The "Streamflow_training_10var" dataset serves as an example dataset to illustrate the functioning and application of the SCE model within the SCE package. It contains various environmental variables measured on a monthly scale, which are used as inputs in the SCE model for model training.
data("Streamflow_training_10var")A data frame with a number of rows (X) and columns (Y) containing the following variables:
The date and time of the data point.
The monthly mean daily precipitation measured in millimeters (mm). This data is derived from the Daymet dataset.
The monthly mean daily short-wave solar radiation measured in Watts per square meter (W/m^2), sourced from the Daymet dataset.
The monthly mean daily maximal temperature recorded in degrees Celsius, taken from the Daymet dataset.
The monthly mean daily minimal temperature recorded in degrees Celsius, also derived from the Daymet dataset.
The monthly mean daily vapor pressure measured in Pascals (Pa), obtained from the Daymet dataset.
The sum of monthly snowmelt measurements in meters (m), taken from the ERA5 land dataset.
The volumetric soil water content in layer 1 measured in cubic meters per cubic meter (m^3/m^3), sourced from the ERA5 land dataset.
The volumetric soil water content in layer 2, measured similarly to swvl1, sourced from the ERA5 land dataset.
The volumetric soil water content in layer 3, measured similarly to swvl1, sourced from the ERA5 land dataset.
The volumetric soil water content in layer 4, measured similarly to swvl1, sourced from the ERA5 land dataset.
The monthly mean daily streamflow rate measured in cubic feet per second (cfs), provided by the United States Geological Survey (USGS).
# Load the "Streamflow_training_10var" dataset and display the first few rows
data(Streamflow_training_10var)
head(Streamflow_training_10var)
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