A modified tank model including snowmelt and infiltration time lags for deep-seated landslides in alpine environments (Aggenalm, Germany)

Abstract

Abstract. Deep-seated landslides are an important and widespread natural hazard within alpine regions and can have significant impacts on infrastructure. Pore water pressure plays an important role in determining the stability of hydrologically triggered deep-seated landslides. Based on a simple tank model structure, we improve groundwater level prediction by introducing time lags associated with groundwater supply caused by snow accumulation, snowmelt and infiltration in deep-seated landslides. In this study, we demonstrate an equivalent infiltration calculation to improve the estimation of time lags using a modified tank model to calculate regional groundwater levels. Applied to the deep-seated Aggenalm landslide in the German Alps at 1000-1200 m a.s.l., our results predict daily changes in pore water pressure ranging from −1 to 1.6 kPa, depending on daily rainfall and snowmelt, which are compared to piezometric measurements in boreholes. The inclusion of time lags improves the results of standard tank models by ∼ 36 % (linear correlation with measurement) after heavy rainfall and by ∼ 82 % following snowmelt in a 1-2-day period. For the modified tank model, we introduced a representation of snow accumulation and snowmelt based on a temperature index and an equivalent infiltration method, i.e. the melted snow-water equivalent. The modified tank model compares well to borehole-derived water pressures. Changes of pore water pressure can be modelled with 0-8 % relative error in rainfall season (standard tank model: 2-16 % relative error) and with 0-7 % relative error in snowmelt season (standard tank model: 2-45 % relative error). Here we demonstrate a modified tank model for deep-seated landslides which includes snow accumulation, snowmelt and infiltration effects and can effectively predict changes in pore water pressure in alpine environments.

Machine Learning: New Potential for Local and Regional Deep-Seated Landslide Nowcasting

“…A bucket or tank model can be used to estimate the ground water level from indirect measurements, such as precipitation, transpiration estimates, and run-off measurements [69][70][71][72]. Run-off of small streams cannot be measured by satellites, and requires in situ or close-range measurements, while the other parameters can be estimated [73].…”

“…This approximation is never perfect, but allows for an indirect estimate of groundwater from surface processes. The groundwater level is then used to estimate the pore pressure, which is related to the stability of the landslide [69,74]. Furthermore, it filters the high-frequency precipitation signal to low-frequency changes in groundwater.…”

“…Physical constraints can be added at multiple stages of the process and bring the solution closer to the physical process. Simple physics, such as the tank model [69], may be used during variable pre-processing to amplify the information content of the variables. This integrates expert knowledge into the empirical system, unintentionally constraining the system to an assumed correlation.…”

Using a Tank Model to Determine Hydro-Meteorological Thresholds for Large-Scale Landslides in Taiwan

“…Currently, the Japan Meteorological Agency (JMA) adopts the SWI as the conceptual soil water content affected by antecedent rainfall as well as event rainfall [24]. Furthermore, the tank model has been successfully applied to discuss the influence of water infiltration on deep-seated landslides [25,26]. The estimation of groundwater supply caused by infiltration using the tank model can be considered as an indicator of pore water pressure changes in the deep layer of a slope.…”

Physical Tank Experiment Investigation on Rainfall Producing Groundwater Level in Homogeneous Material Slopes

“…The lateral water supply tank model can be applied for any slope angle, but its complicated structure produces a higher systematically cumulative error. The highlight of the application of the tank model is using a simple model structure with as-little-as-possible model parameters to describe the water balance including water content and groundwater level [14,15]. Unfortunately, most applications of the tank model are still a theoretic model and require many parameters for calibration.…”