Coupling of the Terrestrial Carbon, Water, and Energy Cycles from the Field to Satellite Footprint Scale

Abstract

The terrestrial carbon, energy, and water cycles are coupled through soil moisture (SM) and evapotranspiration (ET) control on gross primary productivity (GPP) thus controlling the biosphere, land-atmosphere interactions, and climate variations. ET and SM are often estimated using insitu and remote sensing techniques. However, estimates of ET and SM are difficult to quantify at spatio-temporal scales (~daily 30-m) required for precision agricultural water management. Furthermore, GPP, ET, and SM coupling relationships as influenced by physical controls (soil texture, vegetation, climate, etc.) and how these coupling relationships change with scale have not been explored globally using data-driven approaches to date. Thus, this dissertation was aimed at determining ET and SM at high spatiotemporal scales, and the carbon, water and energy coupling at the field and satellite footprint scales. The specific objectives were to: (1) develop a new algorithm to generate high spatio-temporal (daily 30 m) ET by fusing high temporal resolution eddy covariance and high spatial resolution Landsat data; (2) develop an algorithm to generate daily spatially distributed rootzone SM at the 30-m resolution by integrating remote sensing and insitu observations, and time varying soil hydraulic properties; (3) determine the ET-SM coupling relationships and SM limiting thresholds for ET, and their dominant physical controls between the field and satellite footprint scale; and (4) study the carbon, water, and energy coupling relationships at the remote sensing footprint scale across global climate, ecosystems and soil textural types. Our results showed that we can estimate spatially distributed ET at 30-m resolution by fusing eddy covariance and Landsat data and estimate spatially distributed SM at 30-m resolution within agricultural fields using a water balance model and time varying plant available water with reasonable accuracy. We found the predominant functional pathways of carbon, water, and energy coupling across the globe and how they are influenced by land surface heterogeneity and climate. GPP, ET, and SM were found to be strongly coupled in dryland (arid and semiarid) regions as compared to humid regions. We also determined SM and ET thresholds below which land-atmosphere coupling is strongest and plants are water stressed. We further showed that not all geographical locations experience the entire traditional coupling functional form found in seminal studies. The spatially distributed ET and SM algorithms are relevant for precision agriculture water management that requires spatio-temporal ET and SM to determine crop water requirements. Carbon, water, and energy coupling results are useful for constraining earth systems models, and for climatological, economic, hydrological, flood and drought modeling.