Rainfall-induced landslides pose serious threats to civil infrastructure and human life. Stability in a hillslope environment is a function of the hydrologic behavior. The variations in hydrologic behavior are driven by variations in climatological events such as rainfall and evapotranspiration. Thus, because the variations in climatological events are seasonal, prediction of seasonal variation in hydrologic behavior is critical for the prediction of landslides. However, most prediction methods only consider changes to hillslope hydrologic behavior due to rainfall and exclude the contribution of evapotranspiration. This approach does not allow for a complete analysis of the hydrologic behavior during seasonal cycles wetting and drying. Including evapotranspiration constitutes a significant improvement for early warning systems that are based on real-time seasonal hydrologic events. This study presents the development and implementation of an analytical transient infiltration model to predict seasonal variation of soil hydrologic behavior during a complete cycle of a season. The model was applied to three landslide sites in Kentucky. In-situ measurements of volumetric water-content and soil suction allowed for evaluation of seasonal soil moisture and suction fluctuations. Both rainfall and evapotranspiration were considered within a framework that facilitated the prediction of soil suction and volumetric water-content with transient surface flux. In addition, this model only requires unsaturated soil parameters based on the drying season to predict soil hydrologic behavior in the wetting season. The predicted soil hydrologic behavior can be applied directly to a limit equilibrium equation to estimate seasonal variations and the stability of a slope. The practical application of this study is the prediction of seasonal variation of hydrologic data for any site once calibrated, which will support a more realistic assessment of landslide hazards.

降雨引发的山体滑坡对民用基础设施和人类生活构成严重威胁。山坡环境中的稳定性是水文行为的函数。水文行为的变化是由降雨和蒸散等气候事件的变化驱动的。因此，由于气候事件的变化是季节性的，因此预测水文行为的季节性变化对于预测滑坡至关重要。然而，大多数预测方法只考虑降雨引起的山坡水文行为变化，而排除了蒸散量的贡献。这种方法不允许对季节性周期湿润和干燥期间的水文行为进行完整分析。将蒸散量包括在内是对基于实时季节性水文事件的预警系统的重大改进。本研究介绍了分析瞬态渗透模型的开发和实施，以预测在一个完整的季节周期内土壤水文行为的季节性变化。该模型应用于肯塔基州的三个滑坡地点。体积含水量和土壤吸力的原位测量允许评估季节性土壤水分和吸力波动。降雨量和蒸散量都被考虑在一个框架内，该框架有助于通过瞬时表面通量预测土壤吸力和体积含水量。此外，该模型只需要基于干旱季节的非饱和土壤参数来预测湿润季节的土壤水文行为。预测的土壤水文行为可以直接应用于极限平衡方程，以估计季节性变化和斜坡的稳定性。这项研究的实际应用是预测校准后任何站点的水文数据的季节性变化，这将支持更现实的滑坡灾害评估。