Time stability of soil volumetric water content and its optimal sampling design in contrasting forest catchments

Abstract

Characterizing the temporal variation across a forest catchment soil volumetric water content (VWC) with different environmental conditions at different depths for different seasons requires a robust point-scale sampling strategy that balances monitoring cost with predicting accuracy. In the study, the most time-stable locations (MTSLs) using the time-stable concept and the minimum number of required samples (NRS) based on random selection method were studied to explore the optimal sampling design for catchment-mean VWC with an acceptable error (the relative bias (RBIAS) less than 10 %). VWC monitoring was conducted at approximately 25 plots throughout the year in five forest catchments with varying areas and VWC status. Results revealed that the number of MTSLs for mean-VWC estimation with RBIAS within 10 % was directly related to the spatial variability of VWC. Specifically, one MTSL was feasible for accurately estimating mean VWC at different depths in high-VWC catchments with area around or less than 100 ha; one MTSL was adequate for each depth in the catchment with moderate-level VWC; whereas more than one MTSL were necessary for each depth in low-VWC catchment with a larger are of 1800 ha. To identify the MTSL for each catchment, the location with mean VWC was typically situated at the mid-elevation or soil apparent electrical conductivity (ECa) at a certain spatial scale. The NRS for catchment-mean VWC could be determined based on the combination of VWC status, its temporal stability, and potential catchment size, and could be ranked based on the spatial variation of each catchment. If the MTSL cannot be guaranteed for a catchment, the NRS might be a better alternative for optimum sampling design. These finding could be useful in providing guidelines for optimizing VWC monitoring in forest catchments by sampling at a few selected locations representative of the catchment-scale behavior.