.5 Mt yr⁻¹). Our estimates are consistent with reported data at catchment level, and comparable to sediment retention in major river basins such as the Yangtze and Pearl Basins, though slightly lower. Our findings highlight the increasing importance of catchment management and restoration. As 40% of electricity in Africa south of the Sahara is generated from hydropower and irrigation water supply becomes increasingly important, mitigating storage capacity losses is essential, especially in light of climate change intensifying the hydrological cycle, leading to higher evaporation losses and higher sediment yields.
How to cite: Annys, S. and Frankl, A.: Sediment retention by large dams in Africa, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10776, https://doi.org/10.5194/egusphere-egu25-10776, 2025.
Southern Africa is a water-stress hot spot, and is projected to become significantly warmer and likely also drier under low mitigation futures, increasing the risk of devastating droughts. There is increasing concern about water and food security in southern Africa, due to potentially unprecedented climate change impacts on water resources and ecosystems, and limited adaptation options in this water-stressed region. South Africa’s Gauteng Province with more than fifteen million inhabitants is the economic hub of the country and highly vulnerable to the occurrence of multi-year droughts, one of the biggest disasters risks South Africa needs to prepare for in a warmer world.
The Integrated Vaal River System (IVRS), west of the Lesotho Drakensberg in the South African interior, connects several mega-dams to secure the water supply of the Gauteng Province. The alarming low water level (~25%) of the Vaal dam after a period of drought culminating in the El Niño drought of 2015/16 provided early warning that water security of the Gauteng Province may be directly and severely compromised in a changing climate. Potential evapotranspiration will increase as consequence of a strong regional warming, and in the presence of unprecedented future multi-year droughts the risk exists that the water demand in the Gauteng Province will exceed available water resources within the IVRS under future climate change.
This raises the question if under ongoing climate change the natural hydrological system (without considering water transfers between dam catchments) can maintain dam levels in South Africa’s eastern mega-dam region. To answer this question, the aim of this study is to quantify future water balance changes of several dams under changing climate conditions using the Jena Adaptable Modelling System (JAMS), a software framework for component-based development of environmental models. For this purpose, we built process-based hydrological models for several dam catchments. An ensemble of high-resolution regional climate change projections is subsequently used as forcing, to generate future hydrological projections. The applied regional climate projections will include the CORDEX-CORE Africa ensemble and newly generated projections from regional climate models (CCAM and REMO-NH) forced with CMIP6 global climate projections. The analysis of projected changes in hydrological system components (precipitation, evapotranspiration, runoff) provides probabilistic estimates of the occurrence of a regional climate change tipping point - when the natural water supply can’t longer achieve the critical threshold of storage capacity of the mega-dams which supply South Africa’s Gauteng Region.
The research is part of the “Water security in Africa – WASA” programme, project WaRisCo, which deals with water risks and resilience in urban-rural areas in southern Africa and the co-production of hydro-climate services for an adaptive and sustainable disaster risk management.
How to cite: Biskop, S., Kralisch, S., Schreiter, F., Zander, F., Weber, T., and Engelbrecht, F.: Hydrological projections for water risk assessment in South Africa’s eastern mega-dam region, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13398, https://doi.org/10.5194/egusphere-egu25-13398, 2025.
Climate change is expected to significantly impact hydropower generation in Southern Africa, particularly for small-scale producers. The objective of this study was to investigate the impacts of climate change on small-scale hydropower potential for the Pungwe B hydroelectric project. The methodology combined hydro-meteorological data, 15 CMIP6 GCMs' climate projections, statistical analyses (Mann-Kendall, Sen's slopes), and HEC-HMS hydrological modelling to simulate streamflow. The impacts of climate change on hydropower potential were determined using trends analysis and Power Potential Duration Curves (PPDC). The downscaled NEX-GDDP-CMIP6 data was processed and analysed using Python programming, employing bilinear interpolation for spatial downscaling and mean bias correction to ensure data consistency and accuracy. The rainfall data from the NEX-GDDP-CMIP6 (NASA Earth Exchange Global Daily Downscaled Projections) was used in hydrological modelling to simulate streamflow and assess climate impacts on hydropower. The HEC-HMS model performed satisfactorily in simulating streamflow with acceptable accuracy (NSE = 0.57, RMSE = 0.70, PBias = 4.25%). Future temperature trends show significant increases under all SSP scenarios (SSP1.26, SSP2.45, SSP5.85), with positive z-test statistics and p < 0.05. The hydropower potential results indicate distinct trends across different Shared Socioeconomic Pathways (SSPs). Under SSP1 (Sustainability), characterized by low population growth, high economic growth, and a focus on sustainability and equality (SSP1.26), a significant majority (80%, or 12 out of 15) of Global Climate Models (GCMs) predict increases in hydropower potential. In contrast, under SSP2 (Middle of the road), marked by medium population growth, medium economic growth, and a continuation of current trends (SSP2.45), a substantial proportion (87%, or 13 out of 15) of GCMs predict declines. Similarly, under SSP5 (Fossil-fuelled Development), characterized by low population growth, high economic growth, and a focus on fossil fuel development (SSP5.85), a majority (73%, or 11 out of 15) of GCMs also predict declines in hydropower potential. ACCESS-CM2 and HadGEM models show the largest declines (-27 MW), while INM-CM5 predicts increases across all scenarios. Hydropower potential predictions varied by Equilibrium Climate Sensitivity (ECS): High ECS groups consistently predicted decreases (with a few exceptions), medium ECS groups showed mixed trends, and low ECS groups predicted increases. These findings imply that climate change will likely have a negative impact on hydropower potential in the region with the degree of impacts dependent on the magnitude of climate change as represented by ECS. Overall, the study highlights climate change's uncertain impacts on hydropower, stressing need for adaptive management and improved climate models.
Keywords: ECS, SSP; HEC-HMS; CMIP6, Power Potential Duration Curve, NEX-GDDP-CMIP6.
How to cite: Muzava, M., Rwasoka, D. T., Mhizha, A., and Gumindoga, W.: Climate change impacts the small-scale hydropower potential for the Pungwe B hydropower scheme in Zimbabwe using a multi-model climate ensemble., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16015, https://doi.org/10.5194/egusphere-egu25-16015, 2025.
Waterlogging - a phenomenon that leads to poor soil aeration when excess soil water displaces air from the soil - is a critical challenge in heavy clay agricultural soils in humid and sub-humid climates. The resulting air deficit in the root zone inhibits crop growth by impairing root function and reducing transpiration, ultimately affecting crop yields. Agroecological conditions favouring waterlogging, such as the presence of vertisols, intense rainfall and gentle to flat slopes, are prevalent across the main agricultural regions of Ethiopia. In a previous analysis of cropland quality (Wakjira et al., 2024), it was identified that land suitability for cereal crops like wheat is limited especially in the humid parts of the country, highlighting the potential limitations posed by waterlogging. In this study, we conduct a detailed agrohydrological analysis to characterize waterlogging conditions across the rainfed agricultural landscape of Ethiopia. We utilize high-resolution climate, soil and elevation data to simulate root zone water balance components, particularly soil moisture at a daily time step, using a curve number-based hydrological model. We quantify and map waterlogging magnitude and duration at 1x1 km grid scale for the period 1981-2010.
Results indicate that hyper-humid areas experience severe waterlogging with an average air deficit of up to 90%, i.e., the root zone is only 10% aerated. An estimated 9% of the rainfed agricultural region experiences air deficit exceeding 50%, lasting for a total duration of about 65 days per year on average. This suggests that proper remedial measures, for example proper seedbed preparation, field drains, and selection of waterlogging-tolerant variety crops could significantly contribute to bridging the yield gaps in these regions of Ethiopia. In our analysis, we evaluate the potential of improved soil drainage to enhance crop yields across the study area, using empirical relations derived from existing paired yield measurements from well-drained and waterlogged conditions. This research provides critical insights to farmers, planners, policymakers, and decision-makers on the urgent need for agricultural soil drainage in waterlogging-prone areas - a challenge that currently receives insufficient attention.
Reference
Wakjira, M. T., Peleg, N., Six, J., and Molnar, P.: Current and future cropland suitability for cereal production across the rainfed agricultural landscapes of Ethiopia, Agric. For. Meteorol., 358, 110262, https://doi.org/10.1016/j.agrformet.2024.110262, 2024.
How to cite: Molnar, P., Wakjira, M., and Descheemaeker, K.: Assessing waterlogging conditions across Ethiopia’s rainfed agricultural landscape, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15183, https://doi.org/10.5194/egusphere-egu25-15183, 2025.
High-resolution accurate and timely rainfall estimates are essential in many hydrological applications, ranging from flood early warning to urban water management, and essential in many agricultural services. However, many regions in the world, predominantly in the Global South, lack sufficient coverage from dedicated ground-based rainfall sensors such as weather radars and rain gauge networks, and thus have to rely on satellite rainfall products. These products, however, have the downside that their spatial or temporal resolution is often too low for hydrological applications at the kilometer scale. Moreover, many of these products have limited accuracy with regards to measuring near-surface rainfall, especially in the tropics.
An ‘opportunistic’ alternative for high resolution near-surface rainfall estimates comes from the signal attenuation experienced by commercial microwave links (CMLs) in cellular communication networks. When it rains, the radio signal between two cell phone towers is (partially) attenuated, and this rain-induced attenuation can be used to infer the average rainfall intensity along the path. Typically, every 15 minutes the minimum and maximum received signal levels are stored in network management systems by mobile network operators for quality monitoring purposes. Based on these signal levels it is possible to estimate path-averaged rainfall intensities, which can be interpolated to produce high-resolution rainfall maps. Several studies have already shown the potential of this opportunistic measuring technique on the African continent, though most with a relatively small CML data set.
In this study we investigate the use of several thousands of CMLs in Nigeria, predominantly located in heavily urbanized areas across the country. We compare the path-averaged rainfall intensities from these CMLs to the few rain gauges in the area, and quantify the uncertainty range in such a dense CML network. We do a similar comparison by comparing interpolated rainfall maps from CMLs to available gridded (satellite) rainfall products on a seasonal basis. As such, we show the added value and the associated uncertainties in measuring rainfall using this opportunistic source of rainfall estimation in a region that typically lacks this hydrometeorological information.
How to cite: Droste, A., Walraven, B., Overeem, A., Priebe, J., Tricarico, D., and Uijlenhoet, R.: Quantifying precipitation estimates and its uncertainty from a dense Commercial Microwave Link network in Nigeria , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16960, https://doi.org/10.5194/egusphere-egu25-16960, 2025.
Sub-Saharan West Africa is among the regions with the highest climate risk, especially the semi-arid Sahel region which is characteristically a climate hotspot. The Sahel lies at a large latitudinal gradient of mean temperature and precipitation. Therefore, even small variations in the seasonal meridional migration of the Intertropical Convergence Zone (ITCZ) lead to drastic hydro-climatic shifts, such as pronounced drought or increased flood risk --- with severe socio-economic consequences. Densely populated and rapidly growing urban areas, such as Dakar, Senegal, with many informal settlements that have limited adaptation capacity, are disproportionately affected by intense rainfall events. These often lead to flash floods and consequently pose a threat to human lives and infrastructure.
In a future climate, research suggests that the frequency of extreme weather associated with mesoscale thunderstorm, or convective, systems (MCS) will increase and hence improved warnings are required. However, the sparseness of observational data in the region makes reliable prediction of the initiation and evolution of MCS near impossible. Also, forecasts from numerical weather models often exhibit low skills in this region. For the improvement of risk preparedness, short-term prediction based on statistical inference from observational data referred as 'nowcasting' at a lead time of 1-6 hours, is a promising option that can outperform dynamical models. In the current study a new high-resolution observational network for MCS is described. The automatic weather station (AWS) network, currently consisting of 14 multi-variable stations including atmospheric and soil variables, sends data at 1-min resolution to a data cloud through the local mobile network. Within the project "High-resolution weather observations east of Dakar (DakE)" additional 60 low cost weather sensors and 12 flood sensors have been installed. This network of stations will contribute to the understanding of sub-mesoscale (100m-10km) features that are typically under-resolved by a typical operational network and under-represented in numerical models.
How to cite: Bashiru, Y. and the Yahaya Bashiru: Studying monsoonal convective extremes at high resolution in the Dakar region, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19975, https://doi.org/10.5194/egusphere-egu25-19975, 2025.
Sahelian Africa is increasingly exposed to extreme hydrological events. Both fluvial and pluvial floods are becoming more severe and frequent, posing significant new threats to the livelihoods of local communities. To enhance resilience to floods, the development of effective operational tools for assessing risk and supporting decision-making is crucial. When it comes to pluvial floods, the first step towards this goal is to improve the understanding of extreme daily and sub-daily precipitation events and their spatial patterns in the target areas. Within the SLAPIS Project framework, this work does so for the Sirba river basin (Burkina Faso and Niger) proposing a methodology to address the challenges posed by the scarcity of hydrological data typical of the Sahel region. First, it was assessed how well gridded precipitation products (ERA5, TRMM, TAMSAT) match observed rainfall records. Then, bias correction of selected datasets was performed and tested to evaluate its reliability when spatially interpolated through the whole basin. The Metastatistical Extreme Value Distribution was finally applied to the corrected datasets to investigate the precipitation extremes exploiting the bulk of the available data, unlike classical extreme value analysis, which relies on only a small subset of the data. This procedure resulted in the production of extreme daily and sub-daily precipitation maps with enhanced accuracy and robustness, providing novel information on events that can cause pluvial flooding at the settlement scale. The methodology adopted in this study could be applied to other Sahelian basins where enhanced knowledge of extreme precipitation magnitudes and patterns is needed.
How to cite: Saretto, F. and Ganora, D.: Mapping precipitation extremes for pluvial flood risk management in the Sirba river basin, Burkina Faso., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6328, https://doi.org/10.5194/egusphere-egu25-6328, 2025.
Sebeya catchment in north-western Rwanda has been subject to frequent floods over the years. Despite recent investments in structural measures for flood protection in the catchment, a flood event in May 2023 caused a loss of 97 human lives and damages to around 2,200 buildings. The event urged authorities to invest in additional measures and improve flood management practices to minimize the cost of future flood events. To support the decision-making and planning in flood management practices, this study conducts a flood hazard assessment in the Sebeya catchment using a HEC RAS 1D model based on storm events of 10 to 100-year return periods. A 14 km long reach of Sebeya River was modeled using a 12.5-m resolution digital elevation model (DEM) and under the assumption of steady flow for each daily time step to simulate water surface profiles. The model was calibrated with measurements of 181 daily water levels ) by adjusting Manning’s roughness values and validated against 152 daily water levels ). The RMC-Best Fit Software was then applied to analyze flood frequency and generate flood hazard maps for storm events of 10, 25, 50, and 100-year return periods. The flood hazard maps can support policymakers and decision-makers in integrating flood hazard assessments into planning and development processes, enhancing efforts to effectively mitigate flood hazards in the Sebeya catchment and other regions in Rwanda. Moreover, the results will extend the capacity of the Government of Rwanda to understand flood risk and improve efficiency in investments for flood control measures.
Key words: HEC-RAS 1D; Flood analysis; Steady flow; Flood hazard; Sebeya catchment; Rwanda
How to cite: Hahirwabasenga, J., Inamdeen, F., Nilsson, E., and Bizimana, H.: Flood hazard Mapping and 1D Hydrodynamic Modeling for Sebeya River in Northwestern Rwanda. , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10900, https://doi.org/10.5194/egusphere-egu25-10900, 2025.
The island of Madagascar experiences an average of two tropical storms each year, bringing torrential rains and destructive flooding. Despite their impact, these floods have been poorly documented until now. However, with the rise of mobile telephony, there is a significant increase in available privately captured videos of flooding rivers. Advances in video analysis techniques, such as Large-Scale Particle Image Velocimetry (LSPIV), enable systematic use of these videos to estimate water velocities and flows. This opens new opportunities for more effective monitoring of exceptional floods.
The application of LSPIV techniques to videos taken by amateurs on their smartphones, however, poses a number of methodological problems, notably linked to the stabilization and rectification (orthorectification) of the shots, requiring the identification, in the images, of landmarks with known coordinates (at least four landmarks). The aim of the study, the results of which will be presented, is to demonstrate that it is possible to produce reliable flow estimates from LSPIV processing of videos, using landmarks located in geographic databases (Google map, Lidar surveys) instead of reference points obtained from time-consuming topographic field surveys.
This study is based on the analysis of twenty videos of controlled flows (hydroelectric power station return channels) and five videos of major floods, including four in Madagascar. In all cases, treatments based on approximate reference points were compared with treatments based on landmarks derived from topographic field surveys. Monte Carlo simulations were carried out to assess the levels of uncertainty in velocity and flow estimates associated with the location errors of these landmarks. The study also explored the usefulness of Lidar data for determining the geometry (cross-sections) of river beds, which is essential for estimating discharges.
The results show that the LSPIV approach, even in a degraded context and with controlled uncertainties, can be used to estimate extreme flood discharges in a robust manner. The proposed simplified methodology paves the way for generalizing the use of flood videos for similar environments, providing discharge estimates along with associated uncertainties, assessed using Monte Carlo simulations.
How to cite: Tahinandriambelonandro, A., Gaume, E., and Razakamanantsoa, A.: Assessment of flash flood discharges in Madagascar using vidéos: methodological simplification, sensitivity analysis and feedback, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18515, https://doi.org/10.5194/egusphere-egu25-18515, 2025.
West Africa is acutely vulnerable to climate change, which exacerbates droughts and floods driven
by fluctuations in dry and wet spells. This study investigates the spatiotemporal variability of these
spells across northern Ghana's agroecological zones—specifically the Sudan Savanna, Guinea
Savanna, and Transitional zones—over 40 years (1984–2024). Utilizing daily precipitation data from
the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) and soil moisture
content from NASA’s FLDAS Noah Land Surface Model, we assessed critical indices such as
consecutive dry days (CDD), consecutive wet days (CWD), and drought variability throughout the
rainy season from April to October. Results indicate that while the maximum CDD in the Sudan
Savannah decreased from 14 days in 1984-1993 to 11 days by 2014-2024, it still remains lower
than figures from the previous four decades. Increased CDD was recorded in the Guinea Savannah
and Transitional zones, with 2024 displaying higher values than all prior decades. Notably, the
Standardized Crop Yield Index (SYI) mirrored these fluctuations, showing deficits during the drier
years of 2014-2017, and increased yields during normal years, though significantly impacted by
the severity of drought conditions. These findings underscore the critical need for adaptive
management strategies in agriculture to enhance crop resilience and ensure food security. Given
the implications of these climatic shifts, particularly in the critical planting and growing periods,
effective water management and adaptable farming practices are paramount to mitigate the
socioeconomic risks associated with unpredictable rainfall patterns and varying crop yields in the
region.
How to cite: Obahoundje, S., Tilahun, S., and Schmitter, P.: Evaluating Drought and Dry Spells Effects on Crop Productivity inNorthern Ghana, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-21754, https://doi.org/10.5194/egusphere-egu25-21754, 2025.
Water scarcity, flooding and water pollution are causing challenges to life and development in regions facing high poverty and environmental degradation. The Awash River Basin, which lies in the arid and semi-arid part of Ethiopia, is facing more frequent drought and flooding. River pollution is at high risk from the rapid urbanization and industrial developments. This study aims to identify the state of water security by analyzing the socio-hydrological systems. A digital overlay analysis conducted to identify the state of water security in the different parts of the Basin. A framework is developed and used by adding more socio-hydrological variables attributed to the risks of pollution, drought, and flooding. The water-security status was ranked on the scale to 1 to 6, where 1 represents the highest water-insecure units and 6 the least water-insecure. The results showed areas in the Northwestern headwaters as well as highlands of the Southeastern parts of the Basin are relatively water secure, while the middle range and downstream areas are most water-insecure, areas in between the headwaters and middle part of the Basin are moderately water-insecure. This prioritization of water security helps to engage water security interventions for national and international agencies working in the Basin. The study emphasizes the application of a modified socio-ecological overlay analysis tool for background assessment in risk-based water security planning and development activities.
How to cite: Gebrehiwot, S. G., Grasham, C., Birhanu, B., Legasse, A. M., Tessema, B. G., and Breuer, L.: A risk-based socio-hydrological analysis to prioritize water security in the Awash River Basin, Ethiopia, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11402, https://doi.org/10.5194/egusphere-egu25-11402, 2025.
PICO: Tue, 29 Apr | PICO spot A
The combined impacts of climate change, river basin management, planning and development on the components of the Water-Energy-Food-Environment (WEFE) nexus are different depending on the specific scale and location where they are assessed. This implies that a wide variety of natural and anthropogenic components should be modelled together to obtain a comprehensive picture of the inter-connections and tradeoffs among the WEFE components. The main goal of the high-resolution WEFE modelling framework we will present is to provide a quantitative framework for evaluating nexus indicators at a range of locations and at various space and timescales within a river basin. The framework can then be subjected to different scenarios of projected climate, land-use, and socio-economic developments as well as infrastructure operation policies to aid in robust planning and development for an uncertain future.
The concept developed makes use of a two-level modelling approach to quantify the impacts:
Firstly, based on a concise description of the basin and bulk infrastructures, the strategic Multi-Objective Robust Decision Making model produces basin operating rules (policies) through optimization with respect to several key WEFE objectives. This allows a subsequent screening analysis to assess tradeoffs among the policies and objectives set for the different sectors.
In a follow up phase, a high-resolution WEFE simulation model, is used to quantify in greater detail the impact on a broader set of evaluation indicators. This is done by implementing the basin infrastructure developments and policies in the high-resolution model and simulating under various future climate and socio-economic development scenarios. The high-resolution WEFE model is based on a detailed description of the river basin and relevant infrastructures and simulates the WEFE nexus at high spatial and temporal resolution using the optimized policies coming from the strategic model. The goal is to compute an extended set of WEFE evaluation indicators.
We will present an outline of the above methodology and selected results of the framework implementation in the transboundary Zambezi river basin, as part of the European Union funded GoNEXUS project.
How to cite: Sinclair, S., Arnold, W., Smilovic, M., Giuliani, M., Castelletti, A., and Burlando, P.: An application of complementary strategic level and high-resolution modelling of the Water-Energy-Food-Environment nexus in the transboundary Zambezi watercourse, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11311, https://doi.org/10.5194/egusphere-egu25-11311, 2025.
Landscape is the explicit features carved by natural and human forcing. With the exception of urban areas or large artificial constructions, most landscapes are implicitly regulated by water-energy dynamics. However, there has been limited systematic exploration of the linkage between water-energy dynamics and landscape features. This study employs the Budyko framework (comprising the aridity index and evaporative index) alongside landscape metrics (including discharge, land cover, and topographic features) to explicitly illustrate how water-energy dynamics sculpt the landscape. K-means classification and ANOVA were utilized for classification and significance testing, respectively. The results indicate that the five classes derived from the aridity and evaporative indices generally correspond to conventional climate zones. Furthermore, the landscape metrics associated with these five classes can be statistically identified. Transitioning from the very humid to arid classes, baseflow indexes dramatically decreased from 0.71 to 0.04. Consequently, discharge variability increased from 0.38 to 0.68. In terms of topographic features, the average basin slope decreased along the humidity gradient. Interestingly, the junction angles of the stream network also decreased in accordance with the declining humidity gradient. It is evident that water-energy dynamics serve as a primary control mechanism in shaping the landscape and regulating its evolution. Under the influence of global warming, potential changes in landscape features can be assessed through the lens of water-energy dynamics.
How to cite: Huang, J.-C., Chen, C.-W., Getachew Demeke, G., and Mohinuddin, S.: Does the water-energy dynamics control the landscape characteristics and hydrological responses?, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18978, https://doi.org/10.5194/egusphere-egu25-18978, 2025.
Djibouti, located in the Horn of Africa, experiences limited and sporadic rainfall events, typical of arid climates. Although infrequent, these rainfall episodes can be intense and trigger flash floods, resulting in significant damage to infrastructure and livelihoods. With more than 70% of the country’s population concentrated in Djibouti-ville, mitigating flood risks and ensuring sufficient water resources are key priorities for sustainable development. In response to recurring flood threats, the barrage de l’Amitié was constructed on Oued Oueah to protect Djibouti-ville from catastrophic flood events, a role it appears to fulfill effectively. Beyond its primary function of flood control, the dam also supports agricultural irrigation and potentially improves groundwater recharge, as infiltration in the reservoir area can help replenish Djibouti's aquifers
The barrage de l’Amitié located in a catchment of about 494 km², an area typified by arid conditions and subject to only a few of intense rainfall events each year. These irregular yet powerful events are essential for recharging the local water table (Djibouti aquifer), which is used to supply drinking water to the city of Djibouti. However, monitoring efforts are constrained by the single hydrometric station located roughly seven kilometers upstream from the dam. Because it does not measure flows below one meter, smaller or moderate runoff events go unrecorded. This gap introduces notable uncertainty into hydrological models, which depend on accurate data to represent the full range of runoff processes.
To address these challenges, we used five rainfall–runoff events for calibration and validation of two recognized hydrological models: HEC-HMS and GR4H. HEC-HMS employs the Curve Number (CN) loss method and Clark’s Unit Hydrograph, whereas GR4H applies a reservoir-based conceptual approach to capture surface and subsurface flow processes. In addition to standard calibration, a cross-validation procedure tested the transferability of parameters from one event to another, providing a stricter measure of model robustness given the limited dataset.
In HEC-HMS, several events produced high Nash-Sutcliffe (NASH) coefficients during calibration, demonstrating accurate hydrograph simulations under those specific conditions. Yet, validation runs often returned negative NASH values, suggesting that parameter sets calibrated for one event did not translate well to others in this arid environment. Meanwhile, GR4H also calibrated effectively for most events but showed vulnerabilities when confronted with multi-peak storms or complicated runoff patterns, again reflected by negative NASH values in certain cross-validation scenarios.
Overall, both models highlight the need for enhanced data collection particularly measurements capturing low-flow conditions essential for groundwater recharge and irrigation. Improved rainfall monitoring and stage discharge measurements below one meter would significantly enhance model reliability and better inform water resource strategies for Djibouti-ville. By refining model structures, expanding the observational network, and exploring infiltration processes more thoroughly, water managers could achieve a more holistic understanding of the hydrology in Oued Oueah, ultimately reinforcing flood protection and supporting the region’s agricultural and economic goals.
How to cite: Moussa Omar, G., Paturel, J.-E., Salles, C., Mahe, G., and Jalludin, M.: Challenges in Hydrological Modeling in a Data-Limited Catchment: The case of the barrage de l’Amitié, using HEC-HMS and GR4H, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16491, https://doi.org/10.5194/egusphere-egu25-16491, 2025.
Sustainable and adaptive water management strategies require holistic approaches to understand complex systems, mitigate risks from shifting weather patterns, and manage disruptions to hydrological cycles. The main objective of this study was modeling the impact of climate change on water resources vulnerability using machine learning (ML) and the SWAT model, leveraging CMIP6 Global Climate Models (GCMs) under Shared Socioeconomic Pathways (SSPs) in Upper Gilgel Gibe Watershed, Ethiopia. Six ML models were tested for predicting hydroclimatic events, with Extremely Randomized Trees (ERT) and Categorical Boosting (CatBoost) outperforming others in simulating ensemble climate interactions. The ensemble SWAT model performance demonstrated strong agreement between simulated and observed values, supported by indicators Nash-Sutcliffe efficiency (NSE), coefficient of determination (R²), and Percent Bias (PBIAS) values of 0.93, 0.91, and -1.08 for calibration and 0.94, 0.93, and -2.32 for validation periods respectively, confirming reduced input uncertainties using bias-corrected datasets. A novel Hydrological Vulnerability Index (HVI) framework was developed based on water balances to quantify watershed vulnerability across baseline and future scenarios. The HVI ranges from low to extreme, with lower values indicating resilience to hydrological stress and higher values reflecting severe vulnerability. Baseline assessments revealed 54.03% of areas with low HVI, indicating strong resilience, whereas SSP245 showed a significant decline in low HVI (26.48%) and an increase in extreme HVI (43.45%), driven by higher evapotranspiration and extreme drought conditions. SSP370 showed improved hydrological balances, with low HVI covering 49.21% and extreme HVI decreasing to 10.98%. Conversely, SSP585 displayed a slight increase in low HVI (49.51%) but persistent vulnerabilities, with high HVI (14.01%) and extreme HVI (18.02%) concentrated in key regions. The findings highlight substantial spatial variability in hydrological stress, emphasizing the need of scenario-specific water management strategies. Moderate HVI reflects intermediate vulnerability, while extreme HVI denotes sensitive risks of water scarcity, drought, and flooding, with severe implications for ecosystems and communities. Extreme rainfall events under SSP585 pose additional challenges, such as soil erosion, land degradation, and increased water treatment costs. Effective water conservation measures and adaptive infrastructure are essential to mitigate these risks. Furthermore, increased atmospheric water demand under SSP370 and SSP585 raises the potential for drought, threatening agricultural productivity and ecological health. Precipitation patterns under SSP245 suggest manageable water stress, while SSP370 and SSP585 reveal greater challenges from higher emissions, including extreme rainfall and associated flood risks. The HVI framework integrates climate projections with actionable insights, offering a comprehensive approach to sustainable water management, adaptive infrastructure, and targeted interventions. Hence, innovative policies are critical to address extreme HVIs ensuring resilience against water scarcity and ecosystem degradation. This study underscores the importance of coupling data-driven hydrological analysis with climate responsiveness for effective watershed management and environmental sustainability.
Funding: This Research was carried out under 2025 KICT Research Program (Development of IWRM-Korea Technical Convergence Platform Based on Digital New Deal) funded by the Ministry of Science and ICT.
How to cite: Mengistu, T. D., Kim, M., Chung, I.-M., and Chang, S. W.: Modeling Climate Change Impacts on Historical and Projected Water Resources Vulnerability using Machine Learning and SWAT Model, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2962, https://doi.org/10.5194/egusphere-egu25-2962, 2025.
The Lake Kivu catchment, in the African Great Lakes Region, faces significant hydrological challenges due to unsustainable Land Use Land Cover Changes (LULCC) and climate change. Steep slopes, abundant rainfall, and human-induced activities exacerbate environmental disasters, including floods, landslides, and soil erosion, particularly in flood-prone areas such as the Sebeya River catchment. Over the past decades, the catchment has witnessed notable LULCC, including a decline in forest cover from 26.6% to 18.7% and an expansion of agricultural land from 27.7% to 43% between 1990 and 2000. Subsequent forest recovery to 24.8% by 2020 highlights the impact of Rwanda’s sustainable development initiatives. Rapid population growth and urbanization continue to alter hydrological patterns, increasing surface runoff and reducing groundwater recharge. Climate change projections suggest an intensification of extreme precipitation events, escalating flood risks in the region.
This study aims to enhance understanding of the interplay between LULCC, climate change, and hydrological dynamics in the Lake Kivu basin by addressing critical gaps in streamflow data and applying advanced hydrological modelling techniques. A robust stochastic methodology was developed to fill missing streamflow data, enabling accurate analysis of historical trends and future scenarios. The mesoscale hydrological model (mHM) was employed to evaluate historical impacts of LULCC and to simulate future hydrological responses under various LULC and climate scenarios, integrating data from Global Climate Models (GCMs) and Representative Concentration Pathways (RCPs).
Our findings underscore the importance of addressing data scarcity in hydrological research, particularly in data-sparse regions. This research contributes to sustainable land and water management by providing actionable insights into mitigating hydrological disasters and building resilience against future climate extremes.
How to cite: Kayitesi, N., Guzha C., A., Gerber, L., and Mariethoz, G.: Hydrological Modelling in Data-Sparse Regions: Impacts of Land Use and Climate Change on the Hydrological Cycle in the Lake Kivu Basin, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4422, https://doi.org/10.5194/egusphere-egu25-4422, 2025.
In West Africa, hydrological variability remains poorly understood in many watersheds where observation networks are sparse. After gap-filling discharge time series through earth observation datasets and daily rainfall-runoff modeling, past and future hydro-climatic variability in the upper catchments of the Gambia, Koliba-Corubal, Kayanga-Geba, and Senegal rivers is investigated. CHIRPS rainfall and GLEAM evapotranspiration global datasets are used to simulate runoff in 38 sub-basins over 1981-2023 with the GR4J model. Seven RCM models from CORDEX-Africa are then employed to investigate climate change impacts on river flow under RCP4.5 and RCP8.5 scenarios over 2036-2065. Robust performance observed in 34 basins (KGE > 0.5) confirm the effectiveness of the approach including at a daily time step in poorly gauged basins. A dry period (1981- 1993), followed by two wet periods (1994-2007, 2008-2023) are identified using standardized precipitation index (SPI), standardized streamflow index (SSI) and the non-parametric Mann-Kendall test. Increased variability in extreme flows and a later flood are also observed in some basins. Climate change projections point towards an important decrease in flow in the Senegal river subbasins, reaching up to 70% under both scenarios, compared to the reference period (1986-2015). In the Gambia, Kayanga-Geba and Koliba Corubal subbasins, no homogenous trend is detected with some RCMs leading to a decrease while others, including GDFL and CSIRO circulation models, project an increase in runoff. Understanding non-stationarity in West African basins in the context of climate change is essential to support stakeholders in defining adequate river basin development strategies.
Keywords: Gap filling, Remote sensing datasets, Hydrological Modelling, Hydrological Variability, West Africa, Large Rivers; GR4J, CORDEX-Africa, Climate Change.
How to cite: Ndiaye, P. M., Ogilvie, A., Bodian, A., Descroix, L., Legay, T., and Guillet, R.: Hydrological variability of large rivers in West Africa: gap filling with earth observations and daily rainfall-runoff modelling under climate change, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6308, https://doi.org/10.5194/egusphere-egu25-6308, 2025.
Water security in the Global South is increasingly threatened by rapid socioeconomic changes, including urbanization, population growth, and the expansion of irrigated agriculture. These dynamics not only intensify competition for limited water resources but also amplify vulnerability to climate change impacts. The Sudano-Sahelian region, including the Sokoto Rima Basin (study area) in Nigeria, is particularly sensitive to these pressures, having experienced severe droughts in the 1970s and 1980s. This study adopts a participatory approach, leveraging stakeholder input to develop socioeconomic scenarios within the Shared Socioeconomic Pathways (SSPs) 4.5 and 8.5 frameworks. It projects future water use in the region and evaluates the combined effects of socioeconomic and climate change. While the CMIP6 GCMs agree on a wetter future climate for the region, uncertainty persists regarding the magnitude of these changes. Drivers of socioeconomic changes are better understood due to direct stakeholders involvement. Key findings indicate that by 2050, irrigated land, and population are expected to increase by 470%, and 200% respectively, relative to the reference period (1990–2004). This growth is projected to drive water demand up by 190%, outpacing the anticipated 160% increase in water availability due to climate-driven changes. The results underscore that socioeconomic changes pose a significant risk to water security and must be considered when planning climate change adaptation. Informed by stakeholder feedback, the study highlights adaptation strategies, including the adoption of water-efficient technologies, mechanized irrigation, and advanced seed technologies. Small-scale stormwater harvesting through dam construction is proposed as a viable strategy to conserve water and support municipal supplies during drought periods. This novel participatory based scenario development approach provides valuable insights into managing water resources under concurrent socioeconomic and climate challenges, with implications for policy and planning in water-scarce regions.
How to cite: Muhammad, S. K., Walsh, C., and O'Donnell, G.: Stakeholder-Informed Socioeconomic Scenarios for Water Use Projections: A Novel Approach to Assessing Climate Change Impacts in the Sudano-Sahelian Region, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11114, https://doi.org/10.5194/egusphere-egu25-11114, 2025.
Groundwater plays a key role in providing access to drinking water, especially in semi-arid regions where surface water is scarce or absent for much of the year. In the semi-arid region of southern Madagascar, approximately 2,000,000 people face one of the highest poverty rates in the world, making them particularly vulnerable to climatic hazards. As a result, describing and predicting groundwater dynamics is essential to understand and anticipate drought-related humanitarian crises. How to estimate groundwater recharge in a such poorly documented area?
Our work consisted of comparing two complementary approaches for estimating groundwater recharge. First, the Groundwater Resource Observatory for Southwestern Madagascar was established in 2014 in difficult logistical settings to monitor piezometric level from 16 boreholes located in various hydrogeological systems. This observatory provides long-term piezometric time series at an hourly time step, which were used to calculate recharge following the Water Table Fluctuation (WTF) Method.
Second, a spatial hydrology approach was developed to estimate potential recharge using precipitation and evapotranspiration global products based on remote sensing data. The two approaches were compared, revealing the potential and limits of both. Based on these results, we compare our findings with health outcomes, offering new avenues for research.
How to cite: Berthelin, R., Rakotomandrindra, F. P., Alimohammad Nejad, R., Ollivier, C., Andriamiandrisoa, O. N., Texier, M., Ramananjato, T. B., Oudin, L., Satgé, F., Olioso, A., Fonda, S., and Carrière, S. D.: Groundwater monitoring and modelling, a crucial challenge in a semi-arid and poorly documented region affected by a high poverty rate (southern Madagascar), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17526, https://doi.org/10.5194/egusphere-egu25-17526, 2025.
The Lake Chad Basin (LCB), a critical hydrological system in Sub-Saharan Africa, supports over 40 million people across several countries. Characterized by arid and semi-arid climate, the basin’s water resources are under constant threat from declining precipitation and decreasing natural recharge, over pumping, and transboundary management complexities. The main land uses in the basin are the native vegetation and irrigated areas (together with wetland areas). A 3D ‘quasi steady-state’ regional groundwater flow model of the Chad Formation, based on MODFLOW code, to evaluate quantitative recharge and transboundary water fluxes within the basin, to quantitatively develop abstraction scenarios and further impacts on groundwater, lake and connected rivers was developed. Also, long-term sustainability, under different climatic conditions and water abstraction was simulated.
The basic assumption adopted is that the hydrological conditions during the considered model baseline period (2008-2011) are representative of system functioning. To estimate the natural recharge and for the proposed ‘dry scenario’, the strategy adopted for the simulation was to apply a scaling factor of -10% to the baseline recharge data sets obtained from Modflow run. To meet future demand resulting from population growth, water abstraction increases by 10% in the areas where abstraction currently occurs (baseline).
Obtained simulation for the Quaternary aquifer indicates that the impact of reducing recharge by 10% is much more important for aquifer than increasing water abstractions, an expected output for a large-scale model as the one developed. For specific areas of the basin and model run at greater scale, outputs reveal a different behaviour as limited by contour conditions.
How to cite: Candela, L., Salehi Siavashani, N., and Elorza, F. J.: Numerical Model for Lake Chad Basin Groundwater. Results from simulation of water resources under different climatic and abstraction conditions, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20190, https://doi.org/10.5194/egusphere-egu25-20190, 2025.
Cocoa production in Ghana has long been associated with deforestation and encroachment into protected areas, yet little is known about its water consumption patterns. Although data on cocoa yield and planted areas are available, comprehensive insights into water use by cocoa plantations remain limited. This study, conducted under the Transforming Agrifood Systems in West and Central Africa (TAFS-WCA) initiative by CGIAR, presents an innovative modeling framework to bridge this knowledge gap. By integrating open-access Earth observation data, global geospatial datasets, and the Water Accounting Plus (WA+) framework, the study quantifies water availability and water consumption linked to cocoa production and encroachment-driven activities in the Pra Basin, Ghana's largest southwestern river basin and a critical cocoa production zone spanning approximately 23,200 km² across five regions.
Over the 2004–2020 period, the basin received an average annual rainfall of 1,430 mm, with 88% consumed as evapotranspiration, amounting to a total water consumption of 29 km³/year. Cocoa production accounts for 30% of this total, with monoculture cocoa dominating (84%), agro-protected cocoa contributing 14%, and shaded cocoa consuming just 2%. Notably, agro-protected cocoa, which encroaches on protected areas, constitutes 24% of water consumption in these sensitive zones, with 1.22 km3/year of unauthorised water consumption, posing significant threats to biodiversity conservation. Cocoa water productivity ranges from 0.019 kg/m³ to 0.061 kg/m³, highlighting variability across regions.
These findings underscore the critical implications of agricultural-driven nature loss on water resources and biodiversity, emphasizing the need for sustainable cocoa production practices. The study provides actionable insights to inform policy and guide decision-makers in balancing agricultural development with environmental conservation.
How to cite: Dembélé, M., Tilahun, S. A., and Cofie, O.: Unauthorized Water Consumption and Cocoa-Driven Nature Loss in Ghana's Pra Basin, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4849, https://doi.org/10.5194/egusphere-egu25-4849, 2025.
