Assessing the influence of urban greenness and green stormwater infrastructure on hydrology from satellite remote sensing

Modeling the impact of future rainfall changes on the effectiveness of urban stormwater control measures

The convergence of urban expansion, deteriorating infrastructure, and a changing climate will escalate the risks of stormwater pollution and urban flooding in the coming decades. Using outputs from an ensemble of global climate models to drive a high spatial resolution stormwater model, we analyzed climate change impacts on urban stormwater runoff and control measures for 23 cities across the United States. Runoff model outputs for two future emissions scenarios ending in 2055 were compared against a historical scenario to assess changes. All cities showed increases in average annual stormwater runoff, with changes up to 30% over the next 30 years due to a greater frequency of high intensity storm events. Runoff model outputs showed substantial variation across cities with untreated stormwater runoff increasing by as much as 48%. Patterns of future runoff impacts within cities will affect the performance of distributed treatment strategies such as Green Stormwater Infrastructure (GSI) to meet municipal water quality improvement and runoff reduction goals. Results indicate that adoption of adaptable design standards and decision support tools that readily accommodate projected precipitation changes are critical for supporting more resilient designs of stormwater control measures.

Effectiveness of landscape indicators for explaining the variability of benthic macro-invertebrates in urban streams

Landscape indicators - measures of land use and land cover - are widely used as proxies for monitoring urban stream conditions, particularly for benthic invertebrates which are often negatively impacted by watershed urbanization. However, multi-scale and nonlinear relationships between benthic macroinvertebrates and landscape configuration derived from fine spatial resolution land cover are not well explored. Here, we developed a series of landscape indicators and assessed their effectiveness in explaining the variability of benthic macroinvertebrate communities in 63 streams across the Greater Vancouver Region in British Columbia, Canada. We asked: 1) How effective are multi-scale landscape indicators in explaining the variability of instream benthic macroinvertebrates? 2) Does the explanatory power of landscape indicators vary at different spatial scales? 3) Do different urban forest classification schemes and their spatial configurations impact the explanatory power of landscape indicators? We developed high spatial resolution (5-m) landscape indicators and evaluated their utility in statistical models explaining taxa richness, instream benthic indices of biological integrity (B-IBI), % Ephemeroptera, Plecoptera, and Trichoptera (EPT), and % Oligochaetes. For all benthic responses, landscape indicators measured at the watershed scale explained 5-25% more variation than riparian-based indicators. Combining indicators mapped at multiple scales further improved the explanatory power of landscape indicators for % EPT and % Oligochaetes, ultimately explaining over 70% of the variability of benthic macro-invertebrates in streams. Distinguishing deciduous and coniferous forest types improved the explanatory power of landscape indicators in a riparian model for B-IBI by 10%. When considering the spatial arrangement of land cover, patch density of forests in the surrounding watersheds of stream explained as much as 47% of the variability in % Oligochaetes. Our results highlight the importance of investigating nonlinear relationships between benthic macroinvertebrates and landscape configuration. This monitoring approach is transferable across cities interested in maintaining the ecological health of urban streams while supporting urban expansion and growth.

Land Cover Change Effects on Stormflow Characteristics across Broad Hydroclimate Representative Urban Watersheds in the United States

Urban development alters stormflow characteristics and is associated with increasing flood risks. The long-term evaluation of stormflow characteristics that exacerbate floods, such as peak stormflow and time-to-peak stormflow at varying levels of urbanization across different hydroclimates, is limited. This study investigated the long-term (1980s to 2010s) effects of increasing urbanization on key stormflow characteristics using observed 15 min streamflow data across six broad hydroclimate representative urban watersheds in the conterminous United States. The results indicate upward trends in peak stormflow and downward trends in time-to-peak stormflow at four out of six watersheds. The watershed in the Great Plains region had the largest annual increasing (decreasing) percent change in peak stormflow (time-to-peak stormflow). With the current change rates, peak stormflow in the Great Plains region watershed is expected to increase by 55.4% and have a 2.71 h faster time-to-peak stormflow in the next decade.