Real-time forecasting of pesticide concentrations in soil

Gavan McGrath, P. Suresh C. Rao, Per Erik Mellander, Ivan Kennedy, Michael Rose, Lukas van Zwieten

Research output: Contribution to journalArticlepeer-review

8 Citations (Web of Science)

Abstract

Forecasting pesticide residues in soils in real time is essential for agronomic purposes, to manage phytotoxic effects, and in catchments to manage surface and ground water quality. This has not been possible in the past due to both modelling and measurement constraints. Here, the analytical transient probability distribution (pdf) of pesticide concentrations is derived. The pdf results from the random ways in which rain events occur after pesticide application. First-order degradation kinetics and linear equilibrium sorption are assumed. The analytical pdfs allow understanding of the relative contributions that climate (mean storm depth and mean rainfall event frequency) and chemical (sorption and degradation) properties have on the variability of soil concentrations into the future. We demonstrated the two uncertain reaction parameters can be constrained using Bayesian methods. An approach to a Bayesian informed forecast is then presented. With the use of new rapid tests capable of providing quantitative measurements of soil concentrations in the field, real-time forecasting of future pesticide concentrations now looks possible for the first time. Such an approach offers new means to manage crops, soils and water quality, and may be extended to other classes of pesticides for ecological risk assessment purposes.

Original languageEnglish
Pages (from-to)709-717
Number of pages9
JournalScience of the Total Environment
Volume663
DOIs
Publication statusPublished - 1 May 2019

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