Culex Mosquitoes at Stormwater Control Measures and Combined Sewer Overflow Outfalls after Heavy Rainfall

Mosquito borne diseases are increasingly problematic as climate change continues to alter patterns of precipitation, flooding, and temperatures that may favor mosquito habitats. Stormwater control measures (SCMs), ecologically sustainable methods of stormwater management, may have varying impacts on Culex mosquitoes, such as in areas with combined sewer overflows (CSOs). We studied spatial and temporal associations of SCMs and Culex mosquito counts surrounding the SCMs, stratifying our examination amongst those that do/do not use pooling and/or vegetation, as well as surrounding CSO outfalls after heavy rainfall (≥95th percentile) during summer 2018. Results indicate Culex mosquito counts after heavy rainfall were not significantly different at SCMs that use vegetation and/or ponding from at those that do not. We also found a 35.5% reduction in the increase of Culex mosquitoes the day of, and 77.0% reduction 7–8 days after, heavy rainfall at CSO outfalls treated with medium SCM density compared to those without SCMs. Our results suggest that SCMs may be associated with a reduction in the increase of Culex mosquitoes at the CSO outfalls after heavy rainfall. More research is needed to study how the impacts of SCMs on mosquito populations may affect human health.

Linking stormwater control performance to stream ecosystem outcomes: incorporating a performance metric into effective imperviousness

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.

Displacement of Racially and Ethnically Minoritized Groups after the Installation of Stormwater Control Measures (i.e., Green Infrastructure): A Case Study of Washington, DC

Stormwater control measures (SCMs) (i.e., green infrastructure) are advantageous methods of stormwater management. However, studies suggest that urban greening may be associated with gentrification, displacing racially/ethnically minoritized groups due to increased housing costs and loss of feelings of belonging. We studied displacement of racially/ethnically minoritized groups after SCM installation in Washington, DC. We compared the change in percentage of persons in racial/ethnic groups at the Census block group level with varying levels of SCM installation (i.e., area-weighted SCM count at 300 m buffer). We stratified findings by SCM type, pre-installation income, and SCM size. DC installed a higher density of SCMs in areas with a higher percentage of Black and/or Hispanic/Latino residents. Nonetheless, findings suggest SCM installation is associated with displacement of Black residents. The percentage of residents who are Black decreased by 2.2% [95% Confidence Interval: 1.7, 2.7] and 4.1% [95% Confidence Interval: 3.4, 4.8] after low and high levels of SCM installation, respectively. In turn, the change in percentage of residents who are White increased with increasing levels of SCM installation. Compared to ecological studies on SCMs, studies about social impacts are scarce. This research intends to help optimize SCM installations so more residents can enjoy their health, economic, and ecological benefits.

Design and Simulation of Stormwater Control Measures Using Automated Modeling

Stormwater control measures (SCMs) are decentralized technical elements, which can prevent the negative effects of uncontrolled stormwater flow while providing co-benefits. Optimal SCMs have to be selected and designed to achieve the desired hydrological response of an urban catchment. In this study, automated modeling and domain-specific knowledge in the fields of modeling rainfall-runoff (RR) and SCMs are applied to automate the process of optimal SCM design. A new knowledge library for modeling RR and SCMs, compliant with the equation discovery tool ProBMoT (Process-Based Modeling Tool), was developed. The proposed approach was used to a) find the optimal RR model that best fits the available pipe flow measurements, and b) to find the optimal SCMs design that best fits the target catchment outflow. The approach was applied to an urban catchment in the city of Ljubljana, Slovenia. First, nine RR models were created that generally had »very good« performance according to the Nash–Sutcliffe efficiency criteria. Second, six SCM scenarios (i.e., detention pond, storage tank, bio-retention cell, infiltration trench, rain garden, and green roof) were automatically designed and simulated, enabling the assessment of their ability to achieve the target outflow. The proposed approach enables the effective automation of two complex calibration tasks in the field of urban drainage.

Measuring the water balance in stormwater control measures

Stormwater control measures (SCMs), also frequently referred to as sustainable urban drainage systems (SUDS), are of growing importance in cities, as part of a global move towards mitigating the impacts of stormwater on receiving environments. They need to be monitored as parts of UDSM systems but require specific and sometimes innovative methods and sensors. This is particularly the case for SCMs such as swales, rain-gardens, bioretention filters, infiltration trenches, green roofs, etc., which have complex and varied configurations and hydrologic behaviour. This chapter deals with measuring the water balance in SCMs by accounting for its various components: inflows, outflows, overflows, storage, infiltration, exfiltration, intrusion, evaporation, and evapotranspiration. It presents a range of suitable methods and tools, indicates key points to consider, and discusses possible difficulties in obtaining accurate monitoring data. Routine monitoring of decentralized and diversified SCMs is still an emerging field for both researchers and practitioners. A significant evolution is therefore expected with its generalization in the next years.