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RESEARCH ARTICLE

Using maize to evaluate the Mohammadi–Khataar (M–K) model as a salinity weighting function (ωsi) for the integral water capacity

Zahra Asadi https://orcid.org/0000-0003-4423-7205 A , Mohammad Hossein Mohammadi A * , Mehdi Shorafa A and Mohsen Farahbakhsh A
+ Author Affiliations
- Author Affiliations

A Department of Soil Science Engineering, University of Tehran, 1417965463, Karaj, Iran.

* Correspondence to: mhmohmad@ut.ac.ir

Handling Editor: Cameron Grant

Soil Research 60(7) 719-730 https://doi.org/10.1071/SR21046
Submitted: 18 February 2021  Accepted: 2 March 2022   Published: 11 May 2022

© 2022 The Author(s) (or their employer(s)). Published by CSIRO Publishing

Abstract

Context: Soil water availability, as characterised by the integral water capacity, uses weighting functions based on models not yet evaluated using plants, especially in the context of saline soils. Without plant evaluation such weighting functions remain theoretical at best.

Aims: We aimed to use maize plants to evaluate Mohammadi and Khataar’s (2018) conceptual model for a salinity weighting function, against those used in Hydrus 1D.

Methods: We conducted glasshouse experiments with large columns of two sandy loams planted with maize irrigated using different salinities, and repeated without plants. Soil matric suction ranged between saturation and 100 cm, and we measured or predicted plant height, transpiration, evaporation, drainage, storage, and solute concentration over time. The soil water retention curve was measured and the weighted mean hydraulic conductivity was obtained using the van Genuchten model.

Key results: We found a correlation between our salinity weighting function and the relative transpiration rate of maize (grown in two different soils using irrigation water of three different salinities), particularly in the first few days of growth but not thereafter; errors were related to uncertainties in predicting drainage, salt concentration, and soil water storage in planted columns.

Conclusions: The deviation of transpiration rate from that predicted by our salinity weighting function at higher salinities may relate to the linear nature of the Maas–Hoffman salinity weighting function plus heterogeneity of soil water and solute distributions.

Implications: Improving the estimates of drainage and soil water storage in future would make our physical model more useful in larger scale hydrological predictions.

Keywords: drainage, evapotranspiration, field capacity, irrigation, modeling, root water uptake, salinity, soil hydraulic properties, soil water availability.


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