Journal article
Web-based data analytics framework for well forecasting and groundwater quality
The Science of the total environment, Vol.761, 144121
03/20/2021
DOI: 10.1016/j.scitotenv.2020.144121
PMID: 33360127
Abstract
Groundwater supplies drinking water for over one-third of all Americans. However, with aquifers stressed by overdraft, contamination from land use, and the hydrologic impacts of climate change, identifying reliable sources for new wells is increasingly challenging. Well forecasting is a process in which potential groundwater resources are evaluated for a location of interest. While this process forecasts the depth of each aquifer for a given location, it takes historical groundwater well data from nearby locations into account. Conventionally, well forecasting is done by geological survey professionals by manually analyzing the well data and, that makes the process both time and resource-intensive. This study presents a novel web application that performs well forecasting for any location within the state of Iowa in a matter of seconds utilizing client-side computing instead of expensive professional labor. The web application generates well forecasts by triangulating millions of combinations of historical aquifer depth data of nearby wells stored in a state-level database. The proposed web system also provides water quality information for arsenic, nitrate, and bacteria (total c and fecal coliform) on the same interface with forecasts. The system is open to the public and is aimed to provide a go-to tool for homeowners, well drillers and, authorities to help inform decision-making regarding groundwater well development and water quality monitoring efforts.
[Display omitted]
•An automized numeric approach for well forecasting is proposed.•A web application that presents results of the approach is developed and deployed.•The web application is further improved with historical water quality test results.•A case study is presented to compare the system's outputs with real-world findings.
Details
- Title: Subtitle
- Web-based data analytics framework for well forecasting and groundwater quality
- Creators
- Muhammed Sit - University of IowaRichard J Langel - University of IowaDarrin Thompson - University of IowaDavid M Cwiertny - University of IowaIbrahim Demir - University of Iowa
- Resource Type
- Journal article
- Publication Details
- The Science of the total environment, Vol.761, 144121
- DOI
- 10.1016/j.scitotenv.2020.144121
- PMID
- 33360127
- NLM abbreviation
- Sci Total Environ
- ISSN
- 0048-9697
- eISSN
- 1879-1026
- Publisher
- Elsevier B.V
- Grant note
- DOI: 10.13039/100008893, name: University of Iowa
- Language
- English
- Date published
- 03/20/2021
- Academic Unit
- Electrical and Computer Engineering; Center for Health Effects of Environmental Contamination; Civil and Environmental Engineering; Occupational and Environmental Health; IIHR--Hydroscience and Engineering; Injury Prevention Research Center; Public Policy Center (Archive); Chemistry; Chemical and Biochemical Engineering
- Record Identifier
- 9984197093402771
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