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Use of WRF-Hydro to identify landslide-susceptible areas at regional scales

Video Transcript
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Detailed Description

Landslide-triggering weather systems often operate on expansive spatial scales, causing widespread landsliding activity. Diverse landslide-conditioning factors, such as wildfires, antecedent soil moisture, and snowpack, within these weather systems' extensive footprints, along with complex dynamic interactions, make regional landslide susceptibility prediction increasingly challenging and in need of multidisciplinary approaches. 

Here, I argue that regional hydrometeorology, which integrates atmospheric, hydrologic, and geomorphic processes, is key to advancing large-scale landslide susceptibility prediction. This presentation introduces a methodological framework for identifying landslide-prone areas at regional scales using physics-based hydrological simulations from WRF-Hydro. 

It begins by demonstrating WRF-Hydro's ability to simulate landslide-relevant variables, such as soil moisture and streamflow, over a regional domain in California. Next, it presents a case study on numerous postfire debris flows triggered by an atmospheric river along the central Californian coast. Lastly, a case study on widespread landsliding activity caused by the parade of nine atmospheric rivers during the 2022-2023 winter season in California will be presented.

Details

Length:
00:55:42

Sources/Usage

Public Domain.

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