To predict rice-farming pesticide concentrations in river water with imprecise model inputs for screening-level analysis, a basin-scale runoff model was developed. The Monte Carlo method was applied to create estimates of input data regarding agricultural work schedules and parameters for pesticide decomposition and sorption in solids and water. The prediction accuracy of the model was evaluated when used with non-optimised pesticide parameters; the model was calibrated using hydrological data alone without reference to observed pesticide concentration data. Overall, predictions for the pesticide concentrations were successful within order-of-magnitude accuracy. The pesticide rankings according to the predicted concentration roughly agreed with those observed. The success of screening-level analysis indicates that the model prediction can help in selection of pesticides to be monitored and in determining the monitoring schedule for the river basin.
Skip Nav Destination
Article navigation
Research Article|
May 01 2006
Screening level analysis for monitoring pesticide in river water using a hydrological diffuse pollution model with limited input data
Y. Matsui;
*Department of Environmental Engineering, Hokkaido University, Sapporo, 060-8628, Japan,
E-mail: matsui@eng.hokudai.ac.jp
Search for other works by this author on:
K. Narita;
K. Narita
**Department of Civil Engineering, Gifu University, Gifu, 501-1193, Japan
Search for other works by this author on:
T. Inoue;
T. Inoue
***Toyohashi University of Technology, Toyohashi, 441-8580, Japan
Search for other works by this author on:
T. Matsushita
T. Matsushita
**Department of Civil Engineering, Gifu University, Gifu, 501-1193, Japan
Search for other works by this author on:
Water Sci Technol (2006) 53 (10): 173–181.
Citation
Y. Matsui, K. Narita, T. Inoue, T. Matsushita; Screening level analysis for monitoring pesticide in river water using a hydrological diffuse pollution model with limited input data. Water Sci Technol 1 May 2006; 53 (10): 173–181. doi: https://doi.org/10.2166/wst.2006.310
Download citation file:
Sign in
Don't already have an account? Register
Client Account
You could not be signed in. Please check your email address / username and password and try again.
Impact Factor 1.915
CiteScore 3.4 • Q2
13 days submission to first
decision
1,439,880 downloads in 2021
27
Views
8
Citations