Validation of the SOILWAT Hydrological Model for Ecosystems in the Central and Western United States

Monday, 14 December 2015
Poster Hall (Moscone South)
Matthew D Petrie1, John B Bradford2, Daniel Schlaepfer3, Caitlin Andrews2, Kyle A Palmquist4 and William Karl Lauenroth4, (1)University of Wyoming, Laramie, WY, United States, (2)USGS Colorado Plateau Research Station, Flagstaff, AZ, United States, (3)University of Basel, Section of Conservation Biology, Basel, Switzerland, (4)University of Wyoming, Department of Botany, Laramie, WY, United States

21st century climate change is expected to influence central and western United States ecosystems, yet it is difficult to ascribe climate forcings to ecological processes in part because belowground variables of soil moisture (θ) and soil temperature (Ts) often have stronger influences than those of climate drivers. To link climate change to ecological processes, it is desirable to simulate the effects of climate to these belowground variables. We present results of a validation of the SOILWAT ecosystem-scale water balance simulation model, which simulates water interception and infiltration, evaporation and transpiration, snowmelt, hydraulic redistribution and deep drainage for multiple soil layers and vegetation types at the daily time step. SOILWAT can incorporate weather data, soil characteristics, vegetation phenology, and future climate scenarios derived from 2 emissions pathways and 16 general circulation models. We validated SOILWAT for simulations of θand Ts at five depths (5, 10, 20, 50, 100 cm) using data from 35 stations in eight mesic and semiarid ecosystems that are part of the NOAA United States Climate Reference Network (USCRN). Our validation focused on how SOILWAT simulations compare to USCRN data at upper and lower soil layers, during wet and dry years, and between different ecosystems.

SOILWAT outputs of θand Ts were most similar to USCRN data at upper soil layers (5 - 20 cm) and were less similar at deeper layers (50, 100 cm). Simulations of Ts at lower soil layers largely captured annual mean values, but often did not fully capture the amplitude of Ts in summer, which was coupled to fluctuations in air temperature even at lower soil layers. Best fit analysis showed that SOILWAT biases were similar between semiarid western US sites and between mesic central US sites, which reflects similarities in soil types and climate within these subregions. This suggests that SOILWAT outputs may be applied at subregional spatial scales with good fit between sites. Based on these preliminary findings, we propose that SOILWAT may be appropriate for studies of water balance and temperature change in the central and western US, and can provide reasonable projections of changes in temperature and moisture in ecosystems across these subregions that are likely to result from 21st century climate change.