Hydrogeology seminars

The leaky barrel hillside hydrology metaphor—a straightforward “water in – water out” linear reservoir idealization originally applied to landslide studies more than 30 years ago by USGS scientists Ray Wilson and Gerry Wieczorek—remains useful despite (or maybe because of) its age and simplicity, especially for regional hazard forecasting applications potentially covering exceptionally large areas. The presentation will include a contextual overview of hindcasting (i.e., back-calculating) vs forecasting and the value of simple models for decision support, offer a new analytical solution for finite-duration rainfall pulses applied to examples from the Santa Cruz Mountains and Ohio River Valley, propose a rational expression for the originally empirical leaky barrel drainage coefficient, show how a leaky barrel model can be integrated into a factor of safety equation in a computationally efficient probabilistic approach amenable to spatially distributed (e.g., GIS-ish) applications, and finally show how the solutions used as input debris flow runout models.

Landslides remain a major global hazard, with thousands of events each year posing significant impacts to human life, infrastructure, and ecosystems. While advanced constitutive models enable detailed slope-stability analyses at the single-hillslope scale, a critical gap persists in assessing landslide hazards at the community scale. Existing regional-scale models often struggle to balance physical rigor, predictive accuracy, and computational efficiency. They rely either on empirical approaches with limited physical basis or on mechanistic formulations that rely on major simplifying assumptions. This study presents CRISIS (Coupled Regional Rainfall-Induced and Seismic Slope Instability Simulations), a physics-based regional landslide prediction framework. It couples a pseudo-3D slope-stability formulation with a transient three-dimensional groundwater flow model. CRISIS operates in back-analysis and forward-prediction modes, integrating multi-scale topographic, geotechnical, hydraulic, and hydrological data. Back-analysis of both failed and stable slopes from prior events generates high-resolution spatial estimates of shear strength. These estimates are iteratively refined and used for forward prediction of landslide location, size, depth, and timing under future triggering events. Results reveal a strong geospatial connection between hillslope location and dominant failure mechanisms, emphasizing that landslide initiation is inherently geospatial and governed by coupled surface–subsurface processes. Application of the framework to Hurricane Maria in Puerto Rico, where over 70,000 landslides were triggered, demonstrates close agreement between predicted and observed landslide locations, sizes, and timing. The broader vision of this work is to advance regional characterization, assessment, and mitigation of cascading hazards through data-model integration.

We investigated meteorological controls on seasonal deep-seated motion of the Barry Arm landslide, a ~500 Mm³ slope instability with tsunamigenic potential in Prince William Sound, Alaska. Using ground-based synthetic aperture radar, we identified periods of deep-seated displacement, and combined airborne ice-penetrating radar with a glacier melt model driven by local meteorological data to evaluate the role of Cascade Glacier, which covers much of the area contributing groundwater to the landslide. We show that an over-deepened section of Cascade Glacier adjacent to the most active part of the landslide likely acts as a transient reservoir that routes meltwater to the landslide and that deep-seated landslide motion initiated only when modeled glacier discharge exceeded a distinct threshold.

Shallow landslides typically involving just the soil mantle constitute both a primary process driving landscape evolution and a significant geologic hazard. Theory for and empirical documentation of shallow landslides generally assumes that the elevated pore pressures that destabilize soils arise from runoff just within the soil. In many landscapes, however, it has been recognized that groundwater emerging from underlying weathered bedrock can generate destabilizing pore pressures. Here, we develop a coupled hydrologic and slope stability model that explicitly explores how a conductive bedrock weathering zone guides storm runoff and localizes shallow landslides across a watershed. Our findings suggest that first-order variations of deep CZ can provide physical explanations for variations observed in the susceptibility, magnitude, and timing of shallow landslides, and that CZ structure may be inferred from patterns and timing of landsliding.