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.

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.

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.

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.

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.

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.

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.