Displays

The Trans-African Hydro-Meteorological Observatory (TAHMO) was officially founded as a not-for-profit foundation in 2014. TAHMO has become the largest provider of scientific weather and climate data for sub-Sahara Africa, with over 500 stations in 22 countries, and a goal of 20,000.  The projection for 2020 is to have 800 stations running and reporting.  TAHMO has successfully shown that it is possible to run a high-quality cost-effective observation network in Africa through investing in relationships, strategic innovation in technology, management, and on-the-ground operations.

Technology -TAHMO partnered with METER Group in the co-design of the weather station. Originally, the thought was to develop a very cheap ($200) station, but robustness and accuracy were the driving goals, leading to a station with costs closer to $2000.  Many ideas have been bounced between the two teams and tested in the field in Africa, with no fewer than three generations of technology having been tested.

Operation - Over 90% of TAHMO stations are placed at (secondary) schools. This provides physical and, moreover, social protection. Educational material is provided to engage teachers and students and to encourage them to help out with simple maintenance, such as cleaning.

Financial sustainability - Stations have been funded through projects funded largely by donors and agencies. A large investment by IBM / Weather Underground formed the basis for a rapid expansion of 333 stations. To ensure long-term financial sustainability, TAHMO provides data services to commercial users, wherein the value chain run from raw data to actionable information. For this reason, TAHMO has become part of a network of entities that bridge the gap between weather station and information market. TAHMO provides data to the research enterprise and host governments at no cost.

How to cite: Selker, J., van de Giesen, N., and Annor, F.: Climate Observations in 22 African Countries at 550 locations: the TAHMO network, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11529, https://doi.org/10.5194/egusphere-egu2020-11529, 2020.

Evapotranspiration (ET) or the water vapour flux is an important component in the water cycle and is widely studied due to its implications in disciplines ranging from hydrology to agricultural and climate sciences. In the recent past, growing attention has been given to estimating ET fluxes at regional and global scales. However, estimation of ET at large scales has been a difficult task due to direct measurement of ET being possible only at point locations, for example using flux towers. For the African continent, only a limited number of flux tower data are openly available for use, which makes verification of regional and global ET products very difficult. Recent advances in satellite based products provide promising data to fill these observational gaps.

In this study we propose to investigate the Climate Change (CC) impact on crop water productivity across Africa using ET and crop yield predictions of different crop models for future climate scenarios. Different model outputs are evaluated including models from both the ISI-MIP 2a and 2b protocols. Considering the problem of direct observations of ET being difficult to obtain, especially over Africa, we use ET estimates from several remotely sensed derived products as a references to evaluate the crop models (maize) in terms of magnitude, spatial patterns and variations between models. The crop model results for crop yield are compared to FAO reported crop yields at country scale. The results show a very strong disagreement between the different crop models of the baseline scenario and when compared with ET and crop yield data.  Also, a very large uncertainty is obtained for the climate change predictions. It is hence recommended to improve the crop models for application in Africa.

How to cite: Weerasinghe, I., Chawanda, C. J., and van Griensven, A.: Climate change impacts on crop water productivity in Africa using a multi-model inter-comparison, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-14125, https://doi.org/10.5194/egusphere-egu2020-14125, 2020.

Keywords: Cuvette Centrale, Hydrology, Sediments, Carbon,

The Congo River basin is among the largest Rivers in the world in terms of discharge and drainage area. At the heart of the basin lies the Cuvette Centrale-one of the most extensive wetlands in the world. The increasing pressure on wetland resources continues to threaten the role wetlands play in maintaining water resources and ecological service functions. Therefore, in order to understand the role of the Cuvette Centrale in water resources and ecological service functions linked to the quality of water and life in the basin, we first need to quantify its role in the hydrological, sediment and carbon dynamics. To achieve this aim, we use the Soil and Water Assessment Tool model (SWAT) – modified for tropical environments, in order to analyze the hydrology, sediment and organic carbon fluxes flowing in and flowing out of the Cuvette Centrale of the Congo River basin (CRB). The model was calibrated and validated for the 2000-2006 and 2007-2012 periods respectively by comparing the discharge and sediment output with different data sources (gauging stations and altimetry) at a daily and monthly time step. Then by adapting equations of dissolved organic carbon (DOC) and particulate organic carbon (POC) from literature, we are able to quantify the role of the Cuvette Centrale in the CRB carbon dynamics.The results reveal that the models for hydrology, sediments and carbon can represent both temporally and spatially the exports in a watershed and sheds more light on the important regulatory function of the Cuvette and the need for sustainable land use practices as well as protection of ground water resources  in order to maintain wetland water quantities and quality.

How to cite: Datok, P., Fabre, C., Sauvage, S., Moukandi, G., Paris, A., Dos Santos, V., Laraque, A., and Sànchez-Pérez, J.: Investigating the role of the Cuvette Centrale wetlands in the hydrology, sediment and carbon fluxes of the Congo River basin, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10106, https://doi.org/10.5194/egusphere-egu2020-10106, 2020.

Wetland processes considerably influence the flow regime of the downstream river channel, and are important to consider for a better representation of runoff generation within a basin scale hydrological model. The need to understand these processes lead to the development of a wetland sub-model for the monthly time step Pitman hydrological model. However, previous studies highlighted the need to provide guidance to explicitly estimate the wetland parameters rather than using a trial and error calibration approach. In this study, a 2D hydrodynamic river-wetland model (LISFLOOD-FP) is used to explicitly represent the inundation process exchanges between river channels and wetland systems and thereby inform the choice of Pitman wetland model parameters. The hysteretic patterns of these river-wetland processes are quantified through the use of hysteresis indices. Additionally, the hysteretic patterns are connected with the spill and return flow parameters of the wetland sub-model and eventually with the wetland morphometric characteristics. The results show that there is a consistent connection between the degree of hysteresis found in the channel-wetland exchange processes and the Pitman wetland parameters which are also explicitly linked to the wetland morphometric characteristics. The channel capacity to spill (Qcap) is consistently correlated with the hysteresis found between the channel inflow and the wetland storage volume. This anti-clockwise hysteresis represents the time delay between the inundation and drainage processes. The channel spill factor (QSF), in addition to the inundation processes, is also connected with the drainage processes represented by the wetland storage volume and channel outflow anti-clockwise hysteresis. On the other hand, the parameters of the return flow equation have shown a strong consistent relationship with the channel inflow-wetland storage hysteresis. It has also been observed that the wetland average surface slope and the proportion of the wetland storage below the channel banks are the morphometric characteristics that influence the spill and the return flow parameters of the Pitman wetland sub-model. This understanding has a practical advantage for the estimation of the Pitman wetland parameters in the many areas where it is not possible to run complex hydrodynamic models.

How to cite: Kabuya, P., Hughes, D., Tshimanga, R., and Trigg, M.: Understanding factors influencing the wetland parameters of a monthly rainfall-runoff model in the Upper Congo River basin, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-642, https://doi.org/10.5194/egusphere-egu2020-642, 2020.

In East Africa, wetlands are steadily converted to agriculture for food security reasons. This study analyzed high spatial resolution panchromatic and color photographs in the Anyiko wetland in Kenya to reveal wetland conversions between 1966 and 2018. Socio-economic determinants of land use/cover change are also assessed in the Anyiko wetland. Socio-economic data was collected through a questionnaire survey of 226 households. A CHi- squared Automatic Interaction Detector (CHAID) decision tree approach is utilized to assess determinants of wetlands conversion. The results showed that between 1966 and 2018, the wetland area reduced by 55%, mostly attributed to agricultural development. Households were more likely to cultivate the wetland if they did not harvest papyrus for artisanal products, were male-headed and lacked alternative sources of income. The perceptions that wetland is “wasteland” and conversion to agriculture provides higher net monetary benefit did not influence wetland cultivation. Hence, the conversion of the wetland was determined by the socio-economic status of the households rather than perceptions on its value.

How to cite: Ajwang, R., Vuolo, F., Kipkemboi, J., Kitaka, N., Lautsch, E., Hein, T., and Schmid, E.: Socio-economic determinants of land use/cover change in wetlands in East Africa: a case study analysis of the Anyiko wetland, Kenya, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1154, https://doi.org/10.5194/egusphere-egu2020-1154, 2020.

It is the knowledge of the coming months that can be crucial for the management and control of water reservoirs for hydropower generation or for irrigation. This is particularly important in semi-arid regions of Africa that are characterized by distinctive dry seasons, i.e. where rainfall is limited to few months only. In addition, observation data in Africa are usually extremely sparse and computational power for forecasting systems is difficult to access. We present the spatial disaggregation and bias-correction of the globally available ECMWF’s newest seasonal forecast system SEAS5 and its tailored operational processing to support local water resources management and decision-makers. The forecast horizon is up to 7 month lead time, and our final forecasts have 0.1° spatial resolution. For the retrospective years 1981 till 2016 our ensemble consists of 25 members, while for the ongoing forecasts since 2017 there are 51 members available, allowing probabililistic predictions The performance of the regional prediction system is presented for 1) the Tekeze-Atbara and Blue Nile basins in Eithiopia/Sudan, and 2) the Volta and Niger basins in West Africa. The evaluation against the reference ERA5 data shows significant reduction in biases from the monthly averages as well as consistent and lead-independent forecasts characteristics like wet/dry frequencies. The performance metrices considered comprise accuracy (mean absolute error skill score), overall performance (continuous ranked probability skill score), sharpness (interquantile range skill score) and reliability. The operationalized system provides seasonal predictions each month to support water management on regional and local levels.

How to cite: Kunstmann, H., Lorenz, C., Portele, T., Laux, P., Bliefernicht, J., Salack, S., Gaber, A., and Mohammed, Y.: Seasonal Hydrometeorological Forecasts for Water Managment in West- and Northeast Africa: Development, Operationalisation and Performance of a Regional Prediction System, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-16534, https://doi.org/10.5194/egusphere-egu2020-16534, 2020.

There has been limited research conducted on irrigation potential in Uganda. The existing studies provide a wide number of estimates of irrigation potential for Uganda and thus constrain reliable medium term planning and investment in the subsector. This research was aimed at assessing the potential for irrigation development in Nebbi District, which cover 195,300 km², with a view of guiding planning and strategic investment in irrigation. Irrigation potential was assessed as an aggregation of the land suitability, water requirement and the available water for irrigation for three systems (drip, sprinkler and surface). Land suitability evaluation for the three systems was determined based upon topography and soil characteristics. The FAO CROPWAT model was used to determine the water requirements for the selected crops. Water resources assessment was carried out using rainfall data and the stream flow analysis of the available water resources in the study area. For surface irrigation, no area was classified as highly suitable or moderately suitable. Only 0.03% (48.91 ha) is marginally suitable, 36% (68,445.55 ha) currently not suitable whereas 64% (121,606.33 ha) permanently not suitable. For drip irrigation, 58.7% (111,591 ha) is marginally suitable and 25.8% (49,084 ha) is moderately suitable. Furthermore, 15% (28,492 ha) and 0.5% (989 ha) are currently not suitable and permanently not suitable respectively. There was no area classified as highly suitable under drip irrigation. For sprinkler irrigation, 14.1% (26 815.8 ha) of the area is marginally suitable and 0.03% (48.1 ha) is classified as moderately suitable for sprinkler irrigation. 47.5% (90 291.4 ha) and 38.4 % (72 987.2 ha) of the area is currently not suitable and permanently not suitable respectively. The mean capability index (Ci) for surface irrigation was 36.1 (currently not suitable), 45.4 (marginally suitable) for drip irrigation while sprinkler irrigation Ci was 42.8 (marginally suitable). Crop evapotranspiration (ET_c) for the selected crops (tomatoes, cabbages and onions) varied from 2.46 to 5.76 mm/day; 2.87 to 5.92 mm/day and 2.87 to 4.78 mm/day respectively. The results from water resources assessment revealed that the total catchment yield was 2.69 x 10⁹ m³ which permits irrigation for an area of 141,817.65 ha. The results showed that drip irrigation system was more suitable for the Nebbi district.

How to cite: Kiggundu, N., Bwire, C., and Wanyama, J.: Assessment of the potential for irrigation development in Albert Nile basin: A case study of Nebbi district, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1274, https://doi.org/10.5194/egusphere-egu2020-1274, 2020.

A decline in Lake Chad’s water level has been observed for over two decades. With millions of people relying on the lake, and considering its dynamic behavior, methods for the continuous and spatially distributed retrieval of water quantity and quality parameters are vital for proper monitoring and management initiatives. Here, we propose an integrated approach for drought, chlorophyll-a (Chl-a) and turbidity monitoring in Lake Chad using satellite datasets.

First, we used remote sensing information to constrain drought patterns over the immediate lake environment. Vegetation conditions within and around the lake was used to assess drought conditions in this area. Using Landsat multispectral images obtained between 1999 and 2018, Vegetation Temperature Condition Index (VTCI) was derived and used as an indicator for drought monitoring. Vegetation proportion from WorldView-03 images was used to evaluate the accuracy of methods used to derive VTCI. Obtained results showed that most areas experienced mild drought conditions.

Secondly, we assessed the performance of band algorithms in estimating Chl-a concentrations and turbidity levels from Landsat-8 and Sentinel-2A and 2B images. A two-band semi-analytical Chl-a and turbidity retrieval model was used for estimating the Chl-a concentrations and turbidity levels between 2015 and 2019. Due to the absence of in-situ data, estimates from the extraction models were statistically compared with datasets obtained from WorldView-03. Further inter-comparison of Chl-a and turbidity retrieved from the two sensors was carried out.

This study shows how satellite observations can be used to complement sparse and declining in situ drought, Chl-a and turbidity monitoring networks in this area. Solidifying the importance of remote sensing in areas that are difficult to access or with poor availability of conventional data sources.

How to cite: Lee, S. I. and Buma, W. G.: The Use of Landsat 8 and Sentinel-2 Time Series Data for Monitoring Drought, Chlorophyll-a and Turbidity in Lake Chad, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1886, https://doi.org/10.5194/egusphere-egu2020-1886, 2020.

Semi-arid regions are very challenging environments for rainfall-runoff modelling due to the high spatial variation of rainfall alongside extreme wet and dry periods resulting in distinctly different hydrological conditions within the same catchment. In order to account for the extreme wet and dry periods, a new non-linear rainfall-runoff model has been developed. The non-linear model is capable of capturing the quick recessions observed during the wet periods alongside accounting for very little flows during the dry periods. The ability of the new model was assessed by comparing the linear version with the non-linear version on two nested catchments located within South Africa. The catchments areas are 183 and 328 km² and include 15% and 10% urbanisation respectively. The average rainfall during the wet period (May-Sep) is approximately 130mm per month with the dry period (Jan- Apr and Oct-Dec) averaging less than 35mm per month for the years 2000-2017. To challenge the problem of high spatial variation of rainfall, the fifth generation of ECMWF atmospheric reanalysis of the global climate ERA5 data is used. Both locally collected gauge and ERA5 reanalysis data were compared to show that the ERA5 data set was more capable than the local gauge in rainfall-runoff simulations with performance increases of up to 30\%. When comparing the default linear model and the non-linear model results based on ERA5 data showed the same level of performance for each model. However when flow duration curves and hydrographs were examined results showed that the linear model was not capable of adequately capturing the low flows of the catchment, whilst at the same time overestimating the high flows. Conversely, the non-linear model was capable of capturing the low flows recession and whilst it did also overestimate peak flows it was to a lesser extent than the linear model.

How to cite: Fidal, J. and Kjeldsen, T.: Nonlinear rainfall-runoff modelling of semi-arid regions using ERA5 data, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8214, https://doi.org/10.5194/egusphere-egu2020-8214, 2020.

Climate change threatens vulnerable communities in sub-Saharan Africa who face significant challenges for adaptation. Agriculture provides the livelihood for the majority of population. High-resolution assessments of the effects of climate change on crop production are urgently needed for targeted adaptation planning. In Ghana, next to food needs, agriculture plays an important role on international cocoa markets. To this end, we develop and apply a National Agro-Ecological Zoning system (NAEZ Ghana) to analyze the impacts of high-end (RCP8.5) global warming on agricultural production potentials until the end of this century. NAEZ Ghana uses an ensemble of the CORDEX Africa Regional Climate Model, a regional soil map, to assess development trends of crop production potentials for 19 main crops. Results highlight differential impacts across the country. Especially due to the significant increase in the number of days exceeding high-temperature thresholds, rain-fed production of several food and export crops could be reduced significantly compared to the historical 30-year average (1981-2010). Plantain production, an important food crop, could achieve under climate change less than half of its current potential already in the 2050s and less than 10% by the 2080s. Suitable areas for cocoa production decrease strongly resulting in only one third of production potential compared to today. Other crops with detrimental effects of climate change include oil palm, sugarcane, coffee, and rubber. Production of maize, sorghum, and millet cope well with a future warmer climate. The NAEZ Ghana database provides valuable high-resolution information to support agricultural sector development planning and climate change adaptation strategies. The expansion of irrigation development will play a central role in some areas. This requires further research on Ghana’s linkages between food, water, and energy, taking into account climate and socio-economic changes.

How to cite: Tramberend, S., Fischer, G., and van Velthuizen, H.: RCP 8.5 Ghana. High-end climate change impacts on crop production , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8955, https://doi.org/10.5194/egusphere-egu2020-8955, 2020.

The Kilombero catchment is a meso-scale catchment of 40,240 km² in south central Tanzania and is characterized by overall data scarcity like many other African catchments. The catchment consists of a highly dynamic floodplain system at its centre which is sustained by water from the surrounding uplands. It also contains a Ramsar site giving evidence to its valuable ecosystem and importance concerning biodiversity conservation. However, in the last decades land use and land cover changes (LULCC) accelerated drastically towards an agriculturally-shaped landscape, especially at the fringes of the wetland. The wetland system provides fertile soils, water as well as other water-related ecosystem services. Nevertheless, the increasing pressure on natural resources jeopardizes the sustainability of the socio-ecological system, especially in the face of climate change.

In this study, methods of hydrology, meteorology and remote sensing were used to overcome data-scarcity and gather a sound representation of natural processes in the catchment. The Soil and Water Assessment Tool (SWAT) was applied to represent the hydrological processes in the catchment. We utilized Landsat images from several decades to simulate the impact of LULCC from the 1970s until today. Furthermore, we applied the Land Change Modeller (LCM) to simulate potential LULCC until 2030 and their impact on water resources. To account for climatic changes, a regional climate model ensemble of the Coordinated Regional Downscaling Experiment (CORDEX) Africa project was analysed and bias-corrected to investigate changes in climatic patterns until 2060, according to the RCP4.5 (representative concentration pathways) and RCP8.5 scenarios.

The climate change signal indicates rising temperatures, especially in the hot dry season, which reinforces the special features of this season. However, the changes in precipitation signals among the analysed RCMs vary between -8.3% and +22.5% of the annual mean values. The results of the hydrological modelling also show heterogeneous spatial patterns within the catchment area. LULCC simulation results show a 6-8% decrease in low flows for the LULCC scenarios, while high flows increase by up to 84% for combined LULCC and climate change scenarios. The effect of climate change is more pronounced compared to the effect of LULCC, but also contains higher uncertainties. This study exemplarily quantifies the impact of LULCC and climate change in a data-scarce catchment and therefore contributes to the sustainable management of the investigated catchment, as it shows the impact of environmental change on hydrological extremes and determines hot spots, which are crucial for more detailed analyses like hydrodynamic modelling. The information from this study are an essential part to assist local stakeholders protecting the wetlands integrity on the one hand and to ensure sustainable agricultural practices in order to guarantee food security on the other hand in a catchment that has already changed tremendously and is still target to manifold future plans.

How to cite: Näschen, K., Diekkrüger, B., Evers, M., Höllermann, B., Seregina, L. S., Steinbach, S., Thonfeld, F., and van der Linden, R.: The impact of climate change and land use/land cover change on water resources in a data-scarce catchment in Tanzania, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9287, https://doi.org/10.5194/egusphere-egu2020-9287, 2020.

Miombo woodland is the most widespread tropical seasonal woodland and dry forest formation in Africa covering between 2.7 and 3.6 million km² in eleven countries. Leaf fall and leaf flush during the dry season is a major characteristic feature of the various Miombo species. However, the question on what induces the leaf fall process is by far inconclusive. Different studies indicate either moisture or temperature or both elements as inducers for leaf fall. Knowing what induces leaf fall is important for studying the consequence of e.g., climate change on the Miombo forest. To better understand the driver of leaf fall in Miombo forest we employed a simple remote sensing and statistical analysis approach using long term averages (2009 – 2018) of Land Surface Temperature (LST) of the Miombo forest, various vegetation indices (VI), actual evaporation (E_a), and root zone soil moisture (SM). The vegetation indices (VI) included the Normalised Difference Water Index (NDWI) as indicator of vegetation water content and the Normalised Difference Vegetation Index (NDVI) as indicator of plant photosynthetic activities and leaf cover. Results showed that the NDWI, NDVI, E_a and SM begun to decline immediately following the end of the rainy season in early April while the LST remained relatively constant before it began to decline in May when leaf fall in some Miombo species begins. Hysteresis graphs revealed that vegetation water content (i.e. NDWI) responded quicker to changes in both LST and SM. Furthermore, high rates of decrease in NDWI and NDVI values were observed between July and September the same period when LST increased. This is also the same period when leaf fall intensifies in Miombo forest. Correlation analysis revealed strong season-dependent LST relationship with VI and SM with the rainy season exhibiting strong negative linear correlations (R² = 0.77, 0.91, 0.88; for the NDWI, NDVI and SM respectively). In the dry season relatively weaker negative correlations (R² = 0.52, 0.60, 0.55; for NDWI, NDVI and SM respectively) were observed. On the other hand SM showed strong positive linear correlations (R² > 0.6) with NDWI and NDVI (for the rainy and dry seasons respectively). The correlations imply that in Miombo forest soil water content (i.e. SM), vegetation water content (i.e. NDWI) and the photosynthetic activities and leaf cover (i.e. NDVI) declines with increase in LST. These relationships show the possibility of land surface temperature being a major inducing element of leaf fall and changes in canopy structure in the Miombo woodland.

How to cite: Zimba, H., Coenders-Gerrits, M., Kawawa, B., Nyambe, I., Savenije, H., and Winsemius, H.: Land Surface Temperature and Miombo forest canopy phenophases: what induces leaf fall and leaf flush? , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10389, https://doi.org/10.5194/egusphere-egu2020-10389, 2020.

An improved representation of the spatio-temporal patterns of climatological variables is crucial for ecological, agricultural, and hydrological applications and can improve the decision-making process. Traditionally, precipitation (P) and actual evaporation (ETa) are estimated using ground-based measurements from meteorological stations. However, the estimation of spatial patterns derived solely from point-based measurements is subject to large uncertainties, particularly in data-scarce regions as the Nile Basin, which has an area of about 3 million km². This study evaluates six state-of-the-art P products (CHIRPSv2, CMORPHv1, CRU TS4.02, MSWEPv2.2, PERSIANN-CDR and GPCCv2018) and five ETa products (SSEBop, MOD16-ET, WaPOR, GLEAM and GLDAS) over the Nile Basin to identify the best-performing products. The P products were evaluated at monthly and annual temporal scales (from 1983 onwards) through a point-to-pixel approach using the modified Kling-Gupta Efficiency and its components (linear correlation, bias, and variability ratio) as continuous performance indices. The ETa products were evaluated through the water balance approach (due to the lack of ground-based ETa measurements) for 2009-2018 at the multiannual scale. Because streamflow data were not available for this period, an empirical model based on the Random Forest machine learning technique was used to estimate streamflow at 21 catchments at the monthly scale. For this purpose, we used streamflow data from 1983 to 2005 as the dependent variable, while CHIRPSv2 precipitation and ERA5 potential evaporation and temperature data were used as predictors. For the catchments where the model performed well over the validation period, streamflow estimates were generated and used for the water balance analysis. Our results show that CHIRPSv2 was the best performing P product at monthly and annual scale when compared with ground-based measurements, while WaPOR was the best-performing ETa product in the water balance evaluation. This study demonstrates how remote sensing data can be evaluated over extremely data-scarce scenarios to estimate the magnitude of key meteorological variables, yet also highlights the importance of improving data availability so that the characterisation of these variables can be further evaluated and improved.

How to cite: Baez-Villanueva, O. M., McNamara, I., Zambrano-Bigiarini, M., and Ribbe, L.: Evaluation of precipitation and actual evaporation products over the Nile Basin, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11877, https://doi.org/10.5194/egusphere-egu2020-11877, 2020.

Currently 40 % of Africa's population still lacks access to clean water. Twice as many rural people live in hard rock areas as compared to sedimentary areas. In these hard rock areas a thick weathered regolith layer covers the crystalline basement, where groundwater (GW) circulates. In the Sudanian area of West Africa (WA) ,groundwater levels are shallow enough to interact directly with the surface water. Therefore, constructing coupled surface-groundwater models helps to estimate quantities of both, GW and surface flows, and their evolution over time to facilitate integrated water management. However, the sensitivity of such models to aquifer properties (saturated hydraulic conductivity (Ks), porosity, geometry), which are difficult to obtain in heterogeneous crystalline contexts, is still poorly constrained. The heterogeneity of aquifer properties at the scale at which most water management decisions are taken, is twofold: 1) bimodal vertical heterogeneity with an unconsolidated weathered zone (high porosity, low Ks) overlying a fissured zone (low porosity, high Ks) and 2) lateral heterogeneity controlled by substratum features and weathering history. We assessed the sensitivity of a coupled surface-groundwater model (PARFLOW-CLM) to vertical and lateral heterogeneity of Ks. The sensitivity to the lateral heterogeneity was explored either using simulations with homogeneous or distributed Ks following random field approaches with a range of spatial correlation lengths. The representation of a vertically uniform aquifer layer was compared to a two-layer scenario for each of the lateral heterogeneity cases. Here, we focused our analysis on the Northern Oueme catchment in Benin (14 000 km²) and we constructed a model with a spatial resolution of 1 km², preventing the analysis of smaller-scale features, such as macropores or clay accumulations. Hydraulic conductivity and aquifer geometry data to constrain the sensitivity experiments were derived from the literature specific to the target area, but also from regional hard rock aquifers in West Africa. As an output of the model, we obtained streamflow, water table head and evapotranspiration time series (in a monthly and daily resolution). The results that we gained with our model configuration (and resolution) point towards a low sensitivity of the model to lateral and vertical heterogeneity. However, we observed a significant impact of the magnitude of Ks on water table head and particularly on the streamflow amplitude. Regarding the water balance our results show that further exploration of the subsurface is crucial to improve critical zone modeling in the context of WA.

How to cite: Herzog, A., Hector, B., Cohard, J.-M., Lawson, F.-M., Vouillamoz, J.-M., and de Graaf, I.: The sensitivity of a critical zone model to the representation of hydraulic conductivity heterogeneity in a deeply weathered hard rock aquifer in West Africa, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17163, https://doi.org/10.5194/egusphere-egu2020-17163, 2020.

There is an increasing demand for sound climate information in Sub-Saharan Africa (SSA) for both regional and local scales. While climate information from Global Climate Models (GCMs) are usually too coarse for climate impact modelers or decision makers from various disciplines (e.g. hydrology and water management, agriculture, energy), Earth System Models (ESMs) provide feasible solutions for downscaling GCM output to required spatiotemporal scales. However, it is well known that the performance of regional simulations depends a lot on the physical parametrization, which may vary from region to region. Besides land-surface processes, the most crucial processes to be parameterized in ESMs include radiation, convection, and cloud microphysics, partly with complex interactions. Precipitation generation, for instance, involves many coupled processes between cumulus convection, cloud microphysics, radiation, land and ocean surface, and the planetary boundary layer. Before conducting long-term ESM simulations, it is therefore indispensable to identify a suitable physics parametrization combination. Based on the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis product ERA-Interim, we performed a set of 16 high-resolution physics parameterization experiments for SSA, using different cumulus-, microphysics-, planetary boundary layer-, and radiation schemes in the Weather Research and Forecasting (WRF) model for the period 2006-2010 in a spatial resolution of 9 km. Based on traditional (Taylor diagram, probability densities) and more innovative validation metrics (ensemble structure–amplitude–location (eSAL) analysis, Copula functions) and with the use of various observation data for precipitation and temperature, favorable parameterization combinations for whole SSA are identified and will be discussed also w.r.t. the required computing time. Here, we find that complex radiation schemes do not urgently lead to better simulation results for SSA, but increase the computing time tremendously.           

How to cite: Laux, P., Dieng, D., Portele, T., Arnault, J., Lorenz, C., Bliefernicht, J., and Kunstmann, H.: A physically-based ensemble of high-resolution regional climate simulations for Sub-Saharan Africa, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18552, https://doi.org/10.5194/egusphere-egu2020-18552, 2020.

The Green-Ampt model was developed more than 100 years ago and is still one of the most commonly used approaches to consider infiltration in rainfall-runoff models, which can be either conceptual catchment models as well as 2D hydrodynamic models. When coupling, for example, the Green-Ampt model for infiltration with a 2D shallow water model for the flow, the calculated ponding water depths are transferred from the flow model to the Green-Ampt model to calculate the infiltration rates, and the resulting infiltration rates represent then sinks in the mass balance equation of the shallow water model. The so-called Green-Ampt parameters in terms of saturated water content, hydraulic conductivity, and suction head at the wetting front, are needed as model input in addition to the initial water content. Often, the Green-Ampt parameters are not directly measured in the field for the area that should be modeled but are only assumed based on average values from the literature depending on the dominant soil texture class. If reliable data of certain rainfall-runoff events are available for the study area, the values of the Green-Ampt parameters can be determined besides other calibration parameters within reasonable ranges. However, in some cases, a calibration of the Green-Ampt parameters is not possible due to a lack of measurements, for example during suddenly occurring flash floods or in completely ungauged basins. This study aims to investigate with a coupled shallow water flow and infiltration model if the Green-Ampt parameters could be appropriately assumed based on average values from literature depending on the given soil texture classes. Furthermore, the effects that could lead to an inappropriate representation of infiltration with tabulated Green-Ampt parameters are studied, such as surface clogging, sub-grid rill-flow, and coarse DEM resolution. To investigate the general suitability of using average Green-Ampt parameters from literature dependent on soil texture classes, different small-scale test cases with available data for calibration are shown, where two of them are laboratory experiments and one is a rainfall-runoff experiment on a small plot in Senegal. Finally, a case study on flash floods in a desert region in Egypt is represented. The results show that in the laboratory experiments, the infiltration rates with average Green-Ampt parameters are underestimated, while for the field experiment in Senegal infiltration rates are overestimated. For the case study in Egypt, infiltration with Green-Ampt parameters from literature as well as with measured infiltration rates from double ring infiltrometer tests is strongly overestimated in the model. It is planned to conduct plot-scale rainfall-runoff experiments with a rainfall simulator for the study area in Egypt to better represent the natural conditions during heavy rainfalls and compare the measured infiltration rates with the ones from literature and double ring infiltrometer test.

How to cite: Tügel, F., Hassan, A., Wannous, M., Tröger, U., and Hinkelmann, R.: Investigation of the Green-Ampt infiltration model in rainfall-runoff simulations with a robust 2D shallow water model, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19020, https://doi.org/10.5194/egusphere-egu2020-19020, 2020.

The mining industry of the Democratic Republic of the Congo represents the most important sector of the country’s economy being DRC the second-largest diamond-producer in the world. By far the largest diamond-mines in the DRC are located in southern Katanga province.

There are many types of mining techniques and alluvial mining is the one that usually takes place in DRC.

Alluvial diamonds are diamonds that have been removed from the primary source (Kimberlite) by natural erosion, and eventually deposited in a new environment such as a river beds and floodplains. This type of mining leads obviously to a number of impacts: deforestation, river pollution, water resources exploitation, unhealthy, unregulated and sometimes dangerous environments in which diggers work.. All these effects are strictly related and difficult to evaluate since the DRC is in a situation of institutional chaos and humanitarian crisis due to high rate of malnutrition.

Here we analyze the impact of diamond mining industry on natural resources, and population in Democratic Republic of Congo. To this end using spatial and temporal high resolution data we evaluate the tree cover losses and the water resources use associated with mining activity from 2000 to 2018 and using a dynamic and spatially distributed crop water model we provide alternative use of natural resources (i.e. land and water) presently used for mining so assessing the likelihood to contrast malnourishment.

How to cite: Galli, N., Chiarelli, D. D., D'Angelo, M., and Rulli, M. C.: Environmental impacts of diamond mining in the Democratic Republic of Congo, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20634, https://doi.org/10.5194/egusphere-egu2020-20634, 2020.

Future water availability in West Africa: Estimates from high-resolution RCM modeling and multivariate bias correction

Diarra Dieng¹, Cornelius Hald¹, Patrick Laux^1,2, Christof Lorenz¹, Harald Kunstmann^1,2

¹Institute of Meteorology and Climate Research (IMK-IFU), Campus Alpine, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany,

²Institute of Geography, University of Augsburg, Augsburg, Germany,

With a wide range of ecological, climatic, and cultural diversities, West Africa is a rapidly developing region whose agricultural systems remain largely rain-fed and underdeveloped. In this study we examine the potential impacts of climate variability and climate change on the water availability in the mid-21st century in West 
Africa by using high resolution simulations (12km) from the Weather and Research Forecasting (WRF) model and the COSMO-Climate Limited area Modelling (CCLM) for the RCP 4.5 scenario. Our approach is based on the simplified Penman-Monteith (PM) equation for daily ET, which requires the joint information on relative humidity, maximum and minimum daily temperatures, dew point temperature, solar radiation and wind speed. It is not only crucial that the statistical behavior of these modelled variables is close to observations, but also that the interplay between these variables is realistic. We therefore further adapted, applied and analyzed a subsequent bias-correction method for the WRF and CCLM simulations using a nonparametric, trend-preserving quantile mapping approach and a multivariate bias correction approach (MBCn). We present the details of the method and the derived implications for expected water availability in West Africa.

How to cite: Dieng, D., Hald, C., Laux, P., Lorenz, C., and Kunstmann, H.: Future water availability in West Africa: Estimates from high-resolution RCM modeling and multivariate bias correction , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20682, https://doi.org/10.5194/egusphere-egu2020-20682, 2020.