| Popis: |
Stormwater control measures, such as raingardens, tanks, or wetlands, are often employed to mitigate the deleterious effects of urban stormwater drainage on stream ecosystems. However, performance metrics for control measures, most commonly pollutant-load reduction, have not permitted prediction of how they will change stream ecosystems downstream. Stream ecosystem responses have more commonly been predicted by catchment-scale measures such as effective imperviousness (percentage of catchment with impervious cover draining to sealed drains). We adapt effective imperviousness, weighting it by a performance metric for stormwater control measures aimed at stream protection, the stream stormwater impact metric. Weighted effective imperviousness can serve as a predictor of stream response to stormwater control. We demonstrate its application in a before-after-control-reference-impact experiment aiming to test if stream health is improved by dispersed stormwater control measures. Trends in weighted effective imperviousness showed wide variation in degree of stormwater control achieved in the six experimental sub-catchments, despite similar effort in implementing control measures across the sub-catchments. Greater reductions in weighted effective imperviousness (on a log-scale, on which stream response is predicted) per unit effort were observed in smaller catchments with lower starting effective imperviousness. While implementation of control measures was sufficient to expect a stream response in at least two of the experimental sub-catchments, we did not achieve the reduction in effective imperviousness that we were aiming for. Primary limitations to success were the lack of available space in these established suburbs, particularly for final control measures near pipe outlets into streams, and a lack of demand for harvested stormwater. The use of the continuous variable, weighted effective imperviousness, to measure impact on streams, and the protracted period of SCM implementation that varied among catchments, required a new approach to modelling “before-after-control-impact” experiments, which has potentially broader application. |
