California's Central Valley, a vital agricultural area and home to over 1.3 million people, faces significant challenges with winter flooding. A new study aims to address these issues by providing detailed insights into the extent and location of such floods, which are difficult to map due to cloud cover obscuring satellite views.
The research, published on June 4 in the Journal of Flood Risk Management, analyzed two decades of satellite imagery. It found that December through February pose the highest flood risks, particularly during atmospheric river events when heavy rains saturate soils. The study also highlights areas where floodwaters fail to penetrate soils and suggests ways to use this water for recharging depleted groundwater aquifers.
Christine Albano from DRI, the lead author of the study, explained: "We know that atmospheric rivers and winter precipitation are big drivers of flooding... By using daily MODIS imagery, we increase the odds of capturing a glimpse of the land surface."
The research combined satellite data with precipitation and soil moisture information from upstream regions. This approach helped distinguish between rainfall-induced flooding and intentional water management practices like rice field flooding.
Parts of the Central Valley are sinking rapidly due to groundwater extraction. The study's maps pinpoint areas where floodwaters could be redirected or where compacted soils might be tilled for better permeability.
Melissa Rohde, a co-author of the study, stated: "We now have the methods and information we need to support ongoing water management efforts... This is increasingly important as atmospheric river events intensify under a warming climate."
Despite its benefits, MODIS imagery has limitations in urban areas due to its coarser resolution. It also offers only 20 years of data compared to LANDSAT's 50+ years.
Albano noted: "We weren’t able to visualize some of the biggest floods... But our maps offer a view of where higher frequency floods are occurring."
The methods used in this research can be applied elsewhere in the U.S. Chris Soulard from USGS highlighted future possibilities with newer satellites like Sentinel for more comprehensive mapping.
The interactive maps developed from this study provide various ways to view data on surface water classifications and probabilities based on monthly precipitation amounts.
For further details, refer to "Assessing causes and consequences of winter surface water dynamics in California’s Central Valley using satellite remote sensing" available at https://doi.org/10.1111/jfr3.70080
Authors include Christine Albano (DRI), Christopher E. Soulard (USGS), Blake Minor (DRI), Jessica Walker (USGS), Britt W. Smith (USGS), Eric K. Waller (USGS), Michael D. Bartles (USACE), Thomas W. Corringham (UCSD), Anthony T. O’Geen (UC Davis), Melissa M. Rohde (Rohde Environmental Consulting/SUNY), Anne M. Wein (USGS).