These datasets contain streamflow and related environmental variables for training and testing purposes. They are used in examples to demonstrate the SCE package functionality with different levels of complexity.
data("Streamflow_training_10var")
data("Streamflow_training_22var")
data("Streamflow_testing_10var")
data("Streamflow_testing_22var")Streamflow_training_10var: A data frame with basic environmental variables:
The date and time of the data point
The monthly mean daily precipitation measured in millimeters (mm), 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)
Streamflow_training_22var: A data frame with extended variables including climate indices:
Streamflow measurements
Interdecadal Pacific Oscillation
IPO with 1-month lag
IPO with 2-month lag
Nino 3.4 index
Nino 3.4 with 1-month lag
Nino 3.4 with 2-month lag
Pacific Decadal Oscillation
PDO with 1-month lag
PDO with 2-month lag
Pacific North American pattern
PNA with 1-month lag
PNA with 2-month lag
Monthly precipitation
2-month precipitation
Solar radiation
2-month solar radiation
Maximum temperature
2-month maximum temperature
Minimum temperature
2-month minimum temperature
Vapor pressure
2-month vapor pressure
Streamflow_testing_10var: A data frame with basic environmental variables (same structure as training):
Streamflow measurements
Precipitation
Solar radiation
Maximum temperature
Minimum temperature
Vapor pressure
Index variable
Snow melt
Soil water volume layer 1
Soil water volume layer 2
Soil water volume layer 3
Soil water volume layer 4
Streamflow_testing_22var: A data frame with extended variables including climate indices (same structure as training):
Streamflow measurements
Interdecadal Pacific Oscillation
IPO with 1-month lag
IPO with 2-month lag
Nino 3.4 index
Nino 3.4 with 1-month lag
Nino 3.4 with 2-month lag
Pacific Decadal Oscillation
PDO with 1-month lag
PDO with 2-month lag
Pacific North American pattern
PNA with 1-month lag
PNA with 2-month lag
Monthly precipitation
2-month precipitation
Solar radiation
2-month solar radiation
Maximum temperature
2-month maximum temperature
Minimum temperature
2-month minimum temperature
Vapor pressure
2-month vapor pressure
Dataset Categories:
Training Datasets: Used for building SCA and SCE models
Streamflow_training_10var: Basic dataset with 12 variables, suitable for introductory examples
Streamflow_training_22var: Extended dataset with 24 variables, includes climate indices and lagged values
Testing Datasets: Used for evaluating trained models
Streamflow_testing_10var: Basic dataset with 12 variables, matches training structure
Streamflow_testing_22var: Extended dataset with 24 variables, matches training structure
Variable Categories:
Hydrological: Flow, Precipitation, Snow melt, Soil water volumes
Meteorological: Temperature (max/min), Solar radiation, Vapor pressure
Climate Indices: IPO, Nino3.4, PDO, PNA (with lagged versions)
Time Aggregations: 2-month averages for key variables
Climate Indices:
IPO: Interdecadal Pacific Oscillation - long-term climate pattern
Nino3.4: El Niño-Southern Oscillation index
PDO: Pacific Decadal Oscillation - long-term ocean temperature pattern
PNA: Pacific North American pattern - atmospheric circulation pattern
Data Sources: The data is compiled from various recognized sources including:
ERA5 Land: A global land-surface dataset at 9km resolution, available from the Copernicus Climate Change Service
Daymet Version 4: Daily Surface Weather and Climatological Summaries
United States Geological Survey (USGS): A scientific agency of the United States government that studies natural resources, natural hazards, and the landscape of the United States
Climate indices databases for the extended datasets