This readme.txt file was generated on 2022/05/31 by Daniel Furuta
Recommended citation for the data: 


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GENERAL INFORMATION
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1. Title of Dataset 
Final report and simulation program for "Monitoring Methods for Prioritization and Assessment of Stormwater Practices"

2. Author Information


  Principal Investigator Contact Information
        Name: Bruce Wilson
           Institution: University of Minnesota Bioproducts and Biosystems Engineering
           Address: 1390 Eckles Ave, St Paul MN 55108
           Email: wilson@umn.edu
	   ORCID: 0000-0003-0921-3136

  Associate or Co-investigator Contact Information
        Name: Daniel Furuta
           Institution: University of Minnesota Bioproducts and Biosystems Engineering
           Address: 1390 Eckles Ave, St Paul MN 55108
           Email: furut011@umn.edu
	   ORCID: 0000-0002-9603-9262

  Associate or Co-investigator Contact Information
        Name: John Chapman
           Institution: University of Minnesota Bioproducts and Biosystems Engineering
           Address: 1390 Eckles Ave, St Paul MN 55108
           Email: chapm155@umn.edu
	   ORCID: 


3. Date published or finalized for release: 
May 31 2022

4. Date of data collection (single date, range, approximate date) <suggested format YYYYMMDD>
N/A

5. Geographic location of data collection (where was data collected?):  
N/A

6. Information about funding sources that supported the collection of the data: 
This project was supported by the University of Minnesota Water Resources Center through an appropriation from the Clean Water Fund established by Minnesota Clean Water Land and Legacy Amendment and from the Minnesota Stormwater Research Council.  For more information about the Center and the Council, visit https://www.wrc.umn.edu/projects/storm-waste-water 
For more information about the Minnesota Clean Water, Land and Legacy Amendment, visit https://www.legacy.mn.gov/about-funds 

Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the Water Resources Center or Minnesota Stormwater Research Council.

7. Overview of the data (abstract): 
This project developed a framework for simulating stormwater sampling and for evaluating the performance of monitoring methods for runoff pollution. This submission contains the final report and a self-contained program practitioners can use to compare sampling methods, along with source code for the simulation program.

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SHARING/ACCESS INFORMATION
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1. Licenses/restrictions placed on the data:
None

2. Links to publications that cite or use the data:
Publications are forthcoming

3. Was data derived from another source?
           If yes, list source(s):
The rainfall patterns used in the simulation program were derived from 
Floyd A. Huff, “Time Distributions of Heavy Rainstorms in Illinois” (Illinois State Water Survey, 1990), https://www.ideals.illinois.edu/handle/2142/94492

4. Terms of Use: Data Repository for the U of Minnesota (DRUM) By using these files, users agree to the Terms of Use. https://conservancy.umn.edu/pages/drum/policies/#terms-of-use

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DATA & FILE OVERVIEW
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1. File List
   A. Filename: MSRC Monitoring Methods for Stormwater 2022.pdf
      Short description: The final report to the funders for the project, containing information about the simulation framework and some preliminary findings.

   B. Filename: sampling_simulator.zip
	B.1. Filename: sampling_simulator.exe
		Short description: A self-contained program for Windows 10 allowing the user to simulate sampling a runoff event using our framework. 
	B.2. Filename: source_code/sampling_simulator.py
		Short description: Source code for B.1.
	B.3. rain_patterns/huff_1.csv through huff_4.csv
		Short description: Rainfall patterns to use with the simulator, derived from Huff (1990).
	B.4. README.txt
		Short description: A short description of the simulator program, along with information on the package versions used by the source code.


2. Relationship between files:        
The simulation program allows practitioners to evaluate sampling methods using the framework developed in the report.


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METHODOLOGICAL INFORMATION
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1. Description of methods used for collection/generation of data: 
Numerical simulation

2. Methods for processing the data: <describe how the submitted data were generated from the raw or collected data>
See report

3. Instrument- or software-specific information needed to interpret the data:
See report and program README

4. Standards and calibration information, if appropriate:
N/A

5. Environmental/experimental conditions:
N/A

6. Describe any quality-assurance procedures performed on the data:
N/A

7. People involved with sample collection, processing, analysis and/or submission:
Daniel Furuta, Bruce Wilson