Articles | Volume 23, issue 4
https://doi.org/10.5194/nhess-23-1453-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-23-1453-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
20 Apr 2023
Research article |
| 20 Apr 2023
| 20 Apr 2023
Hydrological drought forecasting under a changing environment in the Luanhe River basin
Min Li
CORRESPONDING AUTHOR
College of Hydraulic Science and Engineering, Yangzhou University, Yangzhou, 225000, China
State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin, 300072, China
Mingfeng Zhang
College of Hydraulic Science and Engineering, Yangzhou University, Yangzhou, 225000, China
Runxiang Cao
College of Water Resources, North China University of Water Resources and Electric Power, Zhengzhou, 450046, China
Yidi Sun
College of Hydraulic Science and Engineering, Yangzhou University, Yangzhou, 225000, China
Xiyuan Deng
CORRESPONDING AUTHOR
Nanjing Hydraulic Research Institute, Nanjing, 210029, China
State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Nanjing, 210029, China
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Min Li, Yuhang Yao, Zilong Feng, and Ming Ou
EGUsphere, https://doi.org/10.5194/egusphere-2025-1891, https://doi.org/10.5194/egusphere-2025-1891, 2025
This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
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This study proposes an innovative method for predicting drought in the Huaihe River Basin of China using advanced machine learning and interpretable artificial intelligence techniques. By analyzing more than 50 years of data, the model successfully predicted four drought categories with an accuracy of 79.9 %. It used explanatory methods to analyze the contribution of different drought influencing factors, providing key insights for early warning systems and water resources planning.
Min Li, Zilong Feng, Mingfeng Zhang, Lijie Shi, and Yuhang Yao
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-174, https://doi.org/10.5194/nhess-2024-174, 2025
Preprint under review for NHESS
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The purpose of this study is to analyse the effects of climate change and watershed characteristics on drought transmission. Based on the GAMLSS framework and the Copula model, the probabilities and thresholds for the spread of drought in different seasons are calculated without the influence of climate factors. The results show that the spatio-temporal changes in the spread of drought are influenced by climate change and watershed characteristics.
Min Li, Yuhang Yao, Zilong Feng, and Ming Ou
EGUsphere, https://doi.org/10.5194/egusphere-2025-1891, https://doi.org/10.5194/egusphere-2025-1891, 2025
This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
Short summary
Short summary
This study proposes an innovative method for predicting drought in the Huaihe River Basin of China using advanced machine learning and interpretable artificial intelligence techniques. By analyzing more than 50 years of data, the model successfully predicted four drought categories with an accuracy of 79.9 %. It used explanatory methods to analyze the contribution of different drought influencing factors, providing key insights for early warning systems and water resources planning.
Min Li, Zilong Feng, Mingfeng Zhang, Lijie Shi, and Yuhang Yao
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-174, https://doi.org/10.5194/nhess-2024-174, 2025
Preprint under review for NHESS
Short summary
Short summary
The purpose of this study is to analyse the effects of climate change and watershed characteristics on drought transmission. Based on the GAMLSS framework and the Copula model, the probabilities and thresholds for the spread of drought in different seasons are calculated without the influence of climate factors. The results show that the spatio-temporal changes in the spread of drought are influenced by climate change and watershed characteristics.
Hongwei Liu, Jiufu Liu, Wenzhong Wang, Xing Min, Hao Zheng, Xiyuan Deng, and Niu Wang
Proc. IAHS, 383, 85–91, https://doi.org/10.5194/piahs-383-85-2020, https://doi.org/10.5194/piahs-383-85-2020, 2020
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To improve the hydrometric methods in the high-altitude area, and learn more about the hydrological mechanism in the Qinghai-Tibet Plateau, a series of observation research were carried out in the Niyang River watershed, a tributary of the Yarlung Zangbo River. The applicability of the hydrometric methods and instruments were discussed according to the monitoring situation. Based on the δD, δ18O, and the geochemical observed dataset, the runoff composition characteristics were analyzed.
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Till Francke and Maik Heistermann
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Brandenburg is among the driest federal states in Germany. The low ground water recharge (GWR) is fundamental to both water supply and the support of natural ecosystems. In this study, we show that the decline of observed discharge and groundwater tables since 1980 can be explained by climate change in combination with an increasing leaf area index. Still, simulated GWR rates remain highly uncertain due to the uncertainty of precipitation trends.
Paola Ceresa, Gianbattista Bussi, Simona Denaro, Gabriele Coccia, Paolo Bazzurro, Mario Martina, Ettore Fagà, Carlos Avelar, Mario Ordaz, Benjamin Huerta, Osvaldo Garay, Zhanar Raimbekova, Kanatbek Abdrakhmatov, Sitora Mirzokhonova, Vakhitkhan Ismailov, and Vladimir Belikov
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Roberto Bentivoglio, Elvin Isufi, Sebastiaan Nicolas Jonkman, and Riccardo Taormina
Nat. Hazards Earth Syst. Sci., 25, 335–351, https://doi.org/10.5194/nhess-25-335-2025, https://doi.org/10.5194/nhess-25-335-2025, 2025
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Deep learning methods are increasingly used as surrogates for spatio-temporal flood models but struggle with generalization and speed. Here, we propose a multi-resolution approach using graph neural networks that predicts dike breach floods across different meshes, topographies, and boundary conditions with high accuracy and up to 1000× speed-ups. The model also generalizes to larger more complex case studies with just one additional simulation for fine-tuning.
Maria Staudinger, Martina Kauzlaric, Alexandre Mas, Guillaume Evin, Benoit Hingray, and Daniel Viviroli
Nat. Hazards Earth Syst. Sci., 25, 247–265, https://doi.org/10.5194/nhess-25-247-2025, https://doi.org/10.5194/nhess-25-247-2025, 2025
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Various combinations of antecedent conditions and precipitation result in floods of varying degrees. Antecedent conditions played a crucial role in generating even large ones. The key predictors and spatial patterns of antecedent conditions leading to flooding at the basin's outlet were distinct. Precipitation and soil moisture from almost all sub-catchments were important for more frequent floods. For rarer events, only the predictors of specific sub-catchments were important.
Paul Voit and Maik Heistermann
Nat. Hazards Earth Syst. Sci., 24, 4609–4615, https://doi.org/10.5194/nhess-24-4609-2024, https://doi.org/10.5194/nhess-24-4609-2024, 2024
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Floods have caused significant damage in the past. To prepare for such events, we rely on historical data but face issues due to rare rainfall events, lack of data and climate change. Counterfactuals, or
what ifscenarios, simulate historical rainfall in different locations to estimate flood levels. Our new study refines this by deriving more-plausible local scenarios, using the June 2024 Bavaria flood as a case study. This method could improve preparedness for future floods.
Chinh Luu, Giuseppe Forino, Lynda Yorke, Hang Ha, Quynh Duy Bui, Hanh Hong Tran, Dinh Quoc Nguyen, Hieu Cong Duong, and Matthieu Kervyn
Nat. Hazards Earth Syst. Sci., 24, 4385–4408, https://doi.org/10.5194/nhess-24-4385-2024, https://doi.org/10.5194/nhess-24-4385-2024, 2024
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This study presents a novel and integrated approach to assessing the climate hazards of floods and wildfires. We explore multi-hazard assessment and risk through a machine learning modeling approach. The process includes collecting a database of topography, climate, geology, environment, and building data; developing models for multi-hazard assessment and coding in the Google Earth Engine; and producing credible multi-hazard susceptibility and building exposure maps.
Claudia De Lucia, Michele Amaddii, and Chiara Arrighi
Nat. Hazards Earth Syst. Sci., 24, 4317–4339, https://doi.org/10.5194/nhess-24-4317-2024, https://doi.org/10.5194/nhess-24-4317-2024, 2024
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This work describes the flood damage to cultural heritage (CH) that occurred in September 2022 in central Italy. Datasets related to flood impacts on cultural heritage are rare, and this work aims at highlighting both tangible and intangible aspects and their correlation with physical characteristics of flood (i.e. water depth and flow velocity). The results show that current knowledge and datasets are inadequate for risk assessment of CH.
Pravin Maduwantha, Thomas Wahl, Sara Santamaria-Aguilar, Robert Jane, James F. Booth, Hanbeen Kim, and Gabriele Villarini
Nat. Hazards Earth Syst. Sci., 24, 4091–4107, https://doi.org/10.5194/nhess-24-4091-2024, https://doi.org/10.5194/nhess-24-4091-2024, 2024
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When assessing the likelihood of compound flooding, most studies ignore that it can arise from different storm types with distinct statistical characteristics. Here, we present a new statistical framework that accounts for these differences and shows how neglecting these can impact the likelihood of compound flood potential.
Bruno Merz, Günter Blöschl, Robert Jüpner, Heidi Kreibich, Kai Schröter, and Sergiy Vorogushyn
Nat. Hazards Earth Syst. Sci., 24, 4015–4030, https://doi.org/10.5194/nhess-24-4015-2024, https://doi.org/10.5194/nhess-24-4015-2024, 2024
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Flood risk assessments help us decide how to reduce the risk of flooding. Since these assessments are based on probabilities, it is hard to check their accuracy by comparing them to past data. We suggest a new way to validate these assessments, making sure they are practical for real-life decisions. This approach looks at both the technical details and the real-world situations where decisions are made. We demonstrate its practicality by applying it to flood emergency planning.
Zhi Li, Hanqi Li, Zhibo Zhang, Chaomeng Dai, and Simin Jiang
Nat. Hazards Earth Syst. Sci., 24, 3977–3990, https://doi.org/10.5194/nhess-24-3977-2024, https://doi.org/10.5194/nhess-24-3977-2024, 2024
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This study used advanced computer simulations to investigate how earthquake-induced building collapse affects flooding of the metro stations in Shanghai. Results show that the influences of building collapse on rainfall-driven and river-driven floods are different because these two types of floods have different origination and propagation mechanisms.
Maria Magdalena Warter, Dörthe Tetzlaff, Christian Marx, and Chris Soulsby
Nat. Hazards Earth Syst. Sci., 24, 3907–3924, https://doi.org/10.5194/nhess-24-3907-2024, https://doi.org/10.5194/nhess-24-3907-2024, 2024
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Streams are increasingly impacted by droughts and floods. Still, the amount of water needed for sustainable flows remains unclear and contested. A comparison of two streams in the Berlin–Brandenburg region of northeast Germany, using stable water isotopes, shows strong groundwater dependence with seasonal rainfall contributing to high/low flows. Understanding streamflow variability can help us assess the impacts of climate change on future water resource management.
Samuel Jonson Sutanto, Matthijs Janssen, Mariana Madruga de Brito, and Maria del Pozo Garcia
Nat. Hazards Earth Syst. Sci., 24, 3703–3721, https://doi.org/10.5194/nhess-24-3703-2024, https://doi.org/10.5194/nhess-24-3703-2024, 2024
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A conventional flood risk assessment only evaluates flood hazard in isolation without considering wildfires. This study, therefore, evaluates the effect of wildfires on flood risk, considering both current and future conditions for the Ebro River basin in Spain. Results show that extreme climate change increases the risk of flooding, especially when considering the effect of wildfires, highlighting the importance of adopting a multi-hazard risk management approach.
Miroslav Spano and Jaromir Riha
Nat. Hazards Earth Syst. Sci., 24, 3683–3701, https://doi.org/10.5194/nhess-24-3683-2024, https://doi.org/10.5194/nhess-24-3683-2024, 2024
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The study examines the effects of hydrogeological hazard due to construction of the Skalička Dam near the Hranice Karst on groundwater discharges and water levels in the local karst formations downstream. A simplified pipe model was used to analyze the impact of two dam layouts: lateral and through-flow reservoirs. Results show that the through-flow scheme more significantly influences water levels and the discharge of mineral water, while the lateral layout has only negligible impact.
Rudolf Brázdil, Dominika Faturová, Monika Šulc Michalková, Jan Řehoř, Martin Caletka, and Pavel Zahradníček
Nat. Hazards Earth Syst. Sci., 24, 3663–3682, https://doi.org/10.5194/nhess-24-3663-2024, https://doi.org/10.5194/nhess-24-3663-2024, 2024
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Flash floods belong to natural hazards that can be enhanced in frequency, intensity, and impact during recent climate change. This paper presents a complex analysis of spatiotemporal variability and human impacts (including material damage and fatalities) of flash floods in the Czech Republic for the 2001–2023 period. The analysis generally shows no statistically significant trends in the characteristics analyzed.
Melissa Wood, Ivan D. Haigh, Quan Quan Le, Hung Nghia Nguyen, Hoang Ba Tran, Stephen E. Darby, Robert Marsh, Nikolaos Skliris, and Joël J.-M. Hirschi
Nat. Hazards Earth Syst. Sci., 24, 3627–3649, https://doi.org/10.5194/nhess-24-3627-2024, https://doi.org/10.5194/nhess-24-3627-2024, 2024
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We look at how compound flooding from the combination of river flooding and storm tides (storm surge and 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 the potential to flood the region more extensively and be longer lasting than compound floods today. This is useful to know because it means managers of deltas such as the Mekong can assess options for improving existing flood defences.
Maryam Pakdehi, Ebrahim Ahmadisharaf, Behzad Nazari, and Eunsaem Cho
Nat. Hazards Earth Syst. Sci., 24, 3537–3559, https://doi.org/10.5194/nhess-24-3537-2024, https://doi.org/10.5194/nhess-24-3537-2024, 2024
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Machine learning (ML) algorithms have increasingly received attention for modeling flood events. However, there are concerns about the transferability of these models (their capability in predicting out-of-sample and unseen events). Here, we show that ML models can be transferable for hindcasting maximum river flood depths across extreme events (four hurricanes) in a large coastal watershed (HUC6) when informed by the spatial distribution of pertinent features and underlying physical processes.
Claudia Teutschbein, Thomas Grabs, Markus Giese, Andrijana Todorović, and Roland Barthel
EGUsphere, https://doi.org/10.5194/egusphere-2024-2742, https://doi.org/10.5194/egusphere-2024-2742, 2024
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This study explores how droughts develop and spread in high-latitude regions, focusing on the unique conditions found in areas like Scandinavia. It reveals that droughts affect soil, rivers, and groundwater differently, depending on factors like land cover, water availability, and soil properties. The findings highlight the importance of tailored water management strategies to protect resources and ecosystems in these regions, especially as climate change continues to impact weather patterns.
María Carmen Llasat, Montserrat Llasat-Botija, Erika Pardo, Raül Marcos-Matamoros, and Marc Lemus-Canovas
Nat. Hazards Earth Syst. Sci., 24, 3423–3443, https://doi.org/10.5194/nhess-24-3423-2024, https://doi.org/10.5194/nhess-24-3423-2024, 2024
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This paper shows the first public and systematic dataset of flood episodes referring to the entire Pyrenees massif, at municipal scale, named PIRAGUA_flood. Of the 181 flood events (1981–2015) that produced 154 fatalities, 36 were transnational, with the eastern part of the massif most affected. Dominant weather types show a southern component flow, with a talweg on the Iberian Peninsula and a depression in the vicinity. A positive and significant trend was found in Nouvelle-Aquitaine.
Colin M. Zarzycki, Benjamin D. Ascher, Alan M. Rhoades, and Rachel R. McCrary
Nat. Hazards Earth Syst. Sci., 24, 3315–3335, https://doi.org/10.5194/nhess-24-3315-2024, https://doi.org/10.5194/nhess-24-3315-2024, 2024
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We developed an automated workflow to detect rain-on-snow events, which cause flooding in the northeastern United States, 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.
Dongyu Feng, Zeli Tan, Darren Engwirda, Jonathan D. Wolfe, Donghui Xu, Chang Liao, Gautam Bisht, James J. Benedict, Tian Zhou, Mithun Deb, Hong-Yi Li, and L. Ruby Leung
EGUsphere, https://doi.org/10.5194/egusphere-2024-2785, https://doi.org/10.5194/egusphere-2024-2785, 2024
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Our study explores how riverine and coastal flooding during hurricanes is influenced by the interaction of atmosphere, land, river and ocean conditions. Using an advanced Earth system model, we simulate Hurricane Irene to evaluate how meteorological and hydrological uncertainties affect flood modeling. Our findings reveal the importance of a multi-component modeling system, how hydrological conditions play critical roles in flood modeling, and greater flood risks if multiple factors are present.
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
Nat. Hazards Earth Syst. Sci., 24, 3173–3205, https://doi.org/10.5194/nhess-24-3173-2024, https://doi.org/10.5194/nhess-24-3173-2024, 2024
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Drought is a creeping phenomenon but is often still analysed and managed like an isolated event, without taking into account what happened before and after. Here, we review the literature and analyse five cases to discuss how droughts and their impacts develop over time. We find that the responses of hydrological, ecological, and social systems can be classified into four types and that the systems interact. We provide suggestions for further research and monitoring, modelling, and management.
Sheik Umar Jam-Jalloh, Jia Liu, Yicheng Wang, and Yuchen Liu
Nat. Hazards Earth Syst. Sci., 24, 3155–3172, https://doi.org/10.5194/nhess-24-3155-2024, https://doi.org/10.5194/nhess-24-3155-2024, 2024
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Our paper explores improving flood forecasting using advanced weather and hydrological models. By coupling the WRF model with WRF-Hydro and HEC-HMS, we achieved more accurate forecasts. WRF–WRF-Hydro excels for short, intense storms, while WRF–HEC-HMS is better for longer, evenly distributed storms. Our research shows how these models provide insights for adaptive atmospheric–hydrologic systems and aims to boost flood preparedness and response with more reliable, timely predictions.
Tao Liu, Luke A. McGuire, Ann M. Youberg, Charles J. Abolt, and Adam L. Atchley
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-151, https://doi.org/10.5194/nhess-2024-151, 2024
Revised manuscript accepted for NHESS
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After a fire, soil infiltration decreases, increasing flash flood risks, worsened by intense rainfall from climate change. Using data from a burned watershed in Arizona and a hydrological model, we examined postfire soil changes under medium and high emissions scenarios. Results showed soil infiltration increased sixfold from the first to third postfire year. Both scenarios suggest that rainfall intensification will extend high flood risks after fires by late century.
Yu Gao, Haipeng Lu, Yaru Zhang, Hengxu Jin, Shuai Wu, Yixuan Gao, and Shuliang Zhang
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-144, https://doi.org/10.5194/nhess-2024-144, 2024
Revised manuscript accepted for NHESS
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This study focuses on the Yangtze River Delta Urban Agglomeration (YRDUA), where we determined flood risk assessment indices across different dimensions, including hazard, exposure, vulnerability, and resilience. We constructed a flood risk assessment model using AutoML and AHP to examine the spatial and temporal changes in flood risk in the region over the past 30 years (1990 to 2020), aiming to provide a scientific basis for flood prevention and resilience strategies in the YRDUA.
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
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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
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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
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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
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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
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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.
Tabea Wilke, Katharina Lengfeld, and Markus Schultze
EGUsphere, https://doi.org/10.5194/egusphere-2024-2507, https://doi.org/10.5194/egusphere-2024-2507, 2024
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Hail in Germany is a natural hazard that is not in everyone's focus, even though it can cause great damage. In this study we focus on hail frequency, sizes and spatial distribution in Germany based on crowd sourcing and weather radar data. We compare different algorithms based on weather radar data with crowd sourced data and show the annual and diurnal cycle of hail in Germany.
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
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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
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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
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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
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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
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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
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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.
Cited articles
Abbasi, A., Khalili K., Behmanesh, J., and Shirzad, A.: Estimation of ARIMA
model parameters for drought prediction using the genetic algorithm, Arab.
J. Geosci., 14, 841–841, https://doi.org/10.1007/s12517-021-07140-0, 2021.
Aghelpour, P. and Varshavian, V.: Forecasting Different Types of Droughts Simultaneously Using Multivariate Standardized Precipitation Index (MSPI), MLP Neural Network, and Imperialistic Competitive Algorithm (ICA),
Complexity, 2021, 6610228, https://doi.org/10.1155/2021/6610228, 2021.
Ahnadi, M.: Climatic drought forecasting using artificial neural network in
Hamedan region, New York Science Journal, 4, 15–19, https://doi.org/10.7537/marsnys040811.03, 2011.
Alquraish, M. A., Abuhasel, K. S., and Alqahtani, A. K.: SPI-Based Hybrid
Hidden Markov–GA, ARIMA–GA, and ARIMA–GA–ANN Models for Meteorological
Drought Forecasting, Sustainability, 13, 12576–12576,
https://doi.org/10.3390/su132212576, 2021.
Behzad, A. and Hamid, M.: Revisiting hydrological drought propagation and
recovery considering water quantity and quality, Hydrol. Process., 33, 1492–1505, https://doi.org/10.1002/hyp.13417, 2019.
Bishara, A. J. and Hittner, J. B.: Testing the significance of a
correlation with nonnormal data: comparison of Pearson, Spearman, transformation, and resampling approaches, Psychol. Methods, 17,
399–417, https://doi.org/10.1037/a0028087, 2012.
Bonaccorso, B., Cancelliere, A., and Rossi, G.: Probabilistic forecasting of
drought class transitions in Sicily (Italy) using Standardized Precipitation
Index and North Atlantic Oscillation Index, J. Hydrol., 526, 136–150, https://doi.org/10.1016/j.jhydrol.2015.01.070, 2015.
Cammalleri, C. and Vogt, J. V.: Non-stationarity in MODIS fAPAR
time-series and its impact on operational drought detection, Int. J. Remote Sens., 40, 1428–1444, https://doi.org/10.1080/01431161.2018.1524603, 2018.
Cancelliere, A., Di Mauro, G., and Bonaccorso, B.: Drought forecasting using the standardized precipitation index, Water Resour. Manage., 21, 801–819, https://doi.org/10.1007/s11269-006-9062-y, 2007.
Chang, G. B., Zhang, S. B., and Liu, Z. P.: Understanding the adjusment from
an information theoretic perspective, Geomatics and Information Science of
Wuhan University, 2022, 1–17,
https://kns.cnki.net/kcms/detail/42.1676.TN.20211125.1422.006.html (last access: 25 November 2021), 2022 (in Chinese).
Chen, J., Brissette, F. P., Chaumont, D., and Braun, M.: Performance and
uncertainty evaluation of empirical downscaling methods in quantifying the
climate change impacts on hydrology over two North American river basins,
J. Hydrol., 479, 200–214, https://doi.org/10.1016/j.jhydrol.2012.11.062, 2013.
Chen, X., Han, R. G., Feng, P., and Wang, Y. J.: Combined effects of
predicted climate and land use changes on future hydrological droughts in
the Luanhe River basin, China, Nat. Hazards, 2021, 1–33, https://doi.org/10.1007/s11069-021-04992-3, 2021.
Dehghani, M., Saghafian, B., and Zargar, M.: Probabilistic hydrological drought index forecasting based on meteorological drought index using Archimedean copulas, Hydrol. Res., 50, 1230–1250, https://doi.org/10.2166/nh.2019.051, 2019.
Ding, Y. B., Xu, J. T., Wang, X. W., Cai, H. J., Zhou, Z. Q., Sun, Y. N., and Shi, H. Y.: Propagation of meteorological to hydrological drought for different climate regions in China, J. Environ. Manag., 283, 111980,
https://doi.org/10.1016/j.jenvman.2021.111980, 2021.
Dixit, S. and Jayakumar, K. V.: A Non-stationary and Probabilistic Approach
for Drought Characterization Using Trivariate and Pairwise Copula
Construction (PCC) Model, Water Resour. Manag., 36, 1217–1236, https://doi.org/10.1007/s11269-022-03069-5, 2022.
Fendeková, M., Gauster, T., Labudová, L., Vrablíková, D., Danáčová, Z., Fendek, M., and Pekárová, P.: Analysing 21st century meteorological and hydrological drought events in Slovakia, J. Hydrol. Hydromech., 66, 393–403, https://doi.org/10.2478/johh-2018-0026, 2018.
Fuentes, I., Padarian, J., and Vervoort, R. W.: Spatial and Temporal Global
Patterns of Drought Propagation, Frontiers in Environmental Science, 10,
788248, https://doi.org/10.3389/fenvs.2022.788248, 2022.
Gong, H. N., Xie, B. T., and Wang J. R.: Long-term prediction of extreme
response of deepwater floating platform based on environmental contour
method, Ocean Eng., 39, 28–38,
https://doi.org/10.16483/j.issn.1005-9865.2021.05.003, 2021 (in Chinese).
Jehanzaib, M., Shah, S. A., Yoo, J., and Kim, T.-W.: Investigating the
impacts of climate change and human activities on hydrological drought using
non-stationary approaches, J. Hydrol., 588, 125052,
https://doi.org/10.1016/j.jhydrol.2020.125052, 2020.
Kolachian, R. and Saghafian, B.: Hydrological drought class early warning
using support vector machines and rough sets, Environ. Earth Sci., 80, 390–390, https://doi.org/10.1007/s12665-021-09536-3, 2021.
Koudahe, K., Koffi, D., Kayode, J. A., Awokola, S. O., and Adebola, A. A.:
Impact of Climate Variability on Crop Yields in Southern Togo, Environment
Pollution and Climate Change, 2, 1–9, https://doi.org/10.4172/2573-458X.1000148, 2018.
Li, J. Z., Wang, Y. X., Li, S. F., and Hu, R.: A Nonstationary Standardized
Precipitation Index incorporating climate indices as covariates, J. Geophys. Res.-Atmos., 120, 12082–12095, https://doi.org/10.1002/2015JD023920, 2015.
Li, L. C., Yao, N., Li, Y., Liu, D. L., Wang, B., and Ayantobo, O. O.: Future
projections of extreme temperature events in different sub-regions of China,
Atmos. Res., 217, 150–164, https://doi.org/10.1016/j.atmosres.2018.10.019, 2018.
Li, X., Fang, G. H., Wen, X., Xu, M., and Zhang, Y.: Characteristics
analysis of drought at multiple spatiotemporal scale and assessment of CMIP6
performance over the Huaihe River Basin, Journal of Hydrology: Regional
Studies, 41, 101–103, https://doi.org/10.1016/j.ejrh.2022.101103, 2022.
Li, X. X., Ma, X. X., Li, X. D., and Zhang, W. J.: Method Consideration of
Variation Diagnosis and Design Value Calculation of Flood Sequence in Yiluo
River Basin, China, Water, 12, 2722–2722, https://doi.org/10.3390/w12102722, 2020.
Malede, D. A., Agumassie, T. A., Kosgei, J. R., Linh, N. T. T., and Andualem,
T. G.: Analysis of rainfall and streamflow trend and variability over Birr
River watershed, Abbay basin, Ethiopia, Environmental Challenges, 7,
100528, https://doi.org/10.1016/j.envc.2022.100528, 2022.
Mallya, G., Tripathi, S., Kirshner, S., and Govindaraju, R. S.: Probabilistic
Assessment of Drought Characteristics Using Hidden Markov Model, J. Hydrol. Eng., 18, 834–845, https://doi.org/10.1061/(ASCE)HE.1943-5584.0000699, 2013.
McKee, T. B., Doesken, N. J., and Kleist, J.: The relationship of drought
frequency and duration to time scale, in: Proceedings of the Eighth
Conference on Applied Climatology, American Meteorological Society, 179–184, 1993.
Moghimi, M. M., Zarei, A. R., and Mahmoudi, M. R.: Seasonal drought
forecasting in arid regions, using different time series models and RDI
index, J. Water Clim. Change, 11, 633–654, https://doi.org/10.2166/wcc.2019.009, 2020.
Mokhtarzad, M., Eskandari, F., Jamshidi Vanjani, N., and Arabasadi, A.: Drought forecasting by ANN, ANFIS, and SVM and comparison of the models, Environ. Earth Sci., 76, 729–729, https://doi.org/10.1007/s12665-017-7064-0, 2017.
Natsagdorj, E., Renchin, T., Maeyer, P. D., and Darkhijav, B.: Spatial
Distribution of Soil Moisture in Mongolia Using SMAP and MODIS Satellite
Data: A Time Series Model (2010–2025), Remote Sensing., 13, 347–347,
https://doi.org/10.3390/RS13030347, 2021.
Oertel, M., Meza, F. J., Gironás, J., Scott, C. A., Rojas, F., and Pineda-Pablos, N.: Drought Propagation in Semi-Arid River Basins in Latin
America: Lessons from Mexico to the Southern Cone, Water, 10, 1564–1564, https://doi.org/10.3390/w10111564, 2018.
Onyutha, C.: On Rigorous Drought Assessment Using Daily Time Scale:
Non-Stationary Frequency Analyses, Revisited Concepts, and a New Method to
Yield Non-Parametric Indices, Hydrology, 4, 48–48,
https://doi.org/10.3390/hydrology4040048, 2017.
Ren, W., Wang, Y., Li, J., Feng, P., and Smith, R. J.: Drought forecasting in
Luanhe River basin involving climatic indices, Theor. Appl. Climatol., 130, 1133–1148, https://doi.org/10.1007/s00704-016-1952-1, 2017.
Rezaeianzadeh, M., Stein, A., and Cox, J. P.: Drought Forecasting using Markov Chain Model and Artificial Neural Networks, Water Resour. Manag., 30, 2245–2259, https://doi.org/10.1007/s11269-016-1283-0, 2016.
Shukla, S. and Wood, A. W.: Use of a standardized runoff index for
characterizing hydrologic drought, Geophys. Res. Lett., 35, L02405, https://doi.org/10.1029/2007GL032487, 2008.
Stojković, M., Plavšić, J., Prohaska, S., Pavlović, D., and
Despotović, J.: A two-stage time series model for monthly hydrological
projections under climate change in the Lim River basin (southeast Europe),
Hydrolog. Sci. J., 65, 387–400, https://doi.org/10.1080/02626667.2019.1699241, 2020.
Vicente-Serrano, S., Beguería, S., and López-Moreno, J.: A Multiscalar Drought Index Sensitive to Global Warming: The Standardized Precipitation Evapotranspiration Index, J. Climate, 23, 1696–1718, https://doi.org/10.1175/2009JCLI2909.1, 2010.
Wang, M., Jiang, S., Ren, L., Xu, C.-Y., Menzel, L., Yuan, F., Xu, Q., Liu,
Y., and Yang, X.: Separating the effects of climate change and human activities on drought propagation via a natural and human-impacted catchment comparison method, J. Hydrol., 603, 126913, https://doi.org/10.1016/j.jhydrol.2021.126913, 2021.
Wang, Y., Li, J., Feng, P., and Chen, F.: Effects of large-scale climate
patterns and human activities on hydrological drought: a case study in the
Luanhe River basin, China, Nat. Hazards, 76, 1687–1710,
https://doi.org/10.1007/s11069-014-1564-y, 2015.
Wang, Y., Li, J., Feng, P., and Hu, R.: Analysis of drought characteristics
over Luanhe River basin using the joint deficit index, J. Water Clim. Change, 7, 340–352, https://doi.org/10.2166/wcc.2015.108, 2016.
Wang, Y., Zhang, T., Chen, X., Li, J., and Feng, P.: Spatial and temporal
characteristics of droughts in Luanhe River basin, China, Theor. Appl. Climatol., 131, 1369–1385, https://doi.org/10.1007/s00704-017-2059-z, 2018.
Wang, Y., Duan, L., Liu, T., Li, J., and Feng, P.: A Non-stationary
Standardized Streamflow Index for hydrological drought using climate and
human-induced indices as covariates, Sci. Total Environ., 699, 134278, https://doi.org/10.1016/j.scitotenv.2019.134278, 2020.
Wang, Y., Peng, T., Lin, Q., Singh, V., Dong, X., Chen, C., Liu, J., Chang,
W., and Wang, G.: A New Non-stationary Hydrological Drought Index
Encompassing Climate Indices and Modified Reservoir Index as Covariates,
Water Resour. Manag., 36, 2433–2454, https://doi.org/10.1007/S11269-022-03151-Y, 2022.
Xu, Y., Zhang, X., Wang, Xiao., Hao, Z., Singh, V., and Hao, F.: Propagation
from meteorological drought to hydrological drought under the impact of
human activities: A case study in northern China, J. Hydrol., 579, 124147, https://doi.org/10.1016/j.jhydrol.2019.124147, 2019.
Yan, X., Bao, Z., Zhang, J., Wang, G., He, R., and Liu, C.: Quantifying
contributions of climate change and local human activities to runoff decline
in the upper reaches of the Luanhe River basin, J. Hydro-Environ. Res., 28, 67–74, https://doi.org/10.1016/j.jher.2018.11.002, 2018.
Zhang, T., Li, J., Hu, R., Wang, Y., and Feng, P.: Drought class transition analysis through different models: a case study in North China, Water Supply, 17, 138–150, https://doi.org/10.2166/ws.2016.123, 2017.
Zhao, G., Gao, H. L., Kao, S. C., Nathalie, V., and Bibi, S. N.: A modeling
framework for evaluating the drought resilience of a surface water supply
system under non-stationarity, J. Hydrol., 563, 22–32,
https://doi.org/10.1016/j.jhydrol.2018.05.037, 2018.
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.
It is an important disaster reduction strategy to forecast hydrological drought. In order to...
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