Implementation of a soil water extraction model on a spatial domain using field capacity and apparent electrical conductivity relationships

D. R. Rudnick, Suat Irmak

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Relationships were developed between apparent electrical conductivity (ECa) measured using a Veris 3100 conductivity instrument (Veris Technologies, Inc., Salina, Kans.) and soil hydraulic parameters [field capacity (FC) and permanent wilting point (PWP)] for use in a soil water extraction model to estimate spatial and temporal changes in maize (Zea mays L.) soil water extraction and plant-available water (PAW) at the South Central Agricultural Laboratory near Clay Center, Nebraska, in 2012. Linear relationships were observed between soil hydraulic parameters and ECa for the top 0.30 m depth, and curvilinear relationships were observed for the sub-layer (0.30-0.90 m). Stronger relationships were observed for the top 0.30 m depth, with R2 and RMSD of 0.68 and 0.008 m3 m-3 for FC and 0.83 and 0.008 m3 m-3 for PWP, respectively, than for the 0.30 to 0.90 m depth, with R2 and RMSD of 0.35 and 0.008 m3 m-3 for FC and 0.39 and 0.007 m3 m-3 for PWP, respectively. Spatial and temporal variability in soil water extraction was observed in the 0-0.30 m, 0.30-0.60 m, and 0.60-0.90 m soil depths as well as PAW in the 0.90 m soil profile using the FC vs. ECa regressions in the soil water extraction model. Irrigation treatment differences were apparent, with less soil water extraction in the 0.30-0.90 m soil layer under rainfed than irrigated conditions. The soil water extraction model using the developed FC vs. Veris ECa regressions performed satisfactorily compared to soil water balance determined seasonal profile (0-0.90 m) actual crop evapotranspiration (ETa), with a resulting R2 and RMSD of 0.72 and 27 mm, respectively. Further research is needed to investigate different ECa sensors as well as different methods for developing relationships between soil hydraulic parameters and ECa, which can include incorporating spatial variability in topsoil and subsoil depth thicknesses prior to regression analysis. The research findings reported here should lead to additional analyses and research for using ECa as an indirect estimator for soil hydraulic parameters for use in estimating soil water extraction and PAW.

Original languageEnglish (US)
Pages (from-to)1359-1373
Number of pages15
JournalTransactions of the ASABE
Volume57
Issue number5
DOIs
StatePublished - 2014

All Science Journal Classification (ASJC) codes

  • Forestry
  • Food Science
  • Biomedical Engineering
  • Agronomy and Crop Science
  • Soil Science

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