Saddle catchment Distributed Hydrology Soil Vegetation Model Simulation (DHSVM) precipitation and transpiration variable outputs (precipitation, total, potential and actual evapotranspiration), 2 meter, 2000-2019.
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资源简介:
The Saddle Catchment of the Niwot Ridge LTER is a densely observed,
high elevation site that is ideal for hydrological model simulation
and calibration. The files produced are the result of a calibration of
the Distributed Hydrology Soil Vegetation model (DHSVM) using
observationally based states and forcings. Input state files of
vegetation, soil properties, shading, and elevation were generated
using ground and satellite observations, which, in the case of
coarse-resolution or point scale observations, were then interpolated
to match the high resolution of the model (2-meter grid cells).
Temporally continuous meteorological forcings at the hourly time-step
were used to force the model to produce an hourly simulation of the
surface and subsurface hydrology within the Saddle catchment. DHSVM
was calibrated to effectively reproduce the annual cycle (r^2) and
total volume (percent bias) of observed runoff using observations of
streamflow at the outflow pour point of the Saddle Catchment from
2001-2019. Calibrated parameters include the lateral conductivity of
soil types, exponential decrease of soil conductivity, snow roughness,
the snow melting temperature threshold, and the vertical conductivity
of the soils. The resulting simulation generated spatially distributed
time series of the snow water equivalent, snow melt, precipitation,
total evapotranspiration, potential evapotranspiration, and a
time-series of the total runoff generated at the outflow pour-point of
the Saddle catchment. This data package contains the spatially
distributed time series of precipitation, total evapotranspiration and
actual evapotranspiration Outputs of snow water equivalent, snow melt,
and runoff, as well as the model configuration file, as well as model
inputs are archived separately on the Environmental Data Initiative.
创建时间:
2022-05-02



