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Integrating real-time subsurface hydrologic monitoring with empirical rainfall thresholds to improve landslide early warning

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Abstract

Early warning for rainfall-induced shallow landsliding can help reduce fatalities and economic losses. Although these commonly occurring landslides are typically triggered by subsurface hydrological processes, most early warning criteria rely exclusively on empirical rainfall thresholds and other indirect proxies for subsurface wetness. We explore the utility of explicitly accounting for antecedent wetness by integrating real-time subsurface hydrologic measurements into landslide early warning criteria. Our efforts build on previous progress with rainfall thresholds, monitoring, and numerical modeling along the landslide-prone railway corridor between Everett and Seattle, Washington, USA. We propose a modification to a previously established recent versus antecedent (RA) cumulative rainfall thresholds by replacing the antecedent 15-day rainfall component with an average saturation observed over the same timeframe. We calculate this antecedent saturation with real-time telemetered measurements from five volumetric water content probes installed in the shallow subsurface within a steep vegetated hillslope. Our hybrid rainfall versus saturation (RS) threshold still relies on the same recent 3-day rainfall component as the existing RA thresholds, to facilitate ready integration with quantitative precipitation forecasts. During the 2015–2017 monitoring period, this RS hybrid approach has an increase of true positives and a decrease of false positives and false negatives relative to the previous RA rainfall-only thresholds. We also demonstrate that alternative hybrid threshold formats could be even more accurate, which suggests that further development and testing during future landslide seasons is needed. The positive results confirm that accounting for antecedent wetness conditions with direct subsurface hydrologic measurements can improve thresholds for alert systems and early warning of rainfall-induced shallow landsliding.

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Acknowledgements

This work was funded in part through a technical assistance agreement between Sound Transit and the U.S. Geological Survey (USGS) Landslides Hazards Program. All rainfall and hydrologic monitoring data are available through the USGS ScienceBase catalog: https://doi.org/10.5066/F7NZ85WX (Smith et al. 2017b). Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

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  1. U.S. Geological Survey, Geologic Hazards Science Center, PO Box 25046, Mail Stop 966, Denver, CO, 80225, USA

    Benjamin B. Mirus, Rachel E. Becker, Rex L. Baum & Joel B. Smith

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  1. Benjamin B. Mirus
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Correspondence to Benjamin B. Mirus.

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Mirus, B.B., Becker, R.E., Baum, R.L. et al. Integrating real-time subsurface hydrologic monitoring with empirical rainfall thresholds to improve landslide early warning. Landslides 15, 1909–1919 (2018). https://doi.org/10.1007/s10346-018-0995-z

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