Multiscale water accounting under climate change in a transboundary West African basin

Paper presented at the European Geosciences Union (EGU) General Assembly 2023, Vienna, Austria and Online, 24-28 April 2023

Potential of satellite and reanalysis evaporation datasets for hydrological modelling under various model calibration strategies

Twelve actual evaporation datasets are evaluated for their ability to improve the performance of the fully distributed mesoscale Hydrologic Model (mHM). The datasets consist of satellite-based diagnostic models (MOD16A2, SSEBop, ALEXI, CMRSET, SEBS), satellite-based prognostic models (GLEAM v3.2a, GLEAM v3.3a, GLEAM v3.2b, GLEAM v3.3b), and reanalysis (ERA5, MERRA-2, JRA-55). Four distinct multivariate calibration strategies (basin-average, pixel-wise, spatial bias-accounting and spatial bias-insensitive) using actual evaporation and streamflow are implemented, resulting in 48 scenarios whose results are compared with a benchmark model calibrated solely with streamflow data. A process-diagnostic approach is adopted to evaluate the model responses with in-situ data of streamflow and independent remotely sensed data of soil moisture from ESA-CCI and terrestrial water storage from GRACE. The method is implemented in the Volta River basin, which is a data scarce region in West Africa, for the period from 2003 to 2012. Results show that the evaporation datasets have a good potential for improving model calibration, but this is dependent on the calibration strategy. All the multivariate calibration strategies outperform the streamflow-only calibration. The highest improvement in the overall model performance is obtained with the spatial bias-accounting strategy (+29%), followed by the spatial bias-insensitive strategy (+26%) and the pixel-wise strategy (+24%), while the basin-average strategy (+20%) gives the lowest improvement. On average, using evaporation data in addition to streamflow for model calibration decreases the model performance for streamflow (-7%), which is counterbalance by the increase in the performance of the terrestrial water storage (+11%), temporal dynamics of soil moisture (+6%) and spatial patterns of soil moisture (+89%). In general, the top three best performing evaporation datasets are MERRA-2, GLEAM v3.3a and SSEBop, while the bottom three datasets are MOD16A2, SEBS and ERA5. However, performances of the evaporation products diverge according to model responses and across climatic zones. These findings open up avenues for improving process representation of hydrological models and advancing the spatiotemporal prediction of floods and droughts under climate and land use changes

Contrasting changes in hydrological processes of the Volta River basin under global warming

A comprehensive evaluation of the impacts of climate change on water resources of the West Africa Volta River basin is conducted in this study, as the region is expected to be hardest hit by global warming. A large ensemble of 12 general circulation models (GCMs) from the fifth Coupled Model Intercomparison Project (CMIP5) that are dynamically downscaled by five regional climate models (RCMs) from the Coordinated Regional-climate Downscaling Experiment (CORDEX)-Africa is used. In total, 43 RCM–GCM combinations are considered under three representative concentration pathways (RCP2.6, RCP4.5, and RCP8.5). The reliability of each of the climate datasets is first evaluated with satellite and reanalysis reference datasets. Subsequently, the Rank Resampling for Distributions and Dependences (R2D2) multivariate bias correction method is applied to the climate datasets. The bias-corrected climate projections are then used as input to the mesoscale Hydrologic Model (mHM) for hydrological projections over the 21st century (1991–2100). Results reveal contrasting dynamics in the seasonality of rainfall, depending on the selected greenhouse gas emission scenarios and the future projection periods. Although air temperature and potential evaporation increase under all RCPs, an increase in the magnitude of all hydrological variables (actual evaporation, total runoff, groundwater recharge, soil moisture, and terrestrial water storage) is only projected under RCP8.5. High- and low-flow analysis suggests an increased flood risk under RCP8.5, particularly in the Black Volta, while hydrological droughts would be recurrent under RCP2.6 and RCP4.5, particularly in the White Volta. The evolutions of streamflow indicate a future delay in the date of occurrence of low flows up to 11 d under RCP8.5, while high flows could occur 6 d earlier (RCP2.6) or 5 d later (RCP8.5), as compared to the historical period. Disparities are observed in the spatial patterns of hydroclimatic variables across climatic zones, with higher warming in the Sahelian zone. Therefore, climate change would have severe implications for future water availability with concerns for rain-fed agriculture, thereby weakening the water–energy–food security nexus and amplifying the vulnerability of the local population. The variability between climate models highlights uncertainties in the projections and indicates a need to better represent complex climate features in regional models. These findings could serve as a guideline for both the scientific community to improve climate change projections and for decision-makers to elaborate adaptation and mitigation strategies to cope with the consequences of climate change and strengthen regional socioeconomic development

Future shifting of annual extreme flows under climate change in the Volta River basin

Global warming is projected to result in changes in streamflow in West Africa with implications for frequent droughts and floods. This study investigates projected shifting in the timing, seasonality and magnitude of mean annual minimum (MAM) and annual maximum flows (AMF) in the Volta River basin (VRB) under climate change, using the method of circular statistics. River flow is simulated with the mesoscale hydrologic model (mHM), forced with bias-corrected climate projection datasets consisting of 43 regional and global climate model combinations under three representative concentration pathways (RCPs). Projected changes indicate that AMF increases between +1 % and +80 % across sub-basins, particularly in the near future (2021–2050), whereas MAM decreases between −19 % and −7 %, mainly from the late century (2071–2100), depending on RCPs. The date of occurrence of AMF is projected to change between −4 and +3 d, while MAM could shift between −4 and +14 d depending on scenarios over the 21st century. Annual high flows denote a strong seasonality with negligible future changes, whereas the seasonality of low flows has a higher variation, with a slight drop in the future

Spatially explicit hydrological modelling for water accounting under climate change in the Volta River Basin in West Africa

Abstract -------- Competition for scarce water resources in the Volta River Basin (VRB) of West Africa will increase in the near future due to the combined effects of rapid population growth and climate change. Residents are dependent on subsistence, mainly rainfed agriculture that is sensitive to climate variabilities. Recurrent floods and droughts damage properties and take lives. Information on water resources and their future trends is fundamental for water actors, as the basis for proper management and implementation of adequate measures to bolster resilience to water scarcity and foster water security. This PhD thesis proposes a novel and clear demonstration of combining the Water Accounting Plus (WA+) framework with hydrological modelling and climate change scenarios to report on the current and future states of water resources in the VRB. WA+ is a standardized framework that provides a comprehensive view of the water resources in terms of water availability and consumptive uses with respect to different land uses. The adopted methodological framework addresses key challenges posed by large-scale hydrological modelling in data scarce environments such as the VRB. These challenges include the issue of missing data in streamflow records, the reliability of satellite and reanalysis data for forcing or calibrating hydrological models as an alternative to in-situ measurements, and the accuracy of the spatial and temporal representation of hydrological processes with spatially explicit models. A novel multivariate model calibration strategy is proposed to improve the representation of hydrological flux and state variables simulated with the fully distributed mesoscale Hydrologic Model (mHM). The proposed calibration strategy relies on the use of multiple satellite and reanalysis datasets from various sources. Then, a large ensemble of climate models are used to assess the impacts of climate change on water resources under various scenarios. The outputs of the mHM model are used to feed the WA+ framework to comprehensively report on the current and future conditions of water resources in the VRB. The results show a clear increase in the projected exploitable water fraction while a decrease is expected in the available water fraction in the near future (2021-2050). Consequently, there is a clear need for adaptation measures to increase the water storage capacity in the VRB to facilitate a good exploitation of the projected increase in the net inflow, which would be beneficial for agriculture production and hydropower generation. -------- Résumé -------- La compétition pour l'usage de l'eau dans le bassin de la Volta (VRB) en Afrique de l'Ouest va s'intensifier dans un futur proche en raison des effets combinés de la croissance démographique galopante et du changement climatique. Les populations du bassin dépendent fortement d'une agriculture pluviale de subsistance qui demeure très sensible aux variabilités climatiques. Les inondations et les sécheresses récurrentes endommagent les infrastructures et créent des pertes en vie humaine. Les informations sur les ressources en eau et leurs tendances futures sont essentielles pour les acteurs de l'eau, car elles constituent la base d'une bonne gestion de l'eau et de la mise en oeuvre de mesures adéquates pour renforcer la résilience à la pénurie d'eau et favoriser la sécurité de l'eau. Cette thèse de doctorat propose une démonstration élaborée et innovante de la combinaison du Water Accounting Plus (WA+) avec la modélisation hydrologique et les scénarios de changement climatique pour faire un rapport de l'état actuel et futur des ressources en eau dans le VRB. WA+ ou "comptabilité de l'eau" est un outil standard de gestion de l'eau qui fournit une analyse complète des ressources en eau en termes de disponibilité et de consommation d'eau en fonction de différents usages du sol. La méthodologie adoptée aborde les principaux défis posés par la modélisation hydrologique à grande échelle dans des régions où les données sont rares, comme le VRB. Ces défis comprennent la question des données manquantes dans les séries temporelles de débit, la fiabilité des données satellitaires et de réanalyse pour faire tourner ou calibrer des modèles hydrologiques comme alternative aux mesures sur site, et la justesse de la représentation spatiale et temporelle des processus hydrologiques avec des modèles spatialement distribués. Une nouvelle stratégie de calibration multivariée est proposée pour améliorer la représentation des processus hydrologiques avec le modèle mesoscale Hydrologic Model (mHM). La nouvelle stratégie de calibration de modèle repose sur l'utilisation de plusieurs données satellitaires et de réanalyse provenant de diverses sources. Un large ensemble de modèles climatiques est utilisé pour évaluer les impacts du changement climatique sur les ressources en eau en considérant divers scénarios. Les sorties du modèle mHM sont utilisées pour alimenter le WA+ afin de faire une description complète des conditions actuelles et futures des ressources en eau dans le VRB. Les résultats montrent une nette augmentation de la fraction d'eau exploitable dans un futur proche (2021-2050), tandis qu'une diminution de la fraction d'eau disponible est attendue. Par conséquent, il est opportun d'adopter des mesures d'adaptation pour augmenter la capacité de stockage de l'eau dans le bassin de la Volta afin de faciliter une bonne exploitation de l'augmentation prévue de l'apport net en eau, ce qui serait bénéfique pour la production agricole et la production hydroélectrique

Satellite rainfall for food security on the African continent: performance and accuracy of seven rainfall products between 2001 and 2016

Food security is the most emerging issue for most countries on the African continent. The major share of the agricultural production in Africa is rain fed whereas many of the irrigated zones are in water scarce and/or transboundary river basins. Accurate and detailed information on rainfall distribution is essential to support food security and water accounting applications. However, the network of meteorological stations that may provide such information is sparse. Gridded precipitation products developed from satellite imagery sources have become increasingly available as an alternative or an addition to observed rainfall. The goal of this study was to evaluate and compare seven existing rainfall products for the Africa continent for the purpose of food security monitoring and water resources applications. We made a point-to-grid comparison for daily, dekadly, monthly and annual time steps of approximately 1,100 WMO stations that reported rainfall between 2001 and 2016. The rainfall products that were included are ARC, CHIRPS, PERSIANN, RFE, TAMSAT, TRMM 3B42 and MSWEP. A set of 5 continuous statistical indicators (Pearson correlation coefficient, Mean Erorr, Bias, Root Mean Square Error and Nash–Sutcliffe Efficiency coefficient) and two categorical indicators (Probability of Detection and False Alarm Ratio) were used. WMO stations are unevenly distributed across Africa; though the total number of daily precipitation observations in Africa has increased by 50% from around 400 in 2001 to 600 in 2016. In West-Africa the coverage has improved significantly with the exception of Guinea-Conakry, Liberia and Sierra Leone. In Eastern and Southern Africa less stations are reporting with the exception of Tanzania. “White areas” are the horn of Africa, the sparsely populated Sahel desert stretching from Mauritania to Sudan and a belt in central Africa from Sudan down south to Angola. Important high intensity rainfall zones in West Africa (Fouta Djallon highlands, Nigeria) and Central Africa (Congo Basin) as well as Ethiopia in East-Africa have poor observation records. Our analysis confirmed earlier findings that daily rainfall estimations of all products are weakly related with daily observation. We therefore focused on the cumulative values for dekads and months that we averaged for all stations in Africa. These values show that the most reliable products are MSWEP, CHIRPS, ARC and RFE, although the last two have the lowest ME equaling -0.80 and 1.22 respectively. TRMM has the highest ME value (0.11) but depicts poor scores for the other six indictors. Weakest products are TAMSAT and PERSIANN that were ranked lowest for almost all statistical indicators. Preliminary spatial results show that the performance of the products for coastal stations is lower than inland stations. The Bias of most products is high in north Africa compared to similar areas in Sub-Saharan Africa

Modelling the impact of climate change on hydrological processes in the Volta river basin

This study evaluates the impacts of climate change on water resources of the Volta River basin located in West Africa. In total, 43 combinations of global climate models (GCM) and five regional climate models (RCM) from CORDEX- Africa are considered under three representative concentration pathways (RCP2.6, RCP4.5 and RCP8.5). The R2D2 multivariate bias correction method is applied to the climate datasets before using them as input to the fully distributed Hydrologic Model (mHM) for hydrological projections over the twenty-first century. The mHM model is constrained with a novel multivariate calibration approach based on the spatial patterns of satellite remote sensing data (Dembélé et al., 2020). Results reveal contrasting changes in the seasonality of precipitation depending on the RCPs and the future projection periods (2021-2050, 2051-2080 and 2071-2100) as compared to the historical period (1991-2020), while a clear increase in the seasonality of temperature is expected. A clear intensification of the hydrological cycle during the twenty-first century is expected only under the RCP8.5 scenario. In this case, an increase is foreseen for the long-term annual estimates of precipitation (+6.2%), average temperature (+9.5%) and potential evaporation (+5.0%). These changes in climatic variables will lead to changes in actual evaporation (+4.2%), surface runoff (+42%), streamflow (+84%), groundwater recharge (+37%), soil moisture (+2.3%) and terrestrial water storage (+3.2%). Consequently, recurrent floods and droughts could weaken the water-energy-food security nexus and amplify the vulnerability of the local population to climate change. These findings could serve as a guideline for decision makers, and contribute to the elaboration of adaptation and mitigation strategies to cope with dramatic consequences of climate change on various sectors including agriculture and hydroelectricity, and strengthen the regional socio-economic development. REFERENCES Dembélé, M., M. Hrachowitz, H. H. G. Savenije, G. Mariéthoz, and B. Schaefli (2020b), Improving the Predictive Skill of a Distributed Hydrological Model by Calibration on Spatial Patterns With Multiple Satellite Data Sets, Water Resources Research, 56(1), https://doi.org/10.1029/2019wr026085

Multivariate and Spatially Calibrated Hydrological Model for Assessing Climate Change Impacts on Hydrological Processes in West Africa

Robust hydrological models are critical for the assessment of climate change impacts on hydrological processes. This study analysis the future evolution of the spatiotemporal dynamics of multiple hydrological processes (i.e. streamflow, soil moisture, evaporation and terrestrial water storage) with the fully distributed mesoscale hydrologic Model (mHM), which is constrained with a novel multivariate calibration approach based on the spatial patterns of satellite remote sensing data (Dembélé et al., 2020). The experiment is done in the large and transboundary Volta River Basin (VRB) in West Africa, which is a hotspot of climate vulnerability. Climate change and land use changes lead to recurrent floods and drought that impact agriculture and affect the lives of the inhabitants. Based on data availability on the Earth System Grid Federation (ESGF) platform, nine Global Circulation Models (i.e. CanESM2, CNRM-CM5, CSIRO-Mk3-6-0, GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-MR, MIROC5, MPI-ESM-LR and NorESM1-M) available from the CORDEX-Africa initiative and dynamically downscaled with the latest version of the Rossby Centre's regional atmospheric model (RCA4) are selected for this study. Daily datasets of meteorological variables (i.e. precipitation and air temperature) for the medium and high emission scenarios (RCP4.5 and RCP8.5) are bias-corrected and used to force the mHM model for the reference period 1991-2020, and the near- and long-term future periods 2021-2050 and 2051-2080. The results show contrasting trends among the hydrological processes as well as among the GCMs. The findings reveal uncertainties in the spatial patterns of hydrological processes (e.g. soil moisture and evaporation), which ultimately have implications for flood and drought predictions. This study highlights the importance of plausible spatial patterns for the assessment of climate change impacts on hydrological processes, and thereby provide valuable information with the potential to reduce the climate vulnerability of the local population