Articles | Volume 22, issue 4
https://doi.org/10.5194/hess-22-2225-2018
© Author(s) 2018. 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/hess-22-2225-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
11 Apr 2018
Research article |
| 11 Apr 2018
| 11 Apr 2018
Statistical forecast of seasonal discharge in Central Asia using observational records: development of a generic linear modelling tool for operational water resource management
GFZ German Research Centre for Geoscience, Section 5.4 Hydrology, Potsdam, Germany
Zharkinay Abdykerimova
Hydro-Meteorological Service of Kyrgyzstan, Bishkek, Kyrgyzstan
Marina Agalhanova
Hydro-Meteorological Service of Turkmenistan, Ashgabat, Turkmenistan
Azamat Baimaganbetov
Hydro-Meteorological Service of Kazakhstan, Almaty, Kazakhstan
Nadejda Gavrilenko
Hydro-Meteorological Service of Uzbekistan, Tashkent, Uzbekistan
Lars Gerlitz
GFZ German Research Centre for Geoscience, Section 5.4 Hydrology, Potsdam, Germany
Olga Kalashnikova
CAIAG Central Asian Institute for Applied Geoscience, Bishkek, Kyrgyzstan
Katy Unger-Shayesteh
GFZ German Research Centre for Geoscience, Section 5.4 Hydrology, Potsdam, Germany
Sergiy Vorogushyn
GFZ German Research Centre for Geoscience, Section 5.4 Hydrology, Potsdam, Germany
Abror Gafurov
GFZ German Research Centre for Geoscience, Section 5.4 Hydrology, Potsdam, Germany
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Shahin Khosh Bin Ghomash, Nithila Devi Nallasamy, and Heiko Apel
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This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
Short summary
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This study explores how the way buildings are represented in flood models influences predictions of flood extent, water depth, flow speed, and overall impact. Using a major flood event in Germany as a case study, we evaluate different representation methods across various model resolutions. The results support more accurate flood modeling and impact assessments, helping cities better prepare for and respond to future floods.
Shahin Khosh Bin Ghomash, Heiko Apel, Kai Schröter, and Max Steinhausen
Nat. Hazards Earth Syst. Sci., 25, 1737–1749, https://doi.org/10.5194/nhess-25-1737-2025, https://doi.org/10.5194/nhess-25-1737-2025, 2025
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This work introduces RIM2D (Rapid Inundation Model 2D), a hydrodynamic model for precise and rapid flood predictions that is ideal for early warning systems. We demonstrate RIM2D's ability to deliver detailed and localized flood forecasts using the June 2023 flood in Braunschweig, Germany, as a case study. This research highlights the readiness of RIM2D and the required hardware for integration into operational flood warning and impact-based forecasting systems.
André Felipe Rocha Silva, Julian Cardoso Eleutério, Heiko Apel, and Heidi Kreibich
Nat. Hazards Earth Syst. Sci., 25, 1501–1520, https://doi.org/10.5194/nhess-25-1501-2025, https://doi.org/10.5194/nhess-25-1501-2025, 2025
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This work uses agent-based modelling to evaluate the impact of flood warning and evacuation systems on human losses during the 2021 Ahr Valley flood in Germany. While the first flood warning with evacuation instructions is identified as timely, its lack of detail and effectiveness resulted in low public risk awareness. Better dissemination of warnings and improved risk perception and preparedness among the population could reduce casualties by up to 80 %.
Tim Busker, Daniela Rodriguez Castro, Sergiy Vorogushyn, Jaap Kwadijk, Davide Zoccatelli, Rafaella Loureiro, Heather J. Murdock, Laurent Pfister, Benjamin Dewals, Kymo Slager, Annegret H. Thieken, Jan Verkade, Patrick Willems, and Jeroen C. J. H. Aerts
EGUsphere, https://doi.org/10.5194/egusphere-2025-828, https://doi.org/10.5194/egusphere-2025-828, 2025
This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
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Elena Macdonald, Bruno Merz, Viet Dung Nguyen, and Sergiy Vorogushyn
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Shahin Khosh Bin Ghomash, Nithila Devi Nallasamy, and Heiko Apel
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-314, https://doi.org/10.5194/hess-2024-314, 2024
Manuscript not accepted for further review
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Zarina Saidaliyeva, Maria Shahgedanova, Vadim Yapiyev, Andrew John Wade, Fakhriddin Akbarov, Mukhammed Esenaman uulu, Olga Kalashnikova, Vassiliy Kapitsa, Nikolay Kasatkin, Ilkhomiddin Rakhimov, Rysbek Satylkanov, Daniiar Sayakbaev, Eleonora Semakova, Igor Severskiy, Maxim Petrov, Gulomjon Umirzakov, and Ryskul Usubaliev
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Ratios of stable isotopes of oxygen and hydrogen in precipitation are used to trace source regions and pathways of atmospheric moisture. A database of these measurements was developed for the mountains of Central Asia and analysed in the context of atmospheric trajectories. Over 50 % of precipitation was formed from moisture re-evaporated from regional terrestrial sources including the irrigated land in the Aral Sea basin, highlighting its support of the water tower function of the mountains.
Shahin Khosh Bin Ghomash, Heiko Apel, and Daniel Caviedes-Voullième
Nat. Hazards Earth Syst. Sci., 24, 2857–2874, https://doi.org/10.5194/nhess-24-2857-2024, https://doi.org/10.5194/nhess-24-2857-2024, 2024
Short summary
Short summary
Early warning is essential to minimise the impact of flash floods. We explore the use of highly detailed flood models to simulate the 2021 flood event in the lower Ahr valley (Germany). Using very high-resolution models resolving individual streets and buildings, we produce detailed, quantitative, and actionable information for early flood warning systems. Using state-of-the-art computational technology, these models can guarantee very fast forecasts which allow for sufficient time to respond.
Xiaoxiang Guan, Dung Viet Nguyen, Paul Voit, Bruno Merz, Maik Heistermann, and Sergiy Vorogushyn
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-143, https://doi.org/10.5194/nhess-2024-143, 2024
Revised manuscript accepted for NHESS
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We evaluated a multi-site stochastic regional weather generator (nsRWG) for its ability to capture the cross-scale extremity of high precipitation events (HPEs) in Germany. We generated 100 realizations of 72 years of daily synthetic precipitation data. The performance was assessed using WEI and xWEI indices, which measure event extremity across spatio-temporal scales. Results show nsRWG simulates well the extremity patterns of HPEs, though it overestimates short-duration, small-extent events.
Kai Schröter, Pia-Johanna Schweizer, Benedikt Gräler, Lydia Cumiskey, Sukaina Bharwani, Janne Parviainen, Chahan Kropf, Viktor Wattin Hakansson, Martin Drews, Tracy Irvine, Clarissa Dondi, Heiko Apel, Jana Löhrlein, Stefan Hochrainer-Stigler, Stefano Bagli, Levente Huszti, Christopher Genillard, Silvia Unguendoli, and Max Steinhausen
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-135, https://doi.org/10.5194/nhess-2024-135, 2024
Revised manuscript accepted for NHESS
Short summary
Short summary
With the increasing negative impacts of extreme weather events globally, it's crucial to align efforts to manage disasters with measures to adapt to climate change. We identify challenges in systems and organizations working together. We suggest that collaboration across various fields is essential and propose an approach to improve collaboration, including a framework for better stakeholder engagement and an open-source data system that helps gather and connect important information.
Atabek Umirbekov, Mayra Daniela Peña-Guerrero, Iulii Didovets, Heiko Apel, Abror Gafurov, and Daniel Müller
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-174, https://doi.org/10.5194/hess-2024-174, 2024
Revised manuscript accepted for HESS
Short summary
Short summary
In snowmelt-dominated catchments, predicting river streamflow typically relies on accumulated snowpack. Our study shows that including large-scale climate patterns like El Niño can improve these predictions. We analyzed climate oscillations, seasonal rainfall, and streamflow, then used these insights and snowpack data in a machine learning model to forecast river streamflow. This method yielded more accurate predictions, useful for long-term forecasting or when snowpack estimates are uncertain.
Elena Macdonald, Bruno Merz, Björn Guse, Viet Dung Nguyen, Xiaoxiang Guan, and Sergiy Vorogushyn
Hydrol. Earth Syst. Sci., 28, 833–850, https://doi.org/10.5194/hess-28-833-2024, https://doi.org/10.5194/hess-28-833-2024, 2024
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In some rivers, the occurrence of extreme flood events is more likely than in other rivers – they have heavy-tailed distributions. We find that threshold processes in the runoff generation lead to such a relatively high occurrence probability of extremes. Further, we find that beyond a certain return period, i.e. for rare events, rainfall is often the dominant control compared to runoff generation. Our results can help to improve the estimation of the occurrence probability of extreme floods.
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Hydrol. Earth Syst. Sci., 28, 575–588, https://doi.org/10.5194/hess-28-575-2024, https://doi.org/10.5194/hess-28-575-2024, 2024
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Short summary
A new algorithm has been developed to quickly produce high-resolution flood maps. It is faster and more accurate than current methods and is available as open-source scripts. This can help communities better prepare for and mitigate flood damages without expensive modelling.
Heidi Kreibich, Kai Schröter, Giuliano Di Baldassarre, Anne F. Van Loon, Maurizio Mazzoleni, Guta Wakbulcho Abeshu, Svetlana Agafonova, Amir AghaKouchak, Hafzullah Aksoy, Camila Alvarez-Garreton, Blanca Aznar, Laila Balkhi, Marlies H. Barendrecht, Sylvain Biancamaria, Liduin Bos-Burgering, Chris Bradley, Yus Budiyono, Wouter Buytaert, Lucinda Capewell, Hayley Carlson, Yonca Cavus, Anaïs Couasnon, Gemma Coxon, Ioannis Daliakopoulos, Marleen C. de Ruiter, Claire Delus, Mathilde Erfurt, Giuseppe Esposito, Didier François, Frédéric Frappart, Jim Freer, Natalia Frolova, Animesh K. Gain, Manolis Grillakis, Jordi Oriol Grima, Diego A. Guzmán, Laurie S. Huning, Monica Ionita, Maxim Kharlamov, Dao Nguyen Khoi, Natalie Kieboom, Maria Kireeva, Aristeidis Koutroulis, Waldo Lavado-Casimiro, Hong-Yi Li, Maria Carmen LLasat, David Macdonald, Johanna Mård, Hannah Mathew-Richards, Andrew McKenzie, Alfonso Mejia, Eduardo Mario Mendiondo, Marjolein Mens, Shifteh Mobini, Guilherme Samprogna Mohor, Viorica Nagavciuc, Thanh Ngo-Duc, Huynh Thi Thao Nguyen, Pham Thi Thao Nhi, Olga Petrucci, Nguyen Hong Quan, Pere Quintana-Seguí, Saman Razavi, Elena Ridolfi, Jannik Riegel, Md Shibly Sadik, Nivedita Sairam, Elisa Savelli, Alexey Sazonov, Sanjib Sharma, Johanna Sörensen, Felipe Augusto Arguello Souza, Kerstin Stahl, Max Steinhausen, Michael Stoelzle, Wiwiana Szalińska, Qiuhong Tang, Fuqiang Tian, Tamara Tokarczyk, Carolina Tovar, Thi Van Thu Tran, Marjolein H. J. van Huijgevoort, Michelle T. H. van Vliet, Sergiy Vorogushyn, Thorsten Wagener, Yueling Wang, Doris E. Wendt, Elliot Wickham, Long Yang, Mauricio Zambrano-Bigiarini, and Philip J. Ward
Earth Syst. Sci. Data, 15, 2009–2023, https://doi.org/10.5194/essd-15-2009-2023, https://doi.org/10.5194/essd-15-2009-2023, 2023
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As the adverse impacts of hydrological extremes increase in many regions of the world, a better understanding of the drivers of changes in risk and impacts is essential for effective flood and drought risk management. We present a dataset containing data of paired events, i.e. two floods or two droughts that occurred in the same area. The dataset enables comparative analyses and allows detailed context-specific assessments. Additionally, it supports the testing of socio-hydrological models.
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
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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.
Cornelia Zech, Tilo Schöne, Julia Illigner, Nico Stolarczuk, Torsten Queißer, Matthias Köppl, Heiko Thoss, Alexander Zubovich, Azamat Sharshebaev, Kakhramon Zakhidov, Khurshid Toshpulatov, Yusufjon Tillayev, Sukhrob Olimov, Zabihullah Paiman, Katy Unger-Shayesteh, Abror Gafurov, and Bolot Moldobekov
Earth Syst. Sci. Data, 13, 1289–1306, https://doi.org/10.5194/essd-13-1289-2021, https://doi.org/10.5194/essd-13-1289-2021, 2021
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The regional research network Water in Central Asia (CAWa) funded by the German Federal Foreign Office consists of 18 remotely operated multi-parameter stations (ROMPSs) in Central Asia, and they are operated by German and Central Asian institutes and national hydrometeorological services. They provide up to 10 years of raw meteorological and hydrological data, especially in remote areas with extreme climate conditions, for applications in climate and water monitoring in Central Asia.
Miriam Bertola, Alberto Viglione, Sergiy Vorogushyn, David Lun, Bruno Merz, and Günter Blöschl
Hydrol. Earth Syst. Sci., 25, 1347–1364, https://doi.org/10.5194/hess-25-1347-2021, https://doi.org/10.5194/hess-25-1347-2021, 2021
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We estimate the contribution of extreme precipitation, antecedent soil moisture and snowmelt to changes in small and large floods across Europe.
In northwestern and eastern Europe, changes in small and large floods are driven mainly by one single driver (i.e. extreme precipitation and snowmelt, respectively). In southern Europe both antecedent soil moisture and extreme precipitation significantly contribute to flood changes, and their relative importance depends on flood magnitude.
Zhihua He, Katy Unger-Shayesteh, Sergiy Vorogushyn, Stephan M. Weise, Doris Duethmann, Olga Kalashnikova, Abror Gafurov, and Bruno Merz
Hydrol. Earth Syst. Sci., 24, 3289–3309, https://doi.org/10.5194/hess-24-3289-2020, https://doi.org/10.5194/hess-24-3289-2020, 2020
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Quantifying the seasonal contributions of the runoff components, including groundwater, snowmelt, glacier melt, and rainfall, to streamflow is highly necessary for understanding the dynamics of water resources in glacierized basins given the vulnerability of snow- and glacier-dominated environments to the current climate warming. Our study provides the first comparison of two end-member mixing approaches for hydrograph separation in glacierized basins.
Benjamin Winter, Klaus Schneeberger, Kristian Förster, and Sergiy Vorogushyn
Nat. Hazards Earth Syst. Sci., 20, 1689–1703, https://doi.org/10.5194/nhess-20-1689-2020, https://doi.org/10.5194/nhess-20-1689-2020, 2020
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In this paper two different methods to generate spatially coherent flood events for probabilistic flood risk modelling are compared: on the one hand, a semi-conditional multi-variate dependence model applied to discharge observations and, on the other hand, a continuous hydrological modelling of synthetic meteorological fields generated by a multi-site weather generator. The results of the two approaches are compared in terms of simulated spatial patterns and overall flood risk estimates.
Heiko Apel, Mai Khiem, Nguyen Hong Quan, and To Quang Toan
Nat. Hazards Earth Syst. Sci., 20, 1609–1616, https://doi.org/10.5194/nhess-20-1609-2020, https://doi.org/10.5194/nhess-20-1609-2020, 2020
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This study deals with salinity intrusion in the Mekong Delta, a pressing issue in the third-largest river delta on Earth. It presents a simple, efficient, and cross-validated seasonal forecast model for salinity intrusion during the dry season based on logistic regression using ENSO34 or standardized streamflow indexes as predictors. The model performs exceptionally well, enabling a reliable forecast of critical salinity threshold exceedance up to 9 months prior to the dry season.
Ayse Duha Metin, Nguyen Viet Dung, Kai Schröter, Sergiy Vorogushyn, Björn Guse, Heidi Kreibich, and Bruno Merz
Nat. Hazards Earth Syst. Sci., 20, 967–979, https://doi.org/10.5194/nhess-20-967-2020, https://doi.org/10.5194/nhess-20-967-2020, 2020
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For effective risk management, flood risk should be properly assessed. Traditionally, risk is assessed by making the assumption of invariant flow or loss probabilities (the chance that a given discharge or loss is exceeded) within the river catchment during a single flood event. However, in reality, flooding is more severe in some regions than others. This study indicates the importance of representing the spatial dependence of flood peaks and damage for risk assessments.
Björn Guse, Bruno Merz, Luzie Wietzke, Sophie Ullrich, Alberto Viglione, and Sergiy Vorogushyn
Hydrol. Earth Syst. Sci., 24, 1633–1648, https://doi.org/10.5194/hess-24-1633-2020, https://doi.org/10.5194/hess-24-1633-2020, 2020
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Floods are influenced by river network processes, among others. Flood characteristics of tributaries may affect flood severity downstream of confluences. The impact of flood wave superposition is investigated with regard to magnitude and temporal matching of flood peaks. Our study in Germany and Austria shows that flood wave superposition is not the major driver of flood severity. However, there is the potential for large floods at some confluences in cases of temporal matching of flood peaks.
Dirk Diederen, Ye Liu, Ben Gouldby, Ferdinand Diermanse, and Sergiy Vorogushyn
Nat. Hazards Earth Syst. Sci., 19, 1041–1053, https://doi.org/10.5194/nhess-19-1041-2019, https://doi.org/10.5194/nhess-19-1041-2019, 2019
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Floods affect many communities and cause a large amount of damage worldwide.
Since we choose to live in natural flood plains and are unable to prevent all floods, a system of insurance and reinsurance was set up.
For these institutes to not fail, estimates are required of the frequency of large-scale flood events.
We explore a new method to obtain a large catalogue of synthetic, spatially coherent, large-scale river discharge events, using a recent (gridded) European discharge data set.
Eva Steirou, Lars Gerlitz, Heiko Apel, Xun Sun, and Bruno Merz
Hydrol. Earth Syst. Sci., 23, 1305–1322, https://doi.org/10.5194/hess-23-1305-2019, https://doi.org/10.5194/hess-23-1305-2019, 2019
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We investigate whether flood probabilities in Europe vary for different large-scale atmospheric circulation conditions. Maximum seasonal river flows from 600 gauges in Europe and five synchronous atmospheric circulation indices are analyzed. We find that a high percentage of stations is influenced by at least one of the climate indices, especially during winter. These results can be useful for preparedness and damage planning by (re-)insurance companies.
Ayse Duha Metin, Nguyen Viet Dung, Kai Schröter, Björn Guse, Heiko Apel, Heidi Kreibich, Sergiy Vorogushyn, and Bruno Merz
Nat. Hazards Earth Syst. Sci., 18, 3089–3108, https://doi.org/10.5194/nhess-18-3089-2018, https://doi.org/10.5194/nhess-18-3089-2018, 2018
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We present a comprehensive sensitivity analysis considering changes along the complete flood risk chain to understand how changes in different drivers affect flood risk. Results show that changes in dike systems or in vulnerability may outweigh changes in often investigated components, such as climate change. Although the specific results are conditional on the case study and assumptions, they highlight the need for a broader consideration of potential drivers of change in a comprehensive way.
Nguyen Van Khanh Triet, Nguyen Viet Dung, Bruno Merz, and Heiko Apel
Nat. Hazards Earth Syst. Sci., 18, 2859–2876, https://doi.org/10.5194/nhess-18-2859-2018, https://doi.org/10.5194/nhess-18-2859-2018, 2018
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In this study we provide an estimation of flood damages and risks to rice cultivation in the Mekong Delta. The derived modelling concept explicitly takes plant phenomenology and timing of floods in a probabilistic modelling framework into account. This results in spatially explicit flood risk maps to rice cultivation, quantified as expected annual damage. Furthermore, the changes in flood risk of two land-use scenarios were estimated and discussed.
Giuliano Di Baldassarre, Heidi Kreibich, Sergiy Vorogushyn, Jeroen Aerts, Karsten Arnbjerg-Nielsen, Marlies Barendrecht, Paul Bates, Marco Borga, Wouter Botzen, Philip Bubeck, Bruna De Marchi, Carmen Llasat, Maurizio Mazzoleni, Daniela Molinari, Elena Mondino, Johanna Mård, Olga Petrucci, Anna Scolobig, Alberto Viglione, and Philip J. Ward
Hydrol. Earth Syst. Sci., 22, 5629–5637, https://doi.org/10.5194/hess-22-5629-2018, https://doi.org/10.5194/hess-22-5629-2018, 2018
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One common approach to cope with floods is the implementation of structural flood protection measures, such as levees. Numerous scholars have problematized this approach and shown that increasing levels of flood protection can generate a false sense of security and attract more people to the risky areas. We briefly review the literature on this topic and then propose a research agenda to explore the unintended consequences of structural flood protection.
Sergey Tyagunov, Sergiy Vorogushyn, Cristina Muñoz Jimenez, Stefano Parolai, and Kevin Fleming
Nat. Hazards Earth Syst. Sci., 18, 2345–2354, https://doi.org/10.5194/nhess-18-2345-2018, https://doi.org/10.5194/nhess-18-2345-2018, 2018
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A methodological framework for the multi-hazard (earthquake and flood) failure analysis of fluvial dikes due to liquefaction is presented. Failure probability of the earthen structures is presented in the form of a fragility surface as a function of both seismic and hydraulic load. It is emphasized that the potential interactions between the two hazards should not be ignored in risk analyses and decision-making.
Marlies Holkje Barendrecht, Alberto Viglione, Heidi Kreibich, Sergiy Vorogushyn, Bruno Merz, and Günter Blöschl
Proc. IAHS, 379, 193–198, https://doi.org/10.5194/piahs-379-193-2018, https://doi.org/10.5194/piahs-379-193-2018, 2018
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The aim of this paper is to assess whether a Socio-Hydrological model can be calibrated to data artificially generated from it. This is not trivial because the model is highly nonlinear and it is not clear what amount of data would be needed for calibration. We demonstrate that, using Bayesian inference, the parameters of the model can be estimated quite accurately from relatively few data, which could be available in real case studies.
Nguyen Le Duy, Ingo Heidbüchel, Hanno Meyer, Bruno Merz, and Heiko Apel
Hydrol. Earth Syst. Sci., 22, 1239–1262, https://doi.org/10.5194/hess-22-1239-2018, https://doi.org/10.5194/hess-22-1239-2018, 2018
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This study analyzes the influence of local and regional meteorological factors on the isotopic composition of precipitation. The impact of the different factors on the isotopic condition was quantified by multiple linear regression of all factor combinations combined with relative importance analysis. The proposed approach might open a pathway for the improved reconstruction of paleoclimates based on isotopic records.
Björn Guse, Matthias Pfannerstill, Abror Gafurov, Jens Kiesel, Christian Lehr, and Nicola Fohrer
Hydrol. Earth Syst. Sci., 21, 5663–5679, https://doi.org/10.5194/hess-21-5663-2017, https://doi.org/10.5194/hess-21-5663-2017, 2017
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Performance measures are used to evaluate the representation of hydrological processes in parameters of hydrological models. In this study, we investigated how strongly model parameters and performance measures are connected. It was found that relationships are different for varying flow conditions, indicating that precise parameter identification requires multiple performance measures. The suggested approach contributes to a better handling of parameters in hydrological modelling.
Martin Hoelzle, Erlan Azisov, Martina Barandun, Matthias Huss, Daniel Farinotti, Abror Gafurov, Wilfried Hagg, Ruslan Kenzhebaev, Marlene Kronenberg, Horst Machguth, Alexandr Merkushkin, Bolot Moldobekov, Maxim Petrov, Tomas Saks, Nadine Salzmann, Tilo Schöne, Yuri Tarasov, Ryskul Usubaliev, Sergiy Vorogushyn, Andrey Yakovlev, and Michael Zemp
Geosci. Instrum. Method. Data Syst., 6, 397–418, https://doi.org/10.5194/gi-6-397-2017, https://doi.org/10.5194/gi-6-397-2017, 2017
Nguyen Van Khanh Triet, Nguyen Viet Dung, Hideto Fujii, Matti Kummu, Bruno Merz, and Heiko Apel
Hydrol. Earth Syst. Sci., 21, 3991–4010, https://doi.org/10.5194/hess-21-3991-2017, https://doi.org/10.5194/hess-21-3991-2017, 2017
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In this study we provide a numerical quantification of changes in flood hazard in the Vietnamese Mekong Delta as a result of dyke development. Other important drivers to the alteration of delta flood hazard are also investigated, e.g. tidal level. The findings of our study are substantial valuable for the decision makers in Vietnam to develop holistic and harmonized floods and flood-related issues management plan for the whole delta.
Ramchandra Karki, Shabeh ul Hasson, Lars Gerlitz, Udo Schickhoff, Thomas Scholten, and Jürgen Böhner
Earth Syst. Dynam., 8, 507–528, https://doi.org/10.5194/esd-8-507-2017, https://doi.org/10.5194/esd-8-507-2017, 2017
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Dynamical downscaling of climate fields at very high resolutions (convection- and topography-resolving scales) over the complex Himalayan terrain of the Nepalese Himalayas shows promising results. It clearly demonstrates the potential of mesoscale models to accurately simulate present and future climate information at very high resolutions over remote, data-scarce mountainous regions for the development of adaptation strategies and impact assessments in the context of changing climate.
Mathias Seibert, Bruno Merz, and Heiko Apel
Hydrol. Earth Syst. Sci., 21, 1611–1629, https://doi.org/10.5194/hess-21-1611-2017, https://doi.org/10.5194/hess-21-1611-2017, 2017
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Seasonal early warning is vital for drought management in arid regions like the Limpopo Basin in southern Africa. This study shows that skilled seasonal forecasts can be achieved with statistical methods built upon driving factors for drought occurrence. These are the hydrological factors for current streamflow and meteorological drivers represented by anomalies in sea surface temperatures of the surrounding oceans, which combine to form unique combinations in the drought forecast models.
Lars Gerlitz, Sergiy Vorogushyn, Heiko Apel, Abror Gafurov, Katy Unger-Shayesteh, and Bruno Merz
Hydrol. Earth Syst. Sci., 20, 4605–4623, https://doi.org/10.5194/hess-20-4605-2016, https://doi.org/10.5194/hess-20-4605-2016, 2016
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Most statistically based seasonal precipitation forecast models utilize a small set of well-known climate indices as potential predictor variables. However, for many target regions, these indices do not lead to sufficient results and customized predictors are required for an accurate prediction.
This study presents a statistically based routine, which automatically identifies suitable predictors from globally gridded SST and climate variables by means of an extensive data mining procedure.
Aline Murawski, Gerd Bürger, Sergiy Vorogushyn, and Bruno Merz
Hydrol. Earth Syst. Sci., 20, 4283–4306, https://doi.org/10.5194/hess-20-4283-2016, https://doi.org/10.5194/hess-20-4283-2016, 2016
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To understand past flood changes in the Rhine catchment and the role of anthropogenic climate change in extreme flows, an attribution study relying on a proper GCM (general circulation model) downscaling is needed. A downscaling based on conditioning a stochastic weather generator on weather patterns is a promising approach. Here the link between patterns and local climate is tested, and the skill of GCMs in reproducing these patterns is evaluated.
O. Conrad, B. Bechtel, M. Bock, H. Dietrich, E. Fischer, L. Gerlitz, J. Wehberg, V. Wichmann, and J. Böhner
Geosci. Model Dev., 8, 1991–2007, https://doi.org/10.5194/gmd-8-1991-2015, https://doi.org/10.5194/gmd-8-1991-2015, 2015
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The System for Automated Geoscientific Analyses (SAGA) is a comprehensive and globally established open source geographic information system (GIS) for scientific analysis and modeling. The current version 2.1.4 offers more than 700 tools that represent the broad scopes of SAGA in numerous fields of geoscientific endeavor. In this paper, we inform about the system’s architecture and functionality and highlight the wide spectrum of scientific applications of SAGA in a review of published studies.
U. Schickhoff, M. Bobrowski, J. Böhner, B. Bürzle, R. P. Chaudhary, L. Gerlitz, H. Heyken, J. Lange, M. Müller, T. Scholten, N. Schwab, and R. Wedegärtner
Earth Syst. Dynam., 6, 245–265, https://doi.org/10.5194/esd-6-245-2015, https://doi.org/10.5194/esd-6-245-2015, 2015
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Near-natural Himalayan treelines are usually krummholz treelines, which are relatively unresponsive to climate change. Intense recruitment of treeline trees suggests a great potential for future treeline advance. Competitive abilities of tree seedlings within krummholz thickets and dwarf scrub heaths will be a major source of variation in treeline dynamics. Tree growth-climate relationships show mature treeline trees to be responsive in particular to high pre-monsoon temperature trends.
A. Gafurov, S. Vorogushyn, D. Farinotti, D. Duethmann, A. Merkushkin, and B. Merz
The Cryosphere, 9, 451–463, https://doi.org/10.5194/tc-9-451-2015, https://doi.org/10.5194/tc-9-451-2015, 2015
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Spatially distributed snow-cover data are available only for the recent past from remote sensing. Sometimes we need snow-cover data over a longer period for climate impact analysis for the calibration/validation of hydrological models. In this study we present a methodology to reconstruct snow cover in the past using available long-term in situ data and recently available remote sensing snow-cover data. The results show about 85% accuracy although only a limited number of stations (7) were used.
L. Gerlitz, O. Conrad, and J. Böhner
Earth Syst. Dynam., 6, 61–81, https://doi.org/10.5194/esd-6-61-2015, https://doi.org/10.5194/esd-6-61-2015, 2015
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In order to assess high-resolution precipitation fields for the Tibetan Plateau and the Himalayan Arc, a novel downscaling approach is presented which integrates traditional statistical downscaling and GIS-based terrain parameterization techniques. The approach enables a detailed analysis of the precipitation heterogeinity over the complex target area.
N. V. Manh, N. V. Dung, N. N. Hung, B. Merz, and H. Apel
Hydrol. Earth Syst. Sci., 18, 3033–3053, https://doi.org/10.5194/hess-18-3033-2014, https://doi.org/10.5194/hess-18-3033-2014, 2014
J. M. Delgado, B. Merz, and H. Apel
Nat. Hazards Earth Syst. Sci., 14, 1579–1589, https://doi.org/10.5194/nhess-14-1579-2014, https://doi.org/10.5194/nhess-14-1579-2014, 2014
S. Vorogushyn and B. Merz
Hydrol. Earth Syst. Sci., 17, 3871–3884, https://doi.org/10.5194/hess-17-3871-2013, https://doi.org/10.5194/hess-17-3871-2013, 2013
A. Domeneghetti, S. Vorogushyn, A. Castellarin, B. Merz, and A. Brath
Hydrol. Earth Syst. Sci., 17, 3127–3140, https://doi.org/10.5194/hess-17-3127-2013, https://doi.org/10.5194/hess-17-3127-2013, 2013
N. V. Manh, B. Merz, and H. Apel
Hydrol. Earth Syst. Sci., 17, 3039–3057, https://doi.org/10.5194/hess-17-3039-2013, https://doi.org/10.5194/hess-17-3039-2013, 2013
D. Duethmann, J. Zimmer, A. Gafurov, A. Güntner, D. Kriegel, B. Merz, and S. Vorogushyn
Hydrol. Earth Syst. Sci., 17, 2415–2434, https://doi.org/10.5194/hess-17-2415-2013, https://doi.org/10.5194/hess-17-2415-2013, 2013
N. V. Dung, B. Merz, A. Bárdossy, and H. Apel
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhessd-1-275-2013, https://doi.org/10.5194/nhessd-1-275-2013, 2013
Revised manuscript not accepted
B. Jongman, H. Kreibich, H. Apel, J. I. Barredo, P. D. Bates, L. Feyen, A. Gericke, J. Neal, J. C. J. H. Aerts, and P. J. Ward
Nat. Hazards Earth Syst. Sci., 12, 3733–3752, https://doi.org/10.5194/nhess-12-3733-2012, https://doi.org/10.5194/nhess-12-3733-2012, 2012
Related subject area
Subject: Hydrometeorology | Techniques and Approaches: Modelling approaches
Implementation of global soil databases in the Noah-MP model and the effects on simulated mean and extreme soil hydrothermal changes
Skilful probabilistic predictions of UK flood risk months ahead using a large-sample machine learning model trained on multimodel ensemble climate forecasts
Towards a robust hydrologic data assimilation system for hurricane-induced river flow forecasting
Enhanced evaluation of hourly and daily extreme precipitation in Norway from convection-permitting models at regional and local scales
Deep-learning-based sub-seasonal precipitation and streamflow ensemble forecasting over the source region of the Yangtze River
High-resolution land surface modelling over Africa: the role of uncertain soil properties in combination with forcing temporal resolution
Investigating the global and regional response of drought to idealized deforestation using multiple global climate models
Distribution, trends, and drivers of flash droughts in the United Kingdom
Are dependencies of extreme rainfall on humidity more reliable in convection-permitting climate models?
Leveraging a radar-based disdrometer network to develop a probabilistic precipitation phase model in eastern Canada
Assessment of seasonal soil moisture forecasts over the Central Mediterranean
Do land models miss key soil hydrological processes controlling soil moisture memory?
Observation-driven model for calculating water-harvesting potential from advective fog in (semi-)arid coastal regions
Review of gridded climate products and their use in hydrological analyses reveals overlaps, gaps, and the need for a more objective approach to selecting model forcing datasets
Barriers of urban hydro-meteorological simulation: a review
Downscaling the probability of heavy rainfall over the Nordic countries
Modelling convective cell life cycles with a copula-based approach
Downscaling precipitation over High-mountain Asia using multi-fidelity Gaussian processes: improved estimates from ERA5
Mapping soil moisture across the UK: assimilating cosmic-ray neutron sensors, remotely sensed indices, rainfall radar and catchment water balance data in a Bayesian hierarchical model
Assessing rainfall radar errors with an inverse stochastic modelling framework
Enhanced hydrological modelling with the WRF-Hydro lake/reservoir module at Convection-Permitting scale: a case study of the Tana River basin in East Africa
Multi-objective calibration and evaluation of the ORCHIDEE land surface model over France at high resolution
Probabilistic precipitation downscaling for ungauged mountain sites: a pilot study for the Hindu Kush Karakoram Himalaya
Spatiotemporal responses of runoff to climate change in the southern Tibetan Plateau
FROSTBYTE: a reproducible data-driven workflow for probabilistic seasonal streamflow forecasting in snow-fed river basins across North America
Storyline Analytical Framework for Understanding Future Severe Low-Water Episodes and Their Consequences
The role of land-atmosphere coupling in subseasonal surface air temperature prediction
On the combined use of rain gauges and GPM IMERG satellite rainfall products for hydrological modelling: impact assessment of the cellular-automata-based methodology in the Tanaro River basin in Italy
An increase in the spatial extent of European floods over the last 70 years
140-year daily ensemble streamflow reconstructions over 661 catchments in France
The agricultural expansion in South America's Dry Chaco: regional hydroclimate effects
Machine-learning-constrained projection of bivariate hydrological drought magnitudes and socioeconomic risks over China
Improving runoff simulation in the Western United States with Noah-MP and VIC models
Spatial variability in the seasonal precipitation lapse rates in complex topographical regions – application in France
Global catalog of soil moisture droughts over the past four decades
Assessing downscaling methods to simulate hydrologically relevant weather scenarios from a global atmospheric reanalysis: case study of the upper Rhône River (1902–2009)
Global total precipitable water variations and trends over the period 1958–2021
Assessing decadal- to centennial-scale nonstationary variability in meteorological drought trends
Identification of compound drought and heatwave events on a daily scale and across four seasons
Potential for historically unprecedented Australian droughts from natural variability and climate change
Flood risk assessment for Indian sub-continental river basins
Key ingredients in regional climate modelling for improving the representation of typhoon tracks and intensities
Divergent future drought projections in UK river flows and groundwater levels
Predicting extreme sub-hourly precipitation intensification based on temperature shifts
Hydroclimatic processes as the primary drivers of the Early Khvalynian transgression of the Caspian Sea: new developments
Accounting for hydroclimatic properties in flood frequency analysis procedures
Understanding the influence of “hot” models in climate impact studies: a hydrological perspective
A semi-parametric hourly space–time weather generator
A principal-component-based strategy for regionalisation of precipitation intensity–duration–frequency (IDF) statistics
Accounting for precipitation asymmetry in a multiplicative random cascade disaggregation model
Kazeem Abiodun Ishola, Gerald Mills, Ankur Prabhat Sati, Benjamin Obe, Matthias Demuzere, Deepak Upreti, Gourav Misra, Paul Lewis, Daire Walsh, Tim McCarthy, and Rowan Fealy
Hydrol. Earth Syst. Sci., 29, 2551–2582, https://doi.org/10.5194/hess-29-2551-2025, https://doi.org/10.5194/hess-29-2551-2025, 2025
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Global soil information introduces uncertainty into models that simulate soil hydrothermal changes. Using the Noah with Multiparameterization (Noah-MP) model with two different global soil datasets, we find under-represented soil properties in wet loam, causing a dry bias in soil moisture. This bias is more pronounced and drought categories are more severe in the SoilGrids dataset. We conclude that models should incorporate detailed, region-specific soil information to minimize model uncertainties.
Simon Moulds, Louise Slater, Louise Arnal, and Andrew W. Wood
Hydrol. Earth Syst. Sci., 29, 2393–2406, https://doi.org/10.5194/hess-29-2393-2025, https://doi.org/10.5194/hess-29-2393-2025, 2025
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Seasonal streamflow forecasts are an important component of flood risk management. Here, we train and test a machine learning model to predict the monthly maximum daily streamflow up to 4 months ahead. We train the model on precipitation and temperature forecasts to produce probabilistic hindcasts for 579 stations across the UK for the period 2004–2016. We show skilful results up to 4 months ahead in many locations, although, in general, the skill declines with increasing lead time.
Peyman Abbaszadeh, Fatemeh Gholizadeh, Keyhan Gavahi, and Hamid Moradkhani
Hydrol. Earth Syst. Sci., 29, 2407–2427, https://doi.org/10.5194/hess-29-2407-2025, https://doi.org/10.5194/hess-29-2407-2025, 2025
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The Hybrid Ensemble and Variational Data Assimilation framework for Environmental Systems (HEAVEN) enhances flood predictions by refining hydrologic models through improved data integration and uncertainty management. Tested in three southeastern US watersheds during hurricanes, HEAVEN assimilates real-time United States Geological Survey (USGS) streamflow data, boosting forecast accuracy.
Kun Xie, Lu Li, Hua Chen, Stephanie Mayer, Andreas Dobler, Chong-Yu Xu, and Ozan Mert Göktürk
Hydrol. Earth Syst. Sci., 29, 2133–2152, https://doi.org/10.5194/hess-29-2133-2025, https://doi.org/10.5194/hess-29-2133-2025, 2025
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We compared hourly and daily extreme precipitation across Norway from HARMONIE Climate models at convection-permitting 3 km (HCLIM3) and 12 km (HCLIM12) resolutions. HCLIM3 more accurately captures the extremes in most regions and seasons (except in summer). Its advantages are more pronounced for hourly extremes than for daily extremes. The results highlight the value of convection-permitting models in improving extreme-precipitation predictions and in helping the local society brace for extreme weather.
Ningpeng Dong, Haoran Hao, Mingxiang Yang, Jianhui Wei, Shiqin Xu, and Harald Kunstmann
Hydrol. Earth Syst. Sci., 29, 2023–2042, https://doi.org/10.5194/hess-29-2023-2025, https://doi.org/10.5194/hess-29-2023-2025, 2025
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Hydrometeorological forecasting is crucial for managing water resources and mitigating extreme weather events, yet current long-term forecast products are often embedded with uncertainties. We develop a deep-learning-based modelling framework to improve 30 d rainfall and streamflow forecasts by combining advanced neural networks and physical models. With the flow forecast error reduced by up to 33 %, the framework has the potential to enhance water management and disaster prevention.
Bamidele Oloruntoba, Stefan Kollet, Carsten Montzka, Harry Vereecken, and Harrie-Jan Hendricks Franssen
Hydrol. Earth Syst. Sci., 29, 1659–1683, https://doi.org/10.5194/hess-29-1659-2025, https://doi.org/10.5194/hess-29-1659-2025, 2025
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We studied how soil and weather data affect land model simulations over Africa. By combining soil data processed in different ways with weather data of varying time intervals, we found that weather inputs had a greater impact on water processes than soil data type. However, the way soil data were processed became crucial when paired with high-frequency weather inputs, showing that detailed weather data can improve local and regional predictions of how water moves and interacts with the land.
Yan Li, Bo Huang, Chunping Tan, Xia Zhang, Francesco Cherubini, and Henning W. Rust
Hydrol. Earth Syst. Sci., 29, 1637–1658, https://doi.org/10.5194/hess-29-1637-2025, https://doi.org/10.5194/hess-29-1637-2025, 2025
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Deforestation has a significant impact on climate, yet its effects on drought remain less understood. This study investigates how deforestation affects drought across various climate zones and timescales. Findings indicate that deforestation leads to drier conditions in tropical regions and wetter conditions in arid areas, with minimal effects in temperate zones. Long-term drought is more affected than short-term drought, offering valuable insights into vegetation–climate interactions.
Iván Noguera, Jamie Hannaford, and Maliko Tanguy
Hydrol. Earth Syst. Sci., 29, 1295–1317, https://doi.org/10.5194/hess-29-1295-2025, https://doi.org/10.5194/hess-29-1295-2025, 2025
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The study provides a detailed characterisation of flash drought in the UK for 1969–2021. The spatio-temporal distribution and trends of flash droughts are highly variable, with important regional and seasonal contrasts. In the UK, flash drought development responds primarily to precipitation variability, while the atmospheric evaporative demand plays a secondary role. We also found that the North Atlantic Oscillation is the main circulation pattern controlling flash drought development.
Geert Lenderink, Nikolina Ban, Erwan Brisson, Ségolène Berthou, Virginia Edith Cortés-Hernández, Elizabeth Kendon, Hayley J. Fowler, and Hylke de Vries
Hydrol. Earth Syst. Sci., 29, 1201–1220, https://doi.org/10.5194/hess-29-1201-2025, https://doi.org/10.5194/hess-29-1201-2025, 2025
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Future extreme rainfall events are influenced by changes in both absolute and relative humidity. The impact of increasing absolute humidity is reasonably well understood, but the role of relative humidity decreases over land remains largely unknown. Using hourly observations from France and the Netherlands, we find that lower relative humidity generally leads to more intense rainfall extremes. This relation is only captured well in recently developed convection-permitting climate models.
Alexis Bédard-Therrien, François Anctil, Julie M. Thériault, Olivier Chalifour, Fanny Payette, Alexandre Vidal, and Daniel F. Nadeau
Hydrol. Earth Syst. Sci., 29, 1135–1158, https://doi.org/10.5194/hess-29-1135-2025, https://doi.org/10.5194/hess-29-1135-2025, 2025
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Precipitation data from an automated observational network in eastern Canada showed a temperature interval where rain and snow could coexist. Random forest models were developed to classify the precipitation phase using meteorological data to evaluate operational applications. The models demonstrated significantly improved phase classification and reduced error compared to benchmark operational models. However, accurate prediction of mixed-phase precipitation remains challenging.
Lorenzo Silvestri, Miriam Saraceni, Bruno Brunone, Silvia Meniconi, Giulia Passadore, and Paolina Bongioannini Cerlini
Hydrol. Earth Syst. Sci., 29, 925–946, https://doi.org/10.5194/hess-29-925-2025, https://doi.org/10.5194/hess-29-925-2025, 2025
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This work demonstrates that seasonal forecasts of soil moisture are a valuable resource for groundwater management in the areas of the Central Mediterranean where longer memory timescales are found. In particular, they show significant correlation coefficients and forecast skill for the deepest soil moisture at 289 cm depth. Wet and dry events can be predicted 6 months in advance, and, in general, dry events are better captured than wet events.
Mohammad A. Farmani, Ali Behrangi, Aniket Gupta, Ahmad Tavakoly, Matthew Geheran, and Guo-Yue Niu
Hydrol. Earth Syst. Sci., 29, 547–566, https://doi.org/10.5194/hess-29-547-2025, https://doi.org/10.5194/hess-29-547-2025, 2025
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Soil moisture memory (SMM) shows how long soil stays moist after rain, impacting climate and ecosystems. Current models often overestimate SMM, causing inaccuracies in evaporation predictions. We enhanced a land model, Noah-MP, to include better water flow and ponding processes, and we tested it against satellite and field data. This improved model reduced overestimations and enhanced short-term predictions, helping create more accurate climate and weather forecasts.
Felipe Lobos-Roco, Jordi Vilà-Guerau de Arellano, and Camilo del Río
Hydrol. Earth Syst. Sci., 29, 109–125, https://doi.org/10.5194/hess-29-109-2025, https://doi.org/10.5194/hess-29-109-2025, 2025
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Water resources are fundamental for the social, economic, and natural development of (semi-)arid regions. Precipitation decreases due to climate change obligate us to find new water resources. Fog harvesting (FH) emerges as a complementary resource in regions where it is abundant but untapped. This research proposes a model to estimate FH potential in coastal (semi-)arid regions. This model could have broader applicability worldwide in regions where FH could be a viable water source.
Kyle R. Mankin, Sushant Mehan, Timothy R. Green, and David M. Barnard
Hydrol. Earth Syst. Sci., 29, 85–108, https://doi.org/10.5194/hess-29-85-2025, https://doi.org/10.5194/hess-29-85-2025, 2025
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We assess 63 gridded ground (G), satellite (S), and reanalysis (R) climate datasets. Higher-density station data and less-hilly terrain improved climate data. In mountainous and humid regions, dataset types performed similarly; however, R outperformed G when underlying data had low station density. G outperformed S or R datasets, although better streamflow modeling did not always follow. Hydrologic analyses need datasets that better represent climate variable dependencies and complex topography.
Xuan Chen, Job Augustijn van der Werf, Arjan Droste, Miriam Coenders-Gerrits, and Remko Uijlenhoet
EGUsphere, https://doi.org/10.5194/egusphere-2024-3988, https://doi.org/10.5194/egusphere-2024-3988, 2025
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Our research highlights the need to integrate urban land surface and hydrological models to better predict and manage compound climate disasters in cities. We find that inadequate representation of water surfaces, hydraulic systems, and detailed building representations are key areas for improvement in future models. Coupled models show promise but face challenges at regional and neighbourhood scales. Interdisciplinary communication is crucial to enhance urban hydrometeorological simulations.
Rasmus E. Benestad, Kajsa M. Parding, and Andreas Dobler
Hydrol. Earth Syst. Sci., 29, 45–65, https://doi.org/10.5194/hess-29-45-2025, https://doi.org/10.5194/hess-29-45-2025, 2025
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We present a new method to calculate the chance of heavy downpour and the maximum rainfall expected over a 25-year period. It is designed to analyse global climate models' reproduction of past and future climates. For the Nordic countries, it projects a wetter climate in the future with increased intensity but not necessarily more wet days. The analysis also shows that rainfall intensity is sensitive to future greenhouse gas emissions, while the number of wet days appears to be less affected.
Chien-Yu Tseng, Li-Pen Wang, and Christian Onof
Hydrol. Earth Syst. Sci., 29, 1–25, https://doi.org/10.5194/hess-29-1-2025, https://doi.org/10.5194/hess-29-1-2025, 2025
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This study presents a new algorithm to model convective storms. We used advanced tracking methods to analyse 165 storm events in Birmingham (UK) and reconstruct storm cell life cycles. We found that cell properties like intensity and size are interrelated and vary over time. The new algorithm, based on vine copulas, accurately simulates these properties and their evolution. It also integrates an exponential shape function for realistic rainfall patterns, enhancing its hydrological applicability.
Kenza Tazi, Andrew Orr, Javier Hernandez-González, Scott Hosking, and Richard E. Turner
Hydrol. Earth Syst. Sci., 28, 4903–4925, https://doi.org/10.5194/hess-28-4903-2024, https://doi.org/10.5194/hess-28-4903-2024, 2024
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This work aims to improve the understanding of precipitation patterns in High-mountain Asia, a crucial water source for around 1.9 billion people. Through a novel machine learning method, we generate high-resolution precipitation predictions, including the likelihoods of floods and droughts. Compared to state-of-the-art methods, our method is simpler to implement and more suitable for small datasets. The method also shows accuracy comparable to or better than existing benchmark datasets.
Peter E. Levy and the COSMOS-UK team
Hydrol. Earth Syst. Sci., 28, 4819–4836, https://doi.org/10.5194/hess-28-4819-2024, https://doi.org/10.5194/hess-28-4819-2024, 2024
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Having accurate up-to-date maps of soil moisture is important for many purposes. However, current modelled and remotely sensed maps are rather coarse and not very accurate. Here, we demonstrate a simple but accurate approach that is closely linked to direct measurements of soil moisture at a network sites across the UK, to the water balance (precipitation minus drainage and evaporation) measured at a large number of catchments (1212) and to remotely sensed satellite estimates.
Amy C. Green, Chris Kilsby, and András Bárdossy
Hydrol. Earth Syst. Sci., 28, 4539–4558, https://doi.org/10.5194/hess-28-4539-2024, https://doi.org/10.5194/hess-28-4539-2024, 2024
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Weather radar is a crucial tool in rainfall estimation, but radar rainfall estimates are subject to many error sources, with the true rainfall field unknown. A flexible model for simulating errors relating to the radar rainfall estimation process is implemented, inverting standard processing methods. This flexible and efficient model performs well in generating realistic weather radar images visually for a large range of event types.
Ling Zhang, Lu Li, Zhongshi Zhang, Joël Arnault, Stefan Sobolowski, Anthony Musili Mwanthi, Pratik Kad, Mohammed Abdullahi Hassan, Tanja Portele, and Harald Kunstmann
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-278, https://doi.org/10.5194/hess-2024-278, 2024
Revised manuscript accepted for HESS
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To address challenges related to unreliable hydrological simulations, we present an enhanced hydrological simulation with a refined climate model and a more comprehensive hydrological model. The model with the two parts outperforms that without, especially in migrating bias in peak flow and dry-season flow. Our findings highlight the enhanced hydrological simulation capability with the refined climate and lake module contributing 24 % and 76 % improvement, respectively.
Peng Huang, Agnès Ducharne, Lucia Rinchiuso, Jan Polcher, Laure Baratgin, Vladislav Bastrikov, and Eric Sauquet
Hydrol. Earth Syst. Sci., 28, 4455–4476, https://doi.org/10.5194/hess-28-4455-2024, https://doi.org/10.5194/hess-28-4455-2024, 2024
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We conducted a high-resolution hydrological simulation from 1959 to 2020 across France. We used a simple trial-and-error calibration to reduce the biases of the simulated water budget compared to observations. The selected simulation satisfactorily reproduces water fluxes, including their spatial contrasts and temporal trends. This work offers a reliable historical overview of water resources and a robust configuration for climate change impact analysis at the nationwide scale of France.
Marc Girona-Mata, Andrew Orr, Martin Widmann, Daniel Bannister, Ghulam Hussain Dars, Scott Hosking, Jesse Norris, David Ocio, Tony Phillips, Jakob Steiner, and Richard E. Turner
EGUsphere, https://doi.org/10.5194/egusphere-2024-2805, https://doi.org/10.5194/egusphere-2024-2805, 2024
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We introduce a novel method for improving daily precipitation maps in mountain regions and pilot it across three basins in the Hindu Kush Karakoram Himalaya (HKH). The approach leverages climate model and weather station data, along with statistical / machine learning techniques. Our results show this approach outperforms traditional methods, especially in remote, ungauged areas, suggesting it could be used to improve precipitation maps across much of the HKH, as well as other mountain regions.
He Sun, Tandong Yao, Fengge Su, Wei Yang, and Deliang Chen
Hydrol. Earth Syst. Sci., 28, 4361–4381, https://doi.org/10.5194/hess-28-4361-2024, https://doi.org/10.5194/hess-28-4361-2024, 2024
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Our findings show that runoff in the Yarlung Zangbo (YZ) basin is primarily driven by rainfall, with the largest glacier runoff contribution in the downstream sub-basin. Annual runoff increased in the upper stream but decreased downstream due to varying precipitation patterns. It is expected to rise throughout the 21st century, mainly driven by increased rainfall.
Louise Arnal, Martyn P. Clark, Alain Pietroniro, Vincent Vionnet, David R. Casson, Paul H. Whitfield, Vincent Fortin, Andrew W. Wood, Wouter J. M. Knoben, Brandi W. Newton, and Colleen Walford
Hydrol. Earth Syst. Sci., 28, 4127–4155, https://doi.org/10.5194/hess-28-4127-2024, https://doi.org/10.5194/hess-28-4127-2024, 2024
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Forecasting river flow months in advance is crucial for water sectors and society. In North America, snowmelt is a key driver of flow. This study presents a statistical workflow using snow data to forecast flow months ahead in North American snow-fed rivers. Variations in the river flow predictability across the continent are evident, raising concerns about future predictability in a changing (snow) climate. The reproducible workflow hosted on GitHub supports collaborative and open science.
Gabriel Rondeau-Genesse, Louis-Philippe Caron, Kristelle Audet, Laurent Da Silva, Daniel Tarte, Rachel Parent, Élise Comeau, and Dominic Matte
EGUsphere, https://doi.org/10.5194/egusphere-2024-2595, https://doi.org/10.5194/egusphere-2024-2595, 2024
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The 2021 drought in Quebec showcased the province’s potential vulnerability. This study uses a storyline approach to explore impacts of future extreme droughts under +2 °C and +3 °C warming scenarios. By combining regional climate and hydrological simulations, it highlights the potential for severe water deficits. Collaboration with water management experts helped project the impacts of those future extreme droughts and their consequences for ecosystems and human activities.
Yuna Lim, Andrea M. Molod, Randal D. Koster, and Joseph A. Santanello
EGUsphere, https://doi.org/10.5194/egusphere-2024-2312, https://doi.org/10.5194/egusphere-2024-2312, 2024
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To better utilize a given set of predictions, identifying “forecasts of opportunity” has great value. It can help anticipate when prediction skill will be higher. This study reveals that when strong L-A coupling is detected 3–4 weeks into a forecast, the prediction skill for surface air temperature at this lead increases across the Midwest and northern Great Plains. Regions experiencing strong L-A coupling exhibit warm and dry anomalies, leading to improved predictions of abnormally warm events.
Annalina Lombardi, Barbara Tomassetti, Valentina Colaiuda, Ludovico Di Antonio, Paolo Tuccella, Mario Montopoli, Giovanni Ravazzani, Frank Silvio Marzano, Raffaele Lidori, and Giulia Panegrossi
Hydrol. Earth Syst. Sci., 28, 3777–3797, https://doi.org/10.5194/hess-28-3777-2024, https://doi.org/10.5194/hess-28-3777-2024, 2024
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The accurate estimation of precipitation and its spatial variability within a watershed is crucial for reliable discharge simulations. The study is the first detailed analysis of the potential usage of the cellular automata technique to merge different rainfall data inputs to hydrological models. This work shows an improvement in the performance of hydrological simulations when satellite and rain gauge data are merged.
Beijing Fang, Emanuele Bevacqua, Oldrich Rakovec, and Jakob Zscheischler
Hydrol. Earth Syst. Sci., 28, 3755–3775, https://doi.org/10.5194/hess-28-3755-2024, https://doi.org/10.5194/hess-28-3755-2024, 2024
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We use grid-based runoff from a hydrological model to identify large spatiotemporally connected flood events in Europe, assess extent trends over the last 70 years, and attribute the trends to different drivers. Our findings reveal a general increase in flood extent, with regional variations driven by diverse factors. The study not only enables a thorough examination of flood events across multiple basins but also highlights the potential challenges arising from changing flood extents.
Alexandre Devers, Jean-Philippe Vidal, Claire Lauvernet, Olivier Vannier, and Laurie Caillouet
Hydrol. Earth Syst. Sci., 28, 3457–3474, https://doi.org/10.5194/hess-28-3457-2024, https://doi.org/10.5194/hess-28-3457-2024, 2024
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Daily streamflow series for 661 near-natural French catchments are reconstructed over 1871–2012 using two ensemble datasets: HydRE and HydREM. They include uncertainties coming from climate forcings, streamflow measurement, and hydrological model error (for HydrREM). Comparisons with other hydrological reconstructions and independent/dependent observations show the added value of the two reconstructions in terms of quality, uncertainty estimation, and representation of extremes.
María Agostina Bracalenti, Omar V. Müller, Miguel A. Lovino, and Ernesto Hugo Berbery
Hydrol. Earth Syst. Sci., 28, 3281–3303, https://doi.org/10.5194/hess-28-3281-2024, https://doi.org/10.5194/hess-28-3281-2024, 2024
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The Gran Chaco is a large, dry forest in South America that has been heavily deforested, particularly in the dry Chaco subregion. This deforestation, mainly driven by the expansion of the agricultural frontier, has changed the land's characteristics, affecting the local and regional climate. The study reveals that deforestation has resulted in reduced precipitation, soil moisture, and runoff, and if intensive agriculture continues, it could make summers in this arid region even drier and hotter.
Rutong Liu, Jiabo Yin, Louise Slater, Shengyu Kang, Yuanhang Yang, Pan Liu, Jiali Guo, Xihui Gu, Xiang Zhang, and Aliaksandr Volchak
Hydrol. Earth Syst. Sci., 28, 3305–3326, https://doi.org/10.5194/hess-28-3305-2024, https://doi.org/10.5194/hess-28-3305-2024, 2024
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Climate change accelerates the water cycle and alters the spatiotemporal distribution of hydrological variables, thus complicating the projection of future streamflow and hydrological droughts. We develop a cascade modeling chain to project future bivariate hydrological drought characteristics over China, using five bias-corrected global climate model outputs under three shared socioeconomic pathways, five hydrological models, and a deep-learning model.
Lu Su, Dennis P. Lettenmaier, Ming Pan, and Benjamin Bass
Hydrol. Earth Syst. Sci., 28, 3079–3097, https://doi.org/10.5194/hess-28-3079-2024, https://doi.org/10.5194/hess-28-3079-2024, 2024
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We fine-tuned the variable infiltration capacity (VIC) and Noah-MP models across 263 river basins in the Western US. We developed transfer relationships to similar basins and extended the fine-tuned parameters to ungauged basins. Both models performed best in humid areas, and the skills improved post-calibration. VIC outperforms Noah-MP in all but interior dry basins following regionalization. VIC simulates annual mean streamflow and high flow well, while Noah-MP performs better for low flows.
Valentin Dura, Guillaume Evin, Anne-Catherine Favre, and David Penot
Hydrol. Earth Syst. Sci., 28, 2579–2601, https://doi.org/10.5194/hess-28-2579-2024, https://doi.org/10.5194/hess-28-2579-2024, 2024
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The increase in precipitation as a function of elevation is poorly understood in areas with complex topography. In this article, the reproduction of these orographic gradients is assessed with several precipitation products. The best product is a simulation from a convection-permitting regional climate model. The corresponding seasonal gradients vary significantly in space, with higher values for the first topographical barriers exposed to the dominant air mass circulations.
Jan Řehoř, Rudolf Brázdil, Oldřich Rakovec, Martin Hanel, Milan Fischer, Rohini Kumar, Jan Balek, Markéta Poděbradská, Vojtěch Moravec, Luis Samaniego, and Miroslav Trnka
EGUsphere, https://doi.org/10.5194/egusphere-2024-1434, https://doi.org/10.5194/egusphere-2024-1434, 2024
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We present a robust method for identification and classification of global land drought events (GLDEs) based on soil moisture. Two models were used to calculate soil moisture and delimit soil drought over global land from 1980–2022, which was clustered into 775/630 GLDEs. Using four spatiotemporal and three motion-related characteristics, we categorized GLDEs into seven severity and seven dynamic categories. The frequency of GLDEs has generally increased in recent decades.
Caroline Legrand, Benoît Hingray, Bruno Wilhelm, and Martin Ménégoz
Hydrol. Earth Syst. Sci., 28, 2139–2166, https://doi.org/10.5194/hess-28-2139-2024, https://doi.org/10.5194/hess-28-2139-2024, 2024
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Climate change is expected to increase flood hazard worldwide. The evolution is typically estimated from multi-model chains, where regional hydrological scenarios are simulated from weather scenarios derived from coarse-resolution atmospheric outputs of climate models. We show that two such chains are able to reproduce, from an atmospheric reanalysis, the 1902–2009 discharge variations and floods of the upper Rhône alpine river, provided that the weather scenarios are bias-corrected.
Nenghan Wan, Xiaomao Lin, Roger A. Pielke Sr., Xubin Zeng, and Amanda M. Nelson
Hydrol. Earth Syst. Sci., 28, 2123–2137, https://doi.org/10.5194/hess-28-2123-2024, https://doi.org/10.5194/hess-28-2123-2024, 2024
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Global warming occurs at a rate of 0.21 K per decade, resulting in about 9.5 % K−1 of water vapor response to temperature from 1993 to 2021. Terrestrial areas experienced greater warming than the ocean, with a ratio of 2 : 1. The total precipitable water change in response to surface temperature changes showed a variation around 6 % K−1–8 % K−1 in the 15–55° N latitude band. Further studies are needed to identify the mechanisms leading to different water vapor responses.
Kyungmin Sung, Max C. A. Torbenson, and James H. Stagge
Hydrol. Earth Syst. Sci., 28, 2047–2063, https://doi.org/10.5194/hess-28-2047-2024, https://doi.org/10.5194/hess-28-2047-2024, 2024
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This study examines centuries of nonstationary trends in meteorological drought and pluvial climatology. A novel approach merges tree-ring proxy data (North American Seasonal Precipitation Atlas – NASPA) with instrumental precipitation datasets by temporally downscaling proxy data, correcting biases, and analyzing shared trends in normal and extreme precipitation anomalies. We identify regions experiencing recent unprecedented shifts towards drier or wetter conditions and shifts in seasonality.
Baoying Shan, Niko E. C. Verhoest, and Bernard De Baets
Hydrol. Earth Syst. Sci., 28, 2065–2080, https://doi.org/10.5194/hess-28-2065-2024, https://doi.org/10.5194/hess-28-2065-2024, 2024
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This study developed a convenient and new method to identify the occurrence of droughts, heatwaves, and co-occurring droughts and heatwaves (CDHW) across four seasons. Using this method, we could establish the start and/or end dates of drought (or heatwave) events. We found an increase in the frequency of heatwaves and CDHW events in Belgium caused by climate change. We also found that different months have different chances of CDHW events.
Georgina M. Falster, Nicky M. Wright, Nerilie J. Abram, Anna M. Ukkola, and Benjamin J. Henley
Hydrol. Earth Syst. Sci., 28, 1383–1401, https://doi.org/10.5194/hess-28-1383-2024, https://doi.org/10.5194/hess-28-1383-2024, 2024
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Multi-year droughts have severe environmental and economic impacts, but the instrumental record is too short to characterise multi-year drought variability. We assessed the nature of Australian multi-year droughts using simulations of the past millennium from 11 climate models. We show that multi-decadal
megadroughtsare a natural feature of the Australian hydroclimate. Human-caused climate change is also driving a tendency towards longer droughts in eastern and southwestern Australia.
Urmin Vegad, Yadu Pokhrel, and Vimal Mishra
Hydrol. Earth Syst. Sci., 28, 1107–1126, https://doi.org/10.5194/hess-28-1107-2024, https://doi.org/10.5194/hess-28-1107-2024, 2024
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A large population is affected by floods, which leave their footprints through human mortality, migration, and damage to agriculture and infrastructure, during almost every summer monsoon season in India. Despite the massive damage of floods, sub-basin level flood risk assessment is still in its infancy and needs to be improved. Using hydrological and hydrodynamic models, we reconstructed sub-basin level observed floods for the 1901–2020 period.
Qi Sun, Patrick Olschewski, Jianhui Wei, Zhan Tian, Laixiang Sun, Harald Kunstmann, and Patrick Laux
Hydrol. Earth Syst. Sci., 28, 761–780, https://doi.org/10.5194/hess-28-761-2024, https://doi.org/10.5194/hess-28-761-2024, 2024
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Tropical cyclones (TCs) often cause high economic loss due to heavy winds and rainfall, particularly in densely populated regions such as the Pearl River Delta (China). This study provides a reference to set up regional climate models for TC simulations. They contribute to a better TC process understanding and assess the potential changes and risks of TCs in the future. This lays the foundation for hydrodynamical modelling, from which the cities' disaster management and defence could benefit.
Simon Parry, Jonathan D. Mackay, Thomas Chitson, Jamie Hannaford, Eugene Magee, Maliko Tanguy, Victoria A. Bell, Katie Facer-Childs, Alison Kay, Rosanna Lane, Robert J. Moore, Stephen Turner, and John Wallbank
Hydrol. Earth Syst. Sci., 28, 417–440, https://doi.org/10.5194/hess-28-417-2024, https://doi.org/10.5194/hess-28-417-2024, 2024
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We studied drought in a dataset of possible future river flows and groundwater levels in the UK and found different outcomes for these two sources of water. Throughout the UK, river flows are likely to be lower in future, with droughts more prolonged and severe. However, whilst these changes are also found in some boreholes, in others, higher levels and less severe drought are indicated for the future. This has implications for the future balance between surface water and groundwater below.
Francesco Marra, Marika Koukoula, Antonio Canale, and Nadav Peleg
Hydrol. Earth Syst. Sci., 28, 375–389, https://doi.org/10.5194/hess-28-375-2024, https://doi.org/10.5194/hess-28-375-2024, 2024
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We present a new physical-based method for estimating extreme sub-hourly precipitation return levels (i.e., intensity–duration–frequency, IDF, curves), which are critical for the estimation of future floods. The proposed model, named TENAX, incorporates temperature as a covariate in a physically consistent manner. It has only a few parameters and can be easily set for any climate station given sub-hourly precipitation and temperature data are available.
Alexander Gelfan, Andrey Panin, Andrey Kalugin, Polina Morozova, Vladimir Semenov, Alexey Sidorchuk, Vadim Ukraintsev, and Konstantin Ushakov
Hydrol. Earth Syst. Sci., 28, 241–259, https://doi.org/10.5194/hess-28-241-2024, https://doi.org/10.5194/hess-28-241-2024, 2024
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Paleogeographical data show that 17–13 ka BP, the Caspian Sea level was 80 m above the current level. There are large disagreements on the genesis of this “Great” Khvalynian transgression of the sea, and we tried to shed light on this issue. Using climate and hydrological models as well as the paleo-reconstructions, we proved that the transgression could be initiated solely by hydroclimatic factors within the deglaciation period in the absence of the glacial meltwater effect.
Joeri B. Reinders and Samuel E. Munoz
Hydrol. Earth Syst. Sci., 28, 217–227, https://doi.org/10.5194/hess-28-217-2024, https://doi.org/10.5194/hess-28-217-2024, 2024
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Flooding presents a major hazard for people and infrastructure along waterways; however, it is challenging to study the likelihood of a flood magnitude occurring regionally due to a lack of long discharge records. We show that hydroclimatic variables like Köppen climate regions and precipitation intensity explain part of the variance in flood frequency distributions and thus reduce the uncertainty of flood probability estimates. This gives water managers a tool to locally improve flood analysis.
Mehrad Rahimpour Asenjan, Francois Brissette, Jean-Luc Martel, and Richard Arsenault
Hydrol. Earth Syst. Sci., 27, 4355–4367, https://doi.org/10.5194/hess-27-4355-2023, https://doi.org/10.5194/hess-27-4355-2023, 2023
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Climate models are central to climate change impact studies. Some models project a future deemed too hot by many. We looked at how including hot models may skew the result of impact studies. Applied to hydrology, this study shows that hot models do not systematically produce hydrological outliers.
Ross Pidoto and Uwe Haberlandt
Hydrol. Earth Syst. Sci., 27, 3957–3975, https://doi.org/10.5194/hess-27-3957-2023, https://doi.org/10.5194/hess-27-3957-2023, 2023
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Long continuous time series of meteorological variables (i.e. rainfall, temperature) are required for the modelling of floods. Observed time series are generally too short or not available. Weather generators are models that reproduce observed weather time series. This study extends an existing station-based rainfall model into space by enforcing observed spatial rainfall characteristics. To model other variables (i.e. temperature) the model is then coupled to a simple resampling approach.
Kajsa Maria Parding, Rasmus Emil Benestad, Anita Verpe Dyrrdal, and Julia Lutz
Hydrol. Earth Syst. Sci., 27, 3719–3732, https://doi.org/10.5194/hess-27-3719-2023, https://doi.org/10.5194/hess-27-3719-2023, 2023
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Intensity–duration–frequency (IDF) curves describe the likelihood of extreme rainfall and are used in hydrology and engineering, for example, for flood forecasting and water management. We develop a model to estimate IDF curves from daily meteorological observations, which are more widely available than the observations on finer timescales (minutes to hours) that are needed for IDF calculations. The method is applied to all data at once, making it efficient and robust to individual errors.
Kaltrina Maloku, Benoit Hingray, and Guillaume Evin
Hydrol. Earth Syst. Sci., 27, 3643–3661, https://doi.org/10.5194/hess-27-3643-2023, https://doi.org/10.5194/hess-27-3643-2023, 2023
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High-resolution precipitation data, needed for many applications in hydrology, are typically rare. Such data can be simulated from daily precipitation with stochastic disaggregation. In this work, multiplicative random cascades are used to disaggregate time series of 40 min precipitation from daily precipitation for 81 Swiss stations. We show that very relevant statistics of precipitation are obtained when precipitation asymmetry is accounted for in a continuous way in the cascade generator.
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Short summary
Central Asia crucially depends on water resources supplied by snow melt in the mountains during summer. To support water resources management we propose a generic tool for statistical forecasts of seasonal discharge based on multiple linear regressions. The predictors are observed precipitation and temperature, snow coverage, and discharge. The automatically derived models for 13 different catchments provided very skilful forecasts in April, and acceptable forecasts in January.
Central Asia crucially depends on water resources supplied by snow melt in the mountains during...
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