Develop predictive models for water quality at your beach using high-frequency (HF) sample data
The scripts in the repository are what I used when aggregating data, exploring trends, and developing and testing models for Searcy and Boehm, 2021. "A Day at the Beach: Enabling Coastal Water Quality Prediction with High-Frequency Sampling and Data-Driven Models" (DOI: https://doi.org/10.1021/acs.est.0c06742).
These should be useful to help get you started in designing your own predictive water quality modeling system. Eventually, this repository will contain a complete package that will enable users to build and test models from scratch.
For questions, please reach out to me at rtsearcy@stanford.edu
Best of luck,
Ryan Searcy January 2021
*** signifies important scripts
Scripts to grab and process data from:
- CDIP (cdip.ucsd.edu, wave data)
- NOAA CO-OPS (https://tidesandcurrents.noaa.gov, tide and met data)
- NCDC (https://www.ncdc.noaa.gov/, met data)
- CIMIS (https://cimis.water.ca.gov/, met data)
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HF_EDA_dataset_combo.py Aggregate FIB and environmental data into a single dataframe
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HF_compare_beaches_bin_plots.py *** Plots and some stats for EDA on the HF sampling and environmental data
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HF_EV_stats_plots.py Bin analysis, correlations, boxplots for environmental data
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HF_EDA_FIB_stats.py *** Statistics related to the FIB variability for all HF events
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wq_modeling.py *** Package of functions to create statistical water quality nowcast models from FIB and environmental data.
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HF_models.py Functions that tests all model types on an input test case
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HF_predictive_models.py Script to develop and test individual models
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HF_model_all.py *** Script to iterate through all HF test cases and develop and test models
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HF_analyze_all_models.py *** Script to aggregate modeling results to summarize
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HF_model_predictions_obs.py Script to plot predictions and observations for specific models