Open AccessModeling Subsurface Fate of S ‐Metolachlor and Metolachlor Ethane Sulfonic Acid in the Westliches Leibnitzer Feld Aquifer
Author(s) -
Kupfersberger Hans,
Klammler Gernot,
Schumann Andrea,
Brückner Lisa,
Kah Mélanie
Publication year - 2017
Publication title -
vadose zone journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.036
H-Index - 81
ISSN - 1539-1663
DOI - 10.2136/vzj2017.01.0030
Subject(s) - lysimeter , aquifer , groundwater , environmental science , hydrology (agriculture) , vadose zone , metolachlor , soil science , environmental chemistry , geology , chemistry , pesticide , soil water , geotechnical engineering , ecology , atrazine , biology
Core Ideas Lysimeter experiments allow site‐specific knowledge about the fate of pesticides. Lysimeter‐based model calibration provides integrated parameter sets. Lysimeter scale‐based models were compiled to represent aquifer scale. Lysimeter scale‐based models were coupled with a groundwater transport model. The groundwater model reproduced observed metabolite groundwater concentrations. Pesticides and their metabolites have been increasingly detected in groundwater bodies in southeastern Austria in recent years. The main objective of this study was to model the fate of the herbicide S ‐metolachlor (2‐chloro‐ N ‐(2‐ethyl‐6‐methylphenyl)‐ N ‐[(1 S )‐2‐methoxy‐1‐methylethyl]acetamide; SMET) and the main metabolite metolachlor ethane sulfonic acid (MESA) at the Westliches Leibnitzer Feld (WLF) aquifer. For this purpose, a modeling approach based on coupling the one‐dimensional vadose zone model PEARL and the two‐dimensional groundwater flow and solute transport model FEFLOW was developed. To calibrate the one‐dimensional pesticide fate model, we used leachate concentrations of SMET and MESA from lysimeter experiments. Additionally, samples of representative soil types in the WLF aquifer were analyzed to infer SMET‐ and MESA‐specific fate parameters (e.g., half‐life DT 50 , Freundlich sorption coefficient K foc ), which were used for the PEARL model. The results show that using SMET fate parameters derived from the lysimeter data considerably improved the fit of the simulation results with the field observations compared with the application of standard laboratory‐derived fate parameters accounting for soil type differences. Although locally an overestimation of the monitoring data prevailed, the description of the subsurface fate of pesticides will improve the interpretation of concentration data and the design of mitigation measures.