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ARS Home » Midwest Area » St. Paul, Minnesota » Soil and Water Management Research » Research » Publications at this Location » Publication #78594


item WU, L
item JURY, W
item CHANG, A
item Allmaras, Raymond

Submitted to: Soil Science Society of America Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/10/1997
Publication Date: N/A
Citation: N/A

Interpretive Summary: Mathematical models are needed to predict water movement and the transport of agrichemicals, and yet use only a few reliable measures of changes of water content. More accurate predictions of water and agrichemicals movement have many applications in hydrology. The time series analysis demonstrated how to use water content measurements near the surface for determining water regime in the root zone of a sandy soil. Overall, the predictions were reasonable, with accuracy increasing as the separation distance to the 25-cm depth decreases. These techniques can be used by scientists interested in a more comprehensive description of water relations where there is a need to trace the movement of agrichemicals in sandy soils.

Technical Abstract: Prediction of the field soil-water regime is important for assessing agrochemical transport and scheduling irrigation. This research was conducted to evaluate the potential for employing the time-series analysis technique to predict the average water content (AWC) of a soil profile and water content at depths of interest from measurements made at a single depth. Volumetric water content of Zimmerman fine sand (mixed, frigid, Argic Udipsamments) in Princeton, MN was measured in situ by time-domain reflectometry (TDR) at 6 depths during the early 1993 growing season. The time series made up of hourly measurements of soil-water content was first-order differenced to obtain stationarity. The differenced data were used to conduct analyses in the frequency domain to evaluate the coherence and cross-amplitude between two time series, and were subsequently fitted to autoregressive moving average models (ARIMA) to obtain coefficients for the transfer function models in the time domain. The transfer function models were then used to predict water contents at depths of interest (50, 75, and 100-cm depths) and AWC in the top 100-cm profile from measured water content at the 25-cm depth. Overall, the predictions were reasonable, with accuracy increasing as the separation distance to the 25-cm depth decreases.