Publication Date:
2023-10-24
Description:
Trends in flood magnitudes vary across the conterminous USA (CONUS). There have been attempts to identify what controls these regionally varying trends, but these attempts were limited to certain—for example, climatic—variables or to smaller regions, using different methods and datasets each time. Here we attribute the trends in annual maximum streamflow for 4,390 gauging stations across the CONUS in the period 1960–2010, while using a novel combination of methods and an unprecedented variety of potential controlling variables to allow large‐scale comparisons and minimize biases. Using process‐based flood classification and complex networks, we find 10 distinct clusters of catchments with similar flood behavior. We compile a set of 31 hydro‐climatological and land use variables as predictors for 10 separate Random Forest models, allowing us to find the main controls the flood magnitude trends for each cluster. By using Accumulated Local Effect plots, we can understand how these controls influence the trends in the flood magnitude. We show that hydro‐climatologic changes and land use are of similar importance for flood magnitude trends across the CONUS. Static land use variables are more important than their trends, suggesting that land use is able to attenuate (forested areas) or amplify (urbanized areas) the effects of climatic changes on flood magnitudes. For some variables, we find opposing effects in different regions, showing that flood trend controls are highly dependent on regional characteristics and that our novel approach is necessary to attribute flood magnitude trends reliably at the continental scale while maintaining sensitivity to regional controls.
Description:
Key Points:
A wide variety of controls are necessary to explain flood magnitude trends across the United States between 1960 and 2010.
Climatic changes and land cover conditions are of similar importance for flood magnitude trends at the regional scale.
Controls on flood trends can have highly nonlinear effects and can have opposing effects in different hydro‐climatological subregions.
Description:
Deutsche Forschungsgemeinschaft
http://dx.doi.org/10.13039/501100001659
Description:
USACE Water Institute
Description:
Bundesministerium für Bildung und Forschung
http://dx.doi.org/10.13039/501100002347
Description:
https://nwis.waterdata.usgs.gov/usa/nwis/peak
Description:
https://water.usgs.gov/GIS/metadata/usgswrd/XML/streamgagebasins.xml
Description:
https://psl.noaa.gov/
Description:
https://www.sciencebase.gov/catalog/item/59692a64e4b0d1f9f05fbd39
Keywords:
ddc:551.48
;
annual maximum flood
;
magnitude trends
;
drivers
;
Random Forest
;
clustering
;
climate change
Language:
English
Type:
doc-type:article
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