| The flow of water and energy fluxes at the Earth's surface and within the climate system is difficult to quantify. Recent advances in remote sensing technologies have provided scientists with a useful means to improve characterization of these complex processes. However, many challenges remain that limit our ability to optimize remote sensing data in determining evapotranspiration (ET) and energy fluxes. For example, periodic cloud cover limits the operational use of remotely sensed data from passive sensors in monitoring seasonal fluxes. Additionally, there are many remote sensing-based single-source surface energy balance (SEB) models, but no clear guidance on which one to use in a particular application. Two widely used models---surface energy balance algorithm for land (SEBAL) and mapping ET at high resolution with internalized calibration (METRIC)---need substantial human-intervention that limits their applicability in broad-scale studies. This dissertation addressed some of these challenges by proposing novel ways to optimize available resources within the SEB-based ET modeling framework. A simple regression-based Landsat-Moderate Resolution Imaging Spectroradiometer (MODIS) fusion model was developed to integrate Landsat spatial and MODIS temporal characteristics in calculating ET. The fusion model produced reliable estimates of seasonal ET at moderate spatial resolution while mitigating the impact that cloud cover can have on image availability. The dissertation also evaluated five commonly used remote sensing-based single-source SEB models and found the surface energy balance system (SEBS) may be the best overall model for use in humid subtropical climates. The study also determined that model accuracy varies with land cover type, for example, all models worked well for wet marsh conditions, but the SEBAL and simplified surface energy balance index (S-SEBI) models worked better than the alternatives for grass cover. A new automated approach based on exhaustive search algorithm was also developed that eliminates the need for human-intervention in SEBAL or METRIC models, which could extend the domain of these models to inexperienced users and facilitate operational applications. Future studies are recommended to incorporate ancillary data within the SEB models to account for changes in soil moisture conditions and to test the advantage of multi-model ensemble approaches for ET modeling. |
