Extending the Measurement Range for Determining Soil Hydraulic Properties with the Simplified Evaporation Method Using Relative Humidity Sensors

A precise knowledge of soil hydraulic properties is crucial for many applications, with the unsaturated hydraulic conductivity being most challenging to measure accurately. Direct measurement under dry conditions presents difficulties, lacking simple and precise methods. While the simplified evaporation method (SEM) has become the standard for determining the water retention curve (WRC) and hydraulic conductivity curve (HCC), its classic implementation only provides conductivity values within a relatively narrow suction range measurable by tensiometers, typically between 60 and 1000 cm. In this study, we extended the experimental setup of the SEM by incorporating small sensors to measure temperature and relative humidity alongside the tensiometers. Applying the Kelvin equation, this addition allows for suction measurements between the wilting point and air-dry conditions. Using this setup, we conducted evaporation experiments on soils spanning various textures, from silt loam to pure sand. Analyzing the data through (i) inverse modeling using the Richards equation and (ii) the SEM revealed that combining tensiometers and relative humidity sensors facilitates the determination of HCC over a broad moisture range. This includes the suction range covered between the measurement ranges of the sensors, given proper interpolation between the two sensor types. Crucially, successful inverse modeling relies on a suitable parametric representation of the soil hydraulic properties, considering water adsorption, film, and vapor flow. Our findings indicate that the classic SEM evaluation tends to overestimate HCC in the tensiometer's measuring range and underestimate it in the hygroscopic range, especially in coarse-textured soils with a narrow pore size distribution. Despite this limitation, the proposed test setup, when coupled with the SEM, offers practical advantages due to its relative simplicity and ease of data evaluation.