Parameterisation, evaluation and comparison of pesticide leaching models to data from a Bologna field site, Italy.
Effective prediction of pesticide fate using mathematical models requires good process descriptions in the models and good choice of parameter values by the user. This paper examines the ability of seven pesticide leaching models (LEACHP, MACRO, PELMO, PESTLA, PLM, PRZM and VARLEACH) to describe an arable field environment where sunflowers are grown in the Po Valley, northern Italy. Two pesticides were considered, aclonifen and ethoprophos. The models were evaluated in terms of their ability to reproduce field data of soil water content and pesticide residues in the soil and ground water. The evaluation was based on a combination of calibrated and uncalibrated runs. The results from the models were compared with each other to explore the differences between the models. The models varied in their ability to predict soil water content in the summer: the capacity models PRZM, PELMO and VARLEACH predicted less drying than MACRO, PESTLA, PLM and LEACHP. The models varied in their ability to simulate the persistence of the pesticides in the soil. Differences in the simulated pesticide degradation rate were observed between the models, due to variations in the simulated soil water content and soil temperature, and also differences in the equation linking degradation rate to soil water content. There were large differences among the predictions of the models for the mean leaching depth of ethoprophos. PRZM, PELMO, PESTLA and LEACHP all showed similar mean leaching depth to each other, whereas VARLEACH predicted lower ethoprophos mobility and PLM and MACRO predicted greater mobility. All the models overpredicted dispersion of ethoprophos through the soil profile, as compared to the field data. None of the models was able to simulate the field data of rapid leaching of pesticide to ground water except PLM after calibration of the percentage of macropores in the mobile pore space. More work is required in the parameterisation of macropore flow for those models that include this process.
Garratt
James A
JA
Department of Agricultural and Environmental Science, University of Newcastle upon Tyne, Newcastle upon Tyne NE1 7RU, UK. j.a.garratt@ncl.ac.uk
Capri
Ettore
E
Trevisan
Marco
M
Errera
Giuseppe
G
Wilkins
Richard M
RM
D000814:Aniline Compounds / Q000032:analysis; D002138:Calibration; D006540:Herbicides / Q000032:analysis; D007558:Italy; D008962:Models, Theoretical; D063086:Organothiophosphates; D009946:Organothiophosphorus Compounds / Q000032:analysis; D010575:Pesticides / Q000032:analysis*; D012621:Seasons; D012989:Soil Pollutants / Q000032:analysis*; D014874:Water Pollutants, Chemical / Q000032:analysis*
D000814:Aniline Compounds; D006540:Herbicides; D063086:Organothiophosphates; D009946:Organothiophosphorus Compounds; D010575:Pesticides; D012989:Soil Pollutants; D014874:Water Pollutants, Chemical; C001182:ethoprop; C106872:aclonifen