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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Environmental Microbial & Food Safety Laboratory » Research » Publications at this Location » Publication #284901

Title: How can climate, soil, and monitoring schedule affect temporal stability of soil water contents

Author
item MARTINEZ, GONZALO - Ciudad University - Spain
item Pachepsky, Yakov
item VEREECKEN, HARRY - National Institute Of Biotechnology And Genetic Engineering (NIBGE)

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 9/1/2012
Publication Date: 12/2/2012
Citation: Martinez, G., Pachepsky, Y.A., Vereecken, H. 2012. How can climate, soil, and monitoring schedule affect temporal stability of soil water contents. [abstract].

Interpretive Summary:

Technical Abstract: Temporal stability (TS) of soil water content (SWC) reflects the spatio-temporal organization of soil water. The TS SWC was originally recognized as a phenomenon that can be used to provide temporal average SWC of an area of interest from observations at a representative location(s). Currently application fields of TS SWC are numerous, e.g. up- and downscaling SWC, SWC monitoring and data assimilation, precision farming, and sensor network design and optimization. However, the factors that control the SWC organization and TS SWC are not completely understood. Among these factors are soil hydraulic properties that are considered as local controls, weather patterns, and the monitoring schedule. The objective of this work was to use modeling to assess the effect of these factors on the spatio-temporal patterns of SWC. We ran the HYDRUS6 code to simulate four years of SWC in 4-m long soil columns. The columns were assumed homogeneous, soil hydraulic conductivity was drawn from lognormal distributions. Sets of columns were generated separately for sandy loam and loamy soils, soil water retention was set to typical values for those soil textures. Simulations were carried out for four climates present at the continental US. The climate-specific weather patterns were obtained with the CLIGEN code using climate-specific weather observation locations that were humid subtropical from College Station (TX), humid continental from Indianapolis (IN), cold semiarid from Moscow (ID) and hot semiarid from Tucson (AZ). We evaluated the TS and representative location (RL) selections by comparing i) different climates; ii) for the same climates different years; iii) different time intervals between samplings; iv) one year duration surveys vs. one month summer campaigns; and v) different seasons of the same year. Spatial variability of the mean relative differences (MRD) differed among climates for both soils, as the probability of observing the same variance in the MRD was lower than 29%. These differences were smaller for the loamy soils than for the sandy loam and may be related to more inertia to changes in SWC in the loam soil. The probability that the variance in MRD depended on sampling frequency was always higher than 89% in the sandy loam soil and was above 97% in the loamy soil. Same variability of MRD with July and the whole year SWC was generally low probable and depended on the soil type and climate. Different variability of the MRD with season was found with at least a 55% probability. Larger differences were observed for the robustness of the MRD than for its spatial variability. The inter-annual difference in MRD variation from short and intensive summer campaigns was highly probable for all climates. There were more coincidences under the different scenarios analyzed in the RL selected for the sandy loam soil than for the loamy soil. Among the methods used for selection of RL, those that are based on a minimum difference with MRD of zero showed more consistency than others. The TS appears to be the result of the interplay between climate, soil properties, and survey protocols. One implication of this factor interaction effect on TS SWC is that a simulation study can be useful to decide on the feasibility of including a search for the representative location based on TS for a specific site.