Articles | Volume 20, issue 1
Hydrol. Earth Syst. Sci., 20, 487–503, 2016
Hydrol. Earth Syst. Sci., 20, 487–503, 2016

Research article 29 Jan 2016

Research article | 29 Jan 2016

Sensitivity of water stress in a two-layered sandy grassland soil to variations in groundwater depth and soil hydraulic parameters

M. Rezaei1,2, P. Seuntjens1,2,3, I. Joris2, W. Boënne2, S. Van Hoey4, P. Campling2, and W. M. Cornelis1 M. Rezaei et al.
  • 1Department of Soil Management, Ghent University, Coupure Links 653, 9000 Ghent, Belgium
  • 2Unit Environmental Modelling, Flemish Institute for Technological Research (VITO NV), Boeretang 200, 2400 Mol, Belgium
  • 3Department of Bioscience Engineering, University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp, Belgium
  • 4Department of Mathematical Modelling, Statistics and Bioinformatics, Ghent University, Coupure Links 653, 9000 Ghent, Belgium

Abstract. Monitoring and modelling tools may improve irrigation strategies in precision agriculture. We used non-invasive soil moisture monitoring, a crop growth and a soil hydrological model to predict soil water content fluctuations and crop yield in a heterogeneous sandy grassland soil under supplementary irrigation. The sensitivity of the soil hydrological model to hydraulic parameters, water stress, crop yield and lower boundary conditions was assessed after integrating models. Free drainage and incremental constant head conditions were implemented in a lower boundary sensitivity analysis. A time-dependent sensitivity analysis of the hydraulic parameters showed that changes in soil water content are mainly affected by the soil saturated hydraulic conductivity Ks and the Mualem–van Genuchten retention curve shape parameters n and α. Results further showed that different parameter optimization strategies (two-, three-, four- or six-parameter optimizations) did not affect the calculated water stress and water content as significantly as does the bottom boundary. In this case, a two-parameter scenario, where Ks was optimized for each layer under the condition of a constant groundwater depth at 135–140 cm, performed best. A larger yield reduction, and a larger number and longer duration of stress conditions occurred in the free drainage condition as compared to constant boundary conditions. Numerical results showed that optimal irrigation scheduling using the aforementioned water stress calculations can save up to 12–22 % irrigation water as compared to the current irrigation regime. This resulted in a yield increase of 4.5–6.5 %, simulated by the crop growth model.

Short summary
The sensitivity of the combined model (LINGRA-N and HYDRUS-1D) to hydraulic parameters, water stress, crop yield and lower boundary conditions was assessed. We showed that it is sufficient to estimate limited amount of key parameters in optimization strategies. A combined modelling approach could increase water use efficiency (12–22.5 %) and yield (5–7%) by changing irrigation scheduling. Result calls for taking into account weather forecast and soil water content data in precision agriculture.