Spatiotemporal sampling strategy for characterization of hydraulic properties in heterogeneous soils

Yu, D. and Zha, Y. and Shi, L. and Bolotov, A. and Tso, C.-H.M. (2020) Spatiotemporal sampling strategy for characterization of hydraulic properties in heterogeneous soils. Stochastic Environmental Research and Risk Assessment. ISSN 1436-3240

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Abstract

Accurate characterization and prediction of soil moisture distribution and solute transport in vadose zone require detailed knowledge of the spatial distribution of soil hydraulic properties. Since the direct measurements of these unknown properties are challenging, many studies invert the soil hydraulic parameters by incorporating observation data (e.g., soil moisture and pressure head) at selected point sampling locations into soil moisture flow models. However, a cost-effective sampling strategy for where and when to collect the data, which is vital for saving the costs for monitoring and data interpretation, is relatively rare compared to the direct parameter retrieving efforts. Here, an optimal spatial–temporal sampling strategy was proposed based on cross-correlation analysis between observed state variables and soil hydraulic parameters. Besides, the effects of meteorological condition, observation type, bottom boundary condition, and correlation scale of soil hydraulic parameters are also demonstrated. The proposed sampling strategy was assessed by both synthetic numerical experiments and a real-world case study. Results suggest the retrieval accuracy of heterogeneous soil is acceptable if the spatial/temporal sampling interval is set to be one spatial/temporal correlation length of soil moisture. Besides, surface observation contains the most plentiful information which could be used to derive root-zone soil moisture/parameters, but this ability depends on the correlation scale of soil hydraulic parameters. Besides, the temporal value of soil moisture depends on meteorological condition. It is not necessary to sample repeatedly during dry periods, but more attention should be paid to the observations after rainfall events. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.

Item Type:
Journal Article
Journal or Publication Title:
Stochastic Environmental Research and Risk Assessment
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2200/2213
Subjects:
ID Code:
148241
Deposited By:
Deposited On:
15 Oct 2020 10:40
Refereed?:
Yes
Published?:
Published
Last Modified:
31 Oct 2020 07:23