High-Resolution Modeling of Infill Development Impact on Stormwater Dynamics in Denver, Colorado

Panos, Chelsea L.; Hogue, T. S.; Gilliom, Ryan L.; McCray, J. E.

doi:10.1061/jswbay.0000863

Cited by 22 publications

(32 citation statements)

References 17 publications

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“…As this research was inspired by a City of Denver Department of Public Works request, the results of this study were used to inform the Berkeley Neighborhood Stormwater Feasibility Study. The results of this study were used to inform the hydraulic modeling, future conditions modeling, and, ultimately, to make inferences regarding infill redevelopment's impact on stormwater quality and quantity [31]. The City of Denver is currently using the results of the larger investigation to justify discussions regarding water quality requirements for (re)development on parcels less than one acre, which are currently not mandated to implement water quality measures.…”

Section: Discussionmentioning

confidence: 99%

Predicting Parcel-Scale Redevelopment Using Linear and Logistic Regression—the Berkeley Neighborhood Denver, Colorado Case Study

Cherry

Mollendor²,

Eisenstein

et al. 2019

Sustainability

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Many watershed challenges can be associated with the increased impervious cover that accompanies urban development. This study establishes a methodology of evaluating the spatial and temporal distribution of infill re-development on a parcel scale, using publicly available urban planning data. This was achieved through a combination of linear and logistic regression. First, a “business as usual” linear growth scenario was developed based on available building coverage data. Then, a logistic regression model of historic redevelopment, as a function of various parcel attributes, was used to predict each parcel’s probability of future redevelopment. Finally, the linear growth model forecasts were applied to the parcels with the greatest probability of future redevelopment. Results indicate that building cover change within the study site, from 2004–2014, followed a linear pattern (R2 = 0.98). During this period the total building cover increased by 17%, or 1.7% per year on average. Applying the linear regression model to the 2014 building coverage data resulted in an increase of 820,498 sq. ft. (18.8 acres) in building coverage over a ten-year period, translating to a 14% overall increase in impervious neighborhoods. The parcel and building variables selected for inclusion in the logistic regression model during the model calibration phase were total value, year built, percent difference between current and max building cover, and the current use classifications—rowhome and apartment. The calibrated model was applied to a validation dataset, which predicted redevelopment accuracy at 81%. This method will provide municipalities experiencing infill redevelopment a tool that can be implemented to enhance watershed planning, management, and policy development.

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Section: Discussionmentioning

confidence: 99%

Predicting Parcel-Scale Redevelopment Using Linear and Logistic Regression—the Berkeley Neighborhood Denver, Colorado Case Study

Cherry

Mollendor²,

Eisenstein

et al. 2019

Sustainability

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“…The study area includes the Berkeley neighborhood in northwest Denver, Colorado (39.776110, −105.039245) as investigated in Panos et al (2018) (Figure 1). The Berkeley neighborhood catchment is 419 ha (1.62 mi 2 ).…”

Section: Methodsmentioning

confidence: 99%

“…Panos et al (2018) investigated the impacts of redevelopment on stormwater runoff for the 419‐ha Berkeley neighborhood of northwest Denver, Colorado using future predictions of parcel‐scale impervious cover change (Cherry et al 2019). A calibrated Storm Water Management Model for PC (PCSWMM) was used to quantify the runoff produced from a range of 24‐h design storms and predicted increases of 0.91%–1.63% in stormwater runoff volume per 1% increase in impervious area due to redevelopment (Panos et al 2018). In addition, it was found that the existing storm sewer network is undersized to handle increases in flow, leading to increased flooding volumes and potential flood risk to urban infrastructure and neighborhood residents (Panos et al 2018).…”

Section: Introductionmentioning

confidence: 99%

“…A calibrated Storm Water Management Model for PC (PCSWMM) was used to quantify the runoff produced from a range of 24‐h design storms and predicted increases of 0.91%–1.63% in stormwater runoff volume per 1% increase in impervious area due to redevelopment (Panos et al 2018). In addition, it was found that the existing storm sewer network is undersized to handle increases in flow, leading to increased flooding volumes and potential flood risk to urban infrastructure and neighborhood residents (Panos et al 2018). It is possible that the implementation of low impact development (LID) could reduce runoff volumes enough to counter increases in runoff due to redevelopment.…”

Section: Introductionmentioning

confidence: 99%

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SWMM Sensitivity to LID Siting and Routing Parameters: Implications for Stormwater Regulatory Compliance

Panos

Wolfand

Hogue

2020

J American Water Resour Assoc

Self Cite

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Misrepresentation of sensitive siting and routing parameters for low impact development (LID) affects hydrologic model outputs, stormwater infrastructure design, and regulatory compliance. ABSTRACT: Cities are experiencing new growth through infill development, or "redevelopment," where lower density land uses are redeveloped to high density with increased impervious surfaces. Cities need revised stormwater criteria to manage increases in stormwater runoff and flooding from redevelopment via low impact development (LID). Watershed-scale hydrologic modeling in the Storm Water Management Model (SWMM) can help policy makers revise regulations to adapt to redevelopment. However, LID modeling is still relatively new and the understanding of model sensitivity to certain parameters is lacking. In particular, LID siting and routing parameters such as outflow routing from, area treated by, and placement of LID are not well studied. Using a case study of a redeveloping neighborhood in Denver, Colorado, we tested 32 configurations of these parameters in a calibrated, SWMM for PC (PCSWMM) model. We found some configurations lead to counteracting model processes that result in similar runoff reduction across a variety of configurations, suggesting to policy makers that reduction targets may be met in a myriad of ways. The relative sensitivity of runoff volume to area treated and LID placement was found to be on average 3.0 and 11.2 times higher than other model parameters. Given this sensitivity, practitioners and modelers should consider LID siting and routing parameters in hydrologic modeling efforts that inform regulations.

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“…A pilot project on the Front Range of Colorado found the average annual HND to be 97% in a natural undeveloped catchment, with a runoff ratio of less than 3% [15]. Comparatively, runoff ratios in areas with residential land use typically range from 30% to 80% [16][17][18]. Per the pilot project statute, the postdevelopment runoff may be legally harvested for outdoor use because the volume was not part of the historically appropriated supply [14,19].…”

Section: Introductionmentioning

confidence: 99%

A Rainwater Harvesting Accounting Tool for Water Supply Availability in Colorado

Gilliom

Bell

Hogue

et al. 2019

Water

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Rainwater harvesting (RWH) is a renewable water supply option for nonpotable use, most commonly used for landscaping irrigation. Water rights in Colorado prohibit all RWH except residential rain barrels and a pilot project program that allows centralized rainwater harvesting for new development. Development of a natural catchment creates impervious surfaces, thereby increasing runoff, with a subsequent decrease in infiltration and losses to evapotranspiration; pilot projects are allowed to harvest a volume equal to the predevelopment runoff losses that would have occurred on new impervious areas at the site. To support this administrative policy, a tool was developed for the efficient calculation of daily allowable harvest at nearly any project site in Colorado. A reliable and useful policy tool requires the incorporation of hydrologic science with widely applicable, user-friendly design, a challenging balance of rigor and accessibility that is welcomed by engineers and policymakers alike. The daily allowable harvest is determined for each soil group as a percentage of infiltrated rainfall less the groundwater return. Horton's infiltration method is used to model rainfall-runoff for a range of soil parameters (NRCS hydrologic soil groups) and precipitation events (0.25-to 25-year return periods and 15-min to 24-h durations). For most events, the percent infiltration is 90% of the precipitation depth; this ratio decreases when precipitation exceeds the infiltration rate. Results are simplified in a spreadsheet tool for policy application, with allowable harvest rules binned by event duration and frequency. Simulations using the tool for a 2010-2017 precipitation record from Colorado's Front Range showed that RWH can supply up to 50% of the annual demand for traditional landscaping and over 100% of the water-smart landscaping demand.

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High-Resolution Modeling of Infill Development Impact on Stormwater Dynamics in Denver, Colorado

Cited by 22 publications

References 17 publications

Predicting Parcel-Scale Redevelopment Using Linear and Logistic Regression—the Berkeley Neighborhood Denver, Colorado Case Study

Predicting Parcel-Scale Redevelopment Using Linear and Logistic Regression—the Berkeley Neighborhood Denver, Colorado Case Study

SWMM Sensitivity to LID Siting and Routing Parameters: Implications for Stormwater Regulatory Compliance

A Rainwater Harvesting Accounting Tool for Water Supply Availability in Colorado

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