Detection of the effects of stormwater control measure in streams using a Bayesian BACI power analysis

The unpredictable timing and magnitude of precipitation events and the spatiotemporal variability of constituent concentrations are major complications to effective monitoring of watershed nutrient and sediment loads. Furthermore, detecting small changes in constituent loads in response to implementation of Stormwater control measures (SCMs) against natural variability is a challenge. Nevertheless, regulatory frameworks that direct reductions of pollutants to streams frequently depend on the ability to quantify changes in loads after management interventions. The before-after-control impact (BACI) sampling design is often used to assess the effects of an environmental change made at a known point in time. However, this approach may be complicated to apply to nutrient and sediment loads in streams as the relative impact of SCMs on nutrient concentration conditional on the long term variability of discharges has not been evaluated. Multi-scale monitoring studies that provide estimates of the natural temporal and spatial variability of discharge and concentrations could provide useful information in designing a BACI study. Here we use data from the Baltimore Long Term Ecological Research (LTER) sites and urban restoration sites to develop multiple statistical measures of the effectiveness of a given monitoring scheme in revealing the hypothesized restoration effects in terms of hydrology and nutrient loads. Stratified sampling over baseflow and stormflow and the use of multiple control streams were useful tools to detect long term cumulative reductions in concentrations due to SCMs. Moderate reductions in concentration (20%), however, were not detectable with the design options considered. We emphasize that appropriate pre-planning of monitoring schemes and sampling frequency is essential to determine if the effects on constituent loads resulting from a given watershed restoration activity are measurable.