#GRIDDED RESPONSE SIMULATOR#

Past studies have compared and evaluated the performance of GMF against weather stations ( Behnke etВ al., 2016 Daly etВ al., 2008 Muche etВ al., 2020).

Recently, GMF products, notably Daily Surface Weather and Climatological SummariesВ (Daymet) ( Thornton etВ al., 1997, 2021), the Parameter-elevation Regressions on Independent Slopes ModelВ (PRISM) ( Daly etВ al., 2008), and the North American Land Data Assimilation SystemВ (NLDAS) ( Mitchell, 2004 Xia etВ al., 2012)), have become popular for hydrologic modeling within the conterminous United StatesВ (CONUS) owing to their temporally and spatially complete coverage and relatively high spatiotemporal resolution. Due to different interpolation methods and data sources, GMF is available at different spatial and temporal resolutions and contains considerable uncertainties ( SchreinerвЂђMcGraw and Ajami, 2020). These models often require gridded meteorological forcingВ (GMF), which is typically fused from various sources, including ground-based gages, radar, satellite remote sensing, as well as regional and global climate models.

#GRIDDED RESPONSE SIMULATOR#

With the advancement of high-performance computing and the development of integrated hydrologic models (e.g., Amanzi-Advanced Terrestrial Simulator вЂ“ ATS Coon etВ al., 2019, ParFlow, Kollet and Maxwell, 2006, and HydroGeoSphere, Aquanty, 2015), simulating the watershed hydrological cycle at high temporal and spatial resolution has become possible ( Wood etВ al., 2011). The accuracy of meteorological forcings such as precipitation plays a crucial role in simulating the watershed hydrological cycle. Our findings suggest that the choice of GMF and its spatiotemporal resolution depends on the quantity of interest and its spatial and temporal scale, which may have important implications for model calibration and watershed management decisions. Conversely, the simulated streamflow shows better performance using daily resolution compared to that using sub-daily resolution. Using the temporally disaggregated PRISM, we compared models forced by different temporal resolutions (hourly to daily), and sub-daily resolution preserves the dynamic watershed responses (e.g., diurnal fluctuation of streamflow) that are absent in results forced by daily resolution. However, the 4вЂ‰km-resolution has much worse performance than finer resolution in spatially distributed variables such as SWE. By comparing various spatial resolutions (ranging from 400вЂ‰m to 4вЂ‰km) of PRISM, the simulated streamflow only becomes marginally worse when spatial resolution of meteorological forcing is coarsened to 4вЂ‰km (or 30вЂ‰% of the watershed area). We compared simulated watershed hydrologic responses including streamflow and distributed variables such as evapotranspiration, snow water equivalentВ (SWE), and groundwater table driven by three publicly available, gridded meteorological forcingsВ (GMFs) вЂ“ Daily Surface Weather and Climatological SummariesВ (Daymet), the Parameter-elevation Regressions on Independent Slopes ModelВ (PRISM), and the North American Land Data Assimilation SystemВ (NLDAS). In this study, we utilized the Advanced Terrestrial SimulatorВ (ATS), an integrated watershed model, to simulate surface and subsurface flow and land surface processes using unstructured meshes at the Coal Creek Watershed near Crested Butte (Colorado).

These hyperresolution watershed models require high resolution of meteorological forcing as model input to ensure the fidelity and accuracy of simulated responses. With the advancement of high-performance computing and the development of integrated watershed models, simulating the watershed hydrological cycle at high temporal (hourly to daily) and spatial resolution (tens of meters) has become efficient and computationally affordable. Meteorological forcing plays a critical role in accurately simulating the watershed hydrological cycle.

Gridded response