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  • 1
    Publication Date: 2023-07-19
    Description: Precipitation extremes will increase in a warming climate, but the response of flood magnitudes to heavier precipitation events is less clear. Historically, there is little evidence for systematic increases in flood magnitude despite observed increases in precipitation extremes. Here we investigate how flood magnitudes change in response to warming, using a large initial-condition ensemble of simulations with a single climate model, coupled to a hydrological model. The model chain was applied to historical (1961–2000) and warmer future (2060–2099) climate conditions for 78 watersheds in hydrological Bavaria, a region comprising the headwater catchments of the Inn, Danube and Main River, thus representing an area of expressed hydrological heterogeneity. For the majority of the catchments, we identify a ‘return interval threshold’ in the relationship between precipitation and flood increases: at return intervals above this threshold, further increases in extreme precipitation frequency and magnitude clearly yield increased flood magnitudes; below the threshold, flood magnitude is modulated by land surface processes. We suggest that this threshold behaviour can reconcile climatological and hydrological perspectives on changing flood risk in a warming climate.
    Description: The response of flood risk in Bavaria, Germany to increases in rainfall extremes in a warming climate is modulated by land surface processes below a precipitation threshold, but not above, suggest ensemble simulations with a hydrological model.
    Description: Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (Swiss National Science Foundation) https://doi.org/10.13039/501100001711
    Description: National Science Foundation (NSF) https://doi.org/10.13039/100000001
    Description: Funder: Bavarian State Ministry for the Environment and Consumer Protection Reference Number: 81-0270-024570/2015
    Description: http://www.hydroshare.org/resource/945d7b4f61d145d789eb090f0bf51cb5
    Keywords: ddc:551.46 ; Atmospheric science ; Climate-change impacts ; Hydrology ; Natural hazards
    Language: English
    Type: doc-type:article
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  • 2
    Publication Date: 2021-06-27
    Description: Predictions of floods, droughts, and fast drought‐flood transitions are required at different time scales to develop management strategies targeted at minimizing negative societal and economic impacts. Forecasts at daily and seasonal scale are vital for early warning, estimation of event frequency for hydraulic design, and long‐term projections for developing adaptation strategies to future conditions. All three types of predictions—forecasts, frequency estimates, and projections—typically treat droughts and floods independently, even though both types of extremes can be studied using related approaches and have similar challenges. In this review, we (a) identify challenges common to drought and flood prediction and their joint assessment and (b) discuss tractable approaches to tackle these challenges. We group challenges related to flood and drought prediction into four interrelated categories: data, process understanding, modeling and prediction, and human–water interactions. Data‐related challenges include data availability and event definition. Process‐related challenges include the multivariate and spatial characteristics of extremes, non‐stationarities, and future changes in extremes. Modeling challenges arise in frequency analysis, stochastic, hydrological, earth system, and hydraulic modeling. Challenges with respect to human–water interactions lie in establishing links to impacts, representing human–water interactions, and science communication. We discuss potential ways of tackling these challenges including exploiting new data sources, studying droughts and floods in a joint framework, studying societal influences and compounding drivers, developing continuous stochastic models or non‐stationary models, and obtaining stakeholder feedback. Tackling one or several of these challenges will improve flood and drought predictions and help to minimize the negative impacts of extreme events. This article is categorized under: Science of Water 〉 Science of Water
    Description: Drought and flood modeling and prediction challenges related to (a) data, (b) process understanding, (c) modeling and prediction, and (d) human–water interactions. image
    Description: Swiss National Science Foundation http://dx.doi.org/10.13039/501100001711
    Keywords: 551.48 ; droughts ; floods ; forecasting ; hydrologic extremes ; prediction
    Type: article
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  • 3
    Publication Date: 2022-03-28
    Description: Hydrologic extremes such as floods and droughts are often spatially related, which increases management challenges and potential impacts. However, these spatial relationships in high and low flows are often overlooked in risk assessments and we know little about their differences and origins. Here, we ask how spatial relationships of both types of hydrologic extremes and their potential hydro‐meteorological drivers differ and vary by season. We propose lagged upper‐ and lower‐tail correlation as a measure of extremal dependence for temporally ordered events to build complex networks of high and low flows. We compare complex networks of overall, low and high flows, determine hydro‐meteorological drivers of these networks, and map past changes in spatial relationships using a large‐sample data set in Central Europe. Our network comparison shows that low flows are correlated more strongly and over longer distances than high flows and high‐ and low‐flow networks are strongest in spring and weakest in summer. Our driver analysis shows that high‐flow dependence is most strongly governed by precipitation in winter and evapotranspiration in summer while low‐flow dependence is most strongly governed by snowmelt in winter and evapotranspiration in fall. Finally, our change analysis shows that changes in connectedness (i.e., the number of catchments a catchments shows strong flow correlations with) vary spatially and are mostly positive for high flows. We conclude that spatial flow correlations are considerable for both high and particularly low flows as a result of a combination of spatially related hydro‐meteorological drivers whose importance varies by extreme type and season.
    Description: Plain Language Summary: Droughts and floods can happen in multiple locations at once with important implications for flood and drought risk. Still, the spatial relationships between events and the reasons for them are not well studied. Here, we therefore ask how spatial relationships of both types of extremes and their meteorological drivers differ and vary by season. We compare networks of overall, low and high flows, determine hydro‐meteorological drivers of these networks, and map past changes in flow dependence using a large‐sample data set in Central Europe. Our network comparison shows that low flows are correlated more strongly and over longer distances than high flows and both high‐ and low‐flow networks are strongest in spring and weakest in summer. Our driver analysis shows that high‐flow dependence is governed by precipitation dependence in winter and evapotranspiration dependence in summer and fall while low flow dependence is most strongly governed by snowmelt in winter and evapotranspiration and snowmelt in fall. Finally, our change analysis shows that changes in connectedness (i.e., the number of catchments a catchments shows strong flow correlations with) vary spatially and are mostly positive for high flows. We conclude that spatial flow correlation is considerable for both high and particularly low flows highlighting the need to consider it in risk assessments.
    Description: Key Points: We propose and use a tail dependence measure to map and compare complex networks of high and low flows in Central Europe at a seasonal scale. Low flows are related more strongly and over longer distances than high flows and relationships are strong in spring and weak in summer. Seasonal flow correlation is shaped by spatial dependence in drivers with varying importance of precipitation, evaporation, and snowmelt.
    Description: Swiss National Science Foundation
    Keywords: ddc:551.57 ; ddc:551.48
    Language: English
    Type: doc-type:article
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  • 4
    Publication Date: 2023-01-12
    Description: Hydrological extreme events are generated by different sequences of hydrometeorological drivers, the importance of which may vary within the sample of drought events. Here, we investigate how the importance of different hydrometeorological driver sequences varies by event magnitude using a large sample of catchments in Europe. To do so, we develop an automated classification scheme for streamflow drought events. The classification scheme standardizes a previous qualitative drought typology and assigns events to one of eight drought event types—each characterized by a set of single or compounding drivers—using information about seasonality, precipitation deficits, and snow availability. The objective event classification reveals how drought drivers vary not just in space and by season, but also with event magnitude. Specifically, we show that (a) rainfall deficit droughts and cold snow season droughts are the dominant drought event type in Western Europe and Eastern and Northern Europe, respectively; (b) rainfall deficit and cold snow season droughts are important from autumn to spring while snowmelt and wet‐to‐dry season droughts are important in summer; and (c) moderate droughts are mainly driven by rainfall deficits while severe events are mainly driven by snowmelt deficits in colder climates and by streamflow deficits transitioning from the wet to the dry season in warmer climates. These differences in sequences of drought generation mechanisms for severe and moderate events suggest that future changes in hydrometeorological drivers may affect moderate and severe events differently.
    Description: Key Points: We develop a standardized and objective classification scheme for streamflow droughts using hydroclimatic information. The most severe drought events are governed by other processes than moderate events. Moderate droughts are dominated by rainfall deficits and severe droughts by snowmelt deficits or prolonged rainfall deficit droughts.
    Description: Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659
    Description: EC/H2020/PRIORITY 'Excellent science'/H2020 European Research Council http://dx.doi.org/10.13039/100010663
    Description: https://www.bafg.de/GRDC/EN/02_srvcs/21_tmsrs/riverdischarge_node.html
    Description: https://doi.pangaea.de/10.1594/PANGAEA.887470
    Description: https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-land?tab=overview
    Description: http://www.hydroshare.org/resource/77114d4dfdfd4dd39e0e1d99165f27b3
    Keywords: ddc:551.6 ; drought types ; drought generation ; extremes ; typology ; classification ; streamflow
    Language: English
    Type: doc-type:article
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