SYNERGISTIC OBSERVATIONS AND MODELING OVER A SNOW-DOMINATED MOUNTAIN BASIN

Over the last 50 years in the mountainous western US, climate change has modified the temporal and spatial distribution and magnitude of forcings, thereby altering the snowmelt-dominated hydrologic cycle in these watersheds by changing how seasonal snowcover and associated thermodynamics and melt processes are distributed over mountain landscapes. To understand how these hydro-climatic changes will impact streamflow and water supply, we coupled the Pennsylvania State University Integrated Hydrology Model to the Isnobal energy balance snow model and applied it over a headwater basin in the Reynolds Creek Experimental Watershed. The test basin is a highly instrumented watershed with a rich history of intensive winter field experiments, instrumentation and model development, testing and validation. Long-term data include meteorological variables snow depth and mass, soil moisture and temperature and groundwater at multiple measurement sites, in addition to stream discharge at the outlet. The objective of this effort is to understand how the complex distribution of forcing parameters and associated hydrologic and thermodynamic processes determine the hydrologic state of a mountain basin. We first develop a suite of software tools and models to generate spatially distributed forcing fields of radiation, temperature, humidity, wind, precipitation and snow, based on convolving observations with topography and vegetation canopy structure. We then use the distributed fields to force the model to simulate coherent, coupled surface and sub-surface hydrologic processes across the basin. Because of the extensive forcing data in the test basin, we can characterize the sensitivity of predicted spatial patterns of snow deposition and melt, soil moisture and temperature, evaporative losses to the atmosphere, and predicted streamflow from the basin to different levels of complexity in the forcing data. This experiment allows us to develop a strategy for synergistic observation and modeling, which will help characterize the response of western mountain basins to climate warming. It will allow us to determine the optimal configuration of observation sites and the value of measuring additional parameters in mountain basins, and will ultimately lead to improved simulation modeling for water supply forecasts.