Journal
GEODERMA
Volume 199, Issue -, Pages 22-29Publisher
ELSEVIER
DOI: 10.1016/j.geoderma.2012.07.018
Keywords
EM31; EM38; SAGA wetness index; Water table; Precision irrigation
Categories
Ask authors/readers for more resources
Electromagnetic surveys have been used to quantify soil variability with respect to soil water storage in an irrigated maize field. A fluctuating water table sub-irrigates the crop in some places, and a wireless sensor network simultaneously monitors real-time depth of water table and soil moisture content, with large differences in soil moisture measured at any one time in these uniformly textured sands. These large differences justify assessment of the spatio-temporal variability of soil hydraulic properties when aiming for precision management of the resource. Regression models were used to spatially predict water table depth and moisture content at 50 cm using EM38 survey data, a rainfall time series and a wetness index extracted from a digital elevation model. A multiple linear regression modelling (MLM) approach was compared with a data-mining approach using a random forest model (RF). The RE model implements a more thorough interrogation of the data using classification trees with subsequent regression of the data and provided the best prediction of soil moisture (R-2=0.94; RMSE = 0.03 m(3) m(-3) using RE; R-2=0.77; RMSE = 0.06 m(3) m(-3) using MLM) and water table depth (R-2=0.91; RMSE = 7.17 cm using RF; R-2=0.71; RMSE = 12.48 cm using MLM). (C) 2012 Elsevier B.V. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available