One of the goals of the Southern Sierra Critical Zone Observatory (SSCZO) is to strategically combine field data and spatial models to improve our ability to predict how ecohydrologic variables (snow, soil moisture, ET, photosynthesis and streamflow) will respond to a warming climate. While there have been a variety of modeling studies in the Sierra that have examined how these variables respond to warming, most studies have been done at relatively coarse spatial scales (120m grids). Further calibration and validation of these models often relies solely on streamflow data. The SSCZO provides an opportunity to assess how well models of coupled eco‐hydrologic processes captures plot‐hillslope scale patterns of ecohydrologic variables, and then to test whether including this level of spatial heterogeneity in a modeling study is important for accurately estimating aggregate watershed responses to climate variability and change. In the Sierra CZO, we have applied Regional Hydro‐Ecologic Simulation System (RHESSys), a physically based spatially distributed model of coupled carbon, nutrient cycling and hydrology. We initially implement the model at a 30m spatial resolution and calibrate subsurface drainage parameters using measured streamflow. We also compare model predictions with several existing CZO data sets including co‐located snow depth, soil moisture sensor, sapflow and flux tower data. Initial comparisons highlight the importance of microclimate variation and point to inadequacies in current approaches used to upscale point meteorology measurements (or downscale gridded estimates) for ecohydrologic modeling. We then use this baseline model to develop a strategy for further data collection that is explicitly directed at evaluating the model’s ability to capture spatial heterogeneity in eco‐hydrologic processes including soil moisture and transpiration. We present our initial results from this model‐driven data collection and show how it can be used to a) identify weakness in model parameterization and b) develop strategies for improving model estimates. We interpret model results in the context of climate variability and change and show how accounting for both local vegetation‐driven heterogeneity in snow accumulation and melt and related processes and hillslope scale topographic‐driven heterogeneity can be important in estimating aggregate watershed responses
Son, K., Tague, C. (2011): Importance of sub‐watershed spatial heterogeneity in ecohydrological modelling using multi‐scale and multi‐criteria data in the context of climate variation and change. National CZO Program 2011 All Hands Meeting.
This Paper/Book acknowledges NSF CZO grant support.