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

Introduction

This tutorial provides a step-by-step guide on using WRF-Hydro (Weather Research and Forecasting Hydrological Model) to identify landslide-susceptible areas at regional scales. By integrating hydrometeorological processes, WRF-Hydro helps predict landslide occurrences influenced by factors such as soil moisture and streamflow, especially in the context of extreme weather events like atmospheric rivers. This methodology is vital for effective land management and disaster preparedness.

Step 1: Understand WRF-Hydro Capabilities

• Familiarize yourself with the WRF-Hydro model, which simulates hydrological processes.
• Key variables to focus on include:
  • Soil moisture: Essential for assessing landslide risk.
  • Streamflow: Helps determine water movement and potential for erosion.
• Explore the model's ability to cover large regional domains, such as the state of California.

Step 2: Set Up WRF-Hydro Simulations

• Download and install WRF-Hydro following the official documentation.
• Configure the model for your specific geographic area by:
  • Defining the simulation domain: Choose a regional scope relevant to your study.
  • Inputting meteorological data: Ensure you have access to atmospheric data that can trigger landslides, like precipitation forecasts.
• Run preliminary simulations to validate the setup.

Step 3: Analyze Landslide-Triggering Weather Systems

• Review historical data on landslide occurrences in your study area.
• Identify correlations between landslide events and specific weather systems, especially post-wildfire events or atmospheric rivers.
• Use the WRF-Hydro outputs to visualize:
  • Changes in soil moisture before and after significant precipitation events.
  • Streamflow patterns that could indicate potential landslide activity.

Step 4: Conduct Case Studies

• Implement case studies to evaluate the effectiveness of WRF-Hydro in predicting landslide susceptibility:
  • Post-fire debris flows: Examine how soil conditions change after wildfires and the impact of subsequent rainfall.
    • Collect data on recent wildfires and analyze landslide occurrences.
  • Atmospheric river impacts: Focus on events like the 2022-2023 winter season in California.
    • Analyze the sequence of atmospheric rivers and their effects on regional landslides.
• Document your findings and assess the model's predictive accuracy.

Step 5: Integrate Findings into Land Management Strategies

• Share your results with local authorities and land management organizations.
• Use the insights gained from your simulations and case studies to inform:
  • Emergency response planning for landslide-prone areas.
  • Long-term land use planning and risk assessment strategies.
• Consider developing educational resources to raise awareness of landslide risks in affected communities.

Conclusion

This tutorial outlined the process of utilizing WRF-Hydro for identifying landslide-susceptible areas through a systematic approach. By understanding the model's capabilities, setting up simulations, and analyzing relevant weather systems, you can contribute to more effective landslide prediction and management strategies. As a next step, consider exploring additional resources on WRF-Hydro applications or collaborating with local agencies to implement your findings.