Abstract
The soil water retention curve (SWRC) shows the relationship between soil water (θ) and water potential (ψ) and provides fundamental information for quantifying and modeling soil water entry, storage, flow, and groundwater recharge processes. While traditionally it is measured in a laboratory through cumbersome and time-intensive methods, soil sensors measuring in-situ θ and ψ show strong potential to estimate in-situ SWRC. The objective of this study was to estimate in-situ SWRC at different depths under two different soil types by integrating measured θ and ψ using two commercial sensors: time-domain reflectometer (TDR) and dielectric field water potential (e.g., MPS-6) principles. Parametric models were used to quantify θ—ψ relationships at various depths and were compared to laboratory-measured SWRC. The results of the study show that combining TDR and MPS-6 sensors can be used to estimate plant-available water and SWRC, with a mean difference of −0.03 to 0.23 m3m−3 between the modeled data and laboratory data, which could be caused by the sensors’ lack of site-specific calibration or possible air entrapment of field soil. However, consistent trends (with magnitude differences) indicated the potential to use these sensors in estimating in-situ and dynamic SWRC at depths and provided a way forward in overcoming resource-intensive laboratory measurements.
Highlights
Soil water retention curve (SWRC), a relationship between soil water potential (ψ), and soil water content (θ) is critical for various applications in soil science, hydrogeology, and hydrology [1]
Simple water content may not provide a lot of information, time-domain reflectometer (TDR) and MPS data can be used to estimate plant-available water insitu and in real-time
The resulting averaged models showed a strong correlation between the laboratory-measured data and the modeled data with the van Genuchten parametric model being the closest to the laboratory data and Campbell parametric model showing the best fitting performance towards the field measured data
Summary
Soil water retention curve (SWRC), a relationship between soil water potential (ψ), and soil water content (θ) is critical for various applications in soil science, hydrogeology, and hydrology [1] It is often estimated using basic soil properties such as texture, or a water retention function; it is fitted to experimental data and provides an accurate estimation of soil hydrology. While water-saving irrigation methods like sprinkler or drip can improve applied water use efficiency, irrigation scheduling approaches are attractive methods in agriculture due to their enormous potential to save water [5]. Different methods of irrigation scheduling include the hand feel method, electrical resistance blocks, and the water budget approach [9]. The soil water regime approach based on sensors’ measurements of soil water content and soil water potential shows promise in determining irrigation schedules due to their minimal soil interference and real-time continuous soil measurements
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