Physical Sciences and Mathematics Commons^™

Effects Of Stormwater Green Infrastructure On Watershed Outflow: Does Spatial Distribution Matter?, Benjamin Fahy, Heejun Chang

International Journal of Geospatial and Environmental Research

Green Stormwater Infrastructure (GSI) has become a popular method in urban stormwater management. We examined how spatial distribution of GSI affected rainfall-runoff relationships in a recently developed neighborhood in Gresham, Oregon, USA for the 2017-2018 water year. Runoff ratio, peak discharge, and flashiness were compared under four precipitation scenarios (of differing intensity and duration) and different spatial arrangements of GSI. Distributed GSI reduced runoff ratio (10 - 20%), peak discharge (26 - 68%), and flashiness index (56 - 70%). Distributed GSI outperformed centralized structures for all metrics, reducing runoff ratio (22 - 32%), peak discharge 67 to 69%, and flashiness …

Transport Mechanisms For Human Fecal Indicator Bacteria In An Urban Stormwater Basin In Southeastern Wisconsin, Chelsea M. Corson

Theses and Dissertations

Discharge of stormwater runoff to receiving waters is a known source of human pathogens; however the primary mechanisms by which these pathogens enter the stormwater system have yet to be quantified. This study builds upon and utilizes prior research findings in an attempt to explain the influence of the age of the pipes within stormwater and sanitary conveyance systems, rainfall and hydrogeological characteristics, and select infrastructure variables that contribute to the observed contamination of an urban stormwater basin in Southeastern Wisconsin.

Over the course of approximately two years from 2012 to 2014, a total of 260 samples from 22 stormwater …

Sensitivity Of Urban Water Consumption To Weather And Climate Variability At Multiple Temporal Scales: The Case Of Portland, Oregon, Heejun Chang, Sarah Praskievicz, Hossein Parandvash

International Journal of Geospatial and Environmental Research

The sensitivity of municipal water consumption to climate and weather variability is investigated for Portland’s water provider service area between 1960 and 2013. The relationship between detrended seasonal urban water use (the difference between total water use and base use) and weather and climate variables (precipitation, maximum temperature) is examined at daily, monthly, and seasonal scales using stepwise multiple regression and autoregressive integrated moving average (ARIMA) models. At a seasonal and a monthly timescales, interannual variation in maximum temperature is the most important predictor of seasonal water consumption per capita, explaining up to 48% of the variation in seasonal monthly …