A comparison of predicted and measured levels of runoff-related pesticide concentrations in small lowland streams on a landscape level

Short-term pollution events via runoff are typical of streams in agricultural areas. Existing runoff models that simulate pesticide loss from agricultural fields require extensive input of information. There is thus a need for a simple model that can predict runoff-related pesticide concentrations in many streams on a landscape level when only limited data are available. To validate such a model, the runoff-related pesticide load of 18 small lowland streams was predicted with an extended version of the model "simplified formula for indirect loadings caused by runoff" (available from the Organisation for Economic Cooperation and Development, OECD). The authors suggest that the model presented here is suitable for use in routine exposure assessment of pesticides on a landscape level, as all input data (soil, slope, precipitation, pesticide application) are readily available from public authorities or could be generated by simple regional flood hydrograph curves. The predicted concentrations were compared with measured concentrations obtained by runoff-triggered sampling. Fungicides, insecticides and herbicides were detected in 17 streams, with max. concentrations measuring up to 29.7 microg/l for the fungicide azoxystrobin and 0.3 microg/l for the insecticide parathion-ethyl. Herbicides were detected in 16 streams, with max. concentrations between 13.7 and 1.2 microg/l. The linear regression between the predicted and measured concentrations (log-values) shows significant correlations for the following pesticides: azoxystrobin: r2=0.43; p=0.03; epoxiconazole: r2=0.71; por=0.5 microg/l).     

Giardia and Cryptosporidium in pristine protected catchments in central eastern Australia

We report the first confirmed records of the pathogenic protozoa Giardia lamblia and Cryptosporidium parvum from small remote streams in pristine protected areas in Australia, beyond the reach of urban or agricultural contamination.