Understanding Catchment Ecohydrological Processes and Their Interactions Across Multiple Spatiotemporal Scales: A Darwinian Approach

The ecohydrological system is a complex adaptive system. Climatic signals propagation through this system takes nonunique pathways, creating nonlinear interactions between climate, soil, water, and vegetation. The synthesis of the links between these components can be approached by a detailed physics-based process understanding or based on emerging patterns and common functionalities across space and time. This dissertation develops a mechanistic understanding of hydrological and ecological processes interactions at the catchment scale based on the latter approach. It has five main objectives: (1) to develop a simple diagnostic framework for exploring links between water balance and vegetation dynamics, (2) to establish a scale-independent function for carbon-water coupling, (3) to explore hydrological processes underpinning vegetation carbon uptake seasonality, (4) to develop and implement a simple dynamic vegetation model global scale, and (5) to enhance global hydrologic model (Xanthos) by adding some aspects of water management. The dissertation begins with the development and validation of two functions. The first function is an analytical framework for the Horton index, derived based on the generalized proportionality hypothesis. The function helped depict the critical role vegetation plays in hydrologic partitioning. It also explained the space-time similarity of the catchment hydrologic state. The second function is a two-parameter linear relationship between carbon uptake and water balance. It simulated seasonal vegetation carbon uptake at catchment and patch levels reasonably. It is also valuable for understanding the catchment transpiration to vaporization ratio. Exploratory data analysis is performed for objective (3). Hysteresis between water supply and productivity and atmospheric demand and productivity was explained by the efficiency of catchment water, energy, and carbon use. It also reveals that vegetation in catchments oscillating between water- and energy-limited states are under hydrologic stress during the peak growing period. Functions from objectives (1) and (2) were coupled with Xanthos. Simulation with this model captured the seasonality and magnitudes of carbon uptake reasonably. Xanthos is further enhanced by adding a water management module that treats irrigation, hydropower, and flood-control reservoirs differently. It is the first attempt to represent hydropower reservoirs in a global model. The model performance is improved significantly in reproducing observed streamflow.