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.
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
Current and future rainfall-driven flood risk from hurricanes in Puerto Rico under 1.5 and 2 °C climate change
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
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
Flash Flood Detection via Copula-based IDF Curves: Evidence from Jamaica
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
Assessing the next generation of Global Flood Models in the Central Highlands of Vietnam
A methodological framework for the evaluation of short-range flash-flood hydrometeorological forecasts at the event scale
Does a convection-permitting regional climate model bring new perspectives on the projection of Mediterranean floods?
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
Brief communication: The potential use of low-cost acoustic sensors to detect rainfall for short-term urban flood warnings
Brief communication: On the extremeness of the July 2021 precipitation event in western Germany
A climate-conditioned catastrophe risk model for UK flooding
A globally applicable framework for compound flood hazard modeling
Transferability of data-driven models to predict urban pluvial flood water depth in Berlin, Germany
Seasonal forecasting of local-scale soil moisture droughts with Global BROOK90
Brief communication: Inclusiveness in designing an early warning system for flood resilience
Evolution of multivariate drought hazard, vulnerability and risk in India under climate change
A multi-disciplinary analysis of the exceptional flood event of July 2021 in central Europe – Part 1: Event description and analysis
Bare-earth DEM generation from ArcticDEM and its use in flood simulation
Comparison of estimated flood exposure and consequences generated by different event-based inland flood inundation maps
How uncertain are precipitation and peak flow estimates for the July 2021 flooding event?
Estimating the likelihood of roadway pluvial flood based on crowdsourced traffic data and depression-based DEM analysis
A multi-strategy-mode waterlogging-prediction framework for urban flood depth
Multiscale flood risk assessment under climate change: the case of the Miño River in the city of Ourense, Spain
Interactions between precipitation, evapotranspiration and soil-moisture-based indices to characterize drought with high-resolution remote sensing and land-surface model data
How to mitigate flood events similar to the 1979 catastrophic floods in lower Tagus
Rare flood scenarios for a rapidly growing high-mountain city: Pokhara, Nepal
Brief communication: Impact forecasting could substantially improve the emergency management of deadly floods: case study July 2021 floods in Germany
Brief communication: Western Europe flood in 2021 – mapping agriculture flood exposure from synthetic aperture radar (SAR)
Comprehensive space–time hydrometeorological simulations for estimating very rare floods at multiple sites in a large river basin
A new index to quantify the extremeness of precipitation across scales
Effectiveness of Sentinel-1 and Sentinel-2 for flood detection assessment in Europe
Assessing flood hazard changes using climate model forcing
Characterizing multivariate coastal flooding events in a semi-arid region: the implications of copula choice, sampling, and infrastructure
Different drought types and the spatial variability in their hazard, impact, and propagation characteristics
More than heavy rain turning into fast-flowing water – a landscape perspective on the 2021 Eifel floods
Integrated drought risk assessment to support adaptive policymaking in the Netherlands
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.
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.
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.
Dino Collalti, Nekeisha Spencer, and Eric Strobl
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-162, https://doi.org/10.5194/nhess-2023-162, 2023
Revised manuscript accepted for NHESS
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.
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).
Laurence Hawker, Jeffrey Neal, James Savage, Thomas Kirkpatrick, Rachel Lord, Yanos Zylberberg, Andre Groeger, Truong Dang Thuy, Sean Fox, Felix Agyemang, and Khanh Pham Nam
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-93, https://doi.org/10.5194/nhess-2023-93, 2023
Revised manuscript accepted for NHESS
Short summary
Short summary
A global flood model built using a new terrain dataset and evaluated in the central highlands of Vietnam.
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.
Nils Poncet, Philippe Lucas-Picher, Yves Tramblay, Guillaume Thirel, Humberto Vergara, Jonathan Gourley, and Antoinette Alias
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-82, https://doi.org/10.5194/nhess-2023-82, 2023
Revised manuscript accepted for NHESS
Short summary
Short summary
A high resolution convection-permitting climate model is coupled with hydrological models over a Mediterranean catchment to simulate historical and future flood events. Results show the added value of this new generation of climate models for simulating Mediterranean floods. Future projections show an increase of the magnitude of the largest floods while the moderate floods are expected to decrease. Most floods are expected to become flashier i.e. potentially catastrophic in a warmer climate.
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.
Nadav Peleg, Herminia Torelló-Sentelles, Grégoire Mariéthoz, Lionel Benoit, João P. Leitão, and Francesco Marra
Nat. Hazards Earth Syst. Sci., 23, 1233–1240, https://doi.org/10.5194/nhess-23-1233-2023, https://doi.org/10.5194/nhess-23-1233-2023, 2023
Short summary
Short summary
Floods in urban areas are one of the most common natural hazards. Due to climate change enhancing extreme rainfall and cities becoming larger and denser, the impacts of these events are expected to increase. A fast and reliable flood warning system should thus be implemented in flood-prone cities to warn the public of upcoming floods. The purpose of this brief communication is to discuss the potential implementation of low-cost acoustic rainfall sensors in short-term flood warning systems.
Katharina Lengfeld, Paul Voit, Frank Kaspar, and Maik Heistermann
Nat. Hazards Earth Syst. Sci., 23, 1227–1232, https://doi.org/10.5194/nhess-23-1227-2023, https://doi.org/10.5194/nhess-23-1227-2023, 2023
Short summary
Short summary
Estimating the severity of a rainfall event based on the damage caused is easy but highly depends on the affected region. A less biased measure for the extremeness of an event is its rarity combined with its spatial extent. In this brief communication, we investigate the sensitivity of such measures to the underlying dataset and highlight the importance of considering multiple spatial and temporal scales using the devastating rainfall event in July 2021 in central Europe as an example.
Paul D. Bates, James Savage, Oliver Wing, Niall Quinn, Christopher Sampson, Jeffrey Neal, and Andrew Smith
Nat. Hazards Earth Syst. Sci., 23, 891–908, https://doi.org/10.5194/nhess-23-891-2023, https://doi.org/10.5194/nhess-23-891-2023, 2023
Short summary
Short summary
We present and validate a model that simulates current and future flood risk for the UK at high resolution (~ 20–25 m). We show that UK flood losses were ~ 6 % greater in the climate of 2020 compared to recent historical values. The UK can keep any future increase to ~ 8 % if all countries implement their COP26 pledges and net-zero ambitions in full. However, if only the COP26 pledges are fulfilled, then UK flood losses increase by ~ 23 %; and potentially by ~ 37 % in a worst-case scenario.
Dirk Eilander, Anaïs Couasnon, Tim Leijnse, Hiroaki Ikeuchi, Dai Yamazaki, Sanne Muis, Job Dullaart, Arjen Haag, Hessel C. Winsemius, and Philip J. Ward
Nat. Hazards Earth Syst. Sci., 23, 823–846, https://doi.org/10.5194/nhess-23-823-2023, https://doi.org/10.5194/nhess-23-823-2023, 2023
Short summary
Short summary
In coastal deltas, flooding can occur from interactions between coastal, riverine, and pluvial drivers, so-called compound flooding. Global models however ignore these interactions. We present a framework for automated and reproducible compound flood modeling anywhere globally and validate it for two historical events in Mozambique with good results. The analysis reveals differences in compound flood dynamics between both events related to the magnitude of and time lag between drivers.
Omar Seleem, Georgy Ayzel, Axel Bronstert, and Maik Heistermann
Nat. Hazards Earth Syst. Sci., 23, 809–822, https://doi.org/10.5194/nhess-23-809-2023, https://doi.org/10.5194/nhess-23-809-2023, 2023
Short summary
Short summary
Data-driven models are becoming more of a surrogate that overcomes the limitations of the computationally expensive 2D hydrodynamic models to map urban flood hazards. However, the model's ability to generalize outside the training domain is still a major challenge. We evaluate the performance of random forest and convolutional neural networks to predict urban floodwater depth and investigate their transferability outside the training domain.
Ivan Vorobevskii, Thi Thanh Luong, and Rico Kronenberg
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-9, https://doi.org/10.5194/nhess-2023-9, 2023
Revised manuscript accepted for NHESS
Short summary
Short summary
The study presents a new version of a framework which allow to model water balance components at any site for a local scale. In comparison to the first version, the second one incorporates new datasets used to setup and force the model. In particular, we want to highlight the ability of the framework to provide seasonal forecasts. This gives the potential stakeholders (farmers, foresters, policymakers etc.) possibility to forecast e.g. soil moisture drought and thus apply necessary measures.
Tahmina Yasmin, Kieran Khamis, Anthony Ross, Subir Sen, Anita Sharma, Debashish Sen, Sumit Sen, Wouter Buytaert, and David M. Hannah
Nat. Hazards Earth Syst. Sci., 23, 667–674, https://doi.org/10.5194/nhess-23-667-2023, https://doi.org/10.5194/nhess-23-667-2023, 2023
Short summary
Short summary
Floods continue to be a wicked problem that require developing early warning systems with plausible assumptions of risk behaviour, with more targeted conversations with the community at risk. Through this paper we advocate the use of a SMART approach to encourage bottom-up initiatives to develop inclusive and purposeful early warning systems that benefit the community at risk by engaging them at every step of the way along with including other stakeholders at multiple scales of operations.
Venkataswamy Sahana and Arpita Mondal
Nat. Hazards Earth Syst. Sci., 23, 623–641, https://doi.org/10.5194/nhess-23-623-2023, https://doi.org/10.5194/nhess-23-623-2023, 2023
Short summary
Short summary
In an agriculture-dependent, densely populated country such as India, drought risk projection is important to assess future water security. This study presents the first comprehensive drought risk assessment over India, integrating hazard and vulnerability information. Future drought risk is found to be more significantly driven by increased vulnerability resulting from societal developments rather than climate-induced changes in hazard. These findings can inform planning for drought resilience.
Susanna Mohr, Uwe Ehret, Michael Kunz, Patrick Ludwig, Alberto Caldas-Alvarez, James E. Daniell, Florian Ehmele, Hendrik Feldmann, Mário J. Franca, Christian Gattke, Marie Hundhausen, Peter Knippertz, Katharina Küpfer, Bernhard Mühr, Joaquim G. Pinto, Julian Quinting, Andreas M. Schäfer, Marc Scheibel, Frank Seidel, and Christina Wisotzky
Nat. Hazards Earth Syst. Sci., 23, 525–551, https://doi.org/10.5194/nhess-23-525-2023, https://doi.org/10.5194/nhess-23-525-2023, 2023
Short summary
Short summary
The flood event in July 2021 was one of the most severe disasters in Europe in the last half century. The objective of this two-part study is a multi-disciplinary assessment that examines the complex process interactions in different compartments, from meteorology to hydrological conditions to hydro-morphological processes to impacts on assets and environment. In addition, we address the question of what measures are possible to generate added value to early response management.
Yinxue Liu, Paul D. Bates, and Jeffery C. Neal
Nat. Hazards Earth Syst. Sci., 23, 375–391, https://doi.org/10.5194/nhess-23-375-2023, https://doi.org/10.5194/nhess-23-375-2023, 2023
Short summary
Short summary
In this paper, we test two approaches for removing buildings and other above-ground objects from a state-of-the-art satellite photogrammetry topography product, ArcticDEM. Our best technique gives a 70 % reduction in vertical error, with an average difference of 1.02 m from a benchmark lidar for the city of Helsinki, Finland. When used in a simulation of rainfall-driven flooding, the bare-earth version of ArcticDEM yields a significant improvement in predicted inundation extent and water depth.
Joseph L. Gutenson, Ahmad A. Tavakoly, Mohammad S. Islam, Oliver E. J. Wing, William P. Lehman, Chase O. Hamilton, Mark D. Wahl, and T. Christopher Massey
Nat. Hazards Earth Syst. Sci., 23, 261–277, https://doi.org/10.5194/nhess-23-261-2023, https://doi.org/10.5194/nhess-23-261-2023, 2023
Short summary
Short summary
Emergency managers use event-based flood inundation maps (FIMs) to plan and coordinate flood emergency response. We perform a case study test of three different FIM frameworks to see if FIM differences lead to substantial differences in the location and magnitude of flood exposure and consequences. We find that the FIMs are very different spatially and that the spatial differences do produce differences in the location and magnitude of exposure and consequences.
Mohamed Saadi, Carina Furusho-Percot, Alexandre Belleflamme, Ju-Yu Chen, Silke Trömel, and Stefan Kollet
Nat. Hazards Earth Syst. Sci., 23, 159–177, https://doi.org/10.5194/nhess-23-159-2023, https://doi.org/10.5194/nhess-23-159-2023, 2023
Short summary
Short summary
On 14 July 2021, heavy rainfall fell over central Europe, causing considerable damage and human fatalities. We analyzed how accurate our estimates of rainfall and peak flow were for these flooding events in western Germany. We found that the rainfall estimates from radar measurements were improved by including polarimetric variables and their vertical gradients. Peak flow estimates were highly uncertain due to uncertainties in hydrological model parameters and rainfall measurements.
Arefeh Safaei-Moghadam, David Tarboton, and Barbara Minsker
Nat. Hazards Earth Syst. Sci., 23, 1–19, https://doi.org/10.5194/nhess-23-1-2023, https://doi.org/10.5194/nhess-23-1-2023, 2023
Short summary
Short summary
Climate change, urbanization, and aging infrastructure contribute to flooding on roadways. This study evaluates the potential for flood reports collected from Waze – a community-based navigation app – to predict these events. Waze reports correlate primarily with low-lying depressions on roads. Therefore, we developed two data-driven models to determine whether roadways will flood. Analysis showed that in the city of Dallas, drainage area and imperviousness are the most significant contributors.
Zongjia Zhang, Jun Liang, Yujue Zhou, Zhejun Huang, Jie Jiang, Junguo Liu, and Lili Yang
Nat. Hazards Earth Syst. Sci., 22, 4139–4165, https://doi.org/10.5194/nhess-22-4139-2022, https://doi.org/10.5194/nhess-22-4139-2022, 2022
Short summary
Short summary
An innovative multi-strategy-mode waterlogging-prediction framework for predicting waterlogging depth is proposed in the paper. The framework selects eight regression algorithms for comparison and tests the prediction accuracy and robustness of the model under different prediction strategies. Ultimately, the accuracy of predicting water depth after 30 min can exceed 86.1 %. This can aid decision-making in terms of issuing early warning information and determining emergency responses in advance.
Diego Fernández-Nóvoa, Orlando García-Feal, José González-Cao, Maite deCastro, and Moncho Gómez-Gesteira
Nat. Hazards Earth Syst. Sci., 22, 3957–3972, https://doi.org/10.5194/nhess-22-3957-2022, https://doi.org/10.5194/nhess-22-3957-2022, 2022
Short summary
Short summary
A multiscale analysis, where the historical and future precipitation data from the CORDEX project were used as input in a hydrological model (HEC-HMS) that, in turn, feeds a 2D hydraulic model (Iber+), was applied to the case of the Miño-Sil basin (NW Spain), specifically to Ourense city, in order to analyze future changes in flood hazard. Detailed flood maps indicate an increase in the frequency and intensity of future floods, implying an increase in flood hazard in important areas of the city.
Jaime Gaona, Pere Quintana-Seguí, María José Escorihuela, Aaron Boone, and María Carmen Llasat
Nat. Hazards Earth Syst. Sci., 22, 3461–3485, https://doi.org/10.5194/nhess-22-3461-2022, https://doi.org/10.5194/nhess-22-3461-2022, 2022
Short summary
Short summary
Droughts represent a particularly complex natural hazard and require explorations of their multiple causes. Part of the complexity has roots in the interaction between the continuous changes in and deviation from normal conditions of the atmosphere and the land surface. The exchange between the atmospheric and surface conditions defines feedback towards dry or wet conditions. In semi-arid environments, energy seems to exceed water in its impact over the evolution of conditions, favoring drought.
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. Discuss., https://doi.org/10.5194/nhess-2022-243, https://doi.org/10.5194/nhess-2022-243, 2022
Revised manuscript accepted for NHESS
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 Iber+ numerical model and on the development of dam operating strategies to mitigate the flood episodes using the outstating floods of February 1979 as benchmark. Obtained results corroborate the model capability to evaluate floods in the study area and confirm the effectiveness of the proposed strategies to reduce flood impact in lower Tagus valley.
Melanie Fischer, Jana Brettin, Sigrid Roessner, Ariane Walz, Monique Fort, and Oliver Korup
Nat. Hazards Earth Syst. Sci., 22, 3105–3123, https://doi.org/10.5194/nhess-22-3105-2022, https://doi.org/10.5194/nhess-22-3105-2022, 2022
Short summary
Short summary
Nepal’s second-largest city has been rapidly growing since the 1970s, although its valley has been affected by rare, catastrophic floods in recent and historic times. We analyse potential impacts of such floods on urban areas and infrastructure by modelling 10 physically plausible flood scenarios along Pokhara’s main river. We find that hydraulic effects would largely affect a number of squatter settlements, which have expanded rapidly towards the river by a factor of up to 20 since 2008.
Heiko Apel, Sergiy Vorogushyn, and Bruno Merz
Nat. Hazards Earth Syst. Sci., 22, 3005–3014, https://doi.org/10.5194/nhess-22-3005-2022, https://doi.org/10.5194/nhess-22-3005-2022, 2022
Short summary
Short summary
The paper presents a fast 2D hydraulic simulation model for flood propagation that enables operational forecasts of spatially distributed inundation depths, flood extent, flow velocities, and other flood impacts. The detailed spatial forecast of floods and flood impacts is a large step forward from the currently operational forecasts of discharges at selected gauges, thus enabling a more targeted flood management and early warning.
Kang He, Qing Yang, Xinyi Shen, and Emmanouil N. Anagnostou
Nat. Hazards Earth Syst. Sci., 22, 2921–2927, https://doi.org/10.5194/nhess-22-2921-2022, https://doi.org/10.5194/nhess-22-2921-2022, 2022
Short summary
Short summary
This study depicts the flood-affected areas in western Europe in July 2021 and particularly the agriculture land that was under flood inundation. The results indicate that the total inundated area over western Europe is about 1920 km2, of which 1320 km2 is in France. Around 64 % of the inundated area is agricultural land. We expect that the agricultural productivity in western Europe will have been severely impacted.
Daniel Viviroli, Anna E. Sikorska-Senoner, Guillaume Evin, Maria Staudinger, Martina Kauzlaric, Jérémy Chardon, Anne-Catherine Favre, Benoit Hingray, Gilles Nicolet, Damien Raynaud, Jan Seibert, Rolf Weingartner, and Calvin Whealton
Nat. Hazards Earth Syst. Sci., 22, 2891–2920, https://doi.org/10.5194/nhess-22-2891-2022, https://doi.org/10.5194/nhess-22-2891-2022, 2022
Short summary
Short summary
Estimating the magnitude of rare to very rare floods is a challenging task due to a lack of sufficiently long observations. The challenge is even greater in large river basins, where precipitation patterns and amounts differ considerably between individual events and floods from different parts of the basin coincide. We show that a hydrometeorological model chain can provide plausible estimates in this setting and can thus inform flood risk and safety assessments for critical infrastructure.
Paul Voit and Maik Heistermann
Nat. Hazards Earth Syst. Sci., 22, 2791–2805, https://doi.org/10.5194/nhess-22-2791-2022, https://doi.org/10.5194/nhess-22-2791-2022, 2022
Short summary
Short summary
To better understand how the frequency and intensity of heavy precipitation events (HPEs) will change with changing climate and to adapt disaster risk management accordingly, we have to quantify the extremeness of HPEs in a reliable way. We introduce the xWEI (cross-scale WEI) and show that this index can reveal important characteristics of HPEs that would otherwise remain hidden. We conclude that the xWEI could be a valuable instrument in both disaster risk management and research.
Angelica Tarpanelli, Alessandro C. Mondini, and Stefania Camici
Nat. Hazards Earth Syst. Sci., 22, 2473–2489, https://doi.org/10.5194/nhess-22-2473-2022, https://doi.org/10.5194/nhess-22-2473-2022, 2022
Short summary
Short summary
We analysed 10 years of river discharge data from almost 2000 sites in Europe, and we extracted flood events, as proxies of flood inundations, based on the overpasses of Sentinel-1 and Sentinel-2 satellites to derive the percentage of potential inundation events that they were able to observe. Results show that on average 58 % of flood events are potentially observable by Sentinel-1 and only 28 % by Sentinel-2 due to the obstacle of cloud coverage.
David P. Callaghan and Michael G. Hughes
Nat. Hazards Earth Syst. Sci., 22, 2459–2472, https://doi.org/10.5194/nhess-22-2459-2022, https://doi.org/10.5194/nhess-22-2459-2022, 2022
Short summary
Short summary
A new method was developed to estimate changes in flood hazard under climate change. We use climate projections covering New South Wales, Australia, with two emission paths of business as usual and one with reduced emissions. We apply our method to the lower floodplain of the Gwydir Valley with changes in flood hazard provided over the next 90 years compared with the previous 50 years. We find that changes in flood hazard decrease over time within the Gwydir Valley floodplain.
Joseph T. D. Lucey and Timu W. Gallien
Nat. Hazards Earth Syst. Sci., 22, 2145–2167, https://doi.org/10.5194/nhess-22-2145-2022, https://doi.org/10.5194/nhess-22-2145-2022, 2022
Short summary
Short summary
Coastal flooding can result from multiple flood drivers (e.g., tides, waves, river flows, rainfall) occurring at the same time. This study characterizes flooding events caused by high marine water levels and rain. Results show that wet-season coinciding sampling may better describe extreme flooding events in a dry, tidally dominated region. A joint-probability-based function is then used to estimate sea wall impacts on urban coastal flooding.
Erik Tijdeman, Veit Blauhut, Michael Stoelzle, Lucas Menzel, and Kerstin Stahl
Nat. Hazards Earth Syst. Sci., 22, 2099–2116, https://doi.org/10.5194/nhess-22-2099-2022, https://doi.org/10.5194/nhess-22-2099-2022, 2022
Short summary
Short summary
We identified different drought types with typical hazard and impact characteristics. The summer drought type with compounding heat was most impactful. Regional drought propagation of this drought type exhibited typical characteristics that can guide drought management. However, we also found a large spatial variability that caused distinct differences among propagating drought signals. Accordingly, local multivariate drought information was needed to explain the full range of drought impacts.
Michael Dietze, Rainer Bell, Ugur Ozturk, Kristen L. Cook, Christoff Andermann, Alexander R. Beer, Bodo Damm, Ana Lucia, Felix S. Fauer, Katrin M. Nissen, Tobias Sieg, and Annegret H. Thieken
Nat. Hazards Earth Syst. Sci., 22, 1845–1856, https://doi.org/10.5194/nhess-22-1845-2022, https://doi.org/10.5194/nhess-22-1845-2022, 2022
Short summary
Short summary
The flood that hit Europe in July 2021, specifically the Eifel, Germany, was more than a lot of fast-flowing water. The heavy rain that fell during the 3 d before also caused the slope to fail, recruited tree trunks that clogged bridges, and routed debris across the landscape. Especially in the upper parts of the catchments the flood was able to gain momentum. Here, we discuss how different landscape elements interacted and highlight the challenges of holistic future flood anticipation.
Marjolein J. P. Mens, Gigi van Rhee, Femke Schasfoort, and Neeltje Kielen
Nat. Hazards Earth Syst. Sci., 22, 1763–1776, https://doi.org/10.5194/nhess-22-1763-2022, https://doi.org/10.5194/nhess-22-1763-2022, 2022
Short summary
Short summary
Many countries have to prepare for droughts by proposing policy actions to increase water supply, reduce water demand, or limit the societal impact. Societal cost–benefit analysis is required to support decision-making for a range of future scenarios, accounting for climate change and socio-economic developments. This paper presents a framework to assess drought policy actions based on quantification of drought risk and exemplifies it for the Netherlands’ drought risk management strategy.
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