The importance of sub-watershed variability for predicting ecohydrologic responses to inter-annual climate variability and climate warming in California’s Sierra Nevada watersheds

This dissertation improves the understanding of how accounting for fine-scale variability of topography and soil is important for modeling ecohydrologic responses to climate change and variability in California’s Sierra Nevada watersheds. In the first chapter, I apply the Regional Hydrologic-Ecologic Simulation System (RHESSys) to eight small watersheds and investigate how the spatial resolution of digital elevation model (DEM) resolution affects the accuracy of modeling streamflow and model estimates of ecohydrologic responses to inter-annual climate variability. Modeled streamflow estimates become worse with DEM resolution coarser than 10m, the explanation lying in the corresponding reduction in the spatial variance of the wetness index. In the second chapter, I use Generalized Likelihood Uncertainty Estimation (GLUE) to investigate the effect of soil parameter uncertainty in modeling ecohydrologic estimates in the two small watersheds with different snow regimes. The predictive uncertainty of annual evapotranspiration and net primary production estimates for a transient snow watershed are larger than those for a snow-dominated watershed, but the predictive uncertainty in model estimates for daily streamflow is larger for the snow-dominated watershed. The effect of soil parameter uncertainty varies seasonally, between wet and dry years, and its effect on ecohydrologic estimates is often large relative to the effect of climate warming. In the third chapter, I investigate the different hydrologic responses to climate warming between a snow-dominated watershed and a transient snow watershed. The modeling results show that the snow-dominated watershed has greater sensitivity to climate warming than the transient snow watershed. In the both watersheds, leaf area index and wetness index are primary factors controlling spatial patterns of seasonal evapotranspiration under both of historical climate conditions and climate warming scenarios. Climate warming results in increased spatial variability in monthly evapotranspiration, especially in the summer period. In the last chapter, I develop a strategic sampling design for collecting soil moisture and sapflux data to capture watershed ecohydrologic responses to inter-annual climate variability in a transient snow watershed. The comparison of model-based calculated hydrological similarity indicators with measured values shows that spatial patterns of field-sampled soil moisture data are similar to those of model-based estimates. However, the model fails to capture the soil moisture and sapflux dynamics in the riparian zone site, and in a site where lateral subsurface flow may not follow surface topography. Future research will reduce these errors by the use of finer-scale representations of microclimate, topography, vegetation, and soil properties in the model

Riverine organic matter functional diversity increases with catchment size

A large amount of dissolved organic matter (DOM) is transported to the ocean from terrestrial inputs each year (~0.95 Pg C per year) and undergoes a series of abiotic and biotic reactions, causing a significant release of CO2. Combined, these reactions result in variable DOM characteristics (e.g., nominal oxidation state of carbon, double-bond equivalents, chemodiversity) which have demonstrated impacts on biogeochemistry and ecosystem function. Despite this importance, however, comparatively few studies focus on the drivers for DOM chemodiversity along a riverine continuum. Here, we characterized DOM within samples collected from a stream network in the Yakima River Basin using ultrahigh-resolution mass spectrometry (i.e., FTICR-MS). To link DOM chemistry to potential function, we identified putative biochemical transformations within each sample. We also used various molecular characteristics (e.g., thermodynamic favorability, degradability) to calculate a series of functional diversity metrics. We observed that the diversity of biochemical transformations increased with increasing upstream catchment area and landcover. This increase was also connected to expanding functional diversity of the molecular formula. This pattern suggests that as molecular formulas become more diverse in thermodynamics or degradability, there is increased opportunity for biochemical transformations, potentially creating a self-reinforcing cycle where transformations in turn increase diversity and diversity increase transformations. We also observed that these patterns are, in part, connected to landcover whereby the occurrence of many landcover types (e.g., agriculture, urban, forest, shrub) could expand DOM functional diversity. For example, we observed that a novel functional diversity metric measuring similarity to common freshwater molecular formulas (i.e., carboxyl-rich alicyclic molecules) was significantly related to urban coverage. These results show that DOM diversity does not decrease along stream networks, as predicted by a common conceptual model known as the River Continuum Concept, but rather are influenced by the thermodynamic and degradation potential of molecular formula within the DOM, as well as landcover patterns

Effects of Model Spatial Resolution on Ecohydrologic Predictions and Their Sensitivity to Inter-Annual Climate Variability

The effect of fine-scale topographic variability on model estimates of ecohydrologic responses to climate variability in California’s Sierra Nevada watersheds has not been adequately quantified and may be important for supporting reliable climate-impact assessments. This study tested the effect of digital elevation model (DEM) resolution on model accuracy and estimates of the sensitivity of ecohydrologic responses to inter-annual climate variability. The Regional Hydro-Ecologic Simulation System (RHESSys) was applied to eight headwater, high-elevation watersheds located in the Kings River drainage basin. Each watershed was calibrated with measured snow depth (or snow water equivalent) and daily streamflow. Modeled streamflow estimates were sensitive to DEM resolution, even with resolution-specific calibration of soil drainage parameters. For model resolutions coarser than 10 m, the accuracy of streamflow estimates largely decreased. Reduced model accuracy was related to the reduction in spatial variance of a topographic wetness index with coarser DEM resolutions. This study also found that among the long-term average ecohydrologic estimates, summer flow estimates were the most sensitive to DEM resolution, and coarser resolution models overestimated the climatic sensitivity for evapotranspiration and net primary productivity. Therefore, accounting for fine-scale topographic variability in ecohydrologic modeling may be necessary for reliably assessing climate change effects on lower-order Sierra Nevada watersheds (≤2.3 km2)