Literature DB >> 29156441

Modeling spray drift and runoff-related inputs of pesticides to receiving water.

Xuyang Zhang1, Yuzhou Luo2, Kean S Goh2.   

Abstract

Pesticides move to surface water via various pathways including surface runoff, spray drift and subsurface flow. Little is known about the relative contributions of surface runoff and spray drift in agricultural watersheds. This study develops a modeling framework to address the contribution of spray drift to the total loadings of pesticides in receiving water bodies. The modeling framework consists of a GIS module for identifying drift potential, the AgDRIFT model for simulating spray drift, and the Soil and Water Assessment Tool (SWAT) for simulating various hydrological and landscape processes including surface runoff and transport of pesticides. The modeling framework was applied on the Orestimba Creek Watershed, California. Monitoring data collected from daily samples were used for model evaluation. Pesticide mass deposition on the Orestimba Creek ranged from 0.08 to 6.09% of applied mass. Monitoring data suggests that surface runoff was the major pathway for pesticide entering water bodies, accounting for 76% of the annual loading; the rest 24% from spray drift. The results from the modeling framework showed 81 and 19%, respectively, for runoff and spray drift. Spray drift contributed over half of the mass loading during summer months. The slightly lower spray drift contribution as predicted by the modeling framework was mainly due to SWAT's under-prediction of pesticide mass loading during summer and over-prediction of the loading during winter. Although model simulations were associated with various sources of uncertainties, the overall performance of the modeling framework was satisfactory as evaluated by multiple statistics: for simulation of daily flow, the Nash-Sutcliffe Efficiency Coefficient (NSE) ranged from 0.61 to 0.74 and the percent bias (PBIAS) < 28%; for daily pesticide loading, NSE = 0.18 and PBIAS = -1.6%. This modeling framework will be useful for assessing the relative exposure from pesticides related to spray drift and runoff in receiving waters and the design of management practices for mitigating pesticide exposure within a watershed. Published by Elsevier Ltd.

Entities:  

Keywords:  Modeling; Pesticide; Runoff; Spray drift; Water quality

Mesh:

Substances:

Year:  2017        PMID: 29156441     DOI: 10.1016/j.envpol.2017.11.032

Source DB:  PubMed          Journal:  Environ Pollut        ISSN: 0269-7491            Impact factor:   8.071


  4 in total

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Journal:  Water Res       Date:  2021-10-16       Impact factor: 11.236

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Journal:  RSC Adv       Date:  2019-11-11       Impact factor: 4.036

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Authors:  Christoph Leeb; Laura Schuler; Carsten A Brühl; Kathrin Theissinger
Journal:  PLoS One       Date:  2022-08-11       Impact factor: 3.752

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Authors:  Longlong Li; Ruirui Zhang; Liping Chen; Boqin Liu; Linhuan Zhang; Qing Tang; Chenchen Ding; Zhen Zhang; Andrew J Hewitt
Journal:  Front Plant Sci       Date:  2022-07-18       Impact factor: 6.627

  4 in total

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