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Climatology of Africa according to the Koppen–Geiger climate zones classification and location of the stations included in the ADHI database (Tramblay et al., 2021). The circles represent the mean flows (reported on the left) based on HydroAtlas database (Linke et al., 2019)
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For more than a century, river discharge has been measured indirectly through observations of water level and flow velocity, but recently the number of gauging stations worldwide has decreased and the situation is particularly serious in African countries that suffer more than others from discontinuous and incomplete monitoring. As one of the most...
Citations
... Most lakes worldwide are missed by existing radar-based altimeters, which measure water height only at nadir (Alsdorf & Lettenmaier, 2003), and the extremely limited temporal resolution of laser-based systems such as ICESat-2 reduce their utility (Cooley et al., 2021). In addition, the one-dimensional nature of these measurements means that attempts to estimate river discharge and lake water storage from space require incorporation of data from ground-based sources or other satellites (Crétaux et al., 2016;Emery et al., 2018;Tarpanelli et al., 2022), which are rarely available at the same time. Moreover, monitoring inundation depths over floodplains, particularly in ungauged basins, is a very challenging issue, barely achievable from current satellite data. ...
Plain Language Summary
Earth is a water planet. The vast amount of ocean water has stored most of the heat released to the atmosphere since the Industrial Revolution through burning fossil fuels. Climate change is thus moderated by the ocean. Over land the freshwater in lakes, rivers, and reservoirs, a critical natural resource, is affected by the warming climate and direct human modifications. Processes of oceanic uptake of heat and carbon from the atmosphere and cycling of freshwater on land take place at spatial scales too small to have been adequately quantified from space. A new satellite, the Surface Water and Ocean Topography (SWOT) mission, was launched in December 2022. Using advanced radar technology, SWOT provides unprecedented global observations for understanding the ocean's role in climate change and how freshwater resources respond to human influence. SWOT observations near coasts will also advance understanding of how rising sea levels impact those coasts.
... RD (river discharge) is a critical hydrologic variable that links atmospheric, oceanic, and terrestrial processes, which plays a key role in addressing various aspects such as assessing food risks and guiding hydropower stations' operation. The Global Climate Observing System (GCOS) considers it essential to understanding the hydrological cycle and managing water supplies [1]. In most cases, however, RD cannot be measured directly and needs relevant hydraulic parameters to compute its value, such as flow rate at multiple points and cross-section area. ...
Accurately computing river discharge is crucial, but traditional computing methods are complex and need the assistance of many other hydraulic parameters. Therefore, it is of practical value to develop a convenient and effective auto-computation technique for river discharge. Water surface elevation is relatively easy to obtain and there is a strong relationship between river discharge and water surface elevation, which can be used to compute river discharge. Unlike previous usage of deep learning to predict short-term river discharge that need multiple parameters besides water level, this paper proved that deep learning has the potential to accurately compute long-term river discharge purely based on water level. It showed that the majority of relative errors on the test dataset were within ±5%, particularly it could operate continuously for almost one year with high precision without retraining. Then, we used BiGRU to compute river flow with different hyperparameters, and its best RMSE, NSE, MAE, and MAPE values were 256 m3/s, 0.9973, 207 m3/s, and 0.0336, respectively. With this data-driven based technology, it will be more convenient to obtain river discharge time series directly from local water surface elevation time series accurately in natural rivers, which is of practical value to water resources management and flood protection.
... As shown in Fig. 1, these studies can be categorized into two groups. One approach (Fig. 1a) first develops a hydraulic model for estimating river discharge from remotely sensed water level and/or river width, and it then uses these estimates to carry out the calibration of the hydrological model (Khan et al., 2012;Tarpanelli et al., 2022). This approach still partially relies on in situ data. ...
The calibration of macroscale hydrological models is often challenged by the lack of adequate observations of river discharge and infrastructure operations. This modeling backdrop creates a number of potential pitfalls for model calibration, potentially affecting the reliability of hydrological models. Here, we introduce a novel numerical framework conceived to explore and overcome these pitfalls. Our framework consists of VIC-Res (a macroscale model setup for the Upper Mekong Basin), which is a novel variant of the Variable Infiltration Capacity (VIC) model that includes a module for representing reservoir operations, and a hydraulic model used to infer discharge time series from satellite data. Using these two models and global sensitivity analysis, we show the existence of a strong relationship between the parameterization of the hydraulic model and the performance of VIC-Res – a codependence that emerges for a variety of performance metrics that we considered. Using the results provided by the sensitivity analysis, we propose an approach for breaking this codependence and informing the hydrological model calibration, which we finally carry out with the aid of a multi-objective optimization algorithm. The approach used in this study could integrate multiple remotely sensed observations and is transferable to other poorly gauged and heavily regulated river basins.
... In a paper entitled Water resources in Africa: the role of the EO data and hydrodynamic modeling to derive river discharge, Tarpanelli et al. (2023) recall that the number of gauging stations has decreased worldwide and the situation is particularly serious in African countries that suffer more than others from discontinuous and incomplete monitoring. The authors review the methods, including recent developments in the domain of artificial intelligence, for hydrological and hydraulic modeling to estimate river discharge using satellite data, specifically radar altimetry and optical observations. ...
... In addition, Padilla Fernández et al. [32] highlighted that it may be necessary to use water in the production of some raw materials. If these waters are used unconsciously, water resources can be depleted quickly [33,34]. Kyriakopoulos et al. [35], Sang et al. [36] and Karimidastenaei et al. [37] claimed that experiencing water scarcity around the world can also cause life-threatening problems. ...
The purpose of this study is to evaluate the environmental impacts of material production investments. The factors of Higg Materials Sustainability Index are defined as the parameters. These factors are weighted by considering T-SF TOPSIS-DEMATEL. Moreover, the items of the life cycle process are defined as alternative set for measuring the environmental effects of each process in the sustainable production investments. These alternatives are ranked with interval valued SF MAIRCA. The calculations are also made for different t, u and d values with the aim of making comparative evaluations. The main contribution of this study is that a priority analysis has been made so that the most significant indicators are defined for the companies to increase sustainability in material production investment process. Another important novelty of this paper is that a new model is created by the name of TOPSIS-DEMATEL. This situation has a positive influence on both increasing methodological originality and overcoming criticized issues of DEMATEL. The results are quite similar for all conditions, so it is understood that the proposed model provides consistent and coherent findings. It is concluded that chemistry is the most critical factor for environmental impact for material production investments. Moreover, recycle is determined as the most optimal alternative.
... Further use of radar altimetry observations in hydrologic and hydraulic models is discussed in Sect. 3, while the role of water level derived from space to derive river discharge over Africa is discussed by Tarpanelli et al. (2021). ...
... Additionally, there is still a very limited knowledge of water level and slopes at fine spatiotemporal resolution over African surface water, as well as topography in floodplains and flooded forests, preventing to significant improvements in hydraulic modeling of the systems. Similarly, river discharge, which was historically one of the first variables measured in hydrology and the most used to develop and calibrate models, is still not properly measured from space, as discussed in Tarpanelli et al. (2021). This review stresses a need to accurately estimate river discharge across the continent with fine spatial and temporal resolutions. ...
... Further use of radar altimetry observations in hydrologic and hydraulic models is discussed in Sect. 3, while the role of water level derived from space to derive river discharge over Africa is discussed by Tarpanelli et al. (2021). ...
... Additionally, there is still a very limited knowledge of water level and slopes at fine spatiotemporal resolution over African surface water, as well as topography in floodplains and flooded forests, preventing to significant improvements in hydraulic modeling of the systems. Similarly, river discharge, which was historically one of the first variables measured in hydrology and the most used to develop and calibrate models, is still not properly measured from space, as discussed in Tarpanelli et al. (2021). This review stresses a need to accurately estimate river discharge across the continent with fine spatial and temporal resolutions. ...
The African continent hosts some of the largest freshwater systems worldwide, characterized by a large distribution and variability of surface waters that play a key role in the water, energy and carbon cycles and are of major importance to the global climate and
water resources. Freshwater availability in Africa has now become of major concern under
the combined effect of climate change, environmental alterations and anthropogenic pressure. However, the hydrology of the African river basins remains one of the least studied worldwide and a better monitoring and understanding of the hydrological processes across the continent become fundamental. Earth Observation, that offers a cost-effective means for monitoring the terrestrial water cycle, plays a major role in supporting surface hydrology investigations. Remote sensing advances are therefore a game changer to develop comprehensive observing systems to monitor Africa’s land water and manage its water resources. Here, we review the achievements of more than three decades of advances using remote sensing to study surface waters in Africa, highlighting the current benefits and difficulties. We show how the availability of a large number of sensors and observations, coupled with models, offers new possibilities to monitor a continent with scarce gauged stations. In the context of upcoming satellite missions dedicated to surface hydrology, such as the Surface Water and Ocean Topography (SWOT), we discuss future opportunities and how the use of remote sensing could benefit scientific and societal applications, such as water resource management, flood risk prevention and environment monitoring under current global change.
In recent decades, water availability, water use, water sharing and freshwater supply for basic human and economic needs have become central scientific and humanitarian issues. With increasing water scarcity in many regions and increasing frequency of extreme flooding in other regions, there is a need to improve predictive capacity, to collect a large amount of information on key hydrological variables such as flows or water stocks in lakes and floodplains and to best combine these data with hydrological and hydrodynamic models. Most of the world's water demand relies on continental surface waters (rivers, lakes, wetlands and artificial reservoirs) while less on underground aquifers and seawater desalination. However, ground-based hydrological survey networks have steadily and drastically decreased worldwide over the last decades. In this context, current remote sensing techniques have been widely used by several countries for water resource monitoring purposes. In this paper, we present such remote sensing techniques, in particular satellite altimetry and imagery, and discuss how they became essential for the study of the water cycle and hydrological phenomena on a broad range of spatial and temporal scales. Large lakes, rivers and wetlands play a major role in the global water cycle and are also markers, integrators and actors of climate change at work on Earth. We show several examples chosen from the literature that perfectly highlight both current scientific and societal issues, as well as the crucial role of space techniques to monitor terrestrial surface waters.
The calibration of macro-scale hydrological models is often challenged by the lack of adequate observations of river discharge and infrastructure operations. This modelling backdrop creates a number of potential pitfalls for model calibration, potentially affecting the reliability of hydrological models. Here, we introduce a novel numerical framework conceived to explore and overcome these pitfalls. Our framework consists of VIC-Res (a macro-scale model setup for the Upper Mekong River Basin) and a hydraulic model used to infer discharge time series from satellite data. Using these two models and Global Sensitivity Analysis, we show the existence of a strong relationship between the parameterization of the hydraulic model and the performance of VIC-Res – a co-dependence that emerges for a variety of performance metrics we considered. Using the results provided by the sensitivity analysis, we propose an approach for breaking this co-dependence and informing the hydrological model calibration, which we finally carry out with the aid of a multi-objective optimization algorithm. The approach used in this study could integrate multiple remote-sensed observations and is readily transferable to other basins.
