Articles | Volume 24, issue 1
https://doi.org/10.5194/nhess-24-199-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-24-199-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
26 Jan 2024
Research article |
| 26 Jan 2024
| 26 Jan 2024
Impact-based flood forecasting in the Greater Horn of Africa
Lorenzo Alfieri
CORRESPONDING AUTHOR
CIMA Research Foundation, University Campus of Savona, Via Armando Magliotto 2, 17100 Savona, Italy
Andrea Libertino
CIMA Research Foundation, University Campus of Savona, Via Armando Magliotto 2, 17100 Savona, Italy
Lorenzo Campo
CIMA Research Foundation, University Campus of Savona, Via Armando Magliotto 2, 17100 Savona, Italy
Francesco Dottori
CIMA Research Foundation, University Campus of Savona, Via Armando Magliotto 2, 17100 Savona, Italy
Simone Gabellani
CIMA Research Foundation, University Campus of Savona, Via Armando Magliotto 2, 17100 Savona, Italy
Tatiana Ghizzoni
CIMA Research Foundation, University Campus of Savona, Via Armando Magliotto 2, 17100 Savona, Italy
Alessandro Masoero
CIMA Research Foundation, University Campus of Savona, Via Armando Magliotto 2, 17100 Savona, Italy
Lauro Rossi
CIMA Research Foundation, University Campus of Savona, Via Armando Magliotto 2, 17100 Savona, Italy
Roberto Rudari
CIMA Research Foundation, University Campus of Savona, Via Armando Magliotto 2, 17100 Savona, Italy
Nicola Testa
CIMA Research Foundation, University Campus of Savona, Via Armando Magliotto 2, 17100 Savona, Italy
Eva Trasforini
CIMA Research Foundation, University Campus of Savona, Via Armando Magliotto 2, 17100 Savona, Italy
Ahmed Amdihun
IGAD Climate Prediction and Applications Centre (ICPAC), Nairobi, Kenya
Jully Ouma
IGAD Climate Prediction and Applications Centre (ICPAC), Nairobi, Kenya
United Nations Office for Disaster Risk Reduction (UNDRR), Regional Office for Africa, Nairobi, Kenya
Luca Rossi
United Nations Office for Disaster Risk Reduction (UNDRR), Regional Office for Africa, Nairobi, Kenya
Yves Tramblay
HSM, University of Montpellier, CNRS, IRD, Montpellier, France
Espace-Dev, Univ. Montpellier, IRD, Montpellier, France
Huan Wu
Southern Marine Science and Engineering Laboratory (Zhuhai), School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai, 519082, China
Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, Sun Yat-sen University, Guangzhou, 510275, China
Marco Massabò
CIMA Research Foundation, University Campus of Savona, Via Armando Magliotto 2, 17100 Savona, Italy
Related authors
Viet Dung Nguyen, Jeroen Aerts, Max Tesselaar, Wouter Botzen, Heidi Kreibich, Lorenzo Alfieri, and Bruno Merz
Nat. Hazards Earth Syst. Sci., 24, 2923–2937, https://doi.org/10.5194/nhess-24-2923-2024, https://doi.org/10.5194/nhess-24-2923-2024, 2024
Short summary
Short summary
Our study explored how seasonal flood forecasts could enhance insurance premium accuracy. Insurers traditionally rely on historical data, yet climate fluctuations influence flood risk. We employed a method that predicts seasonal floods to adjust premiums accordingly. Our findings showed significant year-to-year variations in flood risk and premiums, underscoring the importance of adaptability. Despite limitations, this research aids insurers in preparing for evolving risks.
Giulia Bruno, Doris Duethmann, Francesco Avanzi, Lorenzo Alfieri, Andrea Libertino, and Simone Gabellani
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-416, https://doi.org/10.5194/hess-2022-416, 2022
Manuscript not accepted for further review
Short summary
Short summary
Hydrological models often have issues during droughts. We used the distributed Continuum model over the Po river basin and independent datasets of streamflow (Q), evapotranspiration (ET), and storage. Continuum simulated Q well during wet years and moderate droughts. Performances declined for a severe drought and we explained this drop with an increased uncertainty in ET anomalies in human-affected croplands. These findings provide guidelines for assessments of model robustness during droughts.
Andrea Taramelli, Margherita Righini, Emiliana Valentini, Lorenzo Alfieri, Ignacio Gatti, and Simone Gabellani
Nat. Hazards Earth Syst. Sci., 22, 3543–3569, https://doi.org/10.5194/nhess-22-3543-2022, https://doi.org/10.5194/nhess-22-3543-2022, 2022
Short summary
Short summary
This work aims to support decision-making processes to prioritize effective interventions for flood risk reduction and mitigation for the implementation of flood risk management concepts in urban areas. Our findings provide new insights into vulnerability spatialization of urban flood events for the residential sector, demonstrating that the nature of flood pathways varies spatially and is influenced by landscape characteristics, as well as building features.
Lorenzo Alfieri, Francesco Avanzi, Fabio Delogu, Simone Gabellani, Giulia Bruno, Lorenzo Campo, Andrea Libertino, Christian Massari, Angelica Tarpanelli, Dominik Rains, Diego G. Miralles, Raphael Quast, Mariette Vreugdenhil, Huan Wu, and Luca Brocca
Hydrol. Earth Syst. Sci., 26, 3921–3939, https://doi.org/10.5194/hess-26-3921-2022, https://doi.org/10.5194/hess-26-3921-2022, 2022
Short summary
Short summary
This work shows advances in high-resolution satellite data for hydrology. We performed hydrological simulations for the Po River basin using various satellite products, including precipitation, evaporation, soil moisture, and snow depth. Evaporation and snow depth improved a simulation based on high-quality ground observations. Interestingly, a model calibration relying on satellite data skillfully reproduces observed discharges, paving the way to satellite-driven hydrological applications.
Francesco Dottori, Lorenzo Alfieri, Alessandra Bianchi, Jon Skoien, and Peter Salamon
Earth Syst. Sci. Data, 14, 1549–1569, https://doi.org/10.5194/essd-14-1549-2022, https://doi.org/10.5194/essd-14-1549-2022, 2022
Short summary
Short summary
We present a set of hazard maps for river flooding for Europe and the Mediterranean basin. The maps depict inundation extent and depth for flood probabilities for up to 1-in-500-year flood hazards and are based on hydrological and hydrodynamic models driven by observed climatology. The maps can identify two-thirds of the flood extent reported by official flood maps, with increasing skill for higher-magnitude floods. The maps are used for evaluating present and future impacts of river floods.
Shaun Harrigan, Ervin Zsoter, Lorenzo Alfieri, Christel Prudhomme, Peter Salamon, Fredrik Wetterhall, Christopher Barnard, Hannah Cloke, and Florian Pappenberger
Earth Syst. Sci. Data, 12, 2043–2060, https://doi.org/10.5194/essd-12-2043-2020, https://doi.org/10.5194/essd-12-2043-2020, 2020
Short summary
Short summary
A new river discharge reanalysis dataset is produced operationally by coupling ECMWF's latest global atmospheric reanalysis, ERA5, with the hydrological modelling component of the Global Flood Awareness System (GloFAS). The GloFAS-ERA5 reanalysis is a global gridded dataset with a horizontal resolution of 0.1° at a daily time step and is freely available from 1979 until near real time. The evaluation against observations shows that the GloFAS-ERA5 reanalysis was skilful in 86 % of catchments.
Guillaume Evin, Benoit Hingray, Guillaume Thirel, Agnès Ducharne, Laurent Strohmenger, Lola Corre, Yves Tramblay, Jean-Philippe Vidal, Jérémie Bonneau, François Colleoni, Joël Gailhard, Florence Habets, Frédéric Hendrickx, Louis Héraut, Peng Huang, Matthieu Le Lay, Claire Magand, Paola Marson, Céline Monteil, Simon Munier, Alix Reverdy, Jean-Michel Soubeyroux, Yoann Robin, Jean-Pierre Vergnes, Mathieu Vrac, and Eric Sauquet
EGUsphere, https://doi.org/10.5194/egusphere-2025-2727, https://doi.org/10.5194/egusphere-2025-2727, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
Short summary
Short summary
Explore2 provides hydrological projections for 1,735 French catchments. Using QUALYPSO, this study assesses uncertainties, including internal variability. By the end of the century, low flows are projected to decline in southern France under high emissions, while other indicators remain uncertain. Emission scenarios and regional climate models are key uncertainty sources. Internal variability is often as large as climate-driven changes.
Alessandro Borre, Daria Ottonelli, Eva Trasforini, Tatiana Ghizzoni, Giacomo Zoppi, Giorgio Boni, and Silvia De Angeli
EGUsphere, https://doi.org/10.5194/egusphere-2025-2379, https://doi.org/10.5194/egusphere-2025-2379, 2025
This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
Short summary
Short summary
This study introduces a generalized mathematical framework to quantify physical damage to assets from concurrent and consecutive hazards over time. Applied to a Puerto Rico case study (Hurricane Maria and the 2019–2020 earthquakes), it shows that ignoring residual damage significantly underestimates total impacts caused by consecutive events. By incorporating amplification effects and recovery dynamics, the framework improves multi-hazard damage assessments for researchers and decision-makers.
Eric Sauquet, Guillaume Evin, Sonia Siauve, Ryma Aissat, Patrick Arnaud, Maud Bérel, Jérémie Bonneau, Flora Branger, Yvan Caballero, François Colléoni, Agnès Ducharne, Joël Gailhard, Florence Habets, Frédéric Hendrickx, Louis Héraut, Benoît Hingray, Peng Huang, Tristan Jaouen, Alexis Jeantet, Sandra Lanini, Matthieu Le Lay, Claire Magand, Louise Mimeau, Céline Monteil, Simon Munier, Charles Perrin, Olivier Robelin, Fabienne Rousset, Jean-Michel Soubeyroux, Laurent Strohmenger, Guillaume Thirel, Flore Tocquer, Yves Tramblay, Jean-Pierre Vergnes, and Jean-Philippe Vidal
EGUsphere, https://doi.org/10.5194/egusphere-2025-1788, https://doi.org/10.5194/egusphere-2025-1788, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
Short summary
Short summary
The Explore2 project has provided an unprecedented set of hydrological projections in terms of the number of hydrological models used and the spatial and temporal resolution. The results have been made available through various media. Under the high-emission scenario, the hydrological models mostly agree on the decrease in seasonal flows in the south of France, confirming its hotspot status, and on the decrease in summer flows throughout France, with the exception of the northern part of France.
Yves Tramblay, Guillaume Thirel, Laurent Strohmenger, Guillaume Evin, Lola Corre, Louis Heraut, and Eric Sauquet
EGUsphere, https://doi.org/10.5194/egusphere-2025-1635, https://doi.org/10.5194/egusphere-2025-1635, 2025
Short summary
Short summary
How climate change impacts floods in France? Using simulations for 3000 rivers in climate projections, results show that flood trends vary depending on the region. In the north, floods may become more severe, but in many other areas, the trends are mixed. Floods from intense rainfall are becoming more frequent, while snowmelt floods are strongly decreasing. Overall, the study shows that understanding what causes floods is key to predicting how they are likely to change with the climate.
Serigne Bassirou Diop, Job Ekolu, Yves Tramblay, Bastien Dieppois, Stefania Grimaldi, Ansoumana Bodian, Juliette Blanchet, Ponnambalam Rameshwaran, Peter Salamon, and Benjamin Sultan
EGUsphere, https://doi.org/10.5194/egusphere-2025-130, https://doi.org/10.5194/egusphere-2025-130, 2025
Short summary
Short summary
West Africa is very vulnerable to rivers floods. Current flood hazards are poorly understood due to limited data. This study is filling this knowledge gap using recent databases and two regional hydrological models to analyze changes in flood risk under two climate scenarios. Results show that most areas will see more frequent and severe floods, with some increasing by over 45 %. These findings stress the urgent need for climate-resilient strategies to protect communities and infrastructure.
Giulia Blandini, Francesco Avanzi, Lorenzo Campo, Simone Gabellani, Kristoffer Aalstad, Manuela Girotto, Satoru Yamaguchi, Hiroyuki Hirashima, and Luca Ferraris
EGUsphere, https://doi.org/10.5194/egusphere-2025-423, https://doi.org/10.5194/egusphere-2025-423, 2025
Short summary
Short summary
Reliable SWE and snow depth estimates are key for water management in snow regions. To tackle computational challenges in data assimilation, we suggest a Long Short-Term Memory neural network for operational data assimilation in snow hydrology. Once trained, it cuts computation by 70 % versus an EnKF, with a slight RMSE increase (+6 mm SWE, +6 cm snow depth). This work advances deep learning in snow hydrology, offering an efficient, scalable, and low-cost modeling framework.
Ather Abbas, Yuan Yang, Ming Pan, Yves Tramblay, Chaopeng Shen, Haoyu Ji, Solomon H. Gebrechorkos, Florian Pappenberger, Jong Cheol Pyo, Dapeng Feng, George Huffman, Phu Nguyen, Christian Massari, Luca Brocca, Tan Jackson, and Hylke E. Beck
EGUsphere, https://doi.org/10.5194/egusphere-2024-4194, https://doi.org/10.5194/egusphere-2024-4194, 2025
Short summary
Short summary
Our study evaluated 23 precipitation datasets using a hydrological model at global scale to assess their suitability and accuracy. We found that MSWEP V2.8 excels due to its ability to integrate data from multiple sources, while others, such as IMERG and JRA-3Q, demonstrated strong regional performances. This research assists in selecting the appropriate dataset for applications in water resource management, hazard assessment, agriculture, and environmental monitoring.
Dominik Paprotny, Belinda Rhein, Michalis I. Vousdoukas, Paweł Terefenko, Francesco Dottori, Simon Treu, Jakub Śledziowski, Luc Feyen, and Heidi Kreibich
Hydrol. Earth Syst. Sci., 28, 3983–4010, https://doi.org/10.5194/hess-28-3983-2024, https://doi.org/10.5194/hess-28-3983-2024, 2024
Short summary
Short summary
Long-term trends in flood losses are regulated by multiple factors, including climate variation, population and economic growth, land-use transitions, reservoir construction, and flood risk reduction measures. Here, we reconstruct the factual circumstances in which almost 15 000 potential riverine, coastal and compound floods in Europe occurred between 1950 and 2020. About 10 % of those events are reported to have caused significant socioeconomic impacts.
Viet Dung Nguyen, Jeroen Aerts, Max Tesselaar, Wouter Botzen, Heidi Kreibich, Lorenzo Alfieri, and Bruno Merz
Nat. Hazards Earth Syst. Sci., 24, 2923–2937, https://doi.org/10.5194/nhess-24-2923-2024, https://doi.org/10.5194/nhess-24-2923-2024, 2024
Short summary
Short summary
Our study explored how seasonal flood forecasts could enhance insurance premium accuracy. Insurers traditionally rely on historical data, yet climate fluctuations influence flood risk. We employed a method that predicts seasonal floods to adjust premiums accordingly. Our findings showed significant year-to-year variations in flood risk and premiums, underscoring the importance of adaptability. Despite limitations, this research aids insurers in preparing for evolving risks.
Nils Poncet, Philippe Lucas-Picher, Yves Tramblay, Guillaume Thirel, Humberto Vergara, Jonathan Gourley, and Antoinette Alias
Nat. Hazards Earth Syst. Sci., 24, 1163–1183, https://doi.org/10.5194/nhess-24-1163-2024, https://doi.org/10.5194/nhess-24-1163-2024, 2024
Short summary
Short summary
High-resolution convection-permitting climate models (CPMs) are now available to better simulate rainstorm events leading to flash floods. In this study, two hydrological models are compared to simulate floods in a Mediterranean basin, showing a better ability of the CPM to reproduce flood peaks compared to coarser-resolution climate models. Future projections are also different, with a projected increase for the most severe floods and a potential decrease for the most frequent events.
Francesca Munerol, Francesco Avanzi, Eleonora Panizza, Marco Altamura, Simone Gabellani, Lara Polo, Marina Mantini, Barbara Alessandri, and Luca Ferraris
Geosci. Commun., 7, 1–15, https://doi.org/10.5194/gc-7-1-2024, https://doi.org/10.5194/gc-7-1-2024, 2024
Short summary
Short summary
To contribute to advancing education in a warming climate and prepare the next generations to play their role in future societies, we designed “Water and Us”, a three-module initiative focusing on the natural and anthropogenic water cycle, climate change, and conflicts. This study aims to introduce the initiative's educational objectives, methods, and early results.
Giulia Blandini, Francesco Avanzi, Simone Gabellani, Denise Ponziani, Hervé Stevenin, Sara Ratto, Luca Ferraris, and Alberto Viglione
The Cryosphere, 17, 5317–5333, https://doi.org/10.5194/tc-17-5317-2023, https://doi.org/10.5194/tc-17-5317-2023, 2023
Short summary
Short summary
Automatic snow depth data are a valuable source of information for hydrologists, but they also tend to be noisy. To maximize the value of these measurements for real-world applications, we developed an automatic procedure to differentiate snow cover from grass or bare ground data, as well as to detect random errors. This procedure can enhance snow data quality, thus providing more reliable data for snow models.
Laurent Strohmenger, Eric Sauquet, Claire Bernard, Jérémie Bonneau, Flora Branger, Amélie Bresson, Pierre Brigode, Rémy Buzier, Olivier Delaigue, Alexandre Devers, Guillaume Evin, Maïté Fournier, Shu-Chen Hsu, Sandra Lanini, Alban de Lavenne, Thibault Lemaitre-Basset, Claire Magand, Guilherme Mendoza Guimarães, Max Mentha, Simon Munier, Charles Perrin, Tristan Podechard, Léo Rouchy, Malak Sadki, Myriam Soutif-Bellenger, François Tilmant, Yves Tramblay, Anne-Lise Véron, Jean-Philippe Vidal, and Guillaume Thirel
Hydrol. Earth Syst. Sci., 27, 3375–3391, https://doi.org/10.5194/hess-27-3375-2023, https://doi.org/10.5194/hess-27-3375-2023, 2023
Short summary
Short summary
We present the results of a large visual inspection campaign of 674 streamflow time series in France. The objective was to detect non-natural records resulting from instrument failure or anthropogenic influences, such as hydroelectric power generation or reservoir management. We conclude that the identification of flaws in flow time series is highly dependent on the objectives and skills of individual evaluators, and we raise the need for better practices for data cleaning.
Yves Tramblay, Patrick Arnaud, Guillaume Artigue, Michel Lang, Emmanuel Paquet, Luc Neppel, and Eric Sauquet
Hydrol. Earth Syst. Sci., 27, 2973–2987, https://doi.org/10.5194/hess-27-2973-2023, https://doi.org/10.5194/hess-27-2973-2023, 2023
Short summary
Short summary
Mediterranean floods are causing major damage, and recent studies have shown that, despite the increase in intense rainfall, there has been no increase in river floods. This study reveals that the seasonality of floods changed in the Mediterranean Basin during 1959–2021. There was also an increased frequency of floods linked to short episodes of intense rain, associated with a decrease in soil moisture. These changes need to be taken into consideration to adapt flood warning systems.
Francesco Avanzi, Simone Gabellani, Fabio Delogu, Francesco Silvestro, Flavio Pignone, Giulia Bruno, Luca Pulvirenti, Giuseppe Squicciarino, Elisabetta Fiori, Lauro Rossi, Silvia Puca, Alexander Toniazzo, Pietro Giordano, Marco Falzacappa, Sara Ratto, Hervè Stevenin, Antonio Cardillo, Matteo Fioletti, Orietta Cazzuli, Edoardo Cremonese, Umberto Morra di Cella, and Luca Ferraris
Earth Syst. Sci. Data, 15, 639–660, https://doi.org/10.5194/essd-15-639-2023, https://doi.org/10.5194/essd-15-639-2023, 2023
Short summary
Short summary
Snow cover has profound implications for worldwide water supply and security, but knowledge of its amount and distribution across the landscape is still elusive. We present IT-SNOW, a reanalysis comprising daily maps of snow amount and distribution across Italy for 11 snow seasons from September 2010 to August 2021. The reanalysis was validated using satellite images and snow measurements and will provide highly needed data to manage snow water resources in a warming climate.
Giulia Bruno, Doris Duethmann, Francesco Avanzi, Lorenzo Alfieri, Andrea Libertino, and Simone Gabellani
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-416, https://doi.org/10.5194/hess-2022-416, 2022
Manuscript not accepted for further review
Short summary
Short summary
Hydrological models often have issues during droughts. We used the distributed Continuum model over the Po river basin and independent datasets of streamflow (Q), evapotranspiration (ET), and storage. Continuum simulated Q well during wet years and moderate droughts. Performances declined for a severe drought and we explained this drop with an increased uncertainty in ET anomalies in human-affected croplands. These findings provide guidelines for assessments of model robustness during droughts.
Andrea Taramelli, Margherita Righini, Emiliana Valentini, Lorenzo Alfieri, Ignacio Gatti, and Simone Gabellani
Nat. Hazards Earth Syst. Sci., 22, 3543–3569, https://doi.org/10.5194/nhess-22-3543-2022, https://doi.org/10.5194/nhess-22-3543-2022, 2022
Short summary
Short summary
This work aims to support decision-making processes to prioritize effective interventions for flood risk reduction and mitigation for the implementation of flood risk management concepts in urban areas. Our findings provide new insights into vulnerability spatialization of urban flood events for the residential sector, demonstrating that the nature of flood pathways varies spatially and is influenced by landscape characteristics, as well as building features.
Lorenzo Alfieri, Francesco Avanzi, Fabio Delogu, Simone Gabellani, Giulia Bruno, Lorenzo Campo, Andrea Libertino, Christian Massari, Angelica Tarpanelli, Dominik Rains, Diego G. Miralles, Raphael Quast, Mariette Vreugdenhil, Huan Wu, and Luca Brocca
Hydrol. Earth Syst. Sci., 26, 3921–3939, https://doi.org/10.5194/hess-26-3921-2022, https://doi.org/10.5194/hess-26-3921-2022, 2022
Short summary
Short summary
This work shows advances in high-resolution satellite data for hydrology. We performed hydrological simulations for the Po River basin using various satellite products, including precipitation, evaporation, soil moisture, and snow depth. Evaporation and snow depth improved a simulation based on high-quality ground observations. Interestingly, a model calibration relying on satellite data skillfully reproduces observed discharges, paving the way to satellite-driven hydrological applications.
Francesco Avanzi, Simone Gabellani, Fabio Delogu, Francesco Silvestro, Edoardo Cremonese, Umberto Morra di Cella, Sara Ratto, and Hervé Stevenin
Geosci. Model Dev., 15, 4853–4879, https://doi.org/10.5194/gmd-15-4853-2022, https://doi.org/10.5194/gmd-15-4853-2022, 2022
Short summary
Short summary
Knowing in real time how much snow and glacier ice has accumulated across the landscape has significant implications for water-resource management and flood control. This paper presents a computer model – S3M – allowing scientists and decision makers to predict snow and ice accumulation during winter and the subsequent melt during spring and summer. S3M has been employed for real-world flood forecasting since the early 2000s but is here being made open source for the first time.
Yves Tramblay and Pere Quintana Seguí
Nat. Hazards Earth Syst. Sci., 22, 1325–1334, https://doi.org/10.5194/nhess-22-1325-2022, https://doi.org/10.5194/nhess-22-1325-2022, 2022
Short summary
Short summary
Monitoring soil moisture is important during droughts, but very few measurements are available. Consequently, land-surface models are essential tools for reproducing soil moisture dynamics. In this study, a hybrid approach allowed for regionalizing soil water content using a machine learning method. This approach proved to be efficient, compared to the use of soil property maps, to run a simple soil moisture accounting model, and therefore it can be applied in various regions.
Francesco Dottori, Lorenzo Alfieri, Alessandra Bianchi, Jon Skoien, and Peter Salamon
Earth Syst. Sci. Data, 14, 1549–1569, https://doi.org/10.5194/essd-14-1549-2022, https://doi.org/10.5194/essd-14-1549-2022, 2022
Short summary
Short summary
We present a set of hazard maps for river flooding for Europe and the Mediterranean basin. The maps depict inundation extent and depth for flood probabilities for up to 1-in-500-year flood hazards and are based on hydrological and hydrodynamic models driven by observed climatology. The maps can identify two-thirds of the flood extent reported by official flood maps, with increasing skill for higher-magnitude floods. The maps are used for evaluating present and future impacts of river floods.
Christian Massari, Francesco Avanzi, Giulia Bruno, Simone Gabellani, Daniele Penna, and Stefania Camici
Hydrol. Earth Syst. Sci., 26, 1527–1543, https://doi.org/10.5194/hess-26-1527-2022, https://doi.org/10.5194/hess-26-1527-2022, 2022
Short summary
Short summary
Droughts are a creeping disaster, meaning that their onset, duration and recovery are challenging to monitor and forecast. Here, we provide further evidence of an additional challenge of droughts, i.e. the fact that the deficit in water supply during droughts is generally much more than expected based on the observed decline in precipitation. At a European scale we explain this with enhanced evapotranspiration, sustained by higher atmospheric demand for moisture during such dry periods.
Josias Láng-Ritter, Marc Berenguer, Francesco Dottori, Milan Kalas, and Daniel Sempere-Torres
Hydrol. Earth Syst. Sci., 26, 689–709, https://doi.org/10.5194/hess-26-689-2022, https://doi.org/10.5194/hess-26-689-2022, 2022
Short summary
Short summary
During flood events, emergency managers such as civil protection authorities rely on flood forecasts to make informed decisions. In the current practice, they monitor several separate forecasts, each one of them covering a different type of flooding. This can be time-consuming and confusing, ultimately compromising the effectiveness of the emergency response. This work illustrates how the automatic combination of flood type-specific impact forecasts can improve decision support systems.
Francesco Avanzi, Giulia Ercolani, Simone Gabellani, Edoardo Cremonese, Paolo Pogliotti, Gianluca Filippa, Umberto Morra di Cella, Sara Ratto, Hervè Stevenin, Marco Cauduro, and Stefano Juglair
Hydrol. Earth Syst. Sci., 25, 2109–2131, https://doi.org/10.5194/hess-25-2109-2021, https://doi.org/10.5194/hess-25-2109-2021, 2021
Short summary
Short summary
Precipitation tends to increase with elevation, but the magnitude and distribution of this enhancement remain poorly understood. By leveraging over 11 000 spatially distributed, manual measurements of snow depth (snow courses) upstream of two reservoirs in the western European Alps, we show that these courses bear a characteristic signature of orographic precipitation. This opens a window of opportunity for improved modeling accuracy and, ultimately, our understanding of the water budget.
Yves Tramblay, Nathalie Rouché, Jean-Emmanuel Paturel, Gil Mahé, Jean-François Boyer, Ernest Amoussou, Ansoumana Bodian, Honoré Dacosta, Hamouda Dakhlaoui, Alain Dezetter, Denis Hughes, Lahoucine Hanich, Christophe Peugeot, Raphael Tshimanga, and Patrick Lachassagne
Earth Syst. Sci. Data, 13, 1547–1560, https://doi.org/10.5194/essd-13-1547-2021, https://doi.org/10.5194/essd-13-1547-2021, 2021
Short summary
Short summary
This dataset provides a set of hydrometric indices for about 1500 stations across Africa with daily discharge data. These indices represent mean flow characteristics and extremes (low flows and floods), allowing us to study the long-term evolution of hydrology in Africa and support the modeling efforts that aim at reducing the vulnerability of African countries to hydro-climatic variability.
Kees C. H. van Ginkel, Francesco Dottori, Lorenzo Alfieri, Luc Feyen, and Elco E. Koks
Nat. Hazards Earth Syst. Sci., 21, 1011–1027, https://doi.org/10.5194/nhess-21-1011-2021, https://doi.org/10.5194/nhess-21-1011-2021, 2021
Short summary
Short summary
This study presents a state-of-the-art approach to assess flood damage for each unique road segment in Europe. We find a mean total flood risk of EUR 230 million per year for all individual road segments combined. We identify flood hotspots in the Alps, along the Sava River, and on the Scandinavian Peninsula. To achieve this, we propose a new set of damage curves for roads and challenge the community to validate and improve these. Analysis of network effects can be easily added to our analysis.
Louise Mimeau, Yves Tramblay, Luca Brocca, Christian Massari, Stefania Camici, and Pascal Finaud-Guyot
Hydrol. Earth Syst. Sci., 25, 653–669, https://doi.org/10.5194/hess-25-653-2021, https://doi.org/10.5194/hess-25-653-2021, 2021
Short summary
Short summary
Soil moisture is a key variable related to droughts and flood genesis, but little is known about the evolution of soil moisture under climate change. Here, using a simulation approach, we show that changes in soil moisture are driven by changes in precipitation intermittence rather than changes in precipitation intensity or in temperature.
El Mahdi El Khalki, Yves Tramblay, Christian Massari, Luca Brocca, Vincent Simonneaux, Simon Gascoin, and Mohamed El Mehdi Saidi
Nat. Hazards Earth Syst. Sci., 20, 2591–2607, https://doi.org/10.5194/nhess-20-2591-2020, https://doi.org/10.5194/nhess-20-2591-2020, 2020
Short summary
Short summary
In North Africa, the vulnerability to floods is high, and there is a need to improve the flood-forecasting systems. Remote-sensing and reanalysis data can palliate the lack of in situ measurements, in particular for soil moisture, which is a crucial parameter to consider when modeling floods. In this study we provide an evaluation of recent globally available soil moisture products for flood modeling in Morocco.
Shaun Harrigan, Ervin Zsoter, Lorenzo Alfieri, Christel Prudhomme, Peter Salamon, Fredrik Wetterhall, Christopher Barnard, Hannah Cloke, and Florian Pappenberger
Earth Syst. Sci. Data, 12, 2043–2060, https://doi.org/10.5194/essd-12-2043-2020, https://doi.org/10.5194/essd-12-2043-2020, 2020
Short summary
Short summary
A new river discharge reanalysis dataset is produced operationally by coupling ECMWF's latest global atmospheric reanalysis, ERA5, with the hydrological modelling component of the Global Flood Awareness System (GloFAS). The GloFAS-ERA5 reanalysis is a global gridded dataset with a horizontal resolution of 0.1° at a daily time step and is freely available from 1979 until near real time. The evaluation against observations shows that the GloFAS-ERA5 reanalysis was skilful in 86 % of catchments.
Cited articles
Alfieri, L., Burek, P., Dutra, E., Krzeminski, B., Muraro, D., Thielen, J., and Pappenberger, F.: GloFAS – global ensemble streamflow forecasting and flood early warning, Hydrol. Earth Syst. Sci., 17, 1161–1175, https://doi.org/10.5194/hess-17-1161-2013, 2013.
Alfieri, L., Bisselink, B., Dottori, F., Naumann, G., de Roo, A., Salamon, P., Wyser, K., and Feyen, L.: Global projections of river flood risk in a warmer world, Earths Future, 5, 171–182, https://doi.org/10.1002/2016EF000485, 2017.
Alfieri, L., Zsoter, E., Harrigan, S., Aga Hirpa, F., Lavaysse, C., Prudhomme, C., and Salamon, P.: Range-dependent thresholds for global flood early warning, J. Hydrol. X, 4, 100034, https://doi.org/10.1016/j.hydroa.2019.100034, 2019.
Alfieri, L., Lorini, V., Hirpa, F. A., Harrigan, S., Zsoter, E., Prudhomme, C., and Salamon, P.: A global streamflow reanalysis for 1980–2018, J. Hydrol. X, 6, 100049, https://doi.org/10.1016/j.hydroa.2019.100049, 2020.
Alfieri, L., Avanzi, F., Delogu, F., Gabellani, S., Bruno, G., Campo, L., Libertino, A., Massari, C., Tarpanelli, A., Rains, D., Miralles, D. G., Quast, R., Vreugdenhil, M., Wu, H., and Brocca, L.: High-resolution satellite products improve hydrological modeling in northern Italy, Hydrol. Earth Syst. Sci., 26, 3921–3939, https://doi.org/10.5194/hess-26-3921-2022, 2022a.
Alfieri, L., Libertino, A., Campo, L., Ghizzoni, T., Masoero, A., Menchise, C., Poletti, M. L., Gabellani, S., Rossi, L., Rudari, R., Rossi, L., Mouakkid Soltesova, K., Gatkuoth, K., Ouma, J., Amdihun, A., Nshimirimana, G., Tramblay, Y., and Massabò, M.: Developing an operational impact-based flood forecasting system for the Greater Horn of Africa region, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8680, https://doi.org/10.5194/egusphere-egu22-8680, 2022b.
Arsenault, K. R., Shukla, S., Hazra, A., Getirana, A., McNally, A., Kumar, S. V., Koster, R. D., Peters-Lidard, C. D., Zaitchik, B. F., Badr, H., Jung, H. C., Narapusetty, B., Navari, M., Wang, S., Mocko, D. M., Funk, C., Harrison, L., Husak, G. J., Adoum, A., Galu, G., Magadzire, T., Roningen, J., Shaw, M., Eylander, J., Bergaoui, K., McDonnell, R. A., and Verdin, J. P.: The NASA Hydrological Forecast System for Food and Water Security Applications, B. Am. Meteorol. Soc., 101, E1007–E1025, https://doi.org/10.1175/BAMS-D-18-0264.1, 2020.
Awange, J. l., Ferreira, V. G., Forootan, E., Khandu, Andam-Akorful, S. A., Agutu, N. O., and He, X. F.: Uncertainties in remotely sensed precipitation data over Africa, Int. J. Climatol., 36, 303–323, https://doi.org/10.1002/joc.4346, 2016.
Beck, H. E., Zimmermann, N. E., McVicar, T. R., Vergopolan, N., Berg, A., and Wood, E. F.: Present and future Köppen-Geiger climate classification maps at 1-km resolution, Sci. Data, 5, 180214, https://doi.org/10.1038/sdata.2018.214, 2018.
Cantoni, E., Tramblay, Y., Grimaldi, S., Salamon, P., Dakhlaoui, H., Dezetter, A., and Thiemig, V.: Hydrological performance of the ERA5 reanalysis for flood modeling in Tunisia with the LISFLOOD and GR4J models, J. Hydrol. Reg. Stud., 42, 101169, https://doi.org/10.1016/j.ejrh.2022.101169, 2022.
Christian Aid: Counting The Cost 2022: A year of climate breakdown, https://www.christianaid.org.uk/sites/default/files/2022-12/counting-the-cost-2022.pdf (last access: 19 January 2024), 2022.
de Bono, A. and Chatenoux, B.: A global exposure model for GAR 2015, UNEP-GRID Geneva, GAR, https://www.researchgate.net/profile/Andrea-De-Bono/publication/275639260_A_Global_Exposure_Model_for_GAR_2015/links/5540dc450cf2b790436aadf1/A-Global-Exposure-Model-for-GAR-2015.pdf (last access: 17 January 2024), 2015.
De Groeve, T., Poljansek, K., and Vernaccini, L.: Index for risk management – INFORM, JRC Sci Policy Reports – Eur. Comm., 96, 636388, https://doi.org/10.2788/78658, 2015.
Delogu, F., Silvestro, F., Gabellani, S., Ercolani, G., and Libertino, A.: c-hydro/hmc-dev, Zenodo [code], https://doi.org/10.5281/zenodo.5032399, 2021.
Di Baldassarre, G., Montanari, A., Lins, H., Koutsoyiannis, D., Brandimarte, L., and Blöschl, G.: Flood fatalities in Africa: From diagnosis to mitigation, Geophys. Res. Lett., 37, L22402, https://doi.org/10.1029/2010GL045467, 2010.
Di Vittorio, C. A. and Georgakakos, A. P.: Hydrologic Modeling of the Sudd Wetland using Satellite-based Data, J. Hydrol. Reg. Stud., 37, 100922, https://doi.org/10.1016/j.ejrh.2021.100922, 2021.
Dottori, F., Salamon, P., Bianchi, A., Alfieri, L., Hirpa, F. A., and Feyen, L.: Development and evaluation of a framework for global flood hazard mapping, Adv. Water Resour., 94, 87–102, https://doi.org/10.1016/j.advwatres.2016.05.002, 2016.
Douglas, I.: Flooding in African cities, scales of causes, teleconnections, risks, vulnerability and impacts, Int. J. Disast. Risk Re., 26, 34–42, https://doi.org/10.1016/j.ijdrr.2017.09.024, 2017.
EM-DAT: The OFDA/CRED International Disaster Database,, Université Catholique de Louvain, Brussels (Belgium), https://www.emdat.be (last access: 19 January 2024), 2023.
ESA: Land Cover CCI Product User Guide Version 2. Tech. Rep., https://www.esa-landcover-cci.org/?q=webfm_send/84 (last access: 22 January 2024), 2017 (data available at: https://maps.elie.ucl.ac.be/CCI/viewer/download.php).
European Commission: River Flood Hazard Maps at European and Global Scale, European Commission [data set], https://data.jrc.ec.europa.eu/collection/id-0054, 2023.
FAO: “The Sudan | 2020 Flood Impact Rapid Assessment”, Food and Agriculture Organization of the United Nations, September 2020, https://www.fao.org/3/cb1463en/CB1463EN.pdf (last access: 19 January 2024), 2020.
FAO and WFP: Special Report – 2021 FAO/WFP Crop and Food Security Assessment Mission (CFSAM) to the Republic of South Sudan, 9 June 2022, Rome, https://doi.org/10.4060/cc0474en, 2022.
Finney, D. L., Marsham, J. H., Walker, D. P., Birch, C. E., Woodhams, B. J., Jackson, L. S., and Hardy, S.: The effect of westerlies on East African rainfall and the associated role of tropical cyclones and the Madden–Julian Oscillation, Q. J. Roy. Meteor. Soc., 146, 647–664, https://doi.org/10.1002/qj.3698, 2020.
Giannoni, F., Roth, G., and Rudari, R.: A semi-distributed rainfall-runoff model based on a geomorphologic approach, Phys. Chem. Earth Pt. B, 25, 665–671, https://doi.org/10.1016/s1464-1909(00)00082-4, 2000.
Haile, G. G., Tang, Q., Hosseini-Moghari, S.-M., Liu, X., Gebremicael, T. G., Leng, G., Kebede, A., Xu, X., and Yun, X.: Projected Impacts of Climate Change on Drought Patterns Over East Africa, Earths Future, 8, e2020EF001502, https://doi.org/10.1029/2020EF001502, 2020.
Hales, R. C., Nelson, E. J., Souffront, M., Gutierrez, A. L., Prudhomme, C., Kopp, S., Ames, D. P., Williams, G. P., and Jones, N. L.: Advancing global hydrologic modeling with the GEOGloWS ECMWF streamflow service, J. Flood Risk Manag., e12859, https://doi.org/10.1111/jfr3.12859, 2022.
Hengl, T., de Jesus, J. M. , Heuvelink, G. B. M., Gonzalez, M. R., Kilibarda, M., Blagotić, A., Shangguan, W., Wright, M. N., Geng, X., Bauer-Marschallinger, B., Guevara, M. A., Vargas, R., MacMillan, R. A., Batjes, N. H., Leenaars, J. G. B., Ribeiro, E., Wheeler, I., Mantel, S., and Kempen, B.: SoilGrids250m: Global gridded soil information based on machine learning, PLOS ONE, 12, e0169748, https://doi.org/10.1371/journal.pone.0169748, 2017 (data available at: https://data.isric.org/geonetwork/srv/ita/catalog.search#/metadata/e33e75c0-d9ab-46b5-a915-cb344345099c).
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020 (data available at: https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview).
Hirpa, F. A., Alfieri, L., Lees, T., Peng, J., Dyer, E., and Dadson, S. J.: Streamflow response to climate change in the Greater Horn of Africa, Clim. Change, 156, 341–363, https://doi.org/10.1007/s10584-019-02547-x, 2019.
Hosking, J. R. M.: L-Moments: Analysis and Estimation of Distributions Using Linear Combinations of Order Statistics, J. Roy. Stat. Soc. B, 52, 105–124, 1990.
ICPAC: Flood Displacement Risk Profile, https://www.icpac.net/documents/747/flood-displacement-risk-profile.pdf (last access: 19 January 2024), 2023.
INFORM: European Commission, DRMKC – Disaster Risk Management Knowledge Centre, https://drmkc.jrc.ec.europa.eu/inform-index/INFORM-Risk/Results-and-data/moduleId/1782/id/469/controller/Admin/action/Results, last access: 17 January 2024.
JAXA: JAXA Global Rainfall Watch, Sharaku [data set], https://sharaku.eorc.jaxa.jp/GSMaP/, 2024.
Knoben, W. J. M., Freer, J. E., and Woods, R. A.: Technical note: Inherent benchmark or not? Comparing Nash–Sutcliffe and Kling–Gupta efficiency scores, Hydrol. Earth Syst. Sci., 23, 4323–4331, https://doi.org/10.5194/hess-23-4323-2019, 2019.
Kubota, T., Aonashi, K., Ushio, T., Shige, S., Takayabu, Y. N., Kachi, M., Arai, Y., Tashima, T., Masaki, T., Kawamoto, N., Mega, T., Yamamoto, M. K., Hamada, A., Yamaji, M., Liu, G., and Oki, R.: Global Satellite Mapping of Precipitation (GSMaP) Products in the GPM Era, in: Satellite Precipitation Measurement, Vol. 1, edited by: Levizzani, V., Kidd, C., Kirschbaum, D. B., Kummerow, C. D., Nakamura, K., and Turk, F. J., Springer International Publishing, Cham, 355–373, https://doi.org/10.1007/978-3-030-24568-9_20, 2020.
Laiolo, P., Gabellani, S., Rebora, N., Rudari, R., Ferraris, L., Ratto, S., Stevenin, H., and Cauduro, M.: Validation of the Flood-PROOFS probabilistic forecasting system, Hydrol. Process., 28, 3466–3481, https://doi.org/10.1002/hyp.9888, 2013.
Lienert, J., Andersson, J. C. M., Hofmann, D., Silva Pinto, F., and Kuller, M.: The role of multi-criteria decision analysis in a transdisciplinary process: co-developing a flood forecasting system in western Africa, Hydrol. Earth Syst. Sci., 26, 2899–2922, https://doi.org/10.5194/hess-26-2899-2022, 2022.
Lyon, B.: Seasonal Drought in the Greater Horn of Africa and Its Recent Increase during the March–May Long Rains, J. Climate, 27, 7953–7975, https://doi.org/10.1175/JCLI-D-13-00459.1, 2014.
Matanó, A., de Ruiter, M. C., Koehler, J., Ward, P. J., and Van Loon, A. F.: Caught Between Extremes: Understanding Human-Water Interactions During Drought-To-Flood Events in the Horn of Africa, Earths Future, 10, e2022EF002747, https://doi.org/10.1029/2022EF002747, 2022.
Maystadt, J.-F., Calderone, M., and You, L.: Local warming and violent conflict in North and South Sudan, J. Econ. Geogr., 15, 649–671, https://doi.org/10.1093/jeg/lbu033, 2015.
Messager, M. L., Lehner, B., Grill, G., Nedeva, I., and Schmitt, O.: Estimating the volume and age of water stored in global lakes using a geo-statistical approach, Nat. Commun., 7, 13603, https://doi.org/10.1038/ncomms13603, 2016 (data available at: https://www.hydrosheds.org/products/hydrolakes).
Mulligan, M., Lehner, B., Zarfl, C., Thieme, M., Beames, P., Soesbergen, A. van, Higgins, J., Januchowski-Hartley, S. R., Brauman, K. A., Felice, L. D., Wen, Q., Leaniz, C. G. de, Belletti, B., Mandle, L., Yang, X., Wang, J., and Mazany-Wright, N.: Global Dam Watch: curated data and tools for management and decision making, Environ. Res., 1, 033003, https://doi.org/10.1088/2634-4505/ac333a, 2021 (data available at: https://www.globaldamwatch.org/directory).
NCEP: Global Forecast System (GFS), NCEP [data set], https://nomads.ncep.noaa.gov/gribfilter.php?ds=gdas_0p25, last access: 17 January 2024.
Nicholson, S. E.: Climate and climatic variability of rainfall over eastern Africa, Rev. Geophys., 55, 590–635, https://doi.org/10.1002/2016RG000544, 2017.
Osima, S., Indasi, V. S., Zaroug, M., Endris, H. S., Gudoshava, M., Misiani, H. O., Nimusiima, A., Anyah, R. O., Otieno, G., Ogwang, B. A., Jain, S., Kondowe, A. L., Mwangi, E., Lennard, C., Nikulin, G., and Dosio, A.: Projected climate over the Greater Horn of Africa under 1.5 ∘C and 2 ∘C global warming, Environ. Res. Lett., 13, 065004, https://doi.org/10.1088/1748-9326/aaba1b, 2018.
Peter, B. G., Cohen, S., Lucey, R., Munasinghe, D., Raney, A., and Brakenridge, G. R.: Google Earth Engine Implementation of the Floodwater Depth Estimation Tool (FwDET-GEE) for Rapid and Large Scale Flood Analysis, IEEE Geosci. Remote S., 19, 1–5, https://doi.org/10.1109/LGRS.2020.3031190, 2022.
Pianosi, F., Sarrazin, F., and Wagener, T.: A Matlab toolbox for Global Sensitivity Analysis, Environ. Model. Softw., 70, 80–85, https://doi.org/10.1016/j.envsoft.2015.04.009, 2015.
Richardson, J., Calow, R., Pichon, F., New, S., and Osborne, R.: Climate risk report for the East Africa region, Met Office, ODI, FCDO, https://www.metoffice.gov.uk/binaries/content/assets/metofficegovuk/pdf/services/government/east-africa-climate-risk-report-final.pdf (last access: 19 January 2024), 2022.
Salamon, P., Mctlormick, N., Reimer, C., Clarke, T., Bauer-Marschallinger, B., Wagner, W., Martinis, S., Chow, C., Böhnke, C., Matgen, P., Chini, M., Hostache, R., Molini, L., Fiori, E., and Walli, A.: The New, Systematic Global Flood Monitoring Product of the Copernicus Emergency Management Service, in: 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, Brussels, Belgium, 11–16 July 2021, 1053–1056, https://doi.org/10.1109/IGARSS47720.2021.9554214, 2021.
Silvestro, F., Gabellani, S., Delogu, F., Rudari, R., and Boni, G.: Exploiting remote sensing land surface temperature in distributed hydrological modelling: the example of the Continuum model, Hydrol. Earth Syst. Sci., 17, 39–62, https://doi.org/10.5194/hess-17-39-2013, 2013.
Sheffield, J., Wood, E. F., Chaney, N., Guan, K., Sadri, S., Yuan, X., Olang, L., Amani, A., Ali, A., and Demuth, S.: A drought monitoring and forecasting system for sub-Sahara African water resources and food security, B. Am. Meteorol. Soc., 95, 861–882, 2014.
Shirazi, M. A. and Boersma, L.: A Unifying Quantitative Analysis of Soil Texture, Soil Sci. Soc. Am. J., 48, 142–147, https://doi.org/10.2136/sssaj1984.03615995004800010026x, 1984.
Tabari, H., Hosseinzadehtalaei, P., Thiery, W., and Willems, P.: Amplified Drought and Flood Risk Under Future Socioeconomic and Climatic Change, Earths Future, 9, e2021EF002295, https://doi.org/10.1029/2021EF002295, 2021.
Tramblay, Y., Rouché, N., Paturel, J.-E., Mahé, G., Boyer, J.-F., Amoussou, E., Bodian, A., Dacosta, H., Dakhlaoui, H., Dezetter, A., Hughes, D., Hanich, L., Peugeot, C., Tshimanga, R., and Lachassagne, P.: ADHI: the African Database of Hydrometric Indices (1950–2018), Earth Syst. Sci. Data, 13, 1547–1560, https://doi.org/10.5194/essd-13-1547-2021, 2021.
Trigg, M. A., Birch, C. E., Neal, J. C., Bates, P. D., Smith, A., Sampson, C. C., Yamazaki, D., Hirabayashi, Y., Pappenberger, F., E Dutra, Ward, P. J., Winsemius, H. C., Salamon, P., Dottori, F., Rudari, R., Kappes, M. S., Simpson, A. L., Hadzilacos, G., and Fewtrell, T. J.: The credibility challenge for global fluvial flood risk analysis, Environ. Res. Lett., 11, 094014, https://doi.org/10.1088/1748-9326/11/9/094014, 2016.
UNDRR: Towards an IGAD regional flood risk profile: preliminary results of the regional flood risk assessment, https://www.icpac.net/documents/749/towards-a-regional-flood-risk-profile.pdf (last access: 19 January 2024), 2021.
UNDRR and CRED: The human cost of disasters: an overview of the last 20 years (2000–2019), https://cred.be/sites/default/files/CredCrunch61-Humancost.pdf (last access: 19 January 2024), 2020.
United Nations: World Population Prospects 2022: Data Sources (UN DESA/POP/2022/DC/NO. 9), Department of Economic and Social Affairs, Population Division, https://population.un.org/wpp/Publications/Files/WPP2022_Data_Sources.pdf (last access: 19 January 2024), 2022.
Verdin, K. L.: Hydrologic Derivatives for Modeling and Analysis – A new global high-resolution database, Hydrologic Derivatives for Modeling and Analysis – A new global high-resolution database, U.S. Geological Survey, Reston, VA, https://doi.org/10.3133/ds1053, 2017.
Wang, H. and Yong, B.: Quasi-Global Evaluation of IMERG and GSMaP Precipitation Products over Land Using Gauge Observations, Water, 12, 243, https://doi.org/10.3390/w12010243, 2020.
Wanzala, M. A., Ficchi, A., Cloke, H. L., Stephens, E. M., Badjana, H. M., and Lavers, D. A.: Assessment of global reanalysis precipitation for hydrological modelling in data-scarce regions: A case study of Kenya, J. Hydrol. Reg. Stud., 41, 101105, https://doi.org/10.1016/j.ejrh.2022.101105, 2022.
Wi, S., Yang, Y. C. E., Steinschneider, S., Khalil, A., and Brown, C. M.: Calibration approaches for distributed hydrologic models in poorly gaged basins: implication for streamflow projections under climate change, Hydrol. Earth Syst. Sci., 19, 857–876, https://doi.org/10.5194/hess-19-857-2015, 2015.
Wilks, D. S.: Statistical Methods in the Atmospheric Sciences: An Introduction, electronic version, Elsevier, San Diego, CA, ISBN 978-0-12-751966-1, 2006.
Winsemius, H. C., Aerts, J. C. J. H., van Beek, L. P. H., Bierkens, M. F. P., Bouwman, A., Jongman, B., Kwadijk, J. C. J., Ligtvoet, W., Lucas, P. L., van Vuuren, D. P., and Ward, P. J.: Global drivers of future river flood risk, Nat. Clim. Change, 6, 381–385, https://doi.org/10.1038/nclimate2893, 2016.
Wu, H., Kimball, J. S., Zhou, N., Alfieri, L., Luo, L., Du, J., and Huang, Z.: Evaluation of real-time global flood modeling with satellite surface inundation observations from SMAP, Remote Sens. Environ., 233, 111360, https://doi.org/10.1016/j.rse.2019.111360, 2019.
Zsoter, E., Prudhomme, C., Stephens, E., Pappenberger, F., and Cloke, H.: Using ensemble reforecasts to generate flood thresholds for improved global flood forecasting, J. Flood Risk Manag., 13, e12658, https://doi.org/10.1111/jfr3.12658, 2020.
Short summary
This work describes Flood-PROOFS East Africa, an impact-based flood forecasting system for the Greater Horn of Africa. It is based on hydrological simulations, inundation mapping, and estimation of population and assets exposed to upcoming river floods. The system supports duty officers in African institutions in the daily monitoring of hydro-meteorological disasters. A first evaluation shows the system performance for the catastrophic floods in the Nile River basin in summer 2020.
This work describes Flood-PROOFS East Africa, an impact-based flood forecasting system for the...
Altmetrics
Final-revised paper
Preprint