Civil and Environmental Engineering Commons^™

Using Machine Learning And Distributed Hydrologic Modeling To Predict Soil Texture, Surface Soil Moisture And Evapotranspiration In Jornada Experimental Range, Southwestern U.S., Jorge Andres Mayo

Open Access Theses & Dissertations

In water-limited ecosystems, detailed knowledge of the soil, vegetation, and atmosphere interactions is critical to understand the processes that control the partitioning of energy, water fluxes, and biogeochemical cycles within the critical zone. This Master's thesis is divided into two main contributing sections. The first, is on the use of machine learning to reconstruct missing soil type information, and the second, on the calibration and validation of a physically-based distributed hydrological model to estimate soil moisture and evapotranspiration within the Jornada Experimental Range of the U.S. in southern New Mexico. For the first contribution, three explainable, shallow machine-learning techniques are …