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Pesticide transport simulation in a tropical catchment by SWAT
M A Bannwarth1, W Sangchan1, C Hugenschmidt1
1Institute of Soil Science and Land Evaluation, Biogeophysics Section, Hohenheim University, Emil-Wolff-Str. 27, 70593 Stuttgart, Germany.
Environmental Pollution (Barking, Essex : 1987)
|May 10, 2014
Summary
This study simulated pesticide fate in Thailand using the SWAT model, showing acceptable accuracy in predicting agrochemical loads. Findings aid in assessing environmental risks from increasing pesticide use in Southeast Asia.
Area of Science:
- Environmental Science
- Hydrology
- Agrochemistry
Background:
- Agrochemical use in Southeast Asia is rapidly increasing in volume, variety, and toxicity.
- Understanding environmental contaminant behavior necessitates robust monitoring and accurate hydrological modeling.
- Pesticide contamination poses a significant risk to ecosystems and human health.
Purpose of the Study:
- To simulate the environmental fate of key pesticide types (herbicide, fungicide, insecticide) using the Soil and Water Assessment Tool (SWAT) model.
- To assess the model's performance in predicting pesticide load dynamics in a mountainous catchment.
- To identify critical parameters influencing pesticide behavior and inform environmental risk assessments.
Main Methods:
- Utilized the SWAT hydrological model for simulation.
- Focused on a mountainous catchment in Northern Thailand.
- Investigated three distinct pesticide types: herbicide, fungicide, and insecticide.
- Identified and analyzed key parameters: sorption coefficient, decay coefficient, and percolation coefficient.
Main Results:
- Achieved satisfactory simulation results for pesticide load dynamics during the calibration period (Nash-Sutcliffe Efficiency [NSE]: 0.92–0.67).
- Demonstrated acceptable simulation performance during the validation period (NSE: 0.61–0.28).
- Provided insights into the modeling behavior of different pesticide types within the SWAT framework.
Conclusions:
- The study successfully modeled pesticide fate, offering valuable data for environmental risk assessment.
- Findings contribute to understanding pesticide behavior in hydrological models, crucial for managing agrochemical impacts.
- Results help identify worst-case scenarios to mitigate environmental risks associated with pesticide contamination.
