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  • 1
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    Rhine flood stories: Spatio‐temporal analysis of historic and projected flood genesis in the Rhine River basin (2023)
    John Wiley & Sons, Inc. | Hoboken, USA
    Details
    Publication Date: 2023-07-19
    Description: 〈title xmlns:mml="http://www.w3.org/1998/Math/MathML"〉Abstract〈/title〉〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉The genesis of floods in large river basins often is complex. Streamflow originating from precipitation and snowmelt and different tributaries can superimpose and cause high water levels, threatening cities and communities along the riverbanks. For better understanding the mechanisms (origin and composition) of flood events in large and complex basins, we capture and share the story behind major historic and projected streamflow peaks in the Rhine River basin. Our analysis is based on hydrological simulations with the mesoscale Hydrological Model forced with both meteorological observations and an ensemble of climate projections. The spatio‐temporal analysis of the flood events includes the assessment and mapping of antecedent liquid precipitation, snow cover changes, generated and routed runoff, areal extents of events, and the above‐average runoff from major sub‐basins up to 10 days before a streamflow peak. We introduce and assess the analytical setup by presenting the flood genesis of the two well‐known Rhine floods that occurred in January 1995 and May 1999. We share our extensive collection of event‐based Rhine River flood genesis, which can be used in‐ and outside the scientific community to explore the complexity and diversity of historic and projected flood genesis in the Rhine basin. An interactive web‐based viewer provides easy access to all major historic and projected streamflow peaks at four locations along the Rhine. The comparison of peak flow genesis depending on different warming levels elucidates the role of changes in snow cover and precipitation characteristics in the (pre‐)Alps for flood hazards along the entire channel of the Rhine. Furthermore, our results suggest a positive correlation between flood magnitudes and areal extents of an event. Further hydro‐climatological research is required to improve the understanding of the climatic impact on the Rhine and beyond.〈/p〉
    Description: 〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉The genesis of riverine floods in large river basins often is complex. Streamflow originating from precipitation and snowmelt and different tributaries can superimpose and cause high water levels threatening cities and communities along the riverbanks. In this study, we capture and share the story behind major historic and projected streamflow peaks in the large and complex basin of the Rhine River.〈boxed-text position="anchor" content-type="graphic" id="hyp14918-blkfxd-0001" xml:lang="en"〉 〈graphic position="anchor" id="jats-graphic-1" xlink:href="urn:x-wiley:08856087:media:hyp14918:hyp14918-toc-0001"〉
    Description: https://doi.org/10.5281/zenodo.3239055
    Description: https://github.com/ERottler/rhine-flood-genesis
    Description: http://natriskchange.ad.umwelt.uni-potsdam.de:3838/rhine-flood-genesis
    Description: https://b2share.eudat.eu/records/72d7a4f5d38043d1a137228b39c7ecc3
    Keywords: ddc:551.46 ; climate change ; flood composition ; flood genesis ; mHM ; model simulations ; quantile extent ; Rhine River ; spatio‐temporal analysis ; web‐based dashboard
    Language: English
    Type: doc-type:article
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    CITATION GEO-LEO
  • 2
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    Toward an adequate level of detail in flood risk assessments (2023)
    Blackwell Publishing Ltd | Oxford, UK
    Details
    Publication Date: 2024-01-24
    Description: 〈title xmlns:mml="http://www.w3.org/1998/Math/MathML"〉Abstract〈/title〉〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉Flood risk assessments require different disciplines to understand and model the underlying components hazard, exposure, and vulnerability. Many methods and data sets have been refined considerably to cover more details of spatial, temporal, or process information. We compile case studies indicating that refined methods and data have a considerable effect on the overall assessment of flood risk. But are these improvements worth the effort? The adequate level of detail is typically unknown and prioritization of improvements in a specific component is hampered by the lack of an overarching view on flood risk. Consequently, creating the dilemma of potentially being too greedy or too wasteful with the resources available for a risk assessment. A “sweet spot” between those two would use methods and data sets that cover all relevant known processes without using resources inefficiently. We provide three key questions as a qualitative guidance toward this “sweet spot.” For quantitative decision support, more overarching case studies in various contexts are needed to reveal the sensitivity of the overall flood risk to individual components. This could also support the anticipation of unforeseen events like the flood event in Germany and Belgium in 2021 and increase the reliability of flood risk assessments.〈/p〉
    Description: Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659
    Description: BMBF http://dx.doi.org/10.13039/501100002347
    Description: Federal Environment Agency http://dx.doi.org/10.13039/501100010809
    Description: http://howas21.gfz-potsdam.de/howas21/
    Description: https://www.umwelt.niedersachsen.de/startseite/themen/wasser/hochwasser_amp_kustenschutz/hochwasserrisikomanagement_richtlinie/hochwassergefahren_und_hochwasserrisikokarten/hochwasserkarten-121920.html
    Description: https://download.geofabrik.de/europe/germany.html
    Description: https://emergency.copernicus.eu/mapping/list-of-components/EMSN024
    Description: https://data.jrc.ec.europa.eu/collection/id-0054
    Description: https://oasishub.co/dataset/surface-water-flooding-footprinthurricane-harvey-august-2017-jba
    Description: https://www.wasser.sachsen.de/hochwassergefahrenkarte-11915.html
    Keywords: ddc:551.48 ; decision support ; extreme events ; integrated flood risk management ; risk assessment
    Language: English
    Type: doc-type:article
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    CITATION GEO-LEO
  • 3
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    Hydro-sedimentological dataset for the mesoscale mountainous Isábena catchment, NE Spain (2018)
    GFZ Data Services
    Details
    Publication Date: 2021-08-31
    Description: Abstract
    Description: Version history: This datased is an updated version of Francke et al. (2017; http://doi.org/10.5880/fidgeo.2017.003) for a revised version of this discussion paper. It contains further data collected, some of which also resulted in the revision of previous data (e.g. updated rating curves).A comprehensive hydro-sedimentological dataset for the Isábena catchment, NE Spain, for the period 2010-2018 is presented to analyse water and sediment fluxes in a Mediterranean meso-scale catchment. The dataset includes rainfall data from twelve rain gauges distributed within the study area complemented by meteorological data of twelve official meteo-stations. It comprises discharge data derived from water stage measurements as well as suspended sediment concentrations (SSC) at six gauging stations of the Isábena river and its sub-catchments. Soil spectroscopic data from 351 suspended sediment samples and 152 soil samples were collected to characterize sediment source regions and sediment properties via fingerprinting analyses.The Isábena catchment (445 km²) is located in the Southern Central Pyrenees ranging from 450 m to 2,720 m in elevation, together with a pronounced topography this leads to distinct temperature and precipitation gradients. The Isábena river shows marked discharge variations and high sediment yields causing severe siltation problems in the downstream Barasona reservoir. Main sediment source are badland areas located on Eocene marls that are well connected to the river network. The dataset features a wide set of parameters in a high spatial and temporal resolution suitable for advanced process understanding of water and sediment fluxes, their origin and connectivity, sediment budgeting and for evaluating and further developing hydro-sedimentological models in Mediterranean meso-scale mountainous catchments.The data have been published with the CUAHSI Water Data Center and is structured according to its guidelines (.csv format). For more detailed information please read the user guide on cloud publications with the CUAHSI Water Dater Center or the ODM guide for uploading data using CUAHSI´s ODM uploader added to the folder CUAHSI_ODM-Guide.zip. The database can be found in the HISCENTRAL catalogue (http://hiscentral.cuahsi.org/pub_network.aspx?n=5622). It is directly accessible via the API (http://hydroportal.cuahsi.org/isabena/cuahsi_1_1.asmx?WSDL) or in zipped archives at this DOI Landing Page (http://doi.org/10.5880/fidgeo.2018.011). For more detailed information, please read the user guide on cloud publications with the CUAHSI Water Dater Center (UserGuide.pdf) or the ODM guide for uploading data using CUAHSI´s ODM uploader in the ODM_Guide.zip archive.The data are available in four thematic zip folders:(1) hydro (hydrological data): water stage (manual readings and automatically recorded), river discharge (meterings and converted from stage)(2) meta (metadata) with the description of the different datafiles relevant for this dataset according to the CUAHSI HIS Standards(3) meteo (meteorological data): rainfall, temperature, radiation, humidity(4) sediment (sedimentological data): turbidity, suspended sediment concentration (from samples and from turbidity), sediment and soil reflectance spectraand are complemented by:(5) CUAHSI_ODM-Guide: User Guide, CUAHSI´s ODM uploader in Excel (.xlsx) and Open Office (.ods) formats(6) scripts: auxiliary R-script templates for data access, data analysis and visualisation(7) supplementary materials: stage-discharge- and turbidimeter rating curves
    Keywords: rainfall ; discharge ; suspended sediment concentration ; soil spectroscopy ; fingerprint properties ; meso-scale ; EARTH SCIENCE 〉 ATMOSPHERE 〉 PRECIPITATION ; EARTH SCIENCE 〉 SPECTRAL/ENGINEERING 〉 INFRARED WAVELENGTHS 〉 REFLECTED INFRARED ; EARTH SCIENCE 〉 TERRESTRIAL HYDROSPHERE 〉 WATER QUALITY/WATER CHEMISTRY 〉 TURBIDITY ; EARTH SCIENCE 〉 TERRESTRIAL HYDROSPHERE 〉 SURFACE WATER 〉 STAGE HEIGHT ; EARTH SCIENCE 〉 TERRESTRIAL HYDROSPHERE 〉 SURFACE WATER 〉 DISCHARGE/FLOW ; EARTH SCIENCE 〉 LAND SURFACE 〉 EROSION/SEDIMENTATION 〉 SEDIMENT TRANSPORT ; EARTH SCIENCE 〉 TERRESTRIAL HYDROSPHERE 〉 SURFACE WATER 〉 RIVERS/STREAMS
    Language: English
    Type: Dataset , Dataset
    Format: 183324730 Bytes
    Format: 10 Files
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    DATA GFZ
  • 4
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    A Novel High-Resolution Gridded Precipitation Dataset for Peruvian and Ecuadorian Watersheds: Development and Hydrological Evaluation (2022)
    In:  Journal of Hydrometeorology
    Details
    Publication Date: 2022-07-13
    Description: A novel approach for estimating precipitation patterns is developed here and applied to generate a new hydrologically corrected daily precipitation dataset, called RAIN4PE (for ‘Rain for Peru and Ecuador’), at 0.1° spatial resolution for the period 1981-2015 covering Peru and Ecuador. It is based on the application of a) the random forest method to merge multi-source precipitation estimates (gauge, satellite, and reanalysis) with terrain elevation, and b) observed and modeled streamflow data to firstly detect biases and secondly further adjust gridded precipitation by inversely applying the simulated results of the eco-hydrological model SWAT (Soil and Water Assessment Tool). Hydrological results using RAIN4PE as input for the Peruvian and Ecuadorian catchments were compared against the ones when feeding other uncorrected (CHIRP and ERA5) and gauge-corrected (CHIRPS, MSWEP, and PISCO) precipitation datasets into the model. For that, SWAT was calibrated and validated at 72 river sections for each dataset using a range of performance metrics, including hydrograph goodness of fit and flow duration curve signatures. Results showed that gauge-corrected precipitation datasets outperformed uncorrected ones for streamflow simulation. However, CHIRPS, MSWEP, and PISCO showed limitations for streamflow simulation in several catchments draining into the Paċific Ocean and the Amazon River. RAIN4PE provided the best overall performance for streamflow simulation, including flow variability (low-, high- and peak-flows) and water budget closure. The overall good performance of RAIN4PE as input for hydrological modeling provides a valuable criterion of its applicability for robust countrywide hydrometeorological applications, including hydroclimatic extremes such as droughts and floods.
    Language: English
    Type: info:eu-repo/semantics/article
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  • 5
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    High-resolution climate projection dataset based on CMIP6 for Peru and Ecuador: BASD-CMIP6-PE (2024)
    In:  Scientific Data
    Details
    Publication Date: 2024-01-09
    Description: Here, we present BASD-CMIP6-PE, a high-resolution (1d, 10 km) climate dataset for Peru and Ecuador based on the bias-adjusted and statistically downscaled CMIP6 climate projections of 10 GCMs. This dataset includes both historical simulations (1850–2014) and future projections (2015–2100) for precipitation and minimum, mean, and maximum temperature under three Shared Socioeconomic Pathways (SSP1-2.6, SSP3-7.0, and SSP5-8.5). The BASD-CMIP6-PE climate data were generated using the trend-preserving Bias Adjustment and Statistical Downscaling (BASD) method. The BASD performance was evaluated using observational data and through hydrological modeling across Peruvian and Ecuadorian river basins in the historical period. Results demonstrated that BASD significantly reduced biases between CMIP6-GCM simulations and observational data, enhancing long-term statistical representations, including mean and extreme values, and seasonal patterns. Furthermore, the hydrological evaluation highlighted the appropriateness of adjusted GCM simulations for simulating streamflow, including mean, low, and high flows. These findings underscore the reliability of BASD-CMIP6-PE in assessing regional climate change impacts on agriculture, water resources, and hydrological extremes.
    Language: English
    Type: info:eu-repo/semantics/article
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  • 6
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    BASD-CMIP6-PE: bias-adjusted and statistically downscaled CMIP6 projections over Peru and Ecuador (2023)
    GFZ Data Services
    Details
    Publication Date: 2024-01-24
    Description: The new climate dataset, BASD-CMIP6-PE, for Peru and Ecuador is based on bias-adjusted and statistically downscaled CMIP6 climate projections from 10 GCMs. It addresses the need for reliable high-resolution (1d, 10km) climate data covering Peru and Ecuador. This dataset includes historical simulations (1850-2014) and future projections (2015-2100) for precipitation and minimum, mean, and maximum temperature under three Shared Socioeconomic Pathways (SSPs:SSP1-2.6, SSP3-7.0, and SSP5-8.5). The BASD-CMIP6-PE climate data were generated using the trend-preserving Bias Adjustment and Statistical Downscaling (BASD) method (Lange, 2019, 2021) and data from regional observational datasets such as RAIN4PE (Fernandez-Palomino et al., 2021a,b) for precipitation and PISCO-temperature (Huerta et al., 2018) for temperatures as reference data. The reliability of the BASD-CMIP6-PE was evaluated using observational data and through hydrological modeling across Peruvian and Ecuadorian river basins in the historical period. The evaluation demonstrated the dataset’s reliability in describing spatial patterns of atmospheric variables and streamflow simulation, including mean, low, and high flows. This suggests the usefulness of the new dataset for assessing regional climate change impacts on agriculture, water resources, and hydrological extremes. The BASD-CMIP6-PE data are available for the domain covering Peru and Ecuador, located between 19°S and 2°N and 82°W to 67°W, with a spatial resolution of 0.1° and a daily temporal resolution. The unit for precipitation is millimeters (mm), and for temperature, it is degrees Celsius (°C). The BASD-CMIP6-PE dataset is organized within a "daily" folder, denoting its availability at a 1 daily temporal resolution. Within this directory, four subfolders are present: "historical" containing historical data, "ssp126" for SSP1-2.6, "ssp370" for SSP3-7.0, and "ssp585" for SSP5-8.5. Each of these subfolders further includes ten distinct folders, corresponding to different GCMs: CanESM5, IPSL–CM6A–LR, UKESM1–0–LL, CNRM–CM6–1, CNRM–ESM2–1, MIROC6, GFDL–ESM4, MRI–ESM2–0, MPI–ESM1–2–HR, and EC–Earth3. These folders store the data in the NetCDF format arranged by model, model member, experiment, variable, temporal resolution, and subset period, resulting in file names like "canesm5_r1i1p1f1_ssp126_pr_daily_2015_2020.nc". For a detailed description of the BASD-CMIP6-PE development and evaluation, readers are advised to read Fernandez-Palomino et al. (2023), for which this dataset is supplementary material.
    Language: English
    Type: info:eu-repo/semantics/workingPaper
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  • 7
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    Forensic hydro-meteorological analysis of an extreme flash flood: The 2016-05-29 event in Braunsbach, SW Germany (2018)
    In:  Science of the Total Environment
    Details
    Publication Date: 2020-02-12
    Description: The flash-flood in Braunsbach in the north-eastern part of Baden-Wuerttemberg/Germany was a particularly strong and concise event which took place during the floods in southern Germany at the end of May/early June 2016. This article presents a detailed analysis of the hydro-meteorological forcing and the hydrological consequences of this event. A specific approach, the “forensic hydrological analysis” was followed in order to include and combine retrospectively a variety of data from different disciplines. Such an approach investigates the origins, mechanisms and course of such natural events if possible in a “near real time” mode, in order to follow the most recent traces of the event. The results show that it was a very rare rainfall event with extreme intensities which, in combination with catchment properties, led to extreme runoff plus severe geomorphological hazards, i.e. great debris flows, which together resulted in immense damage in this small rural town Braunsbach. It was definitely a record-breaking event and greatly exceeded existing design guidelines for extreme flood discharge for this region, i.e. by a factor of about 10. Being such a rare or even unique event, it is not reliably feasible to put it into a crisp probabilistic context. However, one can conclude that a return period clearly above 100 years can be assigned for all event components: rainfall, peak discharge and sediment transport. Due to the complex and interacting processes, no single flood cause or reason for the very high damage can be identified, since only the interplay and the cascading characteristics of those led to such an event. The roles of different human activities on the origin and/or intensification of such an extreme event are finally discussed.
    Language: English
    Type: info:eu-repo/semantics/article
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  • 8
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    Evaluation of medium-range runoff forecasts for a 50 km² watershed (2012)
    In:  Journal of Hydrology
    Details
    Publication Date: 2020-02-12
    Description: We generated medium-range forecasts of runoff for a 50 km2 headwater catchment upstream of a reservoir using numerical weather predictions (NWPs) of the past as input to an operational hydrological model. NWP data originating from different sources were tested. For a period of 8.5 years, we computed daily forecasts with a lead time of +120 h based on an empirically downscaled version of the ECMWF’s ensemble prediction system. For the last 3.5 years of the test period, we also tried the deterministic COSMO-EU forecast disseminated by the German Weather Service for lead times of up to +72 h. Common measures of skill indicate superiority of the ensemble runoff forecast over single-value forecasts for longer lead times. However, regardless of which NWP data were being used, the probability of event detection (POD) was found to be generally lower than 50%. In many cases, values in the range of 20–30% were obtained. At the same time, the false alarms ratio (FAR) was often found to be considerably high. The observed uncertainties in the hydrological forecasts were shown to originate from both the insufficient quality of precipitation forecasts as well as deficiencies in hydrological modeling and quantitative precipitation estimation. With respect to the anticipatory control of reservoirs in the studied catchment, the value of the tested runoff forecasts appears to be limited. This is due to the unfavorably low POD/FAR ratio in conjunction with a high cost–loss ratio. However, our results indicate that, in many cases, major runoff events related to snow melt can be successfully predicted as early as 4–5 days in advance.
    Language: English
    Type: info:eu-repo/semantics/article
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  • 9
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    Soil Moisture Estimation using a Multi-angular Modified Three Component Polarimetric Decomposition (2009)
    In:  Proceedings of the IEEE Geoscience and Remote Sensing Symposium (IGARSS)
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    Publication Date: 2020-02-12
    Language: English
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  • 10
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    Analysing spatio-temporal land degradation dynamics in dry rangelands using landscape metrics and satellite time series data (2017)
    In:  Geophysical Research Abstracts Vol. 19, EGU2017-10014
    Details
    Publication Date: 2020-02-12
    Description: Many of the dry rangelands of Southern Europe are threatened by land degradation. This process not only reduces the land’s ecological functioning, but also its capacity to provide ecosystem goods and services for local land users. In rangelands, one important aspect is vegetation degradation, which reduces the land’s capacity to support livestock. Thus, there is an urgent need to understand the complex dynamics and drivers of land degradation. In the past, both have been difficult to study due to the extensive spatial and temporal scales involved. In the last decade, a large number of remotely sensed imageries has become available for free, which enables a new approach to this topic. The aim of this research is to study land degradation as a multidimensional process incorporating its spatial and temporal components. We developed a methodological approach that makes use of long-term satellite Landsat data. Here, we use imagery of a typical degraded Mediterranean rangeland in Southern Cyprus (Randi Forest) for the years 1998-2015. We have chosen the NDVI as a proxy for vegetation greenness and applied different spatial landscape metrics to calculate changes in vegetation patterns over time. Further, we applied a time-series based approach (BFAST) on selected pixels, to look for sudden changes and trends in the vegetation dynamics. The results promoted our knowledge on how land degradation dynamics in Mediterranean rangelands can be captured through spatio-temporal vegetation dynamics and allowed us to select the most suitable metrics for further analysis. In the long-term, we aim at using Landsat satellite data covering 30 years. To gain a functional understanding of land degradation, we want to overlay our results from the remotely sensed data with results of an eco-hydrological model (SWAT).
    Language: English
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