Regenerative Stormwater Conveyance: Design Implications of an Urban Case Demonstration in Baltimore, Maryland

This research-design thesis explores the implementation of Regenerative Stormwater Conveyance (RSC) as a retrofit of an existing impervious drainage system in a small catchment in the degraded Jones Falls watershed in Baltimore City. An introduction to RSC is provided, placing its development within a theoretical context of novel ecosystems, biomimicry and Nassauer and Opdam’s (2008) model of landscape innovation. The case site is in Baltimore’s Hampden neighborhood on City-owned land adjacent to rowhomes, open space and an access point to a popular wooded trail along a local stream. The design proposal employs RSC to retrofit an ill-performing stormwater system, simultaneously providing a range of ecological, social and economic services; water quantity, water quality and economic performance of the proposed RSC are quantified. While the proposed design is site-specific the model is adaptable for retrofitting other small-scale impervious drainage systems, providing a strategic tool in addressing Baltimore City’s stormwater challenges.

Assessing the influence of abiotic factors and leaf-level properties on the stability of growing-season canopy greenness in a deciduous forest

Maps depicting spatial pattern in the stability of summer greenness could advance understanding of how forest ecosystems will respond to global changes such as a longer growing season. Declining summer greenness, or “greendown”, is spectrally related to declining near-infrared reflectance and is observed in most remote sensing time series to begin shortly after peak greenness at the end of spring and extend until the beginning of leaf coloration in autumn,. Understanding spatial patterns in the strength of greendown has recently become possible with the advancement of Landsat phenology products, which show that greendown patterns vary at scales appropriate for linking these patterns to proposed environmental forcing factors. This study tested two non-mutually exclusive hypotheses for how leaf measurements and environmental factors correlate with greendown and decreasing NIR reflectance across sites. At the landscape scale, we used linear regression to test the effects of maximum greenness, elevation, slope, aspect, solar irradiance and canopy rugosity on greendown. Secondly, we used leaf chemical traits and reflectance observations to test the effect of nitrogen availability and intrinsic water use efficiency on leaf-level greendown, and landscape-level greendown measured from Landsat. The study was conducted using Quercus alba canopies across 21 sites of an eastern deciduous forest in North America between June and August 2014. Our linear model explained greendown variance with an R2=0.47 with maximum greenness as the greatest model effect. Subsequent models excluding one model effect revealed elevation and aspect were the two topographic factors that explained the greatest amount of greendown variance. Regression results also demonstrated important interactions between all three variables, with the greatest interaction showing that aspect had greater influence on greendown at sites with steeper slopes. Leaf-level reflectance was correlated with foliar δ13C (proxy for intrinsic water use efficiency), but foliar δ13C did not translate into correlations with landscape-level variation in greendown from Landsat. Therefore, we conclude that Landsat greendown is primarily indicative of landscape position, with a small effect of canopy structure, and no measureable effect of leaf reflectance. With this understanding of Landsat greendown we can better explain the effects of landscape factors on vegetation reflectance and perhaps on phenology, which would be very useful for studying phenology in the context of global climate change