Assessing and monitoring agroenvironmental determinants of recreational freshwater quality using remote sensing.

Diverse fecal and nonfecal bacterial contamination and nutrient sources (e.g. agriculture, human activities and wildlife) represent a considerable non-point source load entering natural recreational waters which may adversely affect water quality. Monitoring of natural recreational water microbial quality is most often based mainly on testing a set of microbiological indicators. The cost and labour involved in testing numerous water samples may be significant when a large number of sites must be monitored repetitively over time. In addition to water testing, ongoing monitoring of key environmental factors known to influence microbial contamination may be carried out as an additional component. Monitoring of environmental factors can now be performed using remote sensing technology which represents an increasingly recognized source of rigorous and recurrent data, especially when monitoring over a large or difficult to access territory is needed. To determine whether this technology could be useful in the context of recreational water monitoring, we evaluated a set of agroenvironmental determinants associated with fecal contamination of recreational waters through a multivariable logistic regression model built with data extracted from satellite imagery. We found that variables describing the proportions of land with agricultural and impervious surfaces, as derived from remote sensing observations, were statistically associated (odds ratio, OR = 11 and 5.2, respectively) with a higher level of fecal coliforms in lake waters in the southwestern region of Quebec, Canada. From a technical perspective, remote sensing may provide important added-value in the monitoring of microbial risk from recreational waters and further applications of this technology should be investigated to support public health risk assessments and environmental monitoring programs relating to water quality.

A hydrological modeling framework for defining achievable performance standards for pesticides.

This paper proposes a hydrological modeling framework to define achievable performance standards (APSs) for pesticides that could be attained after implementation of recommended management actions, agricultural practices, and available technologies (i.e., beneficial management practices [BMPs]). An integrated hydrological modeling system, Gestion Intégrée des Bassins versants à l'aide d'un Système Informatisé, was used to quantify APSs for six Canadian watersheds for eight pesticides: atrazine, carbofuran, dicamba, glyphosate, MCPB, MCPA, metolachlor, and 2,4-D. Outputs from simulation runs to predict pesticide concentration under current conditions and in response to implementation of two types of beneficial management practices (reduced pesticide application rate and 1- to 10-m-wide edge-of-field and/or riparian buffer strips, implemented singly or in combination) showed that APS values for scenarios with BMPs were less than those for current conditions. Moreover, APS values at the outlet of watersheds were usually less than ecological thresholds of good condition, when available. Upstream river reaches were at greater risk of having concentrations above a given ecological thresholds because of limited stream flows and overland loads of pesticides. Our integrated approach of "hydrological modeling-APS estimation-ecotoxicological significance" provides the most effective interpretation possible, for management and education purposes, of the potential biological impact of predicted pesticide concentrations in rivers.