Modeling shallow soil moisture dynamics in mountainous landslide active regions

Abstract

Under the worsening climate change, the mountainous landslide active regions are more likely to suffer severe disasters threatening residents. To predict the occurrence of landslides, shallow soil moisture lying in the interface of the hydrological processes has been found as one of the critical factors. However, shallow soil moisture data are often scarce in the landslide active regions. To overcome the severe measurement deficiencies and provide predictions of soil moisture dynamics, we construct a physically-based shallow soil moisture model based on the assumptions of ideal flow, homogeneous and isotropic soil textures, and 1-dimensional water movement dominant by gravity forces. In the model, the meteorological conditions and the physical soil properties are taken into consideration. With limited field measurements, the model can provide reasonably accurate soil moisture predictions. In recognition of the seasonal weather characteristics, we perform a series of sensitivity analyses to examine the response of shallow soil moisture and relate the hydrological processes to air temperature, precipitation intensity, duration, and combinations thereof. Complex interactions of hydrological processes are found with variations in precipitation and air temperature, depending on the interlinked boundary conditions of the soil and water. It demonstrates a strong need for a decent forecast of the complex shallow soil moisture dynamics and the associated hydrologic processes in mountain regions to cope with climate change for landslide preparation and agricultural adaptation in the future.

Use of Soil Moisture as an Indicator for Climate Change, Using the SUPer System

“…The calibration of the SWAT model for the Terra Nova basin is presented in [10], which performed well with a validation coefficient of determination of 0.67. [3] state that landslide-active regions are more likely to experience severe threats to residents under worsening climate change. They claim that to predict the occurrence of landslides, the shallow soil moisture situated at the interface of hydrological processes was found to be one of the critical factors.…”

Spatial and Temporal Variations in Soil Moisture for a Tamarisk Stand under Groundwater Control in a Hyper-Arid Region

“…Lots of investigations into temporal variations and the time stability of soil moisture with different ecosystems or under different climate conditions were carried out through ground or remote sensing-based data [8][9][10][11][12][13]. Stochastic soil moisture dynamic models were developed for different conditions of soil, topography, and vegetation [14][15][16]. The spatial dynamics of soil moisture are mainly influenced by soil texture, vegetation, and topographic patterns [17][18][19][20][21].…”

A Soil Moisture Prediction Model, Based on Depth and Water Balance Equation: A Case Study of the Xilingol League Grassland

“…Prediction methods for the soil moisture fall into two main categories: physics-based process models [19] and data-driven empirical models [20]. Physics-based process models focus on the hydrological processes that control the soil moisture transfer mechanisms through physical equations, and calculate the explanatory variables as part of the land surface data assimilation techniques [21]. Factors, such as precipitation, atmospheric temperature and solar radiation, driven by model-generated or observationally obtained factors, can be used for the seasonal flow prediction, such as soil moisture, runoff and so on [22].…”