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Three basic multiple-linear regression models with different sets of more readily observed environmental variables (land use, topographic and meteorological factors) were developed for the prediction of soil moisture content in space and time. The model performances were evaluated in the Danangou catchment (3.5 km2) on the Loess Plateau, China, with soil moisture content measurements. The soil moisture content measurements were performed biweekly at five depths in the soil profile (0–5, 10–15, 20–25, 40–45 and 70–75 cm) from May to October 1998 and from May to September 1999, using a Delta-T theta probe. It was indicated that the regression models could describe the relationships of soil moisture content with environmental attributes. It was found that the spatiotemporal-SM model showed the best goodness of fit since it explained the greatest fraction of soil moisture variation in both space and time, and the predicted mean, standard deviation, minimum and maximum soil moisture were closest to the observed values. This model was also either the most precise or the most economical in prediction of soil moisture content in space and time since it gives the lowest values in mean absolute error of prediction (MAE) and Akaike information criterion (AIC). There is little difference in performance and cost-benefit between the spatial-GM model and landuse-GM model. The superior robustness of the spatiotemporal-SM model over the other two models is most significant in the prediction of soil moisture content at 0–5 cm, and decreases with increasing soil depth. [Copyright &y& Elsevier]

Presents a study which examined the effects of land use and its patterns on soil moisture and nutrients in the hilly area of Loess Plateau in China. Description of the study area; Comparisons of soil moisture among land uses for wet and dry years; Effects of landscape position on soil nutrients.

Soil moisture plays a critical role in both crop growth and vegetation restoration in semiarid environments. Its spatial and temporal variability results from topography, soils, vegetation and land uses. However, little knowledge exists about the effects of land use structure on soil moisture variability. In order to analyze soil moisture variations in relation to land use patterns, five land use structures and seven land use types were selected to monitor soil moisture. Soil moisture measurements were performed biweekly at 26 locations in a small catchment on the Loess Plateau of China from May to October 1998. The measurements were taken using a Theta-Probe at five depths of soil profile (0–5, 15–20, 25–30, 45–50 and 70–75 cm). These data were analyzed for soil moisture variations in space and time for seven land use types. Three peaks and three troughs of soil moisture variations during the growing season were found. The influence of shrubland on mean soil moisture within 0–70 cm was significantly different from that of cropland, orchard and intercropping land. Three types of soil moisture changes in profile were classified as increasing, decreasing and waving types. An analysis of the differences in soil moisture for five land use structures indicated that the influences of land use patterns on soil moisture were complex. This study provides an insight into the implications for hydrological modeling, runoff and erosion control in this area. [Copyright &y& Elsevier]