Pesticide And Transformation Product Detections And Age-Dating Relations From Till And Sand Deposits

Pesticide and transformation product concentrations and frequencies in ground water from areas of similar crop and pesticide applications may vary substantially with differing lithologies. Pesticide analysis data for atrazine, metolachlor, alachlor, acetochlor, and cyanazine and their pesticide transformation products were collected at 69 monitoring wells in Illinois and northern Indiana to document occurrence of pesticides and their transformation products in two agricultural areas of differing lithologies, till, and sand. The till is primarily tile drained and has preferential fractured flow, whereas the sand primarily has surface water drainage and primary porosity flow. Transformation products represent most of the agricultural pesticides in ground water regardless of aquifer material – till or sand. Transformation products were detected more frequently than parent pesticides in both the till and sand, with metolachlor ethane sulfonic acid being most frequently detected. Estimated ground-water recharge dates for the sand were based on chlorofluorocarbon analyses. These age-dating data indicate that ground water recharged prior to 1990 is more likely to have a detection of a pesticide or pesticide transformation product. Detections were twice as frequent in ground water recharged prior to 1990 (82%) than in ground water recharged on or after 1990 (33%). The highest concentrations of atrazine, alachlor, metolachlor, and their transformation products, also were detected in samples from ground water recharged prior to 1990. These age ⁄ pesticide detection relations are opposite of what would normally be expected, and may be the result of preferential flow and ⁄ or ground-water mixing between aquifers and aquitards as evident by the detection of acetochlor transformation products in samples with estimated ground-water ages predating initial pesticide application

Solving Groundwater Flow Problems with Time Series Analysis: You May Not Even Need Another Model

Time series analysis is a data-driven approach to analyze time series of heads measured in an observation well. Time series models are commonly much simpler and give much better fits than regular groundwater models. Time series analysis with response functions gives insight into why heads vary, while such insight is difficult to gain with black box models out of the artificial intelligence world. An important application is to quantify the contributions to the head variation of different stresses on the aquifer, such as rainfall and evaporation, pumping, and surface water levels. Time series analysis may be applied to answer many groundwater questions without the need for a regular groundwater model, such as what is the drawdown caused by a pumping station? Or, how long will it take before groundwater levels recover after a period of drought? Even when a regular groundwater model is needed to solve a groundwater problem, time series analysis can be of great value. It can be used to clean up the data, identify the major stresses on the aquifer, determine the most important processes that affect flow in the aquifer, and give an indication of the fit that can be expected. In addition, it can be used to determine calibration targets for steady-state models, and it can provide several alternative calibration methods for transient models. In summary, the overarching message of this paper is that it would be wise to do time series analysis for any application that uses measured groundwater heads.Water Resource