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Characterizing spatial-temporal patterns and abrupt changes in deep soil moisture across an intensively managed watershed

Wang, Yunqiang, Sun, Hui, Zhao, Yali
Geoderma 2019 v.341 pp. 181-194
Robinia pseudoacacia, best management practices, humans, issues and policy, models, ravines, roots, soil depth, soil profiles, soil water, soil water content, space and time, vegetation, watersheds, China
Soil moisture content (SMC) is highly variable in space and time due to the combined effects of natural processes and human influences. This study was conducted to explore the temporal-spatial patterns of deep SMC and detect possible abrupt changes in SMC in deep soil layers across an intensively managed watershed. We monitored SMC to a depth of 500 cm from 2016 to 2017 at the Gutun watershed (N = 89) on the Chinese Loess Plateau and determined related soil and vegetation properties. The mean SMC on the slopes at different depths were lower than in the gullies at the intensively managed areas affected by the “Grain for Green” project and the “Gully Land Consolidation” project. With increasing soil depth, slope SMCs gradually increased to 14%, while gully SMCs reached 40%. The spatial structures and patterns of mean SMCs within the 0–500 cm profile were similar but differed among different sub-layers. The detected fast changing layers (FCLs) of SMC (mean thickness = 76 cm) often occurred on the slopes of the watershed, while the relatively stable layers of SMC (mean thickness = 257 cm) were often located in the gullies. In deep soil layers (below 300 cm), we detected deep-FCLs at eight sites (mean thickness = 60 cm) which were all located on the slopes and under the same species (Robinia pseudoacacia L.). The mean SMCs within each of the eight deep-FCLs demonstrated a decreasing trend with time, which may be caused by the distribution of fresh roots. Human management had a profound impact on the spatial and temporal patterns of SMC in deep soil profiles at the watershed scale. This information should be considered by hydrologists and policy makers when developing eco-hydrology models and best management practices at multiple scales in a watershed.