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A new way to assess the propensity of rivers to generate extreme floods

A new way to assess the propensity of rivers to generate extreme floods
Magnitude of the flood divide as a function of its physioclimatic controls. a,b, Normalized magnitude (that is, divided by the long-term mean river discharge q¯) of the flood divide in the study dataset as a function of the hydrograph recession exponent (a) and the coefficient of variation of daily flows (b). Shaded areas span the 95% variability range of theoretical predictions and provide an estimate of their uncertainties. Gray markers display the median (squares), minimum and maximum values of the binning (horizontal bars), and 5th and 95th percentile range (vertical bars) of the observations (dots; equal number of n = 4 case studies for each bin), here used for validation. Credit: Nature Geoscience (2023). DOI: 10.1038/s41561-023-01155-w

A quartet of hydrologists and geoscientists with the Helmholtz Centre for Environmental Research-UFZ, has developed a new way to assess the propensity of rivers to generate extreme floods.

In their study, reported in the journal Nature Geoscience, Stefano Basso, Ralf Merz, Larisa Tarasova and Arianna Miniussi developed an approach based on the analysis of stream networks. Cédric David and Renato Frasson, with CITs Jet Propulsion Laboratory have published a News & Views piece in the same journal issue outlining the work done by the team in Germany.

The researchers began their work by noting that river floods are one of the more common and devastating , affecting millions of people around the world every year. They also noted that predicting risk for extreme floods in places that have not had them before is a challenging endeavor that requires a thorough understanding of the factors that can influence generation and propagation.

They point out that one such factor is spatial organization of stream networks—how water is distributed and routed across the landscape can play a vital role in the magnitude of a disaster related to a given flood.

To make better predictions, the research group proposes a new method for assessing the propensity of rivers to generate extreme floods based on an analysis of long-term hydrology records and process-based models for flood hazard assessment.

Using data from over 3,000 across Europe and the U.S., the team found that they were able to show that the structure of stream networks and types of river flow, control the advent of flood divides—discharge thresholds that mark the transition from a gradual to an abrupt increase in flood magnitude.

The researchers also found that flood divides are more likely to occur in basins with high drainage density, that also have low channel slopes, a high hydrograph recession exponent and a high variation in daily flows. Such metrics reflect the intrinsic properties of river basins that influence their ability to store and release water during flood events.

The research group concludes that extreme floods can be predicted by analyzing the ordinary discharge dynamics of rivers, without relying solely on flood records from the past. The method could improve flood risk management and aid in the development of adaptation strategies in a changing world where extreme floods are expected to become more frequent and severe.

More information: Stefano Basso, Extreme flooding controlled by stream network organization and flow regime, Nature Geoscience (2023). DOI: 10.1038/s41561-023-01155-w.

David, C.H., Frasson, Blame the river not the rain, Nature Geoscience (2023). DOI: 10.1038/s41561-023-01163-w.

Journal information: Nature Geoscience

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Citation: A new way to assess the propensity of rivers to generate extreme floods (2023, March 31) retrieved 30 May 2024 from
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