Articles | Volume 24, issue 2
https://doi.org/10.5194/nhess-24-501-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/nhess-24-501-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
14 Feb 2024
Research article |
| 14 Feb 2024
| 14 Feb 2024
CRHyME (Climatic Rainfall Hydrogeological Modelling Experiment): a new model for geo-hydrological hazard assessment at the basin scale
Andrea Abbate
CORRESPONDING AUTHOR
Ricerca sul Sistema Energetico – RSE, Via Rubattino 54, Milan, Italy
Leonardo Mancusi
Ricerca sul Sistema Energetico – RSE, Via Rubattino 54, Milan, Italy
Francesco Apadula
Ricerca sul Sistema Energetico – RSE, Via Rubattino 54, Milan, Italy
Antonella Frigerio
Ricerca sul Sistema Energetico – RSE, Via Rubattino 54, Milan, Italy
Monica Papini
Dipartimento di Ingegneria Civile e Ambientale (DICA), Politecnico di Milano, Piazza Leonardo da Vinci 32, Milan, Italy
Laura Longoni
CORRESPONDING AUTHOR
Dipartimento di Ingegneria Civile e Ambientale (DICA), Politecnico di Milano, Piazza Leonardo da Vinci 32, Milan, Italy
Related authors
Andrea Abbate, Monica Papini, and Laura Longoni
Nat. Hazards Earth Syst. Sci., 21, 2041–2058, https://doi.org/10.5194/nhess-21-2041-2021, https://doi.org/10.5194/nhess-21-2041-2021, 2021
Short summary
Short summary
In this paper the relation between the intensity of meteorological events and the magnitude of triggered geo-hydrological issues was examined. A back analysis was developed across a region of the central Alps. The meteorological triggers were interpreted using two approaches: the first using local rain gauge data and a new one considering meteorological reanalysis maps. The results obtained were compared and elaborated for defining a magnitude of each geo-hydrological event.
V. Yordanov, X. Q. Truong, M. Corti, L. Longoni, and M. A. Brovelli
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W2-2023, 1089–1096, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-1089-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-1089-2023, 2023
Sourish Basu, Xin Lan, Edward Dlugokencky, Sylvia Michel, Stefan Schwietzke, John B. Miller, Lori Bruhwiler, Youmi Oh, Pieter P. Tans, Francesco Apadula, Luciana V. Gatti, Armin Jordan, Jaroslaw Necki, Motoki Sasakawa, Shinji Morimoto, Tatiana Di Iorio, Haeyoung Lee, Jgor Arduini, and Giovanni Manca
Atmos. Chem. Phys., 22, 15351–15377, https://doi.org/10.5194/acp-22-15351-2022, https://doi.org/10.5194/acp-22-15351-2022, 2022
Short summary
Short summary
Atmospheric methane (CH4) has been growing steadily since 2007 for reasons that are not well understood. Here we determine sources of methane using a technique informed by atmospheric measurements of CH4 and its isotopologue 13CH4. Measurements of 13CH4 provide for better separation of microbial, fossil, and fire sources of methane than CH4 measurements alone. Compared to previous assessments such as the Global Carbon Project, we find a larger microbial contribution to the post-2007 increase.
V. A. Tran, X. Q. Truong, D. A. Nguyen, L. Longoni, and V. Yordanov
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-4-W2-2021, 197–203, https://doi.org/10.5194/isprs-archives-XLVI-4-W2-2021-197-2021, https://doi.org/10.5194/isprs-archives-XLVI-4-W2-2021-197-2021, 2021
Andrea Abbate, Monica Papini, and Laura Longoni
Nat. Hazards Earth Syst. Sci., 21, 2041–2058, https://doi.org/10.5194/nhess-21-2041-2021, https://doi.org/10.5194/nhess-21-2041-2021, 2021
Short summary
Short summary
In this paper the relation between the intensity of meteorological events and the magnitude of triggered geo-hydrological issues was examined. A back analysis was developed across a region of the central Alps. The meteorological triggers were interpreted using two approaches: the first using local rain gauge data and a new one considering meteorological reanalysis maps. The results obtained were compared and elaborated for defining a magnitude of each geo-hydrological event.
M. Scaioni, L. Longoni, L. Zanzi, V. Ivanov, and M. Papini
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIV-3-W1-2020, 131–138, https://doi.org/10.5194/isprs-archives-XLIV-3-W1-2020-131-2020, https://doi.org/10.5194/isprs-archives-XLIV-3-W1-2020-131-2020, 2020
M. Scaioni, J. Crippa, V. Yordanov, L. Longoni, V. I. Ivanov, and M. Papini
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W4, 453–460, https://doi.org/10.5194/isprs-archives-XLII-3-W4-453-2018, https://doi.org/10.5194/isprs-archives-XLII-3-W4-453-2018, 2018
M. Scaioni, J. Crippa, L. Longoni, M. Papini, and L. Zanzi
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-5-W1, 63–70, https://doi.org/10.5194/isprs-annals-IV-5-W1-63-2017, https://doi.org/10.5194/isprs-annals-IV-5-W1-63-2017, 2017
Aki Tsuruta, Tuula Aalto, Leif Backman, Janne Hakkarainen, Ingrid T. van der Laan-Luijkx, Maarten C. Krol, Renato Spahni, Sander Houweling, Marko Laine, Ed Dlugokencky, Angel J. Gomez-Pelaez, Marcel van der Schoot, Ray Langenfelds, Raymond Ellul, Jgor Arduini, Francesco Apadula, Christoph Gerbig, Dietrich G. Feist, Rigel Kivi, Yukio Yoshida, and Wouter Peters
Geosci. Model Dev., 10, 1261–1289, https://doi.org/10.5194/gmd-10-1261-2017, https://doi.org/10.5194/gmd-10-1261-2017, 2017
Short summary
Short summary
In this study, we found that the average global methane emission for 2000–2012, estimated by the CTE-CH4 model, was 516±51 Tg CH4 yr-1, and the estimates for 2007–2012 were 4 % larger than for 2000–2006. The model estimates are sensitive to inputs and setups, but according to sensitivity tests the study suggests that the increase in atmospheric methane concentrations during 21st century was due to an increase in emissions from the 35S-EQ latitudinal bands.
Related subject area
Hydrological Hazards
Precursors and pathways: dynamically informed extreme event forecasting demonstrated on the historic Emilia-Romagna 2023 flood
Demonstrating the use of UNSEEN climate data for hydrological applications: case studies for extreme floods and droughts in England
Exploring the use of seasonal forecasts to adapt flood insurance premiums
Are 2D shallow-water solvers fast enough for early flood warning? A comparative assessment on the 2021 Ahr valley flood event
Water depth estimate and flood extent enhancement for satellite-based inundation maps
Probabilistic flood inundation mapping through copula Bayesian multi-modeling of precipitation products
Flood occurrence and impact models for socioeconomic applications over Canada and the United States
Model-based assessment of climate change impact on inland flood risk at the German North Sea coast caused by compounding storm tide and precipitation events
An improved dynamic bidirectional coupled hydrologic–hydrodynamic model for efficient flood inundation prediction
Quantifying hazard resilience by modeling infrastructure recovery as a resource-constrained project scheduling problem
Hydrometeorological controls of and social response to the 22 October 2019 catastrophic flash flood in Catalonia, north-eastern Spain
A downward-counterfactual analysis of flash floods in Germany
Hyper-resolution flood hazard mapping at the national scale
Compound droughts under climate change in Switzerland
Brief communication: SWM – stochastic weather model for precipitation-related hazard assessments using ERA5-Land data
Text mining uncovers the unique dynamics of socio-economic impacts of the 2018–2022 multi-year drought in Germany
The value of multi-source data for improved flood damage modelling with explicit input data uncertainty treatment: INSYDE 2.0
Risk of compound flooding substantially increases in the future Mekong River delta
Limited effect of the confluence angle and tributary gradient on Alpine confluence morphodynamics under intense sediment loads
Coupling WRF with HEC-HMS and WRF-Hydro for flood forecasting in typical mountainous catchments of northern China
Does a convection-permitting regional climate model bring new perspectives on the projection of Mediterranean floods?
Added value of seasonal hindcasts to create UK hydrological drought storylines
Flash flood detection via copula-based intensity–duration–frequency curves: evidence from Jamaica
Algorithmically Detected Rain-on-Snow Flood Events in Different Climate Datasets: A Case Study of the Susquehanna River Basin
Seasonal forecasting of local-scale soil moisture droughts with Global BROOK90: a case study of the European drought of 2018
How to mitigate flood events similar to the 1979 catastrophic floods in the lower Tagus
Review article: Drought as a continuum: memory effects in interlinked hydrological, ecological, and social systems
Assessing LISFLOOD-FP with the next-generation digital elevation model FABDEM using household survey and remote sensing data in the Central Highlands of Vietnam
Current and future rainfall-driven flood risk from hurricanes in Puerto Rico under 1.5 and 2 °C climate change
Modelling hazards impacting the flow regime in the Hranice Karst due to the proposed Skalička Dam
Using integrated hydrological–hydraulic modelling and global data sources to analyse the February 2023 floods in the Umbeluzi Catchment (Mozambique)
Impact-based flood forecasting in the Greater Horn of Africa
Floods in the Pyrenees: A global view through a regional database
Brief communication: A first hydrological investigation of extreme August 2023 floods in Slovenia, Europe
Multivariate regression trees as an “explainable machine learning” approach to explore relationships between hydroclimatic characteristics and agricultural and hydrological drought severity: case of study Cesar River basin
Review article: Towards improved drought prediction in the Mediterranean region – modeling approaches and future directions
Assessing typhoon-induced compound flood drivers: a case study in Ho Chi Minh City, Vietnam
Assessing the ability of a new seamless short-range ensemble rainfall product to anticipate flash floods in the French Mediterranean area
Sentinel-1-based analysis of the severe flood over Pakistan 2022
Sensitivity analysis of erosion on the landward slope of an earthen flood defense located in southern France submitted to wave overtopping
Transferability of machine learning-based modeling frameworks across flood events for hindcasting maximum river flood depths in coastal watersheds
Better prepared but less resilient: the paradoxical impact of frequent flood experience on adaptive behavior and resilience
Assessing the spatial spread–skill of ensemble flood maps with remote-sensing observations
An integrated modeling approach to evaluate the impacts of nature-based solutions of flood mitigation across a small watershed in the southeast United States
Indicator-to-impact links to help improve agricultural drought preparedness in Thailand
The potential of open-access data for flood estimations: uncovering inundation hotspots in Ho Chi Minh City, Vietnam, through a normalized flood severity index
Analyzing the informative value of alternative hazard indicators for monitoring drought hazard for human water supply and river ecosystems at the global scale
A methodological framework for the evaluation of short-range flash-flood hydrometeorological forecasts at the event scale
Hydrological drought forecasting under a changing environment in the Luanhe River basin
A multi-disciplinary analysis of the exceptional flood event of July 2021 in central Europe – Part 2: Historical context and relation to climate change
Joshua Dorrington, Marta Wenta, Federico Grazzini, Linus Magnusson, Frederic Vitart, and Christian M. Grams
Nat. Hazards Earth Syst. Sci., 24, 2995–3012, https://doi.org/10.5194/nhess-24-2995-2024, https://doi.org/10.5194/nhess-24-2995-2024, 2024
Short summary
Short summary
Extreme rainfall is the leading weather-related source of damages in Europe, but it is still difficult to predict on long timescales. A recent example of this was the devastating floods in the Italian region of Emiglia Romagna in May 2023. We present perspectives based on large-scale dynamical information that allows us to better understand and predict such events.
Alison L. Kay, Nick Dunstone, Gillian Kay, Victoria A. Bell, and Jamie Hannaford
Nat. Hazards Earth Syst. Sci., 24, 2953–2970, https://doi.org/10.5194/nhess-24-2953-2024, https://doi.org/10.5194/nhess-24-2953-2024, 2024
Short summary
Short summary
Hydrological hazards affect people and ecosystems, but extremes are not fully understood due to limited observations. A large climate ensemble and simple hydrological model are used to assess unprecedented but plausible floods and droughts. The chain gives extreme flows outside the observed range: summer 2022 ~ 28 % lower and autumn 2023 ~ 42 % higher. Spatial dependence and temporal persistence are analysed. Planning for such events could help water supply resilience and flood risk management.
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.
Shahin Khosh Bin Ghomash, Heiko Apel, and Daniel Caviedes-Voullième
Nat. Hazards Earth Syst. Sci., 24, 2857–2874, https://doi.org/10.5194/nhess-24-2857-2024, https://doi.org/10.5194/nhess-24-2857-2024, 2024
Short summary
Short summary
Early warning is essential to minimise the impact of flash floods. We explore the use of highly detailed flood models to simulate the 2021 flood event in the lower Ahr valley (Germany). Using very high-resolution models resolving individual streets and buildings, we produce detailed, quantitative, and actionable information for early flood warning systems. Using state-of-the-art computational technology, these models can guarantee very fast forecasts which allow for sufficient time to respond.
Andrea Betterle and Peter Salamon
Nat. Hazards Earth Syst. Sci., 24, 2817–2836, https://doi.org/10.5194/nhess-24-2817-2024, https://doi.org/10.5194/nhess-24-2817-2024, 2024
Short summary
Short summary
The study proposes a new framework, named FLEXTH, to estimate flood water depth and improve satellite-based flood monitoring using topographical data. FLEXTH is readily available as a computer code, offering a practical and scalable solution for estimating flood depth quickly and systematically over large areas. The methodology can reduce the impacts of floods and enhance emergency response efforts, particularly where resources are limited.
Francisco Javier Gomez, Keighobad Jafarzadegan, Hamed Moftakhari, and Hamid Moradkhani
Nat. Hazards Earth Syst. Sci., 24, 2647–2665, https://doi.org/10.5194/nhess-24-2647-2024, https://doi.org/10.5194/nhess-24-2647-2024, 2024
Short summary
Short summary
This study utilizes the global copula Bayesian model averaging technique for accurate and reliable flood modeling, especially in coastal regions. By integrating multiple precipitation datasets within this framework, we can effectively address sources of error in each dataset, leading to the generation of probabilistic flood maps. The creation of these probabilistic maps is essential for disaster preparedness and mitigation in densely populated areas susceptible to extreme weather events.
Manuel Grenier, Mathieu Boudreault, David A. Carozza, Jérémie Boudreault, and Sébastien Raymond
Nat. Hazards Earth Syst. Sci., 24, 2577–2595, https://doi.org/10.5194/nhess-24-2577-2024, https://doi.org/10.5194/nhess-24-2577-2024, 2024
Short summary
Short summary
Modelling floods at the street level for large countries like Canada and the United States is difficult and very costly. However, many applications do not necessarily require that level of detail. As a result, we present a flood modelling framework built with artificial intelligence for socioeconomic studies like trend and scenarios analyses. We find for example that an increase of 10 % in average precipitation yields an increase in displaced population of 18 % in Canada and 14 % in the US.
Helge Bormann, Jenny Kebschull, Lidia Gaslikova, and Ralf Weisse
Nat. Hazards Earth Syst. Sci., 24, 2559–2576, https://doi.org/10.5194/nhess-24-2559-2024, https://doi.org/10.5194/nhess-24-2559-2024, 2024
Short summary
Short summary
Inland flooding is threatening coastal lowlands. If rainfall and storm surges coincide, the risk of inland flooding increases. We examine how such compound events are influenced by climate change. Data analysis and model-based scenario analysis show that climate change induces an increasing frequency and intensity of compounding precipitation and storm tide events along the North Sea coast. Overload of inland drainage systems will also increase if no timely adaptation measures are taken.
Yanxia Shen, Zhenduo Zhu, Qi Zhou, and Chunbo Jiang
Nat. Hazards Earth Syst. Sci., 24, 2315–2330, https://doi.org/10.5194/nhess-24-2315-2024, https://doi.org/10.5194/nhess-24-2315-2024, 2024
Short summary
Short summary
We present an improved Multigrid Dynamical Bidirectional Coupled hydrologic–hydrodynamic Model (IM-DBCM) with two major improvements: (1) automated non-uniform mesh generation based on the D-infinity algorithm was implemented to identify flood-prone areas where high-resolution inundation conditions are needed, and (2) ghost cells and bilinear interpolation were implemented to improve numerical accuracy in interpolating variables between the coarse and fine grids. The improved model was reliable.
Taylor Glen Johnson, Jorge Leandro, and Divine Kwaku Ahadzie
Nat. Hazards Earth Syst. Sci., 24, 2285–2302, https://doi.org/10.5194/nhess-24-2285-2024, https://doi.org/10.5194/nhess-24-2285-2024, 2024
Short summary
Short summary
Reliance on infrastructure creates vulnerabilities to disruptions caused by natural hazards. To assess the impacts of natural hazards on the performance of infrastructure, we present a framework for quantifying resilience and develop a model of recovery based upon an application of project scheduling under resource constraints. The resilience framework and recovery model were applied in a case study to assess the resilience of building infrastructure to flooding hazards in Accra, Ghana.
Arnau Amengual, Romu Romero, María Carmen Llasat, Alejandro Hermoso, and Montserrat Llasat-Botija
Nat. Hazards Earth Syst. Sci., 24, 2215–2242, https://doi.org/10.5194/nhess-24-2215-2024, https://doi.org/10.5194/nhess-24-2215-2024, 2024
Short summary
Short summary
On 22 October 2019, the Francolí River basin experienced a heavy precipitation event, resulting in a catastrophic flash flood. Few studies comprehensively address both the physical and human dimensions and their interrelations during extreme flash flooding. This research takes a step forward towards filling this gap in knowledge by examining the alignment among all these factors.
Paul Voit and Maik Heistermann
Nat. Hazards Earth Syst. Sci., 24, 2147–2164, https://doi.org/10.5194/nhess-24-2147-2024, https://doi.org/10.5194/nhess-24-2147-2024, 2024
Short summary
Short summary
To identify flash flood potential in Germany, we shifted the most extreme rainfall events from the last 22 years systematically across Germany and simulated the consequent runoff reaction. Our results show that almost all areas in Germany have not seen the worst-case scenario of flood peaks within the last 22 years. With a slight spatial change of historical rainfall events, flood peaks of a factor of 2 or more would be achieved for most areas. The results can aid disaster risk management.
Günter Blöschl, Andreas Buttinger-Kreuzhuber, Daniel Cornel, Julia Eisl, Michael Hofer, Markus Hollaus, Zsolt Horváth, Jürgen Komma, Artem Konev, Juraj Parajka, Norbert Pfeifer, Andreas Reithofer, José Salinas, Peter Valent, Roman Výleta, Jürgen Waser, Michael H. Wimmer, and Heinz Stiefelmeyer
Nat. Hazards Earth Syst. Sci., 24, 2071–2091, https://doi.org/10.5194/nhess-24-2071-2024, https://doi.org/10.5194/nhess-24-2071-2024, 2024
Short summary
Short summary
A methodology of regional flood hazard mapping is proposed, based on data in Austria, which combines automatic methods with manual interventions to maximise efficiency and to obtain estimation accuracy similar to that of local studies. Flood discharge records from 781 stations are used to estimate flood hazard patterns of a given return period at a resolution of 2 m over a total stream length of 38 000 km. The hazard maps are used for civil protection, risk awareness and insurance purposes.
Christoph Nathanael von Matt, Regula Muelchi, Lukas Gudmundsson, and Olivia Martius
Nat. Hazards Earth Syst. Sci., 24, 1975–2001, https://doi.org/10.5194/nhess-24-1975-2024, https://doi.org/10.5194/nhess-24-1975-2024, 2024
Short summary
Short summary
The simultaneous occurrence of meteorological (precipitation), agricultural (soil moisture), and hydrological (streamflow) drought can lead to augmented impacts. By analysing drought indices derived from the newest climate scenarios for Switzerland (CH2018, Hydro-CH2018), we show that with climate change the concurrence of all drought types will increase in all studied regions of Switzerland. Our results stress the benefits of and need for both mitigation and adaptation measures at early stages.
Melody Gwyneth Whitehead and Mark Stephen Bebbington
Nat. Hazards Earth Syst. Sci., 24, 1929–1935, https://doi.org/10.5194/nhess-24-1929-2024, https://doi.org/10.5194/nhess-24-1929-2024, 2024
Short summary
Short summary
Precipitation-driven hazards including floods, landslides, and lahars can be catastrophic and difficult to forecast due to high uncertainty around future weather patterns. This work presents a stochastic weather model that produces statistically similar (realistic) rainfall over long time periods at minimal computational cost. These data provide much-needed inputs for hazard simulations to support long-term, time and spatially varying risk assessments.
Jan Sodoge, Christian Kuhlicke, Miguel D. Mahecha, and Mariana Madruga de Brito
Nat. Hazards Earth Syst. Sci., 24, 1757–1777, https://doi.org/10.5194/nhess-24-1757-2024, https://doi.org/10.5194/nhess-24-1757-2024, 2024
Short summary
Short summary
We delved into the socio-economic impacts of the 2018–2022 drought in Germany. We derived a dataset covering the impacts of droughts in Germany between 2000 and 2022 on sectors such as agriculture and forestry based on newspaper articles. Notably, our study illustrated that the longer drought had a wider reach and more varied effects. We show that dealing with longer droughts requires different plans compared to shorter ones, and it is crucial to be ready for the challenges they bring.
Mario Di Bacco, Daniela Molinari, and Anna Rita Scorzini
Nat. Hazards Earth Syst. Sci., 24, 1681–1696, https://doi.org/10.5194/nhess-24-1681-2024, https://doi.org/10.5194/nhess-24-1681-2024, 2024
Short summary
Short summary
INSYDE 2.0 is a tool for modelling flood damage to residential buildings. By incorporating ultra-detailed survey and desk-based data, it improves the reliability and informativeness of damage assessments while addressing input data uncertainties.
Melissa Wood, Ivan D. Haigh, Quan Quan Le, Hung Nghia Nguyen, Hoang Tran Ba, Stephen E. Darby, Robert Marsh, Nikolaos Skliris, and Joël J.-M. Hirschi
EGUsphere, https://doi.org/10.5194/egusphere-2024-949, https://doi.org/10.5194/egusphere-2024-949, 2024
Short summary
Short summary
We look at how compound flooding from the combination of river flooding and storm tide (storm surge plus astronomical tide) may be changing over time due to climate change, with a case study of the Mekong River delta. We found that future compound flooding has potential to flood the region more extensively and be longer lasting than compound floods today. This is useful to know because it means that managers of deltas such as the Mekong can assess options for improving existing flood defences.
Théo St. Pierre Ostrander, Thomé Kraus, Bruno Mazzorana, Johannes Holzner, Andrea Andreoli, Francesco Comiti, and Bernhard Gems
Nat. Hazards Earth Syst. Sci., 24, 1607–1634, https://doi.org/10.5194/nhess-24-1607-2024, https://doi.org/10.5194/nhess-24-1607-2024, 2024
Short summary
Short summary
Mountain river confluences are hazardous during localized flooding events. A physical model was used to determine the dominant controls over mountain confluences. Contrary to lowland confluences, in mountain regions, the channel discharges and (to a lesser degree) the tributary sediment concentration control morphological patterns. Applying conclusions drawn from lowland confluences could misrepresent depositional and erosional patterns and the related flood hazard at mountain river confluences.
Sheik Umar Jam-Jalloh, Jia Liu, Yicheng Wang, and Yuchen Liu
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-20, https://doi.org/10.5194/nhess-2024-20, 2024
Revised manuscript accepted for NHESS
Short summary
Short summary
Explore our paper on improving flood prediction using advanced weather models. We coupled the WRF model with WRF-Hydro and HEC-HMS to enhance accuracy. Discover how our findings contribute to adaptive atmospheric-hydrologic systems for effective flood forecasting.
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.
Wilson C. H. Chan, Nigel W. Arnell, Geoff Darch, Katie Facer-Childs, Theodore G. Shepherd, and Maliko Tanguy
Nat. Hazards Earth Syst. Sci., 24, 1065–1078, https://doi.org/10.5194/nhess-24-1065-2024, https://doi.org/10.5194/nhess-24-1065-2024, 2024
Short summary
Short summary
The most recent drought in the UK was declared in summer 2022. We pooled a large sample of plausible winters from seasonal hindcasts and grouped them into four clusters based on their atmospheric circulation configurations. Drought storylines representative of what the drought could have looked like if winter 2022/23 resembled each winter circulation storyline were created to explore counterfactuals of how bad the 2022 drought could have been over winter 2022/23 and beyond.
Dino Collalti, Nekeisha Spencer, and Eric Strobl
Nat. Hazards Earth Syst. Sci., 24, 873–890, https://doi.org/10.5194/nhess-24-873-2024, https://doi.org/10.5194/nhess-24-873-2024, 2024
Short summary
Short summary
The risk of extreme rainfall events causing floods is likely increasing with climate change. Flash floods, which follow immediately after extreme rainfall, are particularly difficult to forecast and assess. We develop a decision rule for flash flood classification with data on all incidents between 2001 and 2018 in Jamaica with the statistical copula method. This decision rule tells us for any rainfall event of a certain duration how intense it has to be to likely trigger a flash flood.
Colin M. Zarzycki, Benjamin D. Ascher, Alan M. Rhoades, and Rachel R. McCrary
EGUsphere, https://doi.org/10.5194/egusphere-2023-3094, https://doi.org/10.5194/egusphere-2023-3094, 2024
Short summary
Short summary
We developed an automated workflow to detect rain-on-snow events, which cause flooding in the northeastern U.S., in climate data. Analyzing the Susquehanna River Basin, this technique identified known events affecting river flow. Comparing four gridded datasets revealed variations in event frequency and severity, driven by different snowmelt and runoff estimates. This highlights the need for accurate climate data in flood management and risk prediction for these compound extremes.
Ivan Vorobevskii, Thi Thanh Luong, and Rico Kronenberg
Nat. Hazards Earth Syst. Sci., 24, 681–697, https://doi.org/10.5194/nhess-24-681-2024, https://doi.org/10.5194/nhess-24-681-2024, 2024
Short summary
Short summary
This study presents a new version of a framework which allows us to model water balance components at any site on a local scale. Compared with the first version, the second incorporates new datasets used to set up and force the model. In particular, we highlight the ability of the framework to provide seasonal forecasts. This gives potential stakeholders (farmers, foresters, policymakers, etc.) the possibility to forecast, for example, soil moisture drought and thus apply the necessary measures.
Diego Fernández-Nóvoa, Alexandre M. Ramos, José González-Cao, Orlando García-Feal, Cristina Catita, Moncho Gómez-Gesteira, and Ricardo M. Trigo
Nat. Hazards Earth Syst. Sci., 24, 609–630, https://doi.org/10.5194/nhess-24-609-2024, https://doi.org/10.5194/nhess-24-609-2024, 2024
Short summary
Short summary
The present study focuses on an in-depth analysis of floods in the lower section of the Tagus River from a hydrodynamic perspective by means of the Iber+ numerical model and on the development of dam operating strategies to mitigate flood episodes using the exceptional floods of February 1979 as a benchmark. The results corroborate the model's capability to evaluate floods in the study area and confirm the effectiveness of the proposed strategies to reduce flood impact in the lower Tagus valley.
Anne F. Van Loon, Sarra Kchouk, Alessia Matanó, Faranak Tootoonchi, Camila Alvarez-Garreton, Khalid E. A. Hassaballah, Minchao Wu, Marthe L. K. Wens, Anastasiya Shyrokaya, Elena Ridolfi, Riccardo Biella, Viorica Nagavciuc, Marlies H. Barendrecht, Ana Bastos, Louise Cavalcante, Franciska T. de Vries, Margaret Garcia, Johanna Mård, Ileen N. Streefkerk, Claudia Teutschbein, Roshanak Tootoonchi, Ruben Weesie, Valentin Aich, Juan P. Boisier, Giuliano Di Baldassarre, Yiheng Du, Mauricio Galleguillos, René Garreaud, Monica Ionita, Sina Khatami, Johanna K. L. Koehler, Charles H. Luce, Shreedhar Maskey, Heidi D. Mendoza, Moses N. Mwangi, Ilias G. Pechlivanidis, Germano G. Ribeiro Neto, Tirthankar Roy, Robert Stefanski, Patricia Trambauer, Elizabeth A. Koebele, Giulia Vico, and Micha Werner
EGUsphere, https://doi.org/10.5194/egusphere-2024-421, https://doi.org/10.5194/egusphere-2024-421, 2024
Short summary
Short summary
Drought is a creeping phenomenon, but it is often still analysed and managed like an event without taking into consideration what happened before and after. In this paper we review the literature and discuss five cases, where drought, its impacts and responses develop differently over time. We look at the hydrological, ecological and social system and their connections. And we provide suggestions for further research and for monitoring, modelling and management.
Laurence Hawker, Jeffrey Neal, James Savage, Thomas Kirkpatrick, Rachel Lord, Yanos Zylberberg, Andre Groeger, Truong Dang Thuy, Sean Fox, Felix Agyemang, and Pham Khanh Nam
Nat. Hazards Earth Syst. Sci., 24, 539–566, https://doi.org/10.5194/nhess-24-539-2024, https://doi.org/10.5194/nhess-24-539-2024, 2024
Short summary
Short summary
We present a global flood model built using a new terrain data set and evaluated in the Central Highlands of Vietnam.
Leanne Archer, Jeffrey Neal, Paul Bates, Emily Vosper, Dereka Carroll, Jeison Sosa, and Daniel Mitchell
Nat. Hazards Earth Syst. Sci., 24, 375–396, https://doi.org/10.5194/nhess-24-375-2024, https://doi.org/10.5194/nhess-24-375-2024, 2024
Short summary
Short summary
We model hurricane-rainfall-driven flooding to assess how the number of people exposed to flooding changes in Puerto Rico under the 1.5 and 2 °C Paris Agreement goals. Our analysis suggests 8 %–10 % of the population is currently exposed to flooding on average every 5 years, increasing by 2 %–15 % and 1 %–20 % at 1.5 and 2 °C. This has implications for adaptation to more extreme flooding in Puerto Rico and demonstrates that 1.5 °C climate change carries a significant increase in risk.
Miroslav Spano and Jaromir Riha
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-21, https://doi.org/10.5194/nhess-2024-21, 2024
Revised manuscript accepted for NHESS
Short summary
Short summary
Our study examines how building the Skalička Dam near the Hranice Karst affects local groundwater. We used advanced modeling to analyze two dam layouts: lateral and through-flow reservoirs. Results show the through-flow variant significantly alters water levels and mineral water discharge, while the lateral layout has less impact.
Luis Cea, Manuel Álvarez, and Jerónimo Puertas
Nat. Hazards Earth Syst. Sci., 24, 225–243, https://doi.org/10.5194/nhess-24-225-2024, https://doi.org/10.5194/nhess-24-225-2024, 2024
Short summary
Short summary
Mozambique is highly exposed to the impact of floods. To reduce flood damage, it is necessary to develop mitigation measures. Hydrological software is a very useful tool for that purpose, since it allows for a precise quantification of flood hazard in different scenarios. We present a methodology to quantify flood hazard in data-scarce regions, using freely available data and software, and we show its potential by analysing the flood event that took place in the Umbeluzi Basin in February 2023.
Lorenzo Alfieri, Andrea Libertino, Lorenzo Campo, Francesco Dottori, Simone Gabellani, Tatiana Ghizzoni, Alessandro Masoero, Lauro Rossi, Roberto Rudari, Nicola Testa, Eva Trasforini, Ahmed Amdihun, Jully Ouma, Luca Rossi, Yves Tramblay, Huan Wu, and Marco Massabò
Nat. Hazards Earth Syst. Sci., 24, 199–224, https://doi.org/10.5194/nhess-24-199-2024, https://doi.org/10.5194/nhess-24-199-2024, 2024
Short summary
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.
María Carmen Llasat, Montserrat Llasat-Botija, Erika Pardo, Raül Marcos-Matamoros, and Marc Lemus-Canovas
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-206, https://doi.org/10.5194/nhess-2023-206, 2024
Revised manuscript accepted for NHESS
Short summary
Short summary
Climate change is leading in the Pyrenees Massif to a change in socioeconomic increasing their sensitivity to natural risks such as floods. However, until now, no systematic study like this one had been carried out that would allow evaluating the frequency, distribution and main meteorological features of these events on a massif scale. In 35 years there have been 181 flood events that have produced 154 fatalities.
Nejc Bezak, Panos Panagos, Leonidas Liakos, and Matjaž Mikoš
Nat. Hazards Earth Syst. Sci., 23, 3885–3893, https://doi.org/10.5194/nhess-23-3885-2023, https://doi.org/10.5194/nhess-23-3885-2023, 2023
Short summary
Short summary
Extreme flooding occurred in Slovenia in August 2023. This brief communication examines the main causes, mechanisms and effects of this event. The flood disaster of August 2023 can be described as relatively extreme and was probably the most extreme flood event in Slovenia in recent decades. The economic damage was large and could amount to well over 5 % of Slovenia's annual gross domestic product; the event also claimed three lives.
Ana Paez-Trujilo, Jeffer Cañon, Beatriz Hernandez, Gerald Corzo, and Dimitri Solomatine
Nat. Hazards Earth Syst. Sci., 23, 3863–3883, https://doi.org/10.5194/nhess-23-3863-2023, https://doi.org/10.5194/nhess-23-3863-2023, 2023
Short summary
Short summary
This study uses a machine learning technique, the multivariate regression tree approach, to assess the hydroclimatic characteristics that govern agricultural and hydrological drought severity. The results show that the employed technique successfully identified the primary drivers of droughts and their critical thresholds. In addition, it provides relevant information to identify the areas most vulnerable to droughts and design strategies and interventions for drought management.
Bouchra Zellou, Nabil El Moçayd, and El Houcine Bergou
Nat. Hazards Earth Syst. Sci., 23, 3543–3583, https://doi.org/10.5194/nhess-23-3543-2023, https://doi.org/10.5194/nhess-23-3543-2023, 2023
Short summary
Short summary
In this study, we underscore the critical importance of strengthening drought prediction capabilities in the Mediterranean region. We present an in-depth evaluation of current drought forecasting approaches, encompassing statistical, dynamical, and hybrid statistical–dynamical models, and highlight unexplored research opportunities. Additionally, we suggest viable directions to enhance drought prediction and early warning systems within the area.
Francisco Rodrigues do Amaral, Nicolas Gratiot, Thierry Pellarin, and Tran Anh Tu
Nat. Hazards Earth Syst. Sci., 23, 3379–3405, https://doi.org/10.5194/nhess-23-3379-2023, https://doi.org/10.5194/nhess-23-3379-2023, 2023
Short summary
Short summary
We propose an in-depth analysis of typhoon-induced compound flood drivers in the megacity of Ho Chi Minh, Vietnam. We use in situ and satellite measurements throughout the event to form a holistic overview of its impact. No evidence of storm surge was found, and peak precipitation presents a 16 h time lag to peak river discharge, which evacuates only 1.5 % of available water. The astronomical tide controls the river level even during the extreme event, and it is the main urban flood driver.
Juliette Godet, Olivier Payrastre, Pierre Javelle, and François Bouttier
Nat. Hazards Earth Syst. Sci., 23, 3355–3377, https://doi.org/10.5194/nhess-23-3355-2023, https://doi.org/10.5194/nhess-23-3355-2023, 2023
Short summary
Short summary
This article results from a master's research project which was part of a natural hazards programme developed by the French Ministry of Ecological Transition. The objective of this work was to investigate a possible way to improve the operational flash flood warning service by adding rainfall forecasts upstream of the forecasting chain. The results showed that the tested forecast product, which is new and experimental, has a real added value compared to other classical forecast products.
Florian Roth, Bernhard Bauer-Marschallinger, Mark Edwin Tupas, Christoph Reimer, Peter Salamon, and Wolfgang Wagner
Nat. Hazards Earth Syst. Sci., 23, 3305–3317, https://doi.org/10.5194/nhess-23-3305-2023, https://doi.org/10.5194/nhess-23-3305-2023, 2023
Short summary
Short summary
In August and September 2022, millions of people were impacted by a severe flood event in Pakistan. Since many roads and other infrastructure were destroyed, satellite data were the only way of providing large-scale information on the flood's impact. Based on the flood mapping algorithm developed at Technische Universität Wien (TU Wien), we mapped an area of 30 492 km2 that was flooded at least once during the study's time period. This affected area matches about the total area of Belgium.
Clément Houdard, Adrien Poupardin, Philippe Sergent, Abdelkrim Bennabi, and Jena Jeong
Nat. Hazards Earth Syst. Sci., 23, 3111–3124, https://doi.org/10.5194/nhess-23-3111-2023, https://doi.org/10.5194/nhess-23-3111-2023, 2023
Short summary
Short summary
We developed a system able to to predict, knowing the appropriate characteristics of the flood defense structure and sea state, the return periods of potentially dangerous events as well as a ranking of parameters by order of uncertainty.
The model is a combination of statistical and empirical methods that have been applied to a Mediterranean earthen dike. This shows that the most important characteristics of the dyke are its geometrical features, such as its height and slope angles.
Maryam Pakdehi, Ebrahim Ahmadisharaf, Behzad Nazari, and Eunsaem Cho
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-152, https://doi.org/10.5194/nhess-2023-152, 2023
Revised manuscript accepted for NHESS
Short summary
Short summary
Machine learning (ML) models have growingly received attention for predicting flood events. However, there has been concerns about the transferability of these models (their capability in predicting out-of-sample events). Here, we showed that ML models can be transferable for hindcasting maximum river flood depths across major events (Hurricanes Ida, Isaias, Sandy, and Irene) in coastal watersheds when informed by the spatial distribution of pertinent features and underlying physical processes.
Lisa Köhler, Torsten Masson, Sabrina Köhler, and Christian Kuhlicke
Nat. Hazards Earth Syst. Sci., 23, 2787–2806, https://doi.org/10.5194/nhess-23-2787-2023, https://doi.org/10.5194/nhess-23-2787-2023, 2023
Short summary
Short summary
We analyzed the impact of flood experience on adaptive behavior and self-reported resilience. The outcomes draw a paradoxical picture: the most experienced people are the most adapted but the least resilient. We find evidence for non-linear relationships between the number of floods experienced and resilience. We contribute to existing knowledge by focusing specifically on the number of floods experienced and extending the rare scientific literature on the influence of experience on resilience.
Helen Hooker, Sarah L. Dance, David C. Mason, John Bevington, and Kay Shelton
Nat. Hazards Earth Syst. Sci., 23, 2769–2785, https://doi.org/10.5194/nhess-23-2769-2023, https://doi.org/10.5194/nhess-23-2769-2023, 2023
Short summary
Short summary
Ensemble forecasts of flood inundation produce maps indicating the probability of flooding. A new approach is presented to evaluate the spatial performance of an ensemble flood map forecast by comparison against remotely observed flooding extents. This is important for understanding forecast uncertainties and improving flood forecasting systems.
Betina I. Guido, Ioana Popescu, Vidya Samadi, and Biswa Bhattacharya
Nat. Hazards Earth Syst. Sci., 23, 2663–2681, https://doi.org/10.5194/nhess-23-2663-2023, https://doi.org/10.5194/nhess-23-2663-2023, 2023
Short summary
Short summary
We used an integrated model to evaluate the impacts of nature-based solutions (NBSs) on flood mitigation across the Little Pee Dee and Lumber River watershed, the Carolinas, US. This area is strongly affected by climatic disasters, which are expected to increase due to climate change and urbanization, so exploring an NBS approach is crucial for adapting to future alterations. Our research found that NBSs can have visible effects on the reduction in hurricane-driven flooding.
Maliko Tanguy, Michael Eastman, Eugene Magee, Lucy J. Barker, Thomas Chitson, Chaiwat Ekkawatpanit, Daniel Goodwin, Jamie Hannaford, Ian Holman, Liwa Pardthaisong, Simon Parry, Dolores Rey Vicario, and Supattra Visessri
Nat. Hazards Earth Syst. Sci., 23, 2419–2441, https://doi.org/10.5194/nhess-23-2419-2023, https://doi.org/10.5194/nhess-23-2419-2023, 2023
Short summary
Short summary
Droughts in Thailand are becoming more severe due to climate change. Understanding the link between drought impacts on the ground and drought indicators used in drought monitoring systems can help increase a country's preparedness and resilience to drought. With a focus on agricultural droughts, we derive crop- and region-specific indicator-to-impact links that can form the basis of targeted mitigation actions and an improved drought monitoring and early warning system in Thailand.
Leon Scheiber, Mazen Hoballah Jalloul, Christian Jordan, Jan Visscher, Hong Quan Nguyen, and Torsten Schlurmann
Nat. Hazards Earth Syst. Sci., 23, 2313–2332, https://doi.org/10.5194/nhess-23-2313-2023, https://doi.org/10.5194/nhess-23-2313-2023, 2023
Short summary
Short summary
Numerical models are increasingly important for assessing urban flooding, yet reliable input data are oftentimes hard to obtain. Taking Ho Chi Minh City as an example, this paper explores the usability and reliability of open-access data to produce preliminary risk maps that provide first insights into potential flooding hotspots. As a key novelty, a normalized flood severity index is presented which combines flood depth and duration to enhance the interpretation of hydro-numerical results.
Claudia Herbert and Petra Döll
Nat. Hazards Earth Syst. Sci., 23, 2111–2131, https://doi.org/10.5194/nhess-23-2111-2023, https://doi.org/10.5194/nhess-23-2111-2023, 2023
Short summary
Short summary
This paper presents a new method for selecting streamflow drought hazard indicators for monitoring drought hazard for human water supply and river ecosystems in large-scale drought early warning systems. Indicators are classified by their inherent assumptions about the habituation of people and ecosystems to the streamflow regime and their level of drought characterization, namely drought magnitude (water deficit at a certain point in time) and severity (cumulated magnitude since drought onset).
Maryse Charpentier-Noyer, Daniela Peredo, Axelle Fleury, Hugo Marchal, François Bouttier, Eric Gaume, Pierre Nicolle, Olivier Payrastre, and Maria-Helena Ramos
Nat. Hazards Earth Syst. Sci., 23, 2001–2029, https://doi.org/10.5194/nhess-23-2001-2023, https://doi.org/10.5194/nhess-23-2001-2023, 2023
Short summary
Short summary
This paper proposes a methodological framework designed for event-based evaluation in the context of an intense flash-flood event. The evaluation adopts the point of view of end users, with a focus on the anticipation of exceedances of discharge thresholds. With a study of rainfall forecasts, a discharge evaluation and a detailed look at the forecast hydrographs, the evaluation framework should help in drawing robust conclusions about the usefulness of new rainfall ensemble forecasts.
Min Li, Mingfeng Zhang, Runxiang Cao, Yidi Sun, and Xiyuan Deng
Nat. Hazards Earth Syst. Sci., 23, 1453–1464, https://doi.org/10.5194/nhess-23-1453-2023, https://doi.org/10.5194/nhess-23-1453-2023, 2023
Short summary
Short summary
It is an important disaster reduction strategy to forecast hydrological drought. In order to analyse the impact of human activities on hydrological drought, we constructed the human activity factor based on the method of restoration. With the increase of human index (HI) value, hydrological droughts tend to transition to more severe droughts. The conditional distribution model involving of human activity factor can further improve the forecasting accuracy of drought in the Luanhe River basin.
Patrick Ludwig, Florian Ehmele, Mário J. Franca, Susanna Mohr, Alberto Caldas-Alvarez, James E. Daniell, Uwe Ehret, Hendrik Feldmann, Marie Hundhausen, Peter Knippertz, Katharina Küpfer, Michael Kunz, Bernhard Mühr, Joaquim G. Pinto, Julian Quinting, Andreas M. Schäfer, Frank Seidel, and Christina Wisotzky
Nat. Hazards Earth Syst. Sci., 23, 1287–1311, https://doi.org/10.5194/nhess-23-1287-2023, https://doi.org/10.5194/nhess-23-1287-2023, 2023
Short summary
Short summary
Heavy precipitation in July 2021 led to widespread floods in western Germany and neighboring countries. The event was among the five heaviest precipitation events of the past 70 years in Germany, and the river discharges exceeded by far the statistical 100-year return values. Simulations of the event under future climate conditions revealed a strong and non-linear effect on flood peaks: for +2 K global warming, an 18 % increase in rainfall led to a 39 % increase of the flood peak in the Ahr river.
Cited articles
Abbate, A. and Mancusi, L.: Manuale del modello CRHyME (Climate Rainfall Hydrogeological Modelling Experiment), RSE Report RdS 21012462, Milano, RSE , https://www.rse-web.it/rapporti/manuale-del-modello-crhyme-climatic-rainfall-hydrogeological (last access: 1 November 3)202, 2021a.
Abbate, A. and Mancusi, L.: Strumenti per la mappatura delle minacce idrogeologiche per il sistema energetico e incidenza dei cambiamenti climatici, RSE Report RdS 21010317, Milano, RSE, https://www.rse-web.it/rapporti/strumenti-per-la-mappatura-delle-minacce-idrogeologiche-per (last access: 1 November 2023), 2021b.
Abbate, A., Longoni, L., Ivanov, V. I., and Papini, M.: Wildfire impacts on slope stability triggering in mountain areas, MDPI Geosci., 9, 1–15, https://doi.org/10.3390/geosciences9100417, 2019.
Abbate, A., Papini, M., and Longoni, L.: Analysis of meteorological parameters triggering rainfall-induced landslide: a review of 70 years in Valtellina, Nat. Hazards Earth Syst. Sci., 21, 2041–2058, https://doi.org/10.5194/nhess-21-2041-2021, 2021a.
Abbate, A., Papini, M., and Longoni, L.: Extreme Rainfall over Complex Terrain: An Application of the Linear Model of Orographic Precipitation to a Case Study in the Italian Pre-Alps, Geosciences, 11, 18, https://doi.org/10.3390/geosciences11010018, 2021b.
Abeshu, G. W., Li, H.-Y., Zhu, Z., Tan, Z., and Leung, L. R.: Median bed-material sediment particle size across rivers in the contiguous US, Earth Syst. Sci. Data, 14, 929–942, https://doi.org/10.5194/essd-14-929-2022, 2022.
Allan, R., Pereira, L., and Smith, M.: Crop evapotranspiration-Guidelines for computing crop water requirements – FAO Irrigation and drainage paper 56, FAO, https://www.fao.org/3/X0490E/x0490e00.htm (last access: 1 November 2023) 1998.
Alvioli, M., Melillo, M., Guzzetti, F., Rossi, M., Palazzi, E., von Hardenberg, J., Brunetti, M. T., and Peruccacci, S.: Implications of climate change on landslide hazard in Central Italy, Sci. Total Environ., 630, 1528–1543, https://doi.org/10.1016/j.scitotenv.2018.02.315, 2018.
Ancey, C.: Bedload transport: a walk between randomness and determinism. Part 1. The state of the art, J. Hydraul. Res., 58, 1–17, https://doi.org/10.1080/00221686.2019.1702594, 2020.
Anderson, E. I.: Modeling groundwater–surface water interactions using the Dupuit approximation, Adv. Water Resour., 28, 315–327, https://doi.org/10.1016/j.advwatres.2004.11.007, 2005.
Angeli, M. G., Buma, J., Gasparetto, P., and Pasuto, A.: A combined hill slope hydrology/stability model for low-gradient slopes in the Italian Dolomites, Eng. Geol., 49, 1–13, https://doi.org/10.1016/S0013-7952(97)00033-1, 1998.
Autorità di Bacino Distrettuale del Fiume Po: Linee Generali di Assetto Idrogeologico e Quadro degli Interventi, https://pai.adbpo.it/index.php/documentazione-pai/ (last access: 1 November 2023), 2022.
Ballio, F., Brambilla, D., Giorgetti, E., Longoni, L., Papini, M., and Radice, A.: Evaluation of sediment yield from valley slopes: A case study, WIT Trans. Eng. Sci., 67, 149–160, https://doi.org/10.2495/DEB100131, 2010.
Bancheri, M., Rigon, R., and Manfreda, S.: The GEOframe-NewAge Modelling System Applied in a Data Scarce Environment, Water, 12, 86, https://doi.org/10.3390/w12010086, 2020.
Barnes, R.: Parallel Priority-Flood depression filling for trillion cell digital elevation models on desktops or clusters, Comput. Geosci., 96, 56–68, https://doi.org/10.1016/j.cageo.2016.07.001, 2016.
Barnes, R.: Parallel non-divergent flow accumulation for trillion cell digital elevation models on desktops or clusters, Environ. Model. Softw., 92, 202–212, https://doi.org/10.1016/j.envsoft.2017.02.022, 2017.
Bemporad, G. A., Alterach, J., Amighetti, F. F., Peviani, M., and Saccardo, I.: A distributed approach for sediment yield evaluation in Alpine regions, J. Hydrol., 197, 370–392, https://doi.org/10.1016/0022-1694(95)02978-8, 1997.
Berg, J. H.: Prediction of Alluvial Channel Pattern of Perennial Rivers, Geomorphology, 12, 259–279, https://doi.org/10.1016/0169-555X(95)00014-V, 1995.
Bonanno, R., Lacavalla, M., and Sperati, S.: A new high-resolution Meteorological Reanalysis Italian Dataset: MERIDA, Q. J. Roy. Meteorol. Soc., 145, 1756–1779, https://doi.org/10.1002/qj.3530, 2019.
Bordoni, M., Meisina, C., Valentino, R., Lu, N., Bittelli, M., and Chersich, S.: Hydrological factors affecting rainfall-induced shallow landslides: From the field monitoring to a simplified slope stability analysis, Eng. Geol., 193, 19–37, https://doi.org/10.1016/j.enggeo.2015.04.006, 2015.
Bovolo, C. I. and Bathurst, J. C.: Modelling catchment-scale shallow landslide occurrence and sediment yield as a function of rainfall return period, Hydrol. Process., 26, 579–596, https://doi.org/10.1002/hyp.8158, 2012.
Bovy, B., Braun, J., Cordonnier, G., Lange, R., and Yuan, X.: The FastScape software stack: reusable tools for landscape evolution modelling, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9474, https://doi.org/10.5194/egusphere-egu2020-9474, 2020.
Bozzolan, E., Holcombe, E., Pianosi, F., and Wagener, T.: Including informal housing in slope stability analysis – an application to a data-scarce location in the humid tropics, Nat. Hazards Earth Syst. Sci., 20, 3161–3177, https://doi.org/10.5194/nhess-20-3161-2020, 2020.
Brambilla, D., Papini, M., Ivanov, V. I., Bonaventura, L., Abbate, A., and Longoni, L.: Sediment Yield in Mountain Basins, Analysis, and Management: The SMART-SED Project, in: Applied Geology: Approaches to Future Resource Management, edited by: De Maio, M. and Tiwari, A. K., Springer International Publishing, Cham, 43–59, https://doi.org/10.1007/978-3-030-43953-8_3, 2020.
Bresciani, E., Davy, P., and de Dreuzy, J.-R.: Is the Dupuit assumption suitable for predicting the groundwater seepage area in hillslopes?, Water Resour. Res., 50, 2394–2406, https://doi.org/10.1002/2013WR014284, 2014.
Campforts, B., Shobe, C. M., Steer, P., Vanmaercke, M., Lague, D., and Braun, J.: HyLands 1.0: a hybrid landscape evolution model to simulate the impact of landslides and landslide-derived sediment on landscape evolution, Geosci. Model Dev., 13, 3863–3886, https://doi.org/10.5194/gmd-13-3863-2020, 2020.
Cazorzi, F. and Dalla Fontana, G.: Snowmelt modelling by combining air temperature and a distributed radiation index, J. Hydrol., 181, 169–187, https://doi.org/10.1016/0022-1694(95)02913-3, 1996.
Ceriani, M., Lauzi, S., and Padovan, M.: Rainfall thresholds triggering debris-flow in the alpine area of Lombardia Region, central Alps – Italy, in: Proceedings of the Man and Mountain'94, First International Congress for the Protection and Development of Mountain Environmen, 20–24 June 1994, Ponte di Legno, BS, Italy, 1994.
Chen, L. and Young, M. H.: Green-Ampt infiltration model for sloping surfaces, Water Resour. Res., 42, W07420, https://doi.org/10.1029/2005WR004468, 2006.
Chiarelli, D. D., Galizzi, M., Bocchiola, D., Rosso, R., and Rulli, M. C.: Modeling snowmelt influence on shallow landslides in Tartano valley, Italian Alps, Sci. Total Environ., 856, 158772, https://doi.org/10.1016/j.scitotenv.2022.158772, 2023.
Chow, V. T., Maidment, D. R., and Mays, L. W.: Applied hydrology, McGraw-Hill, New York, ISBN 007070242X, ISBN 9780070702424, 1988.
Ciampalini, A., Raspini, F., Lagomarsino, D., Catani, F., and Casagli, N.: Landslide susceptibility map refinement using PSInSAR data, Remote Sens. Environ., 184, 302–315, https://doi.org/10.1016/j.rse.2016.07.018, 2016.
Ciccarese, G., Mulas, M., Alberoni, P. P., Truffelli, G., and Corsini, A.: Debris flows rainfall thresholds in the Apennines of Emilia-Romagna (Italy) derived by the analysis of recent severe rainstorms events and regional meteorological data, Geomorphology, 358, 107097, https://doi.org/10.1016/j.geomorph.2020.107097, 2020.
Ciccarese, G., Mulas, M., and Alessandro, C.: Combining spatial modelling and regionalization of rainfall thresholds for debris flows hazard mapping in the Emilia-Romagna Apennines (Italy), Landslides, 18, 1–17, https://doi.org/10.1007/s10346-021-01739-w, 2021.
Cislaghi, A., Chiaradia, E. A., and Bischetti, G. B.: Including root reinforcement variability in a probabilistic 3D stability model, Earth Surf. Proc. Land., 42, 1789–1806, https://doi.org/10.1002/esp.4127, 2017.
CNR and IRPI: Rapporto Periodico sul Rischio posto alla Popolazione italiana da Frane e Inondazioni, Anno 2020, 19 pp., https://doi.org/10.30437/report2020, 2021.
Collischonn, W., Fleischmann, A., Paiva, R. C. D., and Mejia, A.: Hydraulic Causes for Basin Hydrograph Skewness, Water Resour. Res., 53, 10603–10618, https://doi.org/10.1002/2017WR021543, 2017.
Crosta, G. B. and Frattini, P.: Distributed modelling of shallow landslides triggered by intense rainfall, Nat. Hazards Earth Syst. Sci., 3, 81–93, https://doi.org/10.5194/nhess-3-81-2003, 2003.
Crosta, G. B., Imposimato, S., and Roddeman, D. G.: Numerical modelling of large landslides stability and runout, Nat. Hazards Earth Syst. Sci., 3, 523–538, https://doi.org/10.5194/nhess-3-523-2003, 2003.
Dade, W. B. and Friend, P. F.: Grain-Size, Sediment-Transport Regime, and Channel Slope in Alluvial Rivers, J. Geol., 106, 661–676, https://doi.org/10.1086/516052, 1998.
D'Agostino, V. and Marchi, L.: Debris flow magnitude in the Eastern Italian Alps: Data collection and analysis, Phys. Chem. Earth Pt. C, 26, 657–663, https://doi.org/10.1016/S1464-1917(01)00064-2, 2001.
Daly, C., Taylor, G., and Gibson, W.: The PRISM Approach to Mapping Precipitation and Temperature, https://api.semanticscholar.org/CorpusID:17141237 (last access: 1 November 2023), 1997.
Daly, C., Slater, M. E., Roberti, J. A., Laseter, S. H., and Swift Jr., L. W.: High-resolution precipitation mapping in a mountainous watershed: ground truth for evaluating uncertainty in a national precipitation dataset, Int. J. Climatol., 37, 124–137, https://doi.org/10.1002/joc.4986, 2017.
Davolio, S., Della Fera, S., Laviola, S., Miglietta, M. M., and Levizzani, V.: Heavy precipitation over Italy from the Mediterranean storm “Vaia” in October 2018: Assessing the role of an atmospheric river, Mon. Weather Rev., 148, 3571–3588, 2020.
Davy, P. and Lague, D.: Fluvial erosion/transport equation of landscape evolution models revisited, J. Geophys. Res.-Earth, 114, F03007, https://doi.org/10.1029/2008JF001146, 2009.
de Graaf, I. E. M., Sutanudjaja, E. H., van Beek, L. P. H., and Bierkens, M. F. P.: A high-resolution global-scale groundwater model, Hydrol. Earth Syst. Sci., 19, 823–837, https://doi.org/10.5194/hess-19-823-2015, 2015.
de Vente, J. and Poesen, J.: Predicting soil erosion and sediment yield at the basin scale: Scale issues and semi-quantitative models, Earth-Sci. Rev., 71, 95–125, https://doi.org/10.1016/j.earscirev.2005.02.002, 2005.
Devia, G. K., Ganasri, B. P., and Dwarakish, G. S.: A Review on Hydrological Models, Aquat. Proced., 4, 1001–1007, https://doi.org/10.1016/j.aqpro.2015.02.126, 2015.
De Vita, P., Fusco, F., Tufano, R., and Cusano, D.: Seasonal and Event-Based Hydrological and Slope Stability Modeling of Pyroclastic Fall Deposits Covering Slopes in Campania (Southern Italy), Water, 10, 1140, https://doi.org/10.3390/w10091140, 2018.
D'Odorico, P. and Fagherazzi, S.: A probabilistic model of rainfall-triggered shallow landslides in hollows: A long-term analysis, Water Resour. Res., 39, 1262, https://doi.org/10.1029/2002WR001595, 2003.
Erskine, R. H., Green, T. R., Ramirez, J. A., and MacDonald, L. H.: Comparison of grid-based algorithms for computing upslope contributing area, Water Resour. Res., 42, W09416, https://doi.org/10.1029/2005WR004648, 2006.
Fan, Y., Miguez-Macho, G., Weaver, C. P., Walko, R., and Robock, A.: Incorporating water table dynamics in climate modeling: 1. Water table observations and equilibrium water table simulations, J. Geophys. Res.-Atmos., 112, D10125, https://doi.org/10.1029/2006JD008111, 2007.
Fawcett, T.: An introduction to ROC analysis, Pattern Recog. Lett., 27, 861–874, https://doi.org/10.1016/j.patrec.2005.10.010, 2006.
Formetta, G., Capparelli, G., and Versace, P.: Evaluating performance of simplified physically based models for shallow landslide susceptibility, Hydrol. Earth Syst. Sci., 20, 4585–4603, https://doi.org/10.5194/hess-20-4585-2016, 2016.
Gao, L., Zhang, L. M., and Cheung, R. W. M.: Relationships between natural terrain landslide magnitudes and triggering rainfall based on a large landslide inventory in Hong Kong, Landslides, 15, 727–740, https://doi.org/10.1007/s10346-017-0904-x, 2018.
Gariano, S. L. and Guzzetti, F.: Landslides in a changing climate, Earth-Sci. Rev., 162, 227–252, https://doi.org/10.1016/j.earscirev.2016.08.011, 2016.
GDAL/OGR contributors: GDAL/OGR Geospatial Data Abstraction software Library, Open Source Geospatial Foundation, https://gdal.org/index.html (last access: 1 November 2023), 2020.
Girard, M.-C., Girard, C., Dominique, C., Gilliot, J.-M., Loubersac, L., Meyer-Roux, J., Monget, J.-M., Seguin, B., and Rao, N.: Corine Land Cover, Routledge, 331–344, https://doi.org/10.1201/9780203741917-19, 2018.
Gleick, P. H.: Climate change, hydrology, and water resources, Rev. Geophys., 27, 329–344, https://doi.org/10.1029/RG027i003p00329, 1989.
Globevnik, L., Holjević, D., Petkovšek, G., and Rubinić, J.: 145. Applicability of the Gavrilo vic Method in Erosion Calculation Using Spatial Data Manipulation Techniques, Tunnelling and Underground Space Technology, 14 pp. https://api.semanticscholar.org/CorpusID:54749986 (last access: 1 November 2023), 2003.
Govers, G.: Empirical relationships for the transport capacity of overland flow, https://iahs.info/uploads/dms/8088.45-63-189-Govers.pdf (last access: 1 November 2023), 1989.
Govers, G., Wallings, D. E., Yair, A., and Berkowicz, S.: Empirical relationships for the transport capacity of overland flow, International Association of Hydrological Sciences, 189 pp., 1990.
Groenendyk, D. G., Ferré, T. P. A., Thorp, K. R., and Rice, A. K.: Hydrologic-Process-Based Soil Texture Classifications for Improved Visualization of Landscape Function., PLoS One, 10, e0131299, https://doi.org/10.1371/journal.pone.0131299, 2015.
Guadagno, M., Guzzetti, I., Reichenbach, I., and Tonelli, I.: SICI – Sistema Informativo Catastrofi Idrogeologiche, Istituto di Ricerca per la Protezione Idrogeologica (IRPI) del Consiglio Nazionale delle Ricerche e Gruppo Nazionale per la Difesa dalle Catastrofi Idrogeologiche (GNDCI) del Consiglio Nazionale delle Ricerche, https://sici.irpi.cnr.it/ (last access: 1 November 2023), 2003.
Gudiyangada Nachappa, T., Tavakkoli Piralilou, S., Ghorbanzadeh, O., Shahabi, H., and Blaschke, T.: Landslide Susceptibility Mapping for Austria Using Geons and Optimization with the Dempster-Shafer Theory, Appl. Sci., 9, 5393, https://doi.org/10.3390/app9245393, 2019.
Guzzetti, F. and Tonelli, G.: Information system on hydrological and geomorphological catastrophes in Italy (SICI): a tool for managing landslide and flood hazards, Nat. Hazards Earth Syst. Sci., 4, 213–232, https://doi.org/10.5194/nhess-4-213-2004, 2004.
Guzzetti, F., Reichenbach, P., Cardinali, M., Galli, M., and Ardizzone, F.: Probabilistic landslide hazard assessment at the basin scale, Geomorphology, 72, 272–299, https://doi.org/10.1016/j.geomorph.2005.06.002, 2005.
Guzzetti, F., Peruccacci, S., Rossi, M., and Stark, C. P.: Rainfall thresholds for the initiation of landslides in central and southern Europe, Meteorol. Atmos. Phys., 98, 239–267, https://doi.org/10.1007/s00703-007-0262-7, 2007.
Harp, E. L., Michael, J. A., and Laprade, W. T.: Shallow-landslide hazard map of Seattle, USGS, Washington, Reston, VA, https://doi.org/10.3133/ofr20061139, 2006.
Hayashi, M.: Alpine Hydrogeology: The Critical Role of Groundwater in Sourcing the Headwaters of the World, Groundwater, 58, 498–510, https://doi.org/10.1111/gwat.12965, 2020.
Hengl, T., Mendes de Jesus, J., Heuvelink, G. B. M., Ruiperez Gonzalez, M., 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.
Herrera, M.: Landslide Detection using Random Forest Classifier, Delft University of Technology, Delft, https://doi.org/10.13140/RG.2.2.31365.91369, 2019.
Huscroft, J., Gleeson, T., Hartmann, J., and Börker, J.: Compiling and Mapping Global Permeability of the Unconsolidated and Consolidated Earth: GLobal HYdrogeology MaPS 2.0 (GLHYMPS 2.0), Geophys. Res. Lett., 45, 1897–1904, https://doi.org/10.1002/2017GL075860, 2018.
Iida, T.: A stochastic hydro-geomorphological model for shallow landsliding due to rainstorm, Catena, 34, 293–313, https://doi.org/10.1016/S0341-8162(98)00093-9, 1999.
ISPRA: Dissesto idrogeologico in Italia: pericolosità e indicatori di rischio, Ispra, https://www.isprambiente.gov.it/it/attivita/suolo-e-territorio/dissesto-idrogeologico (last access: 1 November 2023), 2018.
ITCOLD: La gestione dell'interrimento dei serbatoi artificiali italiani, Comitato Nazionale Italiano delle Grandi Dighe, https://www.itcold.it/wpsysfiles/wp-content/uploads/2016/07/RAPPFIN-GdLInterrimento-Fase1-20091.pdf (last access: 1 November 2023), 2009.
ITCOLD: La gestione dell'interrimento dei serbatoi artificiali italiani situazione attuale e prospettive, Comitato Nazionale Italiano delle Grandi Dighe, https://www.itcold.it/wpsysfiles/wp-content/uploads/2016/07/RAPPFIN-GdLInterrimento-Fase2-20092.pdf (last access: 1 November 2023), 2016.
Ivanov, V., Radice, A., Papini, M., and Longoni, L.: Event-scale pebble mobility observed by RFID tracking in a pre-Alpine stream: a field laboratory, Earth Surf. Proc. Land., 45, 535–547, https://doi.org/10.1002/esp.4752, 2020a.
Ivanov, V., Arosio, D., Tresoldi, G., Hojat, A., Zanzi, L., Papini, M., and Longoni, L.: Investigation on the Role of Water for the Stability of Shallow Landslides-Insights from Experimental Tests, Water, 12, 1203, https://doi.org/10.3390/w12041203, 2020b.
Iverson, R., Reid, M., and Lahusen, R.: Debris-flow mobilization from landslides. Annu Rev Earth Planet Sci, Annu. Rev. Earth Planet. Sci., 25, 85–138, https://doi.org/10.1146/annurev.earth.25.1.85, 1997.
Iverson, R. M.: Landslide triggering by rain infiltration, Water Resour. Res., 36, 1897–1910, https://doi.org/10.1029/2000WR900090, 2000.
Jackson, C. R., Bitew, M., and Du, E.: When interflow also percolates: downslope travel distances and hillslope process zones, Hydrol. Process., 28, 3195–3200, https://doi.org/10.1002/hyp.10158, 2014.
Jacob, D., Petersen, J., Eggert, B., Alias, A., Christensen, O. B., Bouwer, L. M., Braun, A., Colette, A., Déqué, M., Georgievski, G., Georgopoulou, E., Gobiet, A., Menut, L., Nikulin, G., Haensler, A., Hempelmann, N., Jones, C., Keuler, K., Kovats, S., Kröner, N., Kotlarski, S., Kriegsmann, A., Martin, E., van Meijgaard, E., Moseley, C., Pfeifer, S., Preuschmann, S., Radermacher, C., Radtke, K., Rechid, D., Rounsevell, M., Samuelsson, P., Somot, S., Soussana, J.-F., Teichmann, C., Valentini, R., Vautard, R., Weber, B., and Yiou, P.: EURO-CORDEX: new high-resolution climate change projections for European impact research, Reg. Environ. Change, 14, 563–578, https://doi.org/10.1007/s10113-013-0499-2, 2014.
Jakob, M. and Hungr, O.: Debris-Flow Hazards and Related Phenomena, Springer, ISBN 978-3-540-20726-9, 2005.
Jakob, M. and Jordan, P.: Design flood estimates in mountain streams – the need for a geomorphic approach, Can. J. Civ. Eng., 28, 425–439, https://doi.org/10.1139/l01-010, 2001.
Kadavi, P., Lee, C.-W., and Lee, S.: Application of Ensemble-Based Machine Learning Models to Landslide Susceptibility Mapping, Remote Sens., 10, 1252, https://doi.org/10.3390/rs10081252, 2018.
Karssenberg, D., Schmitz, O., Salamon, P., de Jong, K., and Bierkens, M. F. P.: A software framework for construction of process-based stochastic spatio-temporal models and data assimilation, Environ. Model. Softw., 25, 489–502, https://doi.org/10.1016/j.envsoft.2009.10.004, 2010.
Kim, K.-S., Kim, M.-I., Lee, M.-S., and Hwang, E.-S.: Regression Equations for Estimating Landslide-Triggering Factors Using Soil Characteristics, Appl. Sci., 10, 3560, https://doi.org/10.3390/app10103560, 2020.
Klaus, J. and Jackson, C. R.: Interflow Is Not Binary: A Continuous Shallow Perched Layer Does Not Imply Continuous Connectivity, Water Resour. Res., 54, 5921–5932, https://doi.org/10.1029/2018WR022920, 2018.
Kobierska, F., Jonas, T., Kirchner, J. W., and Bernasconi, S. M.: Linking baseflow separation and groundwater storage dynamics in an alpine basin (Dammagletscher, Switzerland), Hydrol. Earth Syst. Sci., 19, 3681–3693, https://doi.org/10.5194/hess-19-3681-2015, 2015.
Kondolf, G. M.: Hungry Water: Effects of Dams and Gravel Mining on River Channels, Environ. Manage., 21, 533–551, https://doi.org/10.1007/s002679900048, 1997.
Lamb, M. P. and Venditti, J. G.: The grain size gap and abrupt gravel-sand transitions in rivers due to suspension fallout, Geophys. Res. Lett., 43, 3777–3785, https://doi.org/10.1002/2016GL068713, 2016.
Langland, M. J.: Bathymetry and Sediment-Storage Capacity Change in Three Reservoirs on the Lower Susquehanna River, 1996–2008, USGS, https://doi.org/10.3133/sir20095110, 2009.
Lazzari, M., Piccarreta, M., and Manfreda, S.: The role of antecedent soil moisture conditions on rainfall-triggered shallow landslides, Nat. Hazards Earth Syst. Sci. Discuss. [preprint], https://doi.org/10.5194/nhess-2018-371, 2018.
Lee, K. and Pin Chun, H.: Evaluating the adequateness of kinematic-wave routing for flood forecasting in midstream channel reaches of Taiwan, J. Hydroinform., 14, 1075, https://doi.org/10.2166/hydro.2012.093, 2012.
Legorreta Paulin, G., Bursik, M., Lugo-Hubp, J., and Zamorano Orozco, J. J.: Effect of pixel size on cartographic representation of shallow and deep-seated landslide, and its collateral effects on the forecasting of landslides by SINMAP and Multiple Logistic Regression landslide models, Phys. Chem. Earth Pt. A/B/C, 35, 137–148, https://doi.org/10.1016/j.pce.2010.04.008, 2010.
Lehner, B., Verdin, K., and Jarvis, A.: New Global Hydrography Derived From Spaceborne Elevation Data, Eos Trans. Am. Geophys. Union, 89, 93–94, https://doi.org/10.1029/2008EO100001, 2008.
Li, X., Xiao, Q., Niu, J., Dymond, S., McPherson, E. G., van Doorn, N., Yu, X., Xie, B., Zhang, K., and Li, J.: Rainfall interception by tree crown and leaf litter: An interactive process, Hydrol. Process., 31, 3533–3542, https://doi.org/10.1002/hyp.11275, 2017.
Longoni, L., Ivanov, V. I., Brambilla, D., Radice, A., and Papini, M.: Analysis of the temporal and spatial scales of soil erosion and transport in a Mountain Basin, Ital. J. Eng. Geol. Environ., 16, 17–30, https://doi.org/10.4408/IJEGE.2016-02.O-02, 2016.
López Vicente, M., Pérez-Bielsa, C., López-Montero, T., Lambán, L. J., and Navas, A.: Runoff simulation with eight different flow accumulation algorithms: Recommendations using a spatially distributed and open-source model, Environ. Model. Softw., 62, 11–21, 2014.
Luino, F.: Sequence of instability processes triggered by heavy rainfall in the Northern Italy, Geomorphology, 66, 13–39, https://doi.org/10.1016/j.geomorph.2004.09.010, 2005.
Ly, S., Charles, C., and Degre, A.: Different methods for spatial interpolation of rainfall data for operational hydrology and hydrological modeling at watershed scale. A review, Biotechnol. Agron. Soc. Environ., 17, 392–406, 2013.
Marnezy, A.: Alpine dams. From hydroelectric power to artificial snow, Revue De Geographie Alpine – Journal of Alpine Research, 96, 103–112, 2008.
Meisina, C., Zizioli, D., and Zucca, F.: Methods for shallow landslides susceptibility mapping: an example in Oltrepo Pavese (Northern Italy), Landslides Science and Practice, in: Volume 1: Landslide Inventory and Susceptibility and Hazard, edited by: Zoning Margottini, C., Canuti, P., and Sassa, K., Springer, 451–458, ISBN 978-3-642-31324-0, https://doi.org/10.1007/978-3-642-31325-7, 2013.
Merritt, W. S., Letcher, R. A., and Jakeman, A. J.: A review of erosion and sediment transport models, Environ. Model. Softw., 18, 761–799, https://doi.org/10.1016/S1364-8152(03)00078-1, 2003.
Michel, G. P., Kobiyama, M., and Goerl, R. F.: Comparative analysis of SHALSTAB and SINMAP for landslide susceptibility mapping in the Cunha River basin, southern Brazil, J. Soils Sediments, 14, 1266–1277, https://doi.org/10.1007/s11368-014-0886-4, 2014.
Milanesi, L., Pilotti, M., Clerici, A., and Gavrilovic, Z.: Application of an improved version of the Erosion Potential Method in Alpine areas, Ital. J. Eng. Geol. Environ., 1, 17–30, https://doi.org/10.4408/IJEGE.2015-01.O-02, 2015.
Milledge, D. G., Bellugi, D., McKean, J. A., Densmore, A. L., and Dietrich, W. E.: A multidimensional stability model for predicting shallow landslide size and shape across landscapes, J. Geophys. Res.-Earth, 119, 2481–2504, https://doi.org/10.1002/2014JF003135, 2014.
Mishra, S. K., Tyagi, J. V., and Singh, V. P.: Comparison of infiltration models, Hydrol. Process., 17, 2629–2652, https://doi.org/10.1002/hyp.1257, 2003.
Moges, E., Demissie, Y., Larsen, L., and Yassin, F.: Review: Sources of Hydrological Model Uncertainties and Advances in Their Analysis, Water, 13, 28, https://doi.org/10.3390/w13010028, 2021.
Montrasio, L.: Stability of soil-slip, Risk Analysis II, WIT Press, https://www.witpress.com/Secure/elibrary/papers/RISK00/RISK00033FU.pdf (last access: 1 November 2023), 2008.
Montrasio, L. and Valentino, R.: Modelling Rainfall-induced Shallow Landslides at Different Scales Using SLIP – Part II, Proced. Eng., 158, 482–486, https://doi.org/10.1016/j.proeng.2016.08.476, 2016.
Morbidelli, R., Corradini, C., Saltalippi, C., Flammini, A., Dari, J., and Govindaraju, R. S.: Rainfall Infiltration Modeling: A Review, Water, 10, 1873, https://doi.org/10.3390/w10121873, 2018.
Morgan, R. P. C. and Nearing, M. A. (Eds.): Handbook of erosion modelling, Blackwell Publishing Ltd, ISBN 9781405190107, ISBN 9781444328455, https://doi.org/10.1002/9781444328455, 2011.
Munich Re: Natural disasters caused overall losses of US $ 210bn Relevant natural catastrophe loss events worldwide 2020, https://www.munichre.com/content/dam/munichre/mrwebsiteslaunches/natcat-2021/2020_Jan-Dec_Weltkarte_e.pdf/_jcr_content/renditions/original./2020_Jan-Dec_Weltkarte_e.pdf (last access: 1 November 2023), 2021.
Nazari, M., Sadeghi, S. M. M., Van Stan, J., and Chaichi, M.: Rainfall interception and redistribution by maize farmland in central Iran, J. Hydrol.: Reg. Stud., 27, 100656, https://doi.org/10.1016/j.ejrh.2019.100656, 2019.
Nino, Y.: Simple Model for Downstream Variation of Median Sediment Size in Chilean Rivers, J. Hydraul. Eng., 128, 934–941, 2002.
Oguz, E. A., Depina, I., and Thakur, V.: Effects of soil heterogeneity on susceptibility of shallow landslides, Landslides, 19, 67–83, https://doi.org/10.1007/s10346-021-01738-x, 2022.
Pacina, J., Lenďáková, Z., Štojdl, J., Matys Grygar, T., and Dolejš, M.: Dynamics of Sediments in Reservoir Inflows: A Case Study of the Skalka and Nechranice Reservoirs, Czech Republic, ISPRS Int. J. Geo-Inform., 9, 258, https://doi.org/10.3390/ijgi9040258, 2020.
Panagos, P., Borrelli, P., Poesen, J., Ballabio, C., Lugato, E., Meusburger, K., Montanarella, L., and Alewell, C.: The new assessment of soil loss by water erosion in Europe, Environ. Sci. Policy, 54, 438–447, https://doi.org/10.1016/j.envsci.2015.08.012, 2015.
Papini, M., Ivanov, V., Brambilla, D., Arosio, D., and Longoni, L.: Monitoring bedload sediment transport in a pre-Alpine river: An experimental method, Rendiconti Online della Società Geologica Italiana, 43, 57–63, https://doi.org/10.3301/ROL.2017.35, 2017.
Parenti, C., Rossi, P., Mancini, F., Scorpio, V., Grassi, F., Ciccarese, G., Lugli, F., and Soldati, M.: Multitemporal Analysis of Slow-Moving Landslides and Channel Dynamics through Integrated Remote Sensing and In Situ Techniques, Remote Sens., 15, 3563, https://doi.org/10.3390/rs15143563, 2023.
Pearson, E., Smith, M. W., Klaar, M. J., and Brown, L. E.: Can high resolution 3D topographic surveys provide reliable grain size estimates in gravel bed rivers?, Geomorphology, 293, 143–155, https://doi.org/10.1016/j.geomorph.2017.05.015, 2017.
Pebesma, E. J., de Jong, K., and Briggs, D.: Interactive visualization of uncertain spatial and spatio-temporal data under different scenarios: an air quality example, Int. J. Geogr. Inform. Sci., 21, 515–527, https://doi.org/10.1080/13658810601064009, 2007.
Peirce, S., Ashmore, P., and Leduc, P.: Evolution of grain size distributions and bed mobility during hydrographs in gravel-bed braided rivers, Earth Surf. Proc. Land., 44, 304–316, https://doi.org/10.1002/esp.4511, 2019.
Pelletier, J. D., Broxton, P. D., Hazenberg, P., Zeng, X., Troch, P. A., Niu, G.-Y., Williams, Z., Brunke, M. A., and Gochis, D.: A gridded global data set of soil, intact regolith, and sedimentary deposit thicknesses for regional and global land surface modeling, J. Adv. Model. Earth Syst., 8, 41–65, https://doi.org/10.1002/2015MS000526, 2016.
Pereira, S., Garcia, R., Zêzere, J., Oliveira, S., and Silva, M.: Landslide quantitative risk analysis of buildings at the municipal scale based on a rainfall triggering scenario, Geomat. Nat. Hazards Risk, 8, 624–648, https://doi.org/10.1080/19475705.2016.1250116, 2016.
Pérez-Peña, J. V., Azañón, J. M., and Azor, A.: CalHypso: An ArcGIS extension to calculate hypsometric curves and their statistical moments. Applications to drainage basin analysis in SE Spain, Comput. Geosci., 35, 1214–1223, 2009.
Rahardjo, H., Satyanaga, A., Leong, E. C., Santoso, V. A., and Ng, Y. S.: Performance of an instrumented slope covered with shrubs and deep-rooted grass, Soils Foundat., 54, 417–425, https://doi.org/10.1016/j.sandf.2014.04.010, 2014.
Raj, P. P.: Comparison of True and Residual Friction Angles, Soils Foundat., 21, 99–103, https://doi.org/10.3208/sandf1972.21.3_99, 1981.
Ravi, V., Williams, J. R., and Ouyang, Y.: Estimation of infiltration rate in the vadose zone: compilation of simple mathematical models, https://api.semanticscholar.org/CorpusID:16241319 (last access: 1 November 2023), 1998.
Raziei, T. and Pereira, L.: Estimation of ETo with Hargreaves-Samani and FAO-PM temperature methods for a wide range of climates in Iran, Agr. Water Manage., 121, 1–18, https://doi.org/10.1016/j.agwat.2012.12.019, 2013.
Remondo, J., Bonachea, J., and Cendrero, A.: A statistical approach to landslide risk modelling at basin scale: From landslide susceptibility to quantitative risk assessment, Landslides, 2, 321–328, https://doi.org/10.1007/s10346-005-0016-x, 2005.
Rete Monitoraggio ARPA Emilia-Romagna: Dati di Monitoraggio Idro-Meteorologico, https://www.arpae.it/it/temi-ambientali/meteo/dati-e-osservazioni (last access: 1 November 2023), 2023.
Rete Monitoraggio ARPA Lombardia: Dati di Monitoraggio Idro-Meteorologico, https://www.arpalombardia.it/dati-e-indicatori/meteo-e-clima/ (last access: 1 November 2023), 2023.
Rickenmann, D.: Empirical Relationships for Debris Flows, Nat. Hazards, 19, 47–77, https://doi.org/10.1023/A:1008064220727, 1999.
Rocha, J., Duarte, A., Silva, M., Fabres, S., Vasques, J., Revilla-Romero, B., and Quintela, A.: The Importance of High Resolution Digital Elevation Models for Improved Hydrological Simulations of a Mediterranean Forested Catchment, Remote Sens., 12, 3287, https://doi.org/10.3390/rs12203287, 2020.
Ronchetti, F., Borgatti, L., Cervi, F., C, G., Piccinini, L., Vincenzi, V., and Alessandro, C.: Groundwater processes in a complex landslide, northern Apennines, Italy, Nat. Hazards Earth Syst. Sci., 9, 895–904, https://doi.org/10.5194/nhess-9-895-2009, 2009.
Roo, A., Wesseling, C. G., Jetten, V. G., and Ritsema, C.: LISEM: A physically-based hydrological and soil erosion model incorporated in a GIS, in: Application of geographic information systems in hydrology and water resources management, edited by: Kovar, K. and Nachtnebel, H. P., Wallingford, UK, IAHS Publ., 235, 395–403, 1996.
Ross, C. W., Prihodko, L., Anchang, J., Kumar, S., Ji, W., and Hanan, N. P.: HYSOGs250m, global gridded hydrologic soil groups for curve-number-based runoff modeling, Sci. Data, 5, 180091–180091, https://doi.org/10.1038/sdata.2018.91, 2018.
Salles, T.: eSCAPE: Regional to Global Scale Landscape Evolution Model v2.0, Geosci. Model Dev., 12, 4165–4184, https://doi.org/10.5194/gmd-12-4165-2019, 2019.
Sambrook Smith, G. H. and Ferguson, R. I.: The gravel-sand transition along river channels, J. Sediment. Res., 65, 423–430, https://doi.org/10.1306/D42680E0-2B26-11D7-8648000102C1865D, 1995.
Scheidl, C. and Rickenmann, D.: Topflowdf – a simple gis based model to simulate debris-flow runout on the fan, Ital. J. Eng. Geol. Environ., 253–262, https://doi.org/10.4408/IJEGE.2011-03.B-030, 2011.
Schellekens, J., van Verseveld, W., Visser, M., Winsemius, H., Euserand, T., Bouaziz, L. C. T., de Vriesand, S., Boisgontierand, H., Eilanderand, D., Tollenaarand, D., Weertsand, A., Baartand, F., Hazenbergand, P., Lutz, L., ten Velden, C., Jansen, M., and Benedict, M.: Wflow, openstreams/wflow: unstable-master. OpenStream wflow documentation release, doi: Zenodo. https://doi.org/10.5281/zenodo.4291730, 2020.
Schoener, G. and Stone, M. C.: Monitoring soil moisture at the catchment scale – A novel approach combining antecedent precipitation index and radar-derived rainfall data, J. Hydrol., 589, 125155, https://doi.org/10.1016/j.jhydrol.2020.125155, 2020.
Shobe, C. M., Tucker, G. E., and Barnhart, K. R.: The SPACE 1.0 model: a Landlab component for 2-D calculation of sediment transport, bedrock erosion, and landscape evolution, Geosci. Model Dev., 10, 4577–4604, https://doi.org/10.5194/gmd-10-4577-2017, 2017.
Sklar, L. S., Riebe, C. S., Marshall, J. A., Genetti, J., Leclere, S., Lukens, C. L., and Merces, V.: The problem of predicting the size distribution of sediment supplied by hillslopes to rivers, Geomorphology, 277, 31–49, 2017.
Smith, R. E. and Parlange, J.-Y.: A parameter-efficient hydrologic infiltration model, Water Resour. Res., 14, 533–538, https://doi.org/10.1029/WR014i003p00533, 1978.
Strahler, A. N.: Dynamic basis of geomorphology, Geol. Soc. Am. Bull., 63, 923–938, 1952.
Strauch, R., Istanbulluoglu, E., Nudurupati, S. S., Bandaragoda, C., Gasparini, N. M., and Tucker, G. E.: A hydroclimatological approach to predicting regional landslide probability using Landlab, Earth Surf. Dynam., 6, 49–75, https://doi.org/10.5194/esurf-6-49-2018, 2018.
Sutanudjaja, E. H., van Beek, R., Wanders, N., Wada, Y., Bosmans, J. H. C., Drost, N., van der Ent, R. J., de Graaf, I. E. M., Hoch, J. M., de Jong, K., Karssenberg, D., López López, P., Peßenteiner, S., Schmitz, O., Straatsma, M. W., Vannametee, E., Wisser, D., and Bierkens, M. F. P.: PCR-GLOBWB 2: a 5 arcmin global hydrological and water resources model, Geosci. Model Dev., 11, 2429–2453, https://doi.org/10.5194/gmd-11-2429-2018, 2018.
Takahashi, T.: A Review of Japanese Debris Flow Research, Int. J. Erosion Contr. Eng., 2, 1–14, https://doi.org/10.13101/ijece.2.1, 2009.
Tangi, M., Schmitt, R., Bizzi, S., and Castelletti, A.: The CASCADE toolbox for analyzing river sediment connectivity and management, Environ. Model. Softw., 119, 400–406, https://doi.org/10.1016/j.envsoft.2019.07.008, 2019.
Tanyaş, H., van Westen, C. J., Allstadt, K. E., and Jibson, R. W.: Factors controlling landslide frequency–area distributions, Earth Surf. Proc. Land., 44, 900–917, https://doi.org/10.1002/esp.4543, 2019.
Tavares da Costa, R., Mazzoli, P., and Bagli, S.: Limitations Posed by Free DEMs in Watershed Studies: The Case of River Tanaro in Italy, Front. Earth Sci., 7, 141, https://doi.org/10.3389/feart.2019.00141, 2019.
Terzago, S., Palazzi, E., and von Hardenberg, J.: Stochastic downscaling of precipitation in complex orography: a simple method to reproduce a realistic fine-scale climatology, Nat. Hazards Earth Syst. Sci., 18, 2825–2840, https://doi.org/10.5194/nhess-18-2825-2018, 2018.
Theule, J.: Geomorphic study of sediment dynamics in active debris-flow catchments (French Alps), Environmental Sciences, Doctorat de l'université de Grenoble, Science de la Terre, de l'Univers et de l'Environnement, Grenoble, https://hal.science/tel-02600319/ (last access: 1 November 2023), 2012.
Tian, J., Zhang, B., He, C., and Yang, L.: Variability In Soil Hydraulic Conductivity And Soil Hydrological Response Under Different Land Covers In The Mountainous Area Of The Heihe River Watershed, Northwest China, Land Degrad. Dev., 28, 1437–1449, https://doi.org/10.1002/ldr.2665, 2016.
Tóth, B., Weynants, M., Pásztor, L., and Hengl, T.: 3D soil hydraulic database of Europe at 250 m resolution, Hydrol. Process., 31, 2662–2666, https://doi.org/10.1002/hyp.11203, 2017.
Tramblay, Y., Bouvier, C., Martin, C., Didon-Lescot, J.-F., Todorovik, D., and Domergue, J.-M.: Assessment of initial soil moisture conditions for event-based rainfall–runoff modelling, J. Hydrol., 387, 176–187, https://doi.org/10.1016/j.jhydrol.2010.04.006, 2010.
Uber, M., Vandervaere, J.-P., Zin, I., Braud, I., Heistermann, M., Legoût, C., Molinié, G., and Nord, G.: How does initial soil moisture influence the hydrological response? A case study from southern France, Hydrol. Earth Syst. Sci., 22, 6127–6146, https://doi.org/10.5194/hess-22-6127-2018, 2018.
Vakhshoori, V. and Zare, M.: Is the ROC curve a reliable tool to compare the validity of landslide susceptibility maps?, Geomat. Nat. Hazards Risk, 9, 249–266, https://doi.org/10.1080/19475705.2018.1424043, 2018.
Van Der Knijff, J. M., Younis, J., and De Roo, A. P. J.: LISFLOOD: a GIS-based distributed model for river basin scale water balance and flood simulation, Int. J. Geogr. Inform. Sci., 24, 189–212, https://doi.org/10.1080/13658810802549154, 2010.
Van Genuchten, M.: A Closed-form Equation for Predicting the Hydraulic Conductivity of Unsaturated Soils1, Soil Sci. Soc. Am. J., 44, 892–898, https://doi.org/10.2136/sssaj1980.03615995004400050002x, 1980.
Vetsch, D., Siviglia, A., Caponi, F., Ehrbar, D., Gerke, E., Kammerer, S., Koch, A., Peter, S., Vanzo, D., Vonwiller, L., Facchini, M., Gerber, M., Volz, C., Farshi, D., Mueller, R., Rousselot, P., Veprek, R., and Faeh, R.: System Manuals of BASEMENT Version 2.8, https://people.ee.ethz.ch/~basement/baseweb/download/documentation/BMdoc_Reference_Manual_v2-8-2.pdf (last access: 1 November 2023), 2018.
Vitvar, T., Burns, D. A., Lawrence, G. B., McDonnell, J. J., and Wolock, D. M.: Estimation of baseflow residence times in watersheds from the runoff hydrograph recession: method and application in the Neversink watershed, Catskill Mountains, New York, Hydrol. Process., 16, 1871–1877, https://doi.org/10.1002/hyp.5027, 2002.
Yu, B., Xie, C., Cai, S., Chen, Y., Lv, Y., Mo, Z., Liu, T., and Yang, Z.: Effects of Tree Root Density on Soil Total Porosity and Non-Capillary Porosity Using a Ground-Penetrating Tree Radar Unit in Shanghai, China, Sustainability, 10, 4640, https://doi.org/10.3390/su10124640, 2018.
Zhang, H., Li, Z., Saifullah, M., Li, Q., and Li, X.: Impact of DEM Resolution and Spatial Scale: Analysis of Influence Factors and Parameters on Physically Based Distributed Model, Adv. Meteorol., 2016, 8582041, https://doi.org/10.1155/2016/8582041, 2016.
Zheng, S., Zhang, G., Yuan, X., Ye, F., and Fu, W.: Failure characteristics of shallow soil slope considering surface runoff and interstitial flow, Geomat. Nat. Hazards Risk, 11, 845–868, https://doi.org/10.1080/19475705.2020.1758222, 2020.
Zomlot, Z., Verbeiren, B., Huysmans, M., and Batelaan, O.: Spatial distribution of groundwater recharge and base flow: Assessment of controlling factors, J. Hydrol.: Reg. Stud., 4, 349–368, https://doi.org/10.1016/j.ejrh.2015.07.005, 2015.
Short summary
CRHyME (Climatic Rainfall Hydrogeological Modelling Experiment) is a new physically based and spatially distributed rainfall-runoff model. The main novelties consist of reproducing rainfall-induced geo-hydrological hazards such as shallow landslide, debris flow and watershed erosion through a multi-hazard approach. CRHyME was written in Python, works at a high spatial and temporal resolution, and is a tool suitable for quantifying extreme rainfall consequences at the basin scale.
CRHyME (Climatic Rainfall Hydrogeological Modelling Experiment) is a new physically based and...
Altmetrics
Final-revised paper
Preprint