My research is focused on better understanding the impacts and feedbacks from climate change in complex terrain.
East River Model:
I have just finished the spin-up process for a Parflow-CLM model of the East River Watershed in Gothic, Colorado. The model was built by Christine Pribulick for the East River SFA (scientific focus area for the Department of Energy). It is 273 km2, at 10m resolution, resulting in approximately 14million unknowns. We are currently running the model as a part of the IDEAS project, using the super computer Yellowstone. It runs on 2,304 processors to cover the scale of the computations.
I will be using the model to examine climate impacts at the watershed scale, as a follow-up to my hillslope scale study of the same. Simulations of vegetation succession due to climate change will also be incorporated.
The model will also be used to study biogeochemical cycling in the watershed. The East River SFA is a coalition of many scientists who are all instrumenting, monitoring, and modeling the same region, so model results can be compared with extensive observational data of geology, discharge, isotopes, etc.
Isolating Climate Change Impacts in Simplified Mountain Domains
Foster, L.M., Bearup, L.A., Molotch, N.P., Brooks, P.D. and Maxwell, R.M. Energy Budget Increases Reduce Mean Streamflow More Than Snow-Rain Transitions: Using integrated modeling to isolate climate change impacts on Rocky Mountain hydrology. Environmental Research Letters, 11(40), doi:10.1088/1748-9326/11/4/044015, 2016.
In snow-dominated mountain regions, a warming climate is expected to alter two drivers of hydrology: 1) decrease the fraction of precipitation falling as snow; and 2) increase surface energy available to drive evapotranspiration. This study uses a novel integrated modeling approach to explicitly separate energy budget increases via warming from precipitation phase transitions from snow to rain in two ideal case setups representing mountain headwaters transects of the central Rocky Mountains. Both phase transitions and energy increases had significant, though unique, impacts on semi-arid mountain hydrology in our simulations. A complete shift in precipitation from snow to rain reduced streamflow between 11 and 18%, while 4°C of uniform warming reduced streamflow between 19 and 23%, suggesting that changes in energy-driven evaporative loss, between 27 and 29% for these uniform warming scenarios, may be the dominant driver of annual mean streamflow in a warming climate. Phase changes induced a flashier system, making water availability more susceptible to precipitation variability and eliminating the runoff signature characteristic of snowmelt-dominated systems. The impact of a phase change on mean streamflow was reduced as aridity increased from west to east of the continental divide.
Below is Figure 3 from the Environmental Research Letters paper, the left panel is west of the continental divide, at Pennsylvania Gulch near Breckinridge, CO, the right panel is east of the continental divide, at the North Fork of the Big Thompson River.
Abstract: Sensitivity of hydrologic systems to downscaling atmospheric forcing variables
The impact of climate change on the hydrologic system is still poorly understood. Integrated modeling provides a tool to investigate the way changes propagate through nonlinear systems. These models are driven primarily by atmospheric forcing data at coarser resolution than the models themselves, requiring simplification, downscaling, or regridding of atmospheric variables to the resolution of the hydrologic model. The uncertainty in downscaling methodologies is still poorly understood. This study investigates the range of uncertainty introduced by regridding and downscaling 4km forcing to 1km resolution on a 3500 square kilometer arid mountain domain in Colorado to determine the hydrologic sensitivity to different input variables and different methodologies. Delineating this range is critical to better understanding the magnitude of impact of climate change signals in complex terrain.