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ARS Home » Pacific West Area » Maricopa, Arizona » U.S. Arid Land Agricultural Research Center » Water Management and Conservation Research » Research » Publications at this Location » Publication #321693

Title: Approximate furrow infiltration model for time-variable ponding depth

item Bautista, Eduardo
item WARRICK, ARTHUR - University Of Arizona
item Schlegel, James
item Thorp, Kelly
item Hunsaker, Douglas - Doug

Submitted to: Journal of Irrigation and Drainage Engineering
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/29/2016
Publication Date: 11/8/2016
Publication URL:
Citation: Bautista, E., Warrick, A.W., Schlegel, J.L., Thorp, K.R., Hunsaker, D.J. 2016. Approximate furrow infiltration model for time-variable ponding depth. Journal of Irrigation and Drainage Engineering. 142(11):Article 04016045. Available:

Interpretive Summary: An important challenge to the hydraulic analysis of furrow irrigation systems is predicting infiltration. Furrow infiltration is a two-dimensional process, as water flows vertically and laterally at a particular location depending on the cross section in contact with the water - the wetted perimeter - and the resulting water pressure acting along that perimeter. This effect needs to be incorporated into irrigation simulation models. Currently, the WinSRFR model developed by USDA-ARS, as well other practical simulation models, use empirical procedures to compute the flow-depth dependent furrow infiltration. Because of their underlying assumptions, empirical methods need to be calibrated for specific hydraulic conditions and can be expected to yield reliable predictions only under conditions similar to those used for calibration. Hence, a physically-based infiltration modeling approach that can be more easily adapted to a wider range of hydraulic conditions is desirable. A model that computes flow-depth dependent furrow infiltration was developed. The model approximates the solution to the two-dimensional Richards equation, which is based on porous media flow theory and, thus, represents the infiltration process using physical principles. Because of their computational complexity, solutions of the Richards equation are currently of limited value for practical irrigation analyses. The approximate model is an extension of a previously presented model that computes infiltration for constant flow depth. The model was tested using different combinations of soil hydraulic properties, furrow geometry, and flow depth variations. Results show that the model is reasonably accurate in comparison with solutions of the Richards equation if uncalibrated, and highly accurate if calibrated. An important finding is that the calibration parameter is independent of the pattern of flow depth variation, within the range of conditions studied. The approximate model provides irrigation engineers with a practical and physically-based tool for predicting furrow infiltration. Thus, it should be of interest to both irrigation researchers and practitioners.

Technical Abstract: A methodology is proposed for estimating furrow infiltration under time-variable ponding depth conditions. The methodology approximates the solution to the two-dimensional Richards equation, and is a modification of a procedure that was originally proposed for computing infiltration under constant ponding depth. Two computational approaches were developed and tested using several combinations of soil hydraulic properties, furrow geometry, and flow depth variations. Both methods yielded solutions of reasonable and similar accuracy relative to numerical solutions of the two-dimensional Richards equation. The analysis also showed that the accuracy of the approximate model varies mostly as a function of soil hydraulic properties. The accuracy of the approximate solution can be improved with calibration. Two calibration methods were examined, one assuming that the calibration parameter varies with depth, and the other assuming a constant value. The analysis shows that latter approach, in combination with one of the proposed computational methods, reproduces the Richards equation solution more accurately. This means that a unique calibration parameter can be developed for the particular soil and geometric configuration conditions, and applied to different patterns of ponding depth variation.