LEVERAGING LOW-COST MICRO-CONTROLLERS TO QUANTIFY GROUNDWATER FLUX

Measurements of groundwater flux can assist in the sustainable management of water resources and recovery in artificial and natural settings such as recharge basins or a stream-aquifer system. The monitoring of groundwater flux rates through time can be used to determine when peak infiltration is occurring, clogging of pores, or water discharging from the aquifer to the surface. Determining the magnitude of water moving between the ground and surface has been investigated with different tracers such as dyes, salts, and radiocarbon / isotope tracers, but a method gaining popularity is using the natural temperature changes in the groundwater as a tracer. Using different analytical models, it is possible to quantify flux using diurnal temperature changes in groundwater. This research presents an opportunity to leverage low-cost microcontrollers, small programable computing devices such as Raspberry Pi’s, to determine seepage flux using temperature as a tracer utilizing a python-based program that is free to use and easy to operate. Utilization of a low-cost microcontroller that requires little to zero modeling or programming experience will allow this method to become more widely available to the public. The goal is to expand this methodology to other entities outside of academia, supporting underserved communities, regions, and countries to better manage their water resources with a “plug-and-play” instrument. The instrument posed in this research utilizes a custom-made hardware and software program called “PyLoTemp” that leverages Fast Fourier Transformation and Most Likely Estimation to determine the magnitude and direction of groundwater flux in an easy-to-use instrument that alleviates hassle and difficulty in conducting science. For this research, there was extensive field work performed at three field sites, a smaller clay rich lake (Amherst NY), a quiet and shallow stream (Delevan NY), and a deeper heavy use stream (Rushford NY). There is over four months of field data that was collected, as well as a suite of synthetic data which is being processed by PyLoTemp in concurrence with an analytical model in a MATLAB program called VFLUX2. PyLoTemp solves for much smoother and constant results over VFLUX2 and can be used in the field to determine groundwater flux on a micro-controller.