Corrigendum to “Emerging dryland flooding” [Earth-Science Reviews 281 (2026) 105612] - Yuanyuan Bai; Ting Zhang; Stephen E. Darby; Bruno Merz; Albert J. Kettner; Katerina Michaelides; Shijie Jiang; Shuyue Mao; Yiyi Li; Mingfu Guan; Seifu Tilahun; Dongfeng Li (Earth-Science Reviews, 2026)

Emerging dryland flooding - Yuanyuan Bai; Ting Zhang; Stephen E. Darby; Bruno Merz; Albert J. Kettner; Katerina Michaelides; Shijie Jiang; Shuyue Mao; Yiyi Li; Mingfu Guan; Seifu Tilahun; Dongfeng Li (Earth-Science Reviews, 2026)

Event indicator analysis using depth functions to explain the occurrence of large floods in Germany - Björn Guse; Faizan Anwar; Bruno Merz; Larisa Tarasova; Elena Macdonald; Ralf Merz; András Bárdossy; Sergiy Vorogushyn (Hydrological Sciences Journal, 2026)

Panta Rhei: a decade of progress in research on change in hydrology and society - Heidi Kreibich; Murugesu Sivapalan; Amir AghaKouchak; Nans Addor; Hafzullah Aksoy; Berit Arheimer; Karsten Arnbjerg-Nielsen; Cynthia Vail-Castro; Christophe Cudennec; Mariana Madruga de Brito; Giuliano Di Baldassarre; David C. Finger; et al. (Hydrological Sciences Journal, 2025)

ESA's current approaches to end-of-life strategies for HEO missions - Francesca Letizia; Silvia Sanvido; Stijn Lemmens; Klaus Merz; Richard Southworth; Bruno Sousa (Journal of Space Safety Engineering, 2023)

Assessing compound pluvial-fluvial flooding: Research status and ways forward - Xiaoxiang Guan; Sergiy Vorogushyn; Heiko Apel; Bruno Merz (Water Security, 2023)

Increased likelihood of compound dry and hot extremes in India - Ravi Kumar Guntu; Bruno Merz; Ankit Agarwal (Atmospheric Research, 2023)

Multisite temporal rainfall disaggregation using methods of fragments conditioned on circulation patterns - Xiaoxiang Guan; Katrin Nissen; Viet Dung Nguyen; Bruno Merz; Benjamin Winter; Sergiy Vorogushyn (Journal of Hydrology, 2023)

Spatial coherence patterns of extreme winter precipitation in the U.S. - Abhirup Banerjee; Matthias Kemter; Bedartha Goswami; Bruno Merz; Jürgen Kurths; Norbert Marwan (Theoretical and Applied Climatology, 2023)
Extreme precipitation events have a significant impact on life and property. The U.S. experiences huge economic losses due to severe floods caused by extreme precipitation. With the complex terrain of the region, it becomes increasingly important to understand the spatial variability of extreme precipitation to conduct a proper risk assessment of natural hazards such as floods. In this work, we use a complex network-based approach to identify distinct regions exhibiting spatially coherent precipitation patterns due to various underlying climate mechanisms. To quantify interactions between event series of different locations, we use a nonlinear similarity measure, called the edit-distance method, which considers not only the occurrence of the extreme events but also their intensity, while measuring similarity between two event series. Using network measures, namely, degree and betweenness centrality, we are able to identify the specific regions affected by the landfall of atmospheric rivers in addition to those where the extreme precipitation due to storm track activity is modulated by different mountain ranges such as the Rockies and the Appalachians. Our approach provides a comprehensive picture of the spatial patterns of extreme winter precipitation in the U.S. due to various climate processes despite its vast, complex topography.

Investigating the impact of calibration timescales on streamflow simulation, parameter sensitivity and model performance for Indian catchments - Sridhara Setti; Kamal Kumar Barik; Bruno Merz; Ankit Agarwal; Maheswaran Rathinasamy (Hydrological Sciences Journal, 2022)

On the role of floodplain storage and hydrodynamic interactions in flood risk estimation - Mostafa Farrag; Fabio Brill; Nguyen Viet Dung; Nivedita Sairam; Kai Schröter; Heidi Kreibich; Bruno Merz; Karin M. de Bruijn; Sergiy Vorogushyn (Hydrological Sciences Journal, 2022)

Ranking and characterization of precipitation extremes for the past 113 years for Indian western Himalayas - Saurav Raj; Roopam Shukla; Ricardo M. Trigo; Bruno Merz; Maheswaran Rathinasamy; Alexandre M. Ramos; Ankit Agarwal (International Journal of Climatology, 2021)
Globally, mountain systems are unevenly exposed to risks of extreme precipitation. Within the Himalayan region, precipitation extremes are a rising concern, but their current understanding is limited. In this study, we use 113 years of precipitation data to rank and characterize precipitation extremes in the Indian Western Himalayas (IWH). Our statistical ranking method integrates precipitation spatial extent and its intensity across different durations for determining the severity of extreme events. The proposed ranking method accounts for multi‐day duration ranking method to capture persistent precipitation episodes. Results show that the method accurately detects and ranks the most extreme precipitation events that occurred in the IWH and indicate locations of these events. Our results highlight that critical long duration events in the region (e.g., 10 days) are missed at ranks at shorter duration (e.g., 2–3 days), thereby highlighting the importance to multi‐day precipitation extremes ranking. In addition, the proposed ranking method provides information about the event duration that will be associated with the highest impact on society, carrying high significance. Our findings are valuable for flood risk management and disaster risk reduction.

A nonlinear hybrid model to assess the impacts of climate variability and human activities on runoff at different time scales - Yanhua Qin; Xun Sun; Baofu Li; Bruno Merz (Stochastic Environmental Research and Risk Assessment, 2021)

Comprehensive evaluation of an improved large‐scale multi‐site weather generator for Germany - Viet Dung Nguyen; Bruno Merz; Yeshewatesfa Hundecha; Uwe Haberlandt; Sergiy Vorogushyn (International Journal of Climatology, 2021)
In this work, we present a comprehensive evaluation of a stochastic multi‐site, multi‐variate weather generator at the scale of entire Germany and parts of the neighbouring countries covering the major German river basins Elbe, Upper Danube, Rhine, Weser and Ems with a total area of approximately 580,000 km 2 . The regional weather generator, which is based on a first‐order multi‐variate auto‐regressive model, is setup using 53‐year long daily observational data at 528 locations. The performance is evaluated by investigating the ability of the weather generator to replicate various important statistical properties of the observed variables including precipitation occurrence and dry/wet transition probabilities, mean daily and extreme precipitation, multi‐day precipitation sums, spatial correlation structure, areal precipitation, mean daily and extreme temperature and solar radiation. We explore two marginal distributions for daily precipitation amount: mixed Gamma‐Generalized Pareto and extended Generalized Pareto. Furthermore, we introduce a new procedure to estimate the spatial correlation matrix and model mean daily temperature and solar radiation. The extensive evaluation reveals that the weather generator is greatly capable of capturing most of the crucial properties of the weather variables, particularly of extreme precipitation at individual locations. Some deficiencies are detected in capturing spatial precipitation correlation structure that leads to an overestimation of areal precipitation extremes. Further improvement of the spatial correlation structure is envisaged for future research. The mixed marginal model found to outperform the extended Generalized Pareto in our case. The use of power transformation in combination with normal distribution significantly improves the performance for non‐precipitation variables. The weather generator can be used to generate synthetic event footprints for large‐scale trans‐basin flood risk assessment.

A probabilistic approach to estimating residential losses from different flood types - Dominik Paprotny; Heidi Kreibich; Oswaldo Morales-Nápoles; Dennis Wagenaar; Attilio Castellarin; Francesca Carisi; Xavier Bertin; Bruno Merz; Kai Schröter (Natural Hazards, 2021)
Residential assets, comprising buildings and household contents, are a major source of direct flood losses. Existing damage models are mostly deterministic and limited to particular countries or flood types. Here, we compile building-level losses from Germany, Italy and the Netherlands covering a wide range of fluvial and pluvial flood events. Utilizing a Bayesian network (BN) for continuous variables, we find that relative losses (i.e. loss relative to exposure) to building structure and its contents could be estimated with five variables: water depth, flow velocity, event return period, building usable floor space area and regional disposable income per capita. The model’s ability to predict flood losses is validated for the 11 flood events contained in the sample. Predictions for the German and Italian fluvial floods were better than for pluvial floods or the 1993 Meuse river flood. Further, a case study of a 2010 coastal flood in France is used to test the BN model’s performance for a type of flood not included in the survey dataset. Overall, the BN model achieved better results than any of 10 alternative damage models for reproducing average losses for the 2010 flood. An additional case study of a 2013 fluvial flood has also shown good performance of the model. The study shows that data from many flood events can be combined to derive most important factors driving flood losses across regions and time, and that resulting damage models could be applied in an open data framework.

An event synchronization method to link heavy rainfall events and large‐scale atmospheric circulation features - Federico Conticello; Francesco Cioffi; Bruno Merz; Upmanu Lall (International Journal of Climatology, 2018)
Heavy rainfall, floods and other hydroclimatic extremes may be related to specific states of organization of the atmospheric circulation. The identification of these states and their linkage to local extremes could facilitate a physically meaningful quantification of local extremes in future climates and could allow forecasting extremes conditioned on the large‐scale atmospheric state. A novel methodology is presented that combines non‐linear, non‐parametric methods to link heavy precipitation events (HPEs) to atmospheric circulation states. Using daily rainfall data for the period 1951–2015 from 37 gauges in the Lazio region in Italy, HPEs are defined. For the same period, two atmospheric variables, namely, the 850 hPa geopotential height field and the integrated vapour transport (IVT), are derived from reanalysis data. The geopotential configurations driving heavy precipitation in the region are identified by combing self‐organized maps and event synchronization. First, a finite number of representative geopotential configurations is identified. Rainfall gauges are pooled into clusters, which show synchronized occurrence of heavy precipitation. Furthermore, geopotential configurations are identified, which tend to drive HPEs. For these geopotential states, the probability of HPE occurrence as a function of IVT is calculated through a local logistic regression model. Finally, it is explored whether the identified patterns are related to the occurrence of atmospheric rivers, which govern the atmospheric humidity transport from the tropics and subtropics to Europe. The relation found demonstrates the reliability of the proposed methodology.

High spatial and temporal organization of changes in precipitation over Germany for 1951–2006 - Aline Murawski; Janek Zimmer; Bruno Merz (International Journal of Climatology, 2016)
Temporal changes in daily precipitation observed at more than 2300 stations in Germany during the second half of the 20th century are analysed. Compared to other studies, this analysis is based on a very high spatial density of observation locations and complete areal coverage of Germany. Changes in four precipitation characteristics are investigated: (1) total amount of seasonal and monthly precipitation, (2) mean and 95% quantile (q95) of daily precipitation, (3) transition probabilities to quantify wet and dry spells, and (4) precipitation amounts for a 7‐day event with return period 100 years. For all parameters, strikingly clear trend patterns in space and time (of the year) emerged. Stations with increasing and decreasing trends are never found in direct neighbourhood, but are well separated from each other. Changes are season and even month specific. These clear spatial and temporal patterns are an expression of the organization of precipitation mechanisms over Germany. These findings add a note of caution in regard to trend analyses: Spatially and temporally aggregated trend studies might not disclose the complete range of changes and might miss important details. Interestingly, the variability of daily precipitation has changed in parallel with the mean behaviour: Those regions and seasons that show an increase in mean show also an increase in standard deviation, leading to a disproportional increase in heavy precipitation. In addition, there is a tendency towards higher persistence, in particular, longer wet spells in winter, spring, and autumn, and longer dry spells in summer. If these trends continue, there will be an increasing potential for floods in winter and spring, and increasing problems for water availability in summer in regions that show signs of water stress today.

Preface: climate change proof flood risk management - Frans Klijn; Bruno Merz; Edmund C. Penning-Rowsell; Zbigniew W. Kundzewicz (Mitigation and Adaptation Strategies for Global Change, 2015)

Analysis of current trends in climate parameters, river discharge and glaciers in the Aksu River basin (Central Asia) - Valentina Krysanova; Michel Wortmann; Tobias Bolch; Bruno Merz; Doris Duethmann; Judith Walter; Shaochun Huang; Jiang Tong; Su Buda; Zbigniew W. Kundzewicz (Hydrological Sciences Journal, 2015)

Recent changes in flood preparedness of private households and businesses in Germany - Heidi Kreibich; Isabel Seifert; Annegret H. Thieken; Eric Lindquist; Klaus Wagner; Bruno Merz (Regional Environmental Change, 2011)

Development of FLEMOcs – a new model for the estimation of flood losses in the commercial sector - Heidi Kreibich; Isabel Seifert; Bruno Merz; Annegret H. Thieken (Hydrological Sciences Journal, 2010)

Application and validation of FLEMOcs – a flood-loss estimation model for the commercial sector - Isabel Seifert; Heidi Kreibich; Bruno Merz; Annegret H. Thieken (Hydrological Sciences Journal, 2010)

Flood risk curves and uncertainty bounds - Bruno Merz; Annegret H. Thieken (Natural Hazards, 2009)

Trends der Hochwassergefährdung in Deutschland (1951 bis 2002) und Konsequenzen für die Bemessung - Theresia Petrow; Jose Miguel Martins Delgado; Bruno Merz (WASSERWIRTSCHAFT, 2008)

Improvements on Flood Alleviation in Germany: Lessons Learned from the Elbe Flood in August 2002 - Theresia Petrow; Annegret H. Thieken; Heidi Kreibich; Bruno Merz; Cord Heinrich Bahlburg (Environmental Management, 2006)

A Probabilistic Modelling System for Assessing Flood Risks - Heiko Apel; Annegret H. Thieken; Bruno Merz; Günter Blöschl (Natural Hazards, 2006)

Possibilities and Limitations of Interdisciplinary, User-oriented Research: Experiences from the German Research Network Natural Disasters - Bruno Merz; Jana Friedrich; Markus Disse; Jochen Schwarz; Johann G. Goldammer; Jochen Wächter (Natural Hazards, 2006)

Preface - Bruno Merz; Jana Friedrich; Anselm Smolka (Natural Hazards, 2006)

Abstracts of the 6th FECS Conference 1998 Lectures - F. Sherwood Rowland; Donald R. Blake; B. R. Larsen; Anne Lindskog; Peter J. Peterson; W. Peter Williams; T. J. Wallington; M. J. Pilling; N. Carslaw; D. J. Creasey; D. E. Heard; P. Jacobs; et al. (Environmental Science and Pollution Research, 1998)