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This dataset offers a comprehensive collection of water quality data for approximately 500 stations across the Continental United States (CONUS). It includes 20 common water quality parameters, along with meteorological, hydrological, and land use variables such as streamflow, precipitation, temperature, evapotranspiration, and vegetation indices. To support water quality modeling research, we provide model outputs from both conventional statistical (WRTDS) and advanced deep learning (LSTM) approaches. This dataset is designed to facilitate model development, validation, and application, and to promote reproducible research.
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# Introduction
This dataset contains water quality data collected from approximately 500 stations across the Continental United States (CONUS). The data includes measurements of 20 water quality parameters and corresponding meteorological, hydrological, and land use data. The dataset aims to support research and modeling efforts related to water quality.
# Data Sources
Streamflow and water quality data: USGS
Daily climate forcing: gridMET
Chemical composition of precipitation: National Trends Network (NTN)
Daily remote sensing vegetation indexes: GLASS
# Data Structure
The data is organized into two primary folders:
## stations
This folder contains individual CSV files for each station of size [#time, #variables], with each file covering the period from 1982-01-01 to 2018-12-31. Each row represents a day, and each column contains a specific variable.
- streamflow from USGS:
- streamflow: Streamflow in cubic meters per second (m3/s)
- runoff: Runoff in millimeters (mm)
- Daily climate forcing from gridMET
- pr: Precipitation in millimeters (mm)
- sph: Specific humidity at 2 meters (kg/kg)
- srad: Surface downward shortwave radiation (W/m²)
- tmmn: Minimum temperature at 2 meters (degrees Celsius)
- tmmx: Maximum temperature at 2 meters (degrees Celsius)
- pet: Potential evapotranspiration (mm)
- etr: Actual evapotranspiration (mm)
- Chemical composition of precipitation from the National Trends Network (NTN)
- ph: pH
- Conduc: Conductivity (µS/cm)
- Ca: Calcium concentration (mg/L)
- Mg: Magnesium concentration (mg/L)
- K: Potassium concentration (mg/L)
- Na: Sodium concentration (mg/L)
- NH4: Ammonium concentration (mg/L)
- NO3: Nitrate concentration (mg/L)
- Cl: Chloride concentration (mg/L)
- SO4: Sulfate concentration (mg/L)
- distNTN: Distance to the nearest nutrient sampling site (km)
- Daily remote sensing vegetation indexes from GLASS
- LAI: Leaf Area Index
- FAPAR: Fraction of Absorbed Photosynthetically Active Radiation
- NPP: Net Primary Productivity
- Others
- datenum: Date in datenum format
- sinT: Sine of time
- cosT: Cosine of time
## results
This folder contains the model outputs in CSV format. Each file are of size [#time, #site], has the following structure:
- LSTM_{code}.csv: LSTM predictions for water quality parameter with code {code}.
- WRTDS_{code}.csv: WRTDS predictions for water quality parameter with code {code}.
- Obs_{code}.csv: Observed values for water quality parameter with code {code}.
- streamflow.csv: Streamflow data for all stations.
- maskTrain.csv: Training mask indicating training periods.
- maskTest.csv: Testing mask indicating testing periods.
#Contact
For questions or issues, please contact Kuai Fang kuaifang@stanford.edu.
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Funding Agencies
This resource was created using funding from the following sources:
Human-Centered AI (HAI) program and Data Science fellowship
Contributors
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creation of the resource's content but are not considered authors.
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