Seismic Monitoring of Post-wildfire Debris Flows Following the 2019 Museum Fire, Arizona

In the humid tropics, forest conversion and climate change threaten the hydrological function and stationarity of watersheds, particularly in steep terrain. As climate change intensifies, shifting precipitation patterns and expanding agricultural and pastoral land use may effectively reduce the resilience of headwater catchments. Compounding this problem is the limited long-term monitoring in developing countries for planning in an uncertain future. In this study, we asked which change, climate or land use, more greatly affects stream discharge in humid tropical mountain watersheds? To answer this question, we used the process-based, spatially distributed Soil Moisture Routing model. After first evaluating model performance (Ns = 0.73), we conducted a global sensitivity analysis to identify the model parameters that most strongly influence simulated watershed discharge. In particular, peak flows are most influenced by input model parameters that represent shallow subsurface soil pathways and saturation-excess runoff while low flows are most sensitive to macropore hydraulic conductivity, soil depth and porosity parameters. We then simulated a range of land use and climate scenarios in three mountain watersheds of central Costa Rica. Our results show that deforestation influences streamflow more than altered precipitation and temperature patterns through changes in first-order hydrologic hillslope processes. However, forest conversion coupled with intensifying precipitation events amplifies hydrological extremes, reducing the hydrological resilience to predicted climate shifts in mountain watersheds of the humid tropics. This finding suggests that reforestation can help mitigate the effects of climate change on streamflow dynamics in the tropics including impacts to water availability, flood pulses, channel geomorphology and aquatic habitat associated with altered flow regimes.

In the humid tropics, forest conversion and climate change threaten the hydrological function and stationarity of watersheds, particularly in steep terrain. As climate change intensifies, shifting precipitation patterns and expanding agricultural and pastoral land use may effectively reduce the resilience of headwater catchments. Compounding this problem is the limited long-term monitoring in developing countries for planning in an uncertain future. In this paper, we asked which change, climate or land use, more greatly affects stream discharge in humid tropical mountain watersheds? To answer this question, we used the process-based, spatially distributed Soil Moisture Routing model. After first evaluating model performance (Ns = 0.73), we conducted a global sensitivity analysis to identify the model parameters that most strongly influence simulated watershed discharge. In particular, peak flows are most influenced by input model parameters that represent baseflow and shallow subsurface soil pathways while low flows are most sensitive to antecedent moisture, macropore hydraulic conductivity, soil depth and porosity parameters. We then simulated a range of land use and climate scenarios in three mountain watersheds of central Costa Rica. Our results show that deforestation influences streamflow more than altered precipitation and temperature patterns through changes in first-order hydrologic hillslope processes. However, forest conversion coupled with intensifying precipitation events amplifies hydrological extremes, reducing the hydrological resilience to predicted climate shifts in mountain watersheds of the humid tropics. This finding suggests that reforestation can help mitigate the effects of climate change on streamflow dynamics in the tropics including impacts to water availability, flood pulses, channel geomorphology and aquatic habitat associated with altered flow regimes.

The 2019 Museum Fire burned in a mountainous region near the city of Flagstaff, AZ, USA. Due to the high risk of post-wildfire debris flows and flooding entering the city, we deployed a network of seismometers within the burn area and downstream drainages to examine the efficacy of seismic monitoring for post-fire flows. Seismic instruments were deployed during the 2019, 2020, and 2021 monsoon seasons following the fire and recorded several debris flow and flood events, as well as signals associated with rainfall, lighting and wind. Signal power, frequency content, and wave polarization were measured for multiple events and compared to rain gauge records and images recorded by cameras installed in the study area. We use these data to demonstrate the efficacy of seismic recordings to (1) detect and differentiate between different energy sources, (2) estimate the timing of lightning strikes, (3) calculate rainfall intensities, and (4) determine debris flow timing, size, velocity, and location. This work confirms the validity of theoretical models for interpreting seismic signals associated with debris flows and rainfall in post-wildfire settings and demonstrates the efficacy of seismic data for identifying and characterizing debris flows.