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Rick Wooten

Publications and source records attributed to Rick Wooten.

2 recordsLinked to original sources
USGS2019

Bayesian analysis of the impact of rainfall data product on simulated slope failure for North Carolina locations

In the past decades, many different approaches have been developed in the literature to quantify the load-carrying capacity and geotechnical stability (or the Factor of Safety, F_s) of variably saturated hillslopes. Much of this work has focused on a deterministic characterization of hillslope stability. Yet, simulated F_s values are subject to considerable uncertainty due to our inability to characterize accurately the soil mantle’s properties (hydraulic, geotechnical and geomorphologic) and spatiotemporal variability of the moisture content of the hillslope interior. This is particularly true at larger spatial scales. Thus, uncertainty-incorporating analyses of physically based models of rain-induced landslides are rare in the literature. Such landslide modeling is typically conducted at the hillslope scale using gauge-based rainfall forcing data with rather poor spatiotemporal coverage. For regional landslide modeling, the specific advantages and/or disadvantages of gauge-only, radar-merged and satellite-based rainfall products are not clearly established. Here, we compare and evaluate the performance of the Transient Rainfall Infiltration and Grid-based Regional Slope-stability analysis (TRIGRS) model for three different rainfall products using 112 observed landslides in the period between 2004 and 2011 from the North Carolina Geological Survey database. Our study includes the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis Version 7 (TMPA V7), the North American Land Data Assimilation System Phase 2 (NLDAS-2) analysis, and the reference ‘truth’ Stage IV precipitation. TRIGRS model performance was rather inferior with the use of literature values of the geotechnical parameters and soil hydraulic properties from ROSETTA using soil textural and bulk density data from SSURGO (Soil Survey Geographic database). The performance of TRIGRS improved considerably after Bayesian estimation of the parameters with the DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm using Stage IV precipitation data. Hereto, we use a likelihood function that combines binary slope failure information from landslide event and ‘null’ periods using multivariate frequency distribution-based metrics such as the False Discovery and False Omission Rates. Our results demonstrate that the Stage IV-inferred TRIGRS parameter distributions generalize well to TMPA and NLDAS-2 precipitation data, particularly at sites with considerably larger TMPA and NLDAS-2 rainfall amounts during landslide events than null periods. TRIGRS model performance is then rather similar for all three rainfall products. At higher elevations, however, the TMPA and NLDAS-2 precipitation volumes are insufficient and their performance with the Stage IV-derived parameter distributions indicate their inability to accurately characterize hillslope stability.

North Carolina↗
USGS2019

Conceptual framework for assessing disturbance impacts on debris-flow initiation thresholds across hydroclimatic settings

The destructive and deadly nature of debris flows has motivated research into empirical rainfall thresholds to provide situational awareness, inform early warning systems, and reduce loss of life and property. Disturbances such as wildfire and land-cover change can influence the hydrological processes of infiltration and runoff generation; in steep terrain this typically lowers empirical thresholds for debris-flow initiation. However, disturbance impacts, and the post-disturbance recovery may differ, depending on the severity, nature, extent, and duration of the disturbance, as well as on the prevailing hydroclimatic conditions. Thus, it can be difficult to predict impacts on debris-flows hazards in regions where historically such disturbances have been less frequent or severe. Given the increasing magnitude and incidence of wildfires, among other disturbances, we seek to develop a conceptual framework for assessing their impacts on debris-flow hazards across geographic regions. We characterize the severity of disturbances in terms of changes from undisturbed hydrologic functioning, including hillslope drainage and available unsaturated storage capacity, which can have contrasting influences on debris-flow initiation mechanisms in different hydroclimatic settings. We compare the timescale of disturbance-recovery cycles relative to the return period of threshold exceeding storms to describe vulnerability to post-disturbance debris flows. Similarly, we quantify resilience by comparing the timescales of disturbance-recovery cycles with those of disturbance-recurrence intervals. We illustrate the utility of these concepts using information from U.S. Geological Survey landslide monitoring sites in burned and unburned areas across the United States. Increasing severity of disturbance may influence both recovery timescales and lower the return period for debris-flow inducing storms, thus increasing the vulnerability to disturbance-related hazards while also decreasing system resilience. The proposed conceptual framework can inform future data acquisition and model development to improve debris-flow initiation thresholds in areas experiencing increasingly frequent, severe, and even overlapping landscape disturbances.

Conference Paper↗