Use of a state-space approach to predict soil water storage at the hillslope scale on the Loess Plateau, China

Abstract

Soil water storage is a critical variable controlling hydrological and biological processes. The precise estimation of soil water storage in diverse soil layers is fundamental to understanding hydro-biological processes and efficiently managing water resources. The objectives of this study were to evaluate the effects of topography (elevation) and soil properties (clay, silt, sand content, median grain size, and fractal dimension) on soil water storage and then to estimate soil water storage using a state-space approach. The soil water storage values of three soil layers (0–1, 1–2, and 2–3m) were measured from May to December 2014 at 70 locations along two 187m long transects on a hillslope of the Loess Plateau, China. Samples from various depths were also collected to determine soil properties. The best state-space approach explained 98.8% of the total variation in soil water storage, while the best classical linear regression equation only explained 64.2%. The state-space approach using any combination of variables described the spatial pattern of soil water storage much better than equivalent linear regression equations. Elevation and clay content were identified as the most effective combination for soil water storage estimation in the state-space approach, and were used to effectively predict the soil water storage spatial pattern along the second transect. The state-space approach is thus a useful tool that is recommended for predicting soil water storage spatial patterns at the hillslope scale using topography and soil properties.