Coupled prediction of flood response and debris flow initiation during warm- and cold-season events in the Southern Appalachians, USA

Abstract

Abstract. Debris flows associated with rainstorms are a frequent and devastating hazard in the Southern Appalachians in the United States. Whereas warm-season events are clearly associated with heavy rainfall intensity, the same cannot be said for the cold-season events. Instead, there is a relationship between large (cumulative) rainfall events independently of season, and thus hydrometeorological regime, and debris flows. This suggests that the dynamics of subsurface hydrologic processes play an important role as a trigger mechanism, specifically through soil moisture redistribution by interflow. We further hypothesize that the transient mass fluxes associated with the temporal-spatial dynamics of interflow govern the timing of shallow landslide initiation, and subsequent debris flow mobilization. The first objective of this study is to investigate this relationship. The second objective is to assess the physical basis for a regional coupled flood prediction and debris flow warning system. For this purpose, uncalibrated model simulations of well-documented debris flows in headwater catchments of the Southern Appalachians using a 3-D surface-groundwater hydrologic model coupled with slope stability models are examined in detail. Specifically, we focus on two vulnerable headwater catchments that experience frequent debris flows, the Big Creek and the Jonathan Creek in the Upper Pigeon River Basin, North Carolina, and three distinct weather systems: an extremely heavy summertime convective storm in 2011; a persistent winter storm lasting several days; and a severe winter storm in 2009. These events were selected due to the optimal availability of rainfall observations; availability of detailed field surveys of the landslides shortly after they occurred, which can be used to evaluate model predictions; and because they are representative of events that cause major economic losses in the region. The model results substantiate that interflow is a useful prognostic of conditions necessary for the initiation of slope instability, and should therefore be considered explicitly in landslide hazard assessments. Moreover, the relationships between slope stability and interflow are strongly modulated by the topography and catchment-specific geomorphologic features that determine subsurface flow convergence zones. The three case studies demonstrate the value of coupled prediction of flood response and debris flow initiation potential in the context of developing a regional hazard warning system.

InSAR Meteorology: High‐Resolution Geodetic Data Can Increase Atmospheric Predictability

“…On the one hand, a significant fraction (30-50%) of its precipitation is associated with light rain from fog and low-level clouds (Wilson & Barros, 2014). On the other hand, this region is also often affected by strong precipitation events, often leading to flooding, debris flows, and landslides (Tao & Barros, 2014). Furthermore, these intense events can have multiple origins, including the passage of cold season synoptic storms and warm-season mesoscale convective systems, tropical depressions, and localized convection.…”

Simulating the spatio-temporal dynamics of soil erosion, deposition, and yield using a coupled sediment dynamics and 3D distributed hydrologic model

“…Notably, majority of distributed erosion-deposition models e.g., WEPP, EUROSEM etc., consider simplistic representations of vertical and lateral subsurface water flow, and often do not account for the lateral subsurface water movement, or the coupled dynamic interactions between vadose zone and the groundwater table, or the evolution of soil moisture and groundwater with evapotranspiration. Given that the detachment, transport, and deposition of soil are dominantly influenced by the velocity and volume of overland flow (Julien and Simons, 1985), which in turn may be influenced by antecedent soil moisture conditions (Legates et al, 2011;Penna et al, 2011;Jost et al, 2012;Chen et al, 2014;Hueso-Gonz alez et al, 2015), subsurface heterogeneity (Lewis et al, 2012;Ghimire et al, 2013;Orchard et al, 2013;Zimmermann et al, 2013;Niu et al, 2014;Tao and Barros, 2014), and groundwater distribution (Kumar et al, 2009;Miguez-Macho and Fan, 2012;Rosenberg et al, 2013;Safeeq et al, 2014;von Freyberg et al, 2015), it is important to consider the coupled impacts of antecedent hydrologic states (soil moisture and groundwater distribution) and subsurface hydrogeologic properties on sediment generation and yield. Failing to do so may limit the applicability of these models to a few events (Hessel et al, 2006;Mati et al, 2006;Ramsankaran et al, 2013) or to regimes where the dynamic role of antecedent conditions and subsurface heterogeneity on erosion are not large enough.…”

Geotechnical and hydrological characterization of hillslope deposits for regional landslide prediction modeling

“…In order to prepare the input data and feed the physicallybased models different approaches can be used: (1) the adoption, for each parameter, of a unique constant value for the whole study area as averaged from in situ measurements or derived from literature data (e.g., Jia et al 2012; Peres and Cancelliere 2014), (2) the adoption of a set of constant values of the parameters for distinct geological, lithological or lithotecnical units, as derived from direct measurements (Segoni et al 2009;Baum et al 2010;Montrasio et al 2011;Zizioli et al 2013;Bicocchi et al 2016) or from existing databases and published data (Lepore et al 2013;Ren et al 2014;Tao and Barros 2014), or (3) the definition of cohesion and friction angle values as random variables using a probabilistic or stochastic approach (e.g., Griffiths et al 2011;Park et al 2013;Chen and Zhang 2014;Raia et al 2014;Fanelli et al 2016;Salciarini et al 2017). The latter does not consider any physical process in the spatial distribution of the parameters while the second one assumes that their distribution is related to lithology of the bedrock or to other morphometric parameters.…”