Reply on RC1

Mohammad Farzamian

doi:10.5194/hess-2022-12-ac2

Abstract

Determining soil hydraulic and hydrodispersive properties is crucial for the sustainable management of water resources and agricultural land. Due to the local heterogeneity of soil hydrological properties and the lack of fast in-situ measurement techniques, it is hard to assess these properties at the field scale. The present study proposes a methodology based on the integration of Electromagnetic Induction (EMI) and hydrological modeling to estimate soil hydraulic and transport properties at the field scale. To this aim, two sequential water infiltration and solute transport experiments were carried out over a small field plot. The propagation of wetting front and solute concentration along the soil profile was monitored using an EMI sensor (i.e. CMD mini-Explorer), Time Domain Reflectometry (TDR) probes, and tensiometers. Time-lapse apparent electrical conductivity (σa) data obtained from the EMI sensor were inverted to estimate the evolution of the vertical distribution of the bulk electrical conductivity (σb) over time. The σb distributions were converted to water content and solute concentration by using a laboratory calibration, relating σb to water content (θ) and soil solution electrical conductivity (σw). The hydraulic and hydrodispersive properties were then obtained by an optimization procedure minimizing the deviations between the numerical solution of the water flow and solute transport processes and the estimated water contents and concentrations inferred from the EMI results. The EMI-based results were finally compared to the results obtained from the in-situ TDR and tensiometer measurements. In general, the EMI readings lead to underestimated water contents as compared to the TDR data. And yet, the water content changes over time detected by the EMI closely followed those observed by TDR and contain enough information for effective EMI-based reconstructions of water retention and hydraulic conductivity curves for the soil profile. In addition, this allowed us to reproduce the solute concentration distributions and thus the hydro-dispersive properties of the soil profile. Overall, the results suggest that time-lapse EMI measurements could be used as a rapid, non-invasive, field-scale method to assess soil hydraulic and hydro-dispersive properties, which are critical to hydrological models for agro-environmental applications.

Highlights

Irrigated agriculture plays a crucial role in the food supply in many countries where ecological conditions are characterized by warm and dry summers with high solar radiation and evapotranspiration rates
The results suggest that time-lapse Electromagnetic Induction (EMI) measurements could be used as a rapid, non-invasive, field-scale method to assess soil hydraulic and hydro-dispersive properties, which are critical to hydrological models for agro-environmental applications
We propose a procedure based on a sequence of water infiltration and solute transport experiments, both monitored by an EMI sensor, with the objective of estimating field soil hydraulic and solute dispersivity parameters with a non-invasive sensor and relatively short field experiments

Summary

Introduction

Irrigated agriculture plays a crucial role in the food supply in many countries where ecological conditions are characterized by warm and dry summers with high solar radiation and evapotranspiration rates. Soil hydrological behavior is generally described by solving the Richards’ equation (RE) for water flow and the Advective-Dispersive equation (ADE) for solute transport, which is frequently assumed to apply at different spatial scales, from laboratory to field to larger scales (Sposito, 1998). These equations require the soil water retention and the soil hydraulic conductivity functions, as well as the hydro-dispersive properties, to be known at the scale of concern (Basile et al, 2003, 2006; Zech et al, 2015). This is especially important in the case of solute transport, where the transport process may change significantly depending on the solute travel times correlation among different layers (Coppola et al, 2011b)

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Conclusion