Estimation of spatial mean soil water storage using temporal stability at the hillslope scale in black locust (Robinia pseudoacacia) stands

- Soil water storages (SWSs) in diverse soil layers measured along two transects
- The four methods used to identify the most time stable locations (MTSLs) of SWS
- The index of temporal ability provided the best identification of the MTSLs.
- The mean SWSs were accurately estimated by the MTSLs in two transects.
- The factors influencing the temporal stability of SWS were investigated.

Black locust (Robinia pseudoacacia) has been extensively planted on the Loess Plateau for soil and water conservation, but afforestation with this non-native tree has produced some negative effects such as soil desiccation. Knowledge of the soil water storage (SWS) within soil profiles in black locust stands is thus critical for optimization of forest management for sustainable production. The objectives of this study were to evaluate the temporal stability of SWS to identify the most time-stable locations (MTSLs) for reliably estimating the mean SWS and to further investigate the factors influencing its temporal stability. The SWS values of various soil layers (0-1, 1-2, and 2-3 m) were measured from May 2014 to October 2015 at 70 locations along two 187-m long transects on a hillslope covered with black locust in the Loess Plateau, China. A total of 18 SWS datasets were collected over the period of measurement. Results indicated that the temporal variation of spatial mean SWS decreased and the spatial variation of SWS increased with increasing soil depth. A strong temporal persistence in all soil layers was demonstrated by high Spearman's rank correlation coefficients (P < 0.01), with the temporal stability in deep soil layers relatively more stable than in shallow layer. Among four methods (MRD, mean relative difference; SDRD, standard deviation of relative difference; ITS, index of temporal stability; and MABE, mean absolute bias error) used to identify the MTSLs for the estimation of the mean SWS, the ITS provided the best results. The MTSLs identified in diverse layers of the first transect were then used to successfully predict the mean SWS along the second transect (R2 > 0.91). Elevation, soil saturated hydraulic conductivity, leaf area index, and fine root area density were the major factors influencing the temporal stability of SWS. The results of this study were useful for estimating mean SWS and could improve soil water management and hydrological applications in sloping black locust forested areas of the Loess Plateau.