Spatiotemporal variability of soil-water characteristic curve model parameters of Lanzhou collapsible loess

The spatiotemporal variation of the model parameters of the soil-water characteristic curve (SWCC) reflect the soil water holding capacity and soil pore distribution state. It is an integral part of interdisciplinary disciplines such as soil hydrodynamics and ecohydrology. The authors selected the optimal SWCC model for the Lanzhou collapsible loess, used classical statistics and geostatistics methods to study the spatiotemporal variability of the SWCC model parameters, and using the comprehensive comparison of the mean relative differences (MRD), standard deviations (SDRD) and an index of temporal stability (ITS) determined the representativeness measuring point. The results showed that the SWCC parameter α was medium variability in the 0–30 cm soil layer, n and θs were of low variability, and the spatial distribution of the parameters of different soil layers was consistent. Migration direction prediction of θs was very similar in each layer, α, n and θs were all strongly significantly correlated positively. Moreover, the determination coefficient of representative measuring point 16 had the highest prediction accuracy for the measured values of SWCC. The results of this paper can be used as a simple method to predict SWCC and provide theoretical guidance for soil water management and soil collapse erosion monitoring in the collapsible loess area. HIGHLIGHTS A study is presented of the temporal stability and variability of SWCC in the Lanzhou collapsible loess, using the comprehensive comparison of the mean relative differences (MRD), standard deviations (SDRD) and an index of temporal stability (ITS), and the representativeness measuring point was determined.; The SWCC parameter α is medium variability in the 0–30 cm soil layer, n and θs are of low variability. The spatial distribution of the SWCC parameters was consistent. Migration direction prediction of θs was very similar in each layer. α, n and θs were all strongly significantly correlated positively.; A small amount of observations was used to monitor SWCC on a large scale, providing a fast and effective monitoring method for soil erosion in the Loess Plateau.;