Abstract
Knowledge of spatial and temporal variations of soil pore-water pressure in a slope is vital in hydrogeological and hillslope related processes (i.e., slope failure, slope stability analysis, etc.). Measurements of soil pore-water pressure data are challenging, expensive, time consuming, and difficult task. This paper evaluates the applicability of artificial neural network (ANN) technique for modeling soil pore-water pressure variations at multiple soil depths from the knowledge of rainfall patterns. A multilayer perceptron neural network model was constructed using Levenberg-Marquardt training algorithm for prediction of soil pore-water pressure variations. Time series records of rainfall and pore-water pressures at soil depth of 0.5 m were used to develop the ANN model. To investigate applicability of the model for prediction of spatial and temporal variations of pore-water pressure, the model was tested for the time series data of pore-water pressure at multiple soil depths (i.e., 0.5 m, 1.1 m, 1.7 m, 2.3 m, and 2.9 m). The performance of the ANN model was evaluated by root mean square error, mean absolute error, coefficient of correlation, and coefficient of efficiency. The results revealed that the ANN performed satisfactorily implying that the model can be used to examine the spatial and temporal behavior of time series of pore-water pressures with respect to multiple soil depths from knowledge of rainfall patterns and pore-water pressure with some antecedent conditions.
Highlights
Soil pore-water pressure is an important variable contributing to soil shear strength
Time series of porewater pressure trained with data of 0.5 m soil depth but tested with multiple soil depths was illustrated
The coefficient of efficiency for the artificial neural network (ANN) model evaluated in this study showed CE values which are very close to unity indicating excellent efficiency of the model and thereby suggesting that the learning algorithm chosen to predict pore-water pressure responses to climatic variations is appropriate
Summary
Soil pore-water pressure is an important variable contributing to soil shear strength. In tropical regions unsaturated soil conditions above the groundwater table contribute to the stability of a slope due to the additional shear strength provided by the negative pore-water pressures of the unsaturated soil. During dry periods the soil undergoes drying due to evaporation and transpiration and as a result the pore-water pressure gradually becomes more negative over time. During wet periods the soil undergoes wetting due to rainfall and the pore-water pressure becomes less negative or even positive. This leads to a decrease in the soil shear strength and may eventually trigger a slope failure [1]. Time series of soil porewater pressures in response to climatic conditions, exhibits highly dynamic, nonlinear, and complex behavior [2]
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