ALBERT

Description: This dataset contains catchment average time series of five meteorological or hydrological parameters for 3872 hydrometric stations across Europe from 1960-2010. The parameters are: rainfall, soil moisture saturation, snowmelt, snow cover and convective conditions. All parameters have a daily resolution and were derived from a 0.11x0.11° reanalysis dataset. Daily averages were calculated from the pixels within each catchment, weighted by the fraction of pixel area that lies within the respective catchment. This dataset was originally created for the classification of floods by their generating process, but is also suitable for different hydrological studies.

Description: The dataset comprises a range of variables describing characteristics of flood events and river catchments for 480 gauging stations in Germany and Austria. The event characteristics are asscoiated with annual maximum flood events in the period from 1951 to 2010. They include variables on event precipitation, antecedent catchment state, event catchment response, event timing, and event types. The catchment characteristics include variables on catchment area, catchment wetness, tail heaviness of rainfall, nonlinearity of catchment response, and synchronicity of precipitation and catchment state. The variables were compiled as potential predictors of heavy tail behaviour of flood peak distributions. They are based on gauge observations of discharge, E-OBS meteorological data (Haylock et al. 2008), mHM hydrological model simulations (Samaniego et al., 2010), 4DAS climate reanalysis data (Primo et al., 2019), and the 25x25 m resolution EU-DEM v1.1. A short description of the data processing is included in the file inventory and more details can be found in Macdonald et al. (2022).

Description: The Digital Earth Flood Event Explorer supports geoscientists and experts to analyse flood events along the process cascade event generation, evolution and impact across atmospheric, terrestrial, and marine disciplines. It applies the concept of scientific workflows and the component-based Data Analytics Software Framework (DASF, Eggert and Dransch, 2021) to an exemplary showcase. It aims at answering the following geoscientific questions: - How does precipitation change over the course of the 21st century under different climate scenarios over a certain region? - What are the main hydro-meteorological controls of a specific flood event? - What are useful indicators to assess socio-economic flood impacts? - How do flood events impact the marine environment? - What are the best monitoring sites for upcoming flood events? The Flood Event Explorer developed scientific workflows for each geoscientific question providing enhanced analysis methods from statistics, machine learning, and visual data exploration that are implemented in different languages and software environments, and that access data form a variety of distributed databases. The collaborating scientists are from different Helmholtz research centers and belong to different scientific fields such as hydrology, climate-, marine-, and environmental science, and computer- and data science. It is funded by the Initiative and Networking Fund of the Helmholtz Association through the Digital Earth project (https://www.digitalearth-hgf.de/).

Description: The inventory of dams in Germany contains information on name, date of construction, the start of operation, state, river, dam height, crest length, lake area, lake volume, purpose of the dam, dam type, building characteristics, and coordinates. The inventory is a zip-file composed of 3 tab-delimited files and 1 shapefile. The shapefile contains all 530 dams with all 15 columns and can be opened with every GIS program. The geographic coordinate system used is WGS 1984. The file 2020-005_Speckhann-et-al_Dams_in_Germany_v.1.0.txt has the same information as the shapefile, i.e. contains 530 dams with the same 15 columns and it is delimitated using tab. The 2020-005_Speckhann-et-al_Abreviation.txt file contains 4 different tables which presents every abbreviation used at the inventory. The abbreviations were used for several applications: dam building characteristics, purpose of the dams, German states, and dam’s type. They were separated in 4 different tables (Building characteristics, Purpose, States and Type). The Building Characteristics are related to the structural formation of the dams, for example embankment dam is listed as “EDD”. All abbreviations regarding the building characteristics of the dam can be visualized at Table 2 at the Data description. The Purpose of the dams was divided into 8 categories: energy production, flood control, recreational use, water supply, industrial and agricultural water supply, fishing, transport and nature protection. At the inventory there are multi-purposes dams and single-purposes dams, i.e. a dam might have more than one purpose. The States in Germany were also abbreviated at the inventory using 2 letters. Due to no observed entries at the inventory for Berlin, Bremen and Hamburg, those states are not shown at Table 4. The types of dams were also abbreviated. 2020-005_Speckhann-et-al_Source_v.1.0.txt contains the name of every dam and the main source used for the obtention of the information.

Description: This dataset contains 74 weekly/bi-weekly precipitation sum samples recorded at An Long, in the northern part of the Mekong Delta (Plain of Reed, Dong Thap province, Vietnam). The data were collected as part of a study analyzing the influence of local and regional climatic factors on the stable isotopic composition of rainfall in the Mekong delta as part of the Asian monsoon region (Le Duy et al., 2017).. Samples were taken on a weekly basis between June 2014 and May 2015 and twice a week between June 2015 and December 2015. The rain collector was a dip-in sampler type as described in the guidelines of the IAEA technical procedure for precipitation sampling (IAEA, 2014). It consists of a 5 liters accumulation glass bottle fitted with a vertical 14 cm diameter plastic funnel that reaches almost to the bottom to prevent evaporative losses, and a pressure equilibration plastic tube (2 mm in diameter and 15 m in length) to minimize evaporation out of the collection device. All collected samples were stored in 30 mL plastic sample bottles with tight screw caps to avoid evaporation effects. Between collection and laboratory analysis, the samples were stored in the dark. All stable isotope samples were analyzed at the laboratory of the Alfred-Wegener-Institute (AWI) in Potsdam, Germany. The measurements were performed with a Finnigan MAT Delta-S mass spectrometer using equilibration techniques to determine the ratio of stable oxygen (18O/16O) and hydrogen (2H/1H) isotopes. Analytical results were reported as δ2H and δ18O (‰, relative to Vienna Standard Mean Ocean Water - VSMOW) with internal 1σ errors of better than 0.8‰ and 0.1‰ for δ2H and δ18O, respectively. The deuterium excess (d-excess) was calculated with the equation of Dansgaard (1964): d-excess = δ2H - 8*δ18O

Description: The GFZ Potsdam HART (Hazard and Risk Team) in cooperation with the DFG research training group 2043 NatRiskChange at Potsdam University has enabled the acquisition of Airborne Laser Scanning (ALS) and high-resolution optical data which were acquired between 22 September 2021 and 24 October 2021 by the Milan Geoservice company, Spremberg, Germany. This data acquisition took place in the Eifel regions of North Rhine-Westphalia (NRW) and Rhineland-Palatinate (RLP), which were hit by the 14 July 2021 precipitation event leading to widespread severe inundations, flash floods and caused around 185 victims and massive damage to settlements, river geometry and other geomorphic features. The high-resolution ALS and optical data acquisitions aimed at the documentation and quantification of the extent of flood related changes and destructions as well as their reappraisal before diffusion erases traces. Thus, the generated data are valuable for forensic event analysis and future attempts on flood forecasting and warning in the context of scientific and practical purposes.

Description: This dataset comprises event peak flows, representing extreme floods at 516 stations in Germany. The data generation process involves several key steps. Initially, observed rainfall events associated with 10 historical flood disasters from 1950 to 2021 are undergone spatial shifts. These shifts involve three distances (20, 50, and 100 km) and eight directions (North, Northeast, East, Southeast, South, Southwest, West, Northwest), resulting in 24 counterfactual precipitation events. Including the factual (no shift) event, a total of 25 distinct shifting events are considered. Subsequently, these shifted fields are used as atmospheric forcing for a mesoscale hydrological model (mHM) set up and calibrated for the entire Germany. The model produces daily stream flows across its domain, from which the event peak flows are derived. This dataset is expected to provide a valuable resource for analyzing and modeling the dynamics extreme flood events in Germany.