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Predicting floods: It's not just about rainfall

How can we better understand the looming problem of extreme flooding, as we brace ourselves for an era of escalating rainfall? It turns out that flood prediction is not just about how much it’s raining, but when and how frequently. 

A new study from the Cooperative Institute for Research in Environmental Sciences (CIRES) has shed light on this pressing topic.

The research was led by CIRES Fellow and Western Water Assessment (WWA) director, Ben Livneh, along with his fellow scientist, Kris Karnauskas. 

Focus of the study

“A mystery has emerged as to why patterns of increasing extreme rainfall have not been accompanied by similar levels of flooding, garnering growing attention given concerns over future flood risks,” wrote the researchers.

“Antecedent moisture conditions have been proposed as the missing explanatory factor. Yet, reasons for moisture variability prior to flooding remain largely unstudied.”

“Here, we evaluate the potential utility of precipitation intermittency, defined as the dry spell length prior to a flood, to explain the variability of flooding over 108 watersheds from 1950 to 2022.”

Soil moisture and flood prediction 

Together, the experts have navigated the choppy waters of soil moisture, revealing its significant role in predicting flood events. 

Soil moisture, however, is notorious for its erratic behavior. As Livneh noted, soil water is hard to predict.

The researchers needed a hero, a stand-in for soil moisture. They found one in the form of precipitation intermittency: the time gap between rainfall events. 

It seems simple – the longer the dry spell, the bigger the storm required to trigger a flood. Conversely, when the rains are more frequent, even the tiniest drizzle can escalate to a flood.

“We can actually understand changes in flood risk based on the number of days since the last rain event,” noted Livneh. “We wanted to make it straightforward because soil water is hard to predict.”

Analyzing historical rain events 

The scientists focused their lens on semi-arid and arid regions, homing in on rain rather than snow. The next piece of the puzzle: analyzing historical rain events across 108 watersheds throughout the U.S. from 1950-2022. 

The objective was to understand the correlation between wet or dry soils before heavy rain events and consequent flooding.

Tricky terrain of soil moisture

Navigating the world of soil moisture is not as simple as it may seem. Nels Bjarke is a WWA postdoctoral researcher who led the analysis for the study. 

“We don’t have comprehensive observations of soil moisture that are continuous over space or continuous through time,” said Bjarke.  

“Therefore, it can be difficult to apply some sort of predictive framework for flooding using just soil moisture because the data are sparse.”

The experts turned to precipitation as a stand-in. They found that the timing of the rain, not the quantity, held the key.

Deciphering the code of flood prediction 

The researchers developed a timescale to gauge precipitation intermittency. They broke down intermittency into segments of five days. 

Shorter breaks of ten days or less signified low intermittency, while prolonged dry spells of 20 days or more indicated high intermittency. They discovered that after long dry periods, the probability of a flood reduced by 30 percent.

The 2013 Boulder floods

The devastating floods in Boulder in 2013 serve as an all-too-real example. Seven days of relentless rain nearly doubled the previous rainfall record. The event displaced hundreds and caused $2 billion in property damage, according to NOAA.

The researchers noted that this study can significantly aid forecasters and emergency managers in anticipating flood risks

Since precipitation data is widely available, it can act as a proxy for soil moisture, enabling more accurate flood predictions.

“As we enter the era of big data, we can benefit from simple proxies like the dry-spell length as a way to more intuitively understand extreme events,” said Livneh.

The study is published in the journal Science of the Total Environment.


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