Abstract

Soil moisture plays a decisive role for tree growth and forest ecosystems services supply in dryland regions. Hence, it is necessary to clarify the spatio-temporal variation of soil moisture under field conditions. This study selected a hillslope in the Liupan Mountains covered by the plantation of Larix principis-rupprechtii Mayr (larch), a main afforestation tree species in north and northwest China. The volumetric soil moisture (VSM) in root zone layers was monitored with a time interval of about 15 days during the growing season (from May to October) in 2016 at 48 points on this hillslope. The aim was to evaluate the spatial pattern and temporal stability of soil moisture at slope scale. The results showed a moderate spatial variability of VSM in each soil layer, with the variation coefficients range of 17.12–22.63%. The spatial variability of VSM showed a dependence on the soil wetness and a threshold effect, it increased with rising VSM until the VSM reached a threshold of about 15%, but thereafter decreased. The mean relative difference (MRD) among the 48 points ranged from −30.56% to 27.20%, −29.89% to 39.58%, and −28.13% to 33.71% for the soil layers of 0–20, 20–40, and 40–60 cm, respectively. The associated standard deviation (SDRD) (and range) was 11.38% (5.20–26.06%), 8.28% (4.64–15.63%), and 6.51% (2.00–14.16%) for the soil layers of 0–20, 20–40, and 40–60 cm, respectively. The high Spearman’s rank coefficients (p < 0.05) among the measuring dates at each soil layer indicated that the spatial distribution of VSM in the root zone had strong temporal stability. The decrease of Spearman’ rank correlation coefficient and mean SDRD with rising soil depth indicated an increasing temporal stability of VSM with rising soil depth. The mean VSM of the three soil layers on the entire hillslope can be estimated by the direct method (using representative points determined by the index of temporal stability (ITS)) successfully, and these representative points determined by ITS were mainly located at the points with a ratio of field capacity to leaf area index (LAI) close to the slope mean. Moreover, the mean VSM of the three soil layers on the entire hillslope can also be estimated by indirect method (using the time-stable points determined by mean absolute bias error (MABE) and considering the offset between slope mean VSM and observed VSM at time-stable points), and the prediction accuracy of the indirect method was better than the direct method. Significant correlation between MRD and soil bulk density, field capacity, capillary porosity, and LAI were observed for all soil layers, indicating that both the water-retention ability in root zone soil (expressed mainly by field capacity) and water-consumption ability of trees (expressed mainly by canopy LAI) are the main factors controlling the spatial pattern of root-zone VSM on the larch plantation hillslope studied.

Highlights

  • Soil moisture is a key factor affecting a series of eco- and hydrological processes in dryland regions, because it controls the rainfall infiltration, evapotranspiration, runoff generation, vegetation growth, and photosynthesis [1,2,3]

  • Significant correlation between mean relative difference (MRD) and soil bulk density, field capacity, capillary porosity, and leaf area index (LAI) were observed for all soil layers, indicating that both the water-retention ability in root zone soil and water-consumption ability of trees are the main factors controlling the spatial pattern of root-zone volumetric soil moisture (VSM) on the larch plantation hillslope studied

  • The slope means of VSM during the study period were 15.19% (10.87–23.58%), 20.66% (15.90–28.34%), and 22.99% (19.17–28.82%) in the 0–20, 20–40, 40–60 cm soil layers, respectively. These mean VSM varied significantly with time (Figure 3A) and the variation was correlated among soil layers (p < 0.01), with a decreasing temporal variability (CVT ) along soil depth, i.e., 28.75%, 20.47%, and 14.68%, respectively (Table 2)

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Summary

Introduction

Soil moisture is a key factor affecting a series of eco- and hydrological processes in dryland regions, because it controls the rainfall infiltration, evapotranspiration, runoff generation, vegetation growth, and photosynthesis [1,2,3] It is an important input for hydrologic, tree growth, and climate models [4,5,6,7]. Soil moisture is highly affected by many factors (e.g., land use, soil properties, terrain, meteorology, and vegetation dynamic), and presents great spatio-temporal variation and scale-dependence [8,9,10]. This will certainly affect the associated ecoand hydrological processes and related model applications. An approach that can optimize the sampling points to precisely assess the mean soil moisture is desirable [11]

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