Moeys, Julien
- Institutionen för mark och miljö, Sveriges lantbruksuniversitet
Sammanfattning
Modelling of pesticide leaching is paramount to managing the environmental risks associated with the chemical protection of crops, but it involves large uncertainties in relation to climate, agricultural practices, soil and pesticide properties. We used Latin Hypercube Sampling to estimate the contribution of these input factors with the STICS-MACRO model in the context of a 400 km(2) catchment in France, and two herbicides applied to maize: bentazone and S-metolachlor. For both herbicides, the most influential input factors on modelling of pesticide leaching were the inter-annual variability of climate, the pesticide adsorption coefficient and the soil boundary hydraulic conductivity, followed by the pesticide degradation half-life and the rainfall spatial variability. This work helps to identify the factors requiring greater accuracy to ensure better pesticide risk assessment and to improve environmental management and decision-making processes by quantifying the probability and reliability of prediction of pesticide concentrations in groundwater with STICS-MACRO.
Nyckelord
Uncertainty analysis; Latin hypercube sampling; Meta-model; Pesticide leaching; STICS-MACRO
Publicerad i
Environmental Modelling and Software
2018, volym: 109, sidor: 342-352
Utgivare: ELSEVIER SCI LTD
SLU författare
Associerade SLU-program
SLU Nätverk växtskydd
Globala målen (SDG)
SDG6 Rent vatten och sanitet för alla
SDG12 Hållbar konsumtion och produktion
UKÄ forskningsämne
Jordbruksvetenskap
Publikationens identifierare
- DOI: https://doi.org/10.1016/j.envsoft.2018.08.007
Permanent länk till denna sida (URI)
https://res.slu.se/id/publ/96765