Lindahl, Anna
- Department of Soil and Environment, Swedish University of Agricultural Sciences
Abstract
Since the 90s an increasing number of assessment methods using operational tools like indicators have been proposed for environmental issues linked to pesticides, among them, groundwater contamination by pesticide transfer. To our knowledge none of these indicators address preferential flow, an important process determining pesticide leaching. The objective of this study is twofold: (i) to develop a new groundwater sub indicator for an existing indicator, I-Phy (former Ipest), that explicitly take preferential flow into account, and (ii) to test the possibility of developing an indicator by means of data-mining methods using simulations of a mechanistic model. The groundwater sub indicator developed is in the form of decision trees based on fuzzy inference systems. It was derived through neuro-adaptive learning on data sets from simulations running the process-based MACRO model. Unlike the previous version, the new indicator considers preferential flow, climatic differences and differences in soil texture with depth. Other benefits are less dependency on expert knowledge and the possibility to integrate a broad range of conditions. (C) 2012 Elsevier Ltd. All rights reserved.
Keywords
Data-mining; Fuzzy inference system; I-Phy indicator; MACRO model; Pesticide leaching; Preferential flow
Published in
Ecological Indicators
2012, volume: 23, pages: 95-108
Publisher: ELSEVIER SCIENCE BV
SLU Authors
UKÄ Subject classification
Environmental Sciences
Publication identifier
- DOI: https://doi.org/10.1016/j.ecolind.2012.03.014
Permanent link to this page (URI)
https://res.slu.se/id/publ/45162