Testing and developing an instrumented microlysimeter for automated estimation of in situ soil evaporation - Cominelli, Sofía (Kansas State University, 2024)
In rainfed cropping systems of the U.S. Great Plains, precipitation represents the main input and evapotranspiration, runoff, and drainage represent the main outputs of the soil water balance. In the state of Kansas, about 87% of the annual precipitation returns to the atmosphere through the evapotranspiration process, where unproductive soil evaporative losses can account for 30% to 50% of total evapotranspiration. Given this context, it is essential to identify and assess new crop rotations and agronomic practices aimed at shifting non-productive evaporative losses into productive transpirational losses. Commonly, soil evaporation is measured using the microlysimeter technique, but this technique is labor intensive and only suitable for short periods. Since soil evaporation rate depends on surface soil moisture conditions, this thesis is centered around a pivotal question: Can we use soil moisture observations from electromagnetic sensors to accurately estimate in situ soil evaporation through a data-driven approach? The first chapter of this thesis explores the accuracy of two new electromagnetic sensors, the TEROS 10 and TEROS 12, in sand, loam, and silty clay loam soils at various moisture levels. The second chapter introduces five different data-driven approaches that combine the FAO-56 Dual Crop Coefficient model with 1) in situ observations from a calibrated soil moisture sensor and 2) measurements of green canopy cover to quantify soil evaporation rates in winter wheat and bare soil. Overall, the results of our study demonstrate the feasibility of using a simple model coupled with in situ soil moisture observations to estimate soil evaporation rates during the entire growing season.
Keywords: Soil moisture sensor; Evaporation; Microlysimeter; Data-driven model