Evaluation of the hooghoudt and kirkham tile drain equations in the soil and water assessment tool to simulate tile flow and nitrate-nitrogen

Daniel N. Moriasi, Prasanna H. Gowda, Jeffrey G. Arnold, David J. Mulla, Srinivasulu Ale, Jean L. Steiner, Mark D. Tomer

Research output: Contribution to journalArticlepeer-review

25 Scopus citations

Abstract

Subsurface tile drains in agricultural systems of the midwestern United States are a major contributor of nitrate-N (NO3-N) loadings to hypoxic conditions in the Gulf of Mexico. Hydrologic and water quality models, such as the Soil and Water Assessment Tool, are widely used to simulate tile drainage systems. The Hooghoudt and Kirkham tile drain equations in the Soil and Water Assessment Tool have not been rigorously tested for predicting tile flow and the corresponding NO3-N losses. In this study, long-term (1983-1996) monitoring plot data from southern Minnesota were used to evaluate the SWAT version 2009 revision 531 (hereafter referred to as SWAT) model for accurately estimating subsurface tile drain flows and associated NO3-N losses. A retention parameter adjustment factor was incorporated to account for the effects of tile drainage and slope changes on the computation of surface runoff using the curve number method (hereafter referred to as Revised SWAT). The SWAT and Revised SWAT models were calibrated and validated for tile flow and associated NO3-N losses. Results indicated that, on average, Revised SWAT predicted monthly tile flow and associated NO3-N losses better than SWAT by 48 and 28%, respectively. For the calibration period, the Revised SWAT model simulated tile flow and NO3-N losses within 4 and 1% of the observed data, respectively. For the validation period, it simulated tile flow and NO3-N losses within 8 and 2%, respectively, of the observed values. Therefore, the Revised SWAT model is expected to provide more accurate simulation of the effectiveness of tile drainage and NO3-N management practices.

Original languageEnglish (US)
Pages (from-to)1699-1710
Number of pages12
JournalJournal of Environmental Quality
Volume42
Issue number6
DOIs
StatePublished - Nov 1 2013

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