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Optimization model for the design of bioretention basins with dry wells

Description

Bioretention basins are a common stormwater best management practice (BMP) used to mitigate the hydrologic consequences of urbanization. Dry wells, also known as vadose-zone wells, have been used extensively in bioretention basins in Maricopa County, Arizona to decrease total drain

Bioretention basins are a common stormwater best management practice (BMP) used to mitigate the hydrologic consequences of urbanization. Dry wells, also known as vadose-zone wells, have been used extensively in bioretention basins in Maricopa County, Arizona to decrease total drain time and recharge groundwater. A mixed integer nonlinear programming (MINLP) model has been developed for the minimum cost design of bioretention basins with dry wells.

The model developed simultaneously determines the peak stormwater inflow from watershed parameters and optimizes the size of the basin and the number and depth of dry wells based on infiltration, evapotranspiration (ET), and dry well characteristics and cost inputs. The modified rational method is used for the design storm hydrograph, and the Green-Ampt method is used for infiltration. ET rates are calculated using the Penman Monteith method or the Hargreaves-Samani method. The dry well flow rate is determined using an equation developed for reverse auger-hole flow.

The first phase of development of the model is to expand a nonlinear programming (NLP) for the optimal design of infiltration basins for use with bioretention basins. Next a single dry well is added to the NLP bioretention basin optimization model. Finally the number of dry wells in the basin is modeled as an integer variable creating a MINLP problem. The NLP models and MINLP model are solved using the General Algebraic Modeling System (GAMS). Two example applications demonstrate the efficiency and practicality of the model.

Contributors

Agent

Created

Date Created
2016

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Designing and implementing ecological monitoring of aridland urban ecological infrastructure (UEI): a case-study of design process and outcomes

Description

Cities are increasingly using nature-based approaches to address urban sustainability challenges. These solutions leverage the ecological processes associated with existing or newly constructed Urban Ecological Infrastructure (UEI) to address issues through ecosystem services (e.g. stormwater retention or treatment). The growing

Cities are increasingly using nature-based approaches to address urban sustainability challenges. These solutions leverage the ecological processes associated with existing or newly constructed Urban Ecological Infrastructure (UEI) to address issues through ecosystem services (e.g. stormwater retention or treatment). The growing use of UEI to address urban sustainability challenges can bring together teams of urban researchers and practitioners to co-produce UEI design, monitoring and maintenance. However, this co-production process received little attention in the literature, and has not been studied in the Phoenix Metro Area.

I examined several components of a co-produced design process and related project outcomes associated with a small-scale UEI project – bioswales installed at the Arizona State University (ASU) Orange Mall and Student Pavilion in Tempe, AZ. Specifically, I explored the social design process and ecohydrological and biogeochemical outcomes associated with development of an ecohydrological monitoring protocol for assessing post-construction landscape performance of this site. The monitoring protocol design process was documented using participant observation of collaborative project meetings, and semi-structured interviews with key researchers and practitioners. Throughout this process, I worked together with researchers and practitioners to co-produced a suite of ecohydrological metrics to monitor the performance of the bioswales (UEI) constructed at Orange Mall, with an emphasis on understanding stormwater dynamics. I then installed and operated monitoring equipment from Summer 2018 to Spring 2019 to generate data that can be used to assess system performance with respect to the co-identified performance metrics.

The co-production experience resulted in observable change in attitudes both at the individual and institutional level with regards to the integration and use of urban ecological research to assess and improve UEI design. My ecological monitoring demonstrated that system performance met design goals with regards to stormwater capture, and water quality data suggest the system’s current design has some capacity for stormwater treatment. These data and results are being used by practitioners at ASU and their related design partners to inform future design and management of UEI across the ASU campus. More broadly, this research will provide insights into improving the monitoring, evaluation, and performance efficacy associated with collaborative stormwater UEI projects, independent of scale, in arid cities.

Contributors

Agent

Created

Date Created
2019