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Evolution of High-Filling Loess Slope under Long-Term Seasonal Fluctuation of Groundwater

Catena(2024)

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Abstract
Groundwater is a critical factor influencing the evolution of high-filling loess slopes (HLS). This study examines how long -term seasonal fluctuations in groundwater (SFG) influence the evolution of HLS within the context of the Gully Land Consolidation Project (GLCP) in the Chinese Loess Plateau. According to the field monitoring data, the permeability coefficients of each stratigraphic unit were inverted, then the trend of groundwater change in the HLS was derived by forward modeling based on the existing meteorological data, and it was found that the seasonal fluctuation of the groundwater could reach a state of overall stability by the 18th year. Under the longterm effect of SFG, the stability of the slope gradually decreases. Although the stability safety factor (Fs) dropping by 0.15 when compared to conditions without considering SFG, the slope can still maintain a fundamental level of stability. Considering the impact of rainfall on groundwater and the influence of groundwater on slope stability, the sensitivity of rainfall to groundwater and groundwater to slope stability were quantitatively calculated. And the slope evolution analysis method, which considers the multi-process effects of the rainfall-groundwaterslope was established. Furthermore, the shoulder and foot of the slope were identified as optimal points for monitoring groundwater levels. Additionally, it was observed that prolonged rainfall events generated multiple sensitivity peaks, increasing the probability of slope instability, while intense rainfall events shortened the lagtime of slope stability response to rainfall. Taking groundwater as a disaster monitoring factor, it offers an advance warning window of 0.07-0.38 days, which can significantly improve the disaster response efficiency and provide guidance for the safe production and efficient disaster prevention of GLCP in loess areas.
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Key words
Groundwater,Seasonal evolution,Slope stability,Numerical modelling,Sensitivity analysis,Early warning
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