Back to Search Start Over

Subsurface drain flow and crop yield predictions for different drain spacings using DRAINMOD

Authors :
C.T. Mosley
X. Wang
Eileen J. Kladivko
Jane R. Frankenberger
Source :
Agricultural Water Management. 79:113-136
Publication Year :
2006
Publisher :
Elsevier BV, 2006.

Abstract

DRAINMOD was run for 15 years to predict and compare drain flow for three drain spacings and crop yield for four drain spacings at the Southeastern Purdue Agricultural Center (SEPAC). Data from two continuous years of daily drain flow from one spacing were used to calibrate the eight most uncertain parameters using a multi-objective calibration function and an automatic calibration method. The model was tested using the remaining field data for the 5, 10, and 20 m drain spacings for drain flow and the additional 40 m spacing for yield predictions. Nash–Sutcliffe efficiency (EF) for daily drain flow simulations for the calibration years and drain spacing ranged from 0.62 to 0.79. The daily EF for model testing ranged from −0.66 to 0.81, with the average deviations of 0.01 to 0.07 cm/day and standard errors of 0.03–0.17 cm/day. On a monthly basis, 91% of plot years had EF values over 0.5 and 76% over 0.6 for years with on-site rainfall data. The total yearly drain flow was predicted within ±25% in 71% of plot years, and within ±50% in 93% of plot years with on-site rainfall data. Statistical tests of daily drain flow EF values for three spacings and percent errors of crop relative yield for four spacings indicated that the reliability of the model is not significantly different among different spacings, supporting the use of DRAINMOD to study the efficiencies of different drain spacings and to guide the drain spacing design for specific soils. In general, the model correctly predicted the pattern of yearly relative yield change. The relative corn ( Zea mays L.) and soybean ( Glycine max L.) yields were well predicted on average, with percent errors ranging from 1.3 to 9.7% for corn and from −3.3 to 10.3% for soybean.

Details

ISSN :
03783774
Volume :
79
Database :
OpenAIRE
Journal :
Agricultural Water Management
Accession number :
edsair.doi...........9deaed37d572e27217b7855d131d1d1b
Full Text :
https://doi.org/10.1016/j.agwat.2005.02.002