Literature DB >> 28982080

Predicting pesticide fate in small cultivated mountain watersheds using the DynAPlus model: Toward improved assessment of peak exposure.

Melissa Morselli1, Chiara Maria Vitale1, Alessio Ippolito2, Sara Villa2, Roberto Giacchini2, Marco Vighi2, Antonio Di Guardo3.   

Abstract

The use of plant protection products (PPPs) in agricultural areas implies potential chemical loadings to surface waters, which can pose a risk to aquatic ecosystems and human health. Due to the spatio-temporal variability of PPP applications and of the processes regulating their transport to surface waters, aquatic organisms are typically exposed to pulses of contaminants. In small mountain watersheds, where runoff fluxes are more rapid due to the steep slopes, such exposure peaks are particularly likely to occur. In this work, a spatially explicit, dynamic model for predicting pesticide exposure in surface waters of cultivated mountain basins (DynAPlus) has been developed. The model has been applied to a small mountain watershed (133km2) located in the Italian Eastern Alps and characterized by intensive agriculture (apple orchards) around the main river and its tributaries. DynAPlus performance was evaluated for chlorpyrifos through experimental monitoring, using samples collected during the 2011 and 2012 productive seasons. The comparison between predictions and measurements resulted in a good agreement (R2=0.49, efficiency factor 0.60), although a more accurate spatial information in the input scenario (e.g., field-specific applications, rainfall amount, soil properties) would dramatically improve model performance. A set of illustrative simulations performed for three PPPs highlighted the potential role of DynAPlus in improving exposure predictions for ecological risk assessment and pesticide management practices (e.g., for active ingredient and application rate selection), as well as for planning efficient monitoring campaigns and/or interpreting monitoring data. However, some model improvements (e.g., solid erosion and transport) and a more thorough model validation are desirable to enlarge the applicability domain.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Curve number; DOC; Dynamic scenario; Orchard; Runoff; Slope

Year:  2017        PMID: 28982080     DOI: 10.1016/j.scitotenv.2017.09.287

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  3 in total

1.  Mix-Tool: An Edge-of-Field Approach to Predict Pesticide Mixtures of Concern in Surface Water From Agricultural Crops.

Authors:  Antonio Finizio; Andrea Di Guardo; Luca Menaballi; Anna Barra Caracciolo; Paola Grenni
Journal:  Environ Toxicol Chem       Date:  2022-06-09       Impact factor: 4.218

2.  A Mission Planning Approach for Precision Farming Systems Based on Multi-Objective Optimization.

Authors:  Zhaoyu Zhai; José-Fernán Martínez Ortega; Néstor Lucas Martínez; Jesús Rodríguez-Molina
Journal:  Sensors (Basel)       Date:  2018-06-02       Impact factor: 3.576

3.  Exploring Biophysical Linkages between Coastal Forestry Management Practices and Aquatic Bivalve Contaminant Exposure.

Authors:  Kaegan Scully-Engelmeyer; Elise F Granek; Max Nielsen-Pincus; Andy Lanier; Steven S Rumrill; Patrick Moran; Elena Nilsen; Michelle L Hladik; Lori Pillsbury
Journal:  Toxics       Date:  2021-03-02
  3 in total

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