Exploring improved pesticide management in sub-tropical environments with GIS-supported fate modeling

The sensitivity analysis of pesticide models to input parameters related to crop management practices supplies working hypotheses to improve pesticide uses and environmental quality. Parameters of pesticide models that are influential to model output vary depending on regional environmental conditions, and their probability distribution functions must be identified on a case-oriented basis. While the performance of pesticide models has been extensively tested in temperate regions, comparative studies in subtropical areas are relatively scarce. In this study, we coupled results of landscape analyses supported with a geographical information system (GIS), field data and information about management scenarios of citrus crops in Misiones (Argentina) to inspect the behavior of a field-scale pesticide model (GLEAMSv3.0). Probability distribution functions of model parameters relevant to hydrology, geo-forms and crop distribution were derived from satellite imagery (SAC-C, SRTM), while crop characteristics, information on soils and pesticides were obtained from field data. Spatial descriptors were used to generate sensitivity scenarios to explore the potential effect of management practices on the fate of the pesticides chlorpyrifos, mancozeb, mercaptothion, copper hydroxide, carbendazem, glyphosate and 2-4-D used in citrus crops. Our results indicate that management practices to change the roughness-contouring of the soil, maintaining a high vegetation cover below the citrus crops, and devising pesticide spraying techniques that would efficiently increase the contact with the crop leaves would be expected to significantly reduce pesticide losses. Plant spacing, improving soil textural conditions through soil-correction practices and selecting adequate soil conditions for installing new crops are also potentially effective techniques to the same goal. Glyphosate losses are almost insensitive to management manipulation, which is a favorable trait in cases where management alternatives are constrained by practical or economic considerations. We present comparisons of the sensitivity of the pesticide model in these scenarios in relation to previously reported results with the same model in other cases, and formulate proposals on a normalized format to report sensitivity results to facilitate comparisons among models and cases.