Waterborne Merges Our Field Study Monitoring Capabilities with Advanced Data Solutions, Creating Novel WebTool
In response to the growing needs of our clients, Waterborne data scientists recently saw an opportunity to develop a Monitoring WebTool that aids in management decisions related to modeling, field investigations, and stewardship activities.
Our WebTool combines monitoring data with a spatial component that can be rendered on the fly from GIS mapping data, with basic statistical outputs. The interface provides the end user with a number of options for filtering the data, based on location or compound of interest. By integrating field study data and national datasets that have been scrubbed by our scientist, users are given an in-depth view of their product chemistry within the United States.
Our WebTool allows for large sets of monitoring data to be spatially and tabularly contextualized, which provides a multitude of beneficial options for our clients. Product use and chemical presence identified by location help to inform regulatory decisions and the need for any further exposure modeling work or additional field studies. The tool allows for faster identification of potentially vulnerable areas and provides value in time and cost savings associated with delays in the decision-making process.
Stewardship managers can use the tool directly with growers to identify locations for targeting stewardship activities. The data can also be combined with the ‘boots on the ground’ approaches so that end users can examine data trends over a given timeframe and view the impacts of stewardship activities in the watersheds. When best management practices and other measures are put in place such as label changes, for example, we can examine how the changes are reflected in the monitoring data. Our Monitoring WebTool literally puts these answers at the fingertips of our clients in an easy-to-use visual presentation.
The application of GIS is not a completely novel approach and many spatial tools have been used to generate static images (e.g., maps) that are not easily updated with new data. Since this tool is web-based, updated data are provided in real time, which provides our clients with an independent decision-making tool. Our data scientists acknowledge that this is the future direction of data sources with the implementation of machine learning. This gives us the ability to work with our clients in the development of customized features and filters to address specific higher-tier data needs.
To discuss your specific monitoring needs and how our WebTool can provide customized assistance to your organization, please contact Zack Stone (email@example.com) with questions or comments.