Panta Rhei benchmark dataset: socio-hydrological data of paired events of floods and droughts

Kreibich, Heidi; Schröter, Kai; Di Baldassarre, Giuliano; Van Loon, Anne F.; Mazzoleni, Maurizio; Abeshu, Guta Wakbulcho; Agafonova, Svetlana; AghaKouchak, Amir; Aksoy, Hafzullah; Alvarez-Garreton, Camila; Aznar, Blanca; Balkhi, Laila; Barendrecht, Marlies H.; Biancamaria, Sylvain; Bos-Burgering, Liduin; Bradley, Chris; Budiyono, Yus; Buytaert, Wouter; Capewell, Lucinda; Carlson, Hayley; Cavus, Yonca; Couasnon, Anaïs; Coxon, Gemma; Daliakopoulos, Ioannis; de Ruiter, Marleen C.; Delus, Claire; Erfurt, Mathilde; Esposito, Giuseppe; François, Didier; Frappart, Frédéric; Freer, Jim; Frolova, Natalia; Gain, Animesh K.; Grillakis, Manolis; Grima, Jordi Oriol; Guzmán, Diego A.; Huning, Laurie S.; Ionita, Monica; Kharlamov, Maxim; Khoi, Dao Nguyen; Kieboom, Natalie; Kireeva, Maria; Koutroulis, Aristeidis; Lavado-Casimiro, Waldo; Li, Hong-Yi; LLasat, Maria Carmen; Macdonald, David; Mård, Johanna; Mathew-Richards, Hannah; McKenzie, Andrew; Mejia, Alfonso; Mendiondo, Eduardo Mario; Mens, Marjolein; Mobini, Shifteh; Mohor, Guilherme Samprogna; Nagavciuc, Viorica; Ngo-Duc, Thanh; Nguyen, Huynh Thi Thao; Nhi, Pham Thi Thao; Petrucci, Olga; Quan, Nguyen Hong; Quintana-Seguí, Pere; Razavi, Saman; Ridolfi, Elena; Riegel, Jannik; Sadik, Md Shibly; Sairam, Nivedita; Savelli, Elisa; Sazonov, Alexey; Sharma, Sanjib; Sörensen, Johanna; Souza, Felipe Augusto Arguello; Stahl, Kerstin; Steinhausen, Max; Stoelzle, Michael; Szalińska, Wiwiana; Tang, Qiuhong; Tian, Fuqiang; Tokarczyk, Tamara; Tovar, Carolina; Tran, Thi Van Thu; van Huijgevoort, Marjolein H. J.; van Vliet, Michelle T. H.; Vorogushyn, Sergiy; Wagener, Thorsten; Wang, Yueling; Wendt, Doris E.; Wickham, Elliot; Yang, Long; Zambrano-Bigiarini, Mauricio; Ward, Philip J.. 2023 Panta Rhei benchmark dataset: socio-hydrological data of paired events of floods and droughts. Earth System Science Data, 15 (5). 2009-2023.

Before downloading, please read NORA policies.
Text (Open Access Paper)
essd-15-2009-2023.pdf - Published Version
Available under License Creative Commons Attribution 4.0.

Download (1MB) | Preview


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 and climate adaptation. However, there is currently a lack of comprehensive, empirical data about the processes, interactions, and feedbacks in complex human–water systems leading to flood and drought impacts. Here we present a benchmark dataset containing socio-hydrological data of paired events, i.e. two floods or two droughts that occurred in the same area. The 45 paired events occurred in 42 different study areas and cover a wide range of socio-economic and hydro-climatic conditions. The dataset is unique in covering both floods and droughts, in the number of cases assessed and in the quantity of socio-hydrological data. The benchmark dataset comprises (1) detailed review-style reports about the events and key processes between the two events of a pair; (2) the key data table containing variables that assess the indicators which characterize management shortcomings, hazard, exposure, vulnerability, and impacts of all events; and (3) a table of the indicators of change that indicate the differences between the first and second event of a pair. The advantages of the dataset are that it enables comparative analyses across all the paired events based on the indicators of change and allows for detailed context- and location-specific assessments based on the extensive data and reports of the individual study areas. The dataset can be used by the scientific community for exploratory data analyses, e.g. focused on causal links between risk management; changes in hazard, exposure and vulnerability; and flood or drought impacts. The data can also be used for the development, calibration, and validation of socio-hydrological models. The dataset is available to the public through the GFZ Data Services (Kreibich et al., 2023,

Item Type: Publication - Article
Digital Object Identifier (DOI):
ISSN: 1866-3516
Date made live: 13 Jul 2023 14:39 +0 (UTC)

Actions (login required)

View Item View Item

Document Downloads

Downloads for past 30 days

Downloads per month over past year

More statistics for this item...