Description
This data repository contains the field collected data of sediment quality in irrigation canals. The Python code is to used in the paper entitled "Evaluation of E. Coli in Sediment for assessing irrigation water quality" published in the Science of the Total Environment Journal. For inquiries regarding the contents of this dataset, please contact the Corresponding Author listed in the README.txt file. Administrative inquiries (e.g., removal requests, trouble downloading, etc.) can be directed to [email protected]
| Date made available | 2022 |
|---|---|
| Publisher | University of Arizona Research Data Repository |
Research output
- 1 Article
-
Evaluation of E. coli in sediment for assessing irrigation water quality using machine learning
Tousi, E. G., Duan, J. G., Gundy, P. M., Bright, K. R. & Gerba, C. P., Dec 10 2021, In: Science of the Total Environment. 799, 149286.Research output: Contribution to journal › Article › peer-review
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