A Site Scale Integrated Decision Support Tool for Urban Stormwater ...

World Environmental and Water Resources Congress 2018

A Site Scale Integrated Decision Support Tool for Urban Stormwater Management A. Shojaeizadeh1; M. Geza2; C. Bell3; E. Gallo4; K. Spahr5; T. Hogue6; and J. McCray7 1

Civil and Environmental Engineering Dept., South Dakota School of Mines and Technology Civil and Environmental Engineering Dept., South Dakota School of Mines and Technology 3 Civil and Environmental Engineering Dept., Colorado School of Mines 4 Civil and Environmental Engineering Dept., Colorado School of Mines 5 Civil and Environmental Engineering Dept., Colorado School of Mines 6 Civil and Environmental Engineering Dept., Colorado School of Mines 7 Civil and Environmental Engineering Dept., Colorado School of Mines

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ABSTRACT The objective of this research is to develop of a planning-level, site scale integrated decision support tool (site scale i-DST) for grey and green stormwater infrastructure. The site scale i-DST has several component modules integrated into a single tool. The component modules include runoff estimation module, water quality module, BMP cost module, and an optimization module. Several of the more complex stormwater tools require expertise to build and operate. The site scale i-DST is built on accessible platform (Microsoft Excel VBA) and can be operated with a minimum skillset. It is based on readily available data and provides a comparative analysis among various scenarios for BMP selection, sizing, cost, and performance. Site scale i-DST is fully automated optimization tool that selects BMPs based on input data such as quality and quantity of stormwater, target water quality, runoff reduction requirements, and technical and economic criteria. It was demonstrated through scenario evaluation that the tool recommended cost effective BMPs. The tool is flexible allowing user interaction through a graphical user interface. Users can change BMP selection criteria and weights, include or exclude BMP types from the selection process depending on site specific criteria. The tool includes a hydrologic module for simulation of runoff on event and continuous basis. The site scale i-DST is intended for designers, regulators, and municipalities for quick analysis of scenarios involving the interaction of several factors. The output includes most effective BMP(s) with respect to the technical and economic criteria which meets target water quality and flow reduction requirements. Keywords: Stormwater management, BMP selection, Optimization, Site scale 1. INTRODUCTION Urbanization impacts the quality of urban water resources, and ineffective stormwater treatment plays a major role. Land use change due to urbanization alters hydrological characteristics of watersheds (USEPA, 2011, Grimm et al., 2008) by increasing impervious cover. Consequently, stormwater infiltration is reduced and runoff is increased (Dietz, 2007; Brabec et al., 2002). The US Census Bureau’s (2012) predicted that by 2030 more than 60% of the world’s population will live in an urban area. Increased buildings, roadways and parking lot densities associated with urbanization result in an expansion of impervious cover in urban watersheds. Impervious cover is often used as an indicator of the intensity of the urban environment (Brabec et al., 2002; Paul and Meyer, 2001). Thus, modern stormwater management practices consider a combination of structural (focusing on physical interventions and engineered infrastructure for improved drainage) and non-structural (focusing on green

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infrastructure) to achieve an integrated stormwater management (Parkinson, 2003). Green infrastructure is an evolving stormwater management approach using natural processes (Medina et al., 2011). Low impact development (LID) is one type of green infrastructure that specifically emphasizes better management of urban stormwater through reductions in post-development runoff by increasing on-site infiltration and reducing impervious surface cover (Pitt and Clark, 2008;). Across the nation, there is increasing interest in the use of LID as a means of reducing urban runoff and associated pollutant loads to receiving waters (USEPA, 2011, Dietz and Clausen, 2008; Khader and Montalto, 2008). The use of LID to manage and treat urban stormwater runoff has become a common alternative practice to conventional solutions in urban watershed management. The U.S. Environmental Protection Agency (EPA) considers LID as a stormwater control best management practice (BMP) and, along with other federal agencies, is encouraging the implementation of LID. The evaluation and decision for implementation of LID at scales beyond the site level is critical as community and watershed-level land use management planning decisions are typically performed at the larger neighborhood or watershed scale (Grimm et al., 2008). Most previous LID implementation projects have encouraged site scale projects for the treatment of minimally-sized storms. Prior research efforts regarding the application of these LID site designs have been optimized relative to site-specific factors such as type, area, depth, and plants as well as investigated for the potential impact of site conditions such as weather, precipitation amount, soil type, and percent impervious area (Montalto et al. 2007). Site scale i-DST can handle different storm sizes can help stormwater managers in making decisions considering variable water quality, cost and BMP efficiency. Table 1. Comparing the capability of stormwater management tools database Tool WERF SELECT

Platform

Runoff volume

Excel

Peak flow

Pollutant loads

BMP/ GI

Cost/ LCCA

√

√

√

√

√

√

Cobenefits analysis

Climate change

Integrated optimization

Uncertainty assessment

√

√

Green Values

Web

STEPL

Excel

√

SWMM

Fortran

√

√

√

√

WinSLAMM

Fortran

√

√

√

√

SUSTAIN

Fortran

√

√

√

√

L-THIA

Excel

√

√

√

MUSIC

Fortran

√

√

√

LIDRA

Web

√

i-DST-SB

Excel

√

√

√

√ √

√

√

√

√

√

√

√

√

2. METHODOLOGY Several stormwater tools have been developed. Prior to the development of site scale i-DST a review of literature has been conducted to look into existing stormwater management tools and their capabilities and stormwater database that has been developed. Table 1 shows the summary of existing stormwater management tools and their capabilities in comparison to site scale i-DST developed in this study. Site scale i-DST has modules to estimate runoff, cost and can be used

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for planning and design. Site scale i-DST has a user friendly graphical user interface for data inputting and displaying outputs. Planners and mangers can easily change technical and economic inputs and evaluate various scenarios in a short time with minimal skillset to operate and use the tool. Figure 1 shows the conceptual framework of site scale i-DST in which there are different modules for runoff calculation, cost analysis, water quality data, and BMP efficiencies. Each module is integrated into an optimization module that generates optimal solutions including optimized BMP(s), cost estimates and discharge of water quality and quantity through an iterative process.

Figure 1. Site scale i-DST conceptual framework 2.2 2.1 Site Scale i-DST runoff estimation module Models of varying levels complexity including event-based models and more detailed continuous simulation model are implemented in this study. An event model represents a single event occurring over a relatively short period of time ranging from about an hour to several days. If long term analysis involving life cycle cost is needed, the continuous simulation model within i-DST can be used. On the other hand, continuous simulation models are input data intensive. The joint event and continuous modeling implemented in this study can strengthen the overall modeling capability. (a) Event-based runoff estimation module: The site scale tool will have an event based model for assessment of the impact of extreme events. At times, this may be the only level of tool that is required by planners to provide flood estimates or when there is no data to justify a continuous simulation model. Common event-based hydrologic models include HEC-HMS, SCS TR-20 and TR-55, and Rational Methods. To simplify the integration to other modules an excel VBA based event based module is developed. The event based hydrologic module will be used to estimate runoff from an individual storm event, i.e., describing a relatively short period within the hydrologic record. Two approaches (curve number and Green-Ampt) are implemented in the integrated site sale tool for event runoff simulation. Both methods allow for evaluation of pre and post development peak runoff estimates that are used in the selection and sizing of BMPs. The

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first approach, the curve number approach uses design storm for the site (e.g. 2 yr, 10 yr and or 100 yr 24 hr storms). The method has built NRCS rainfall distribution option based on type I, type IA, type II and type III. The method allows for calculation of weighted curve number for sites with mixed land use and soil types (hydrologic soil groups). The method also includes an approach to transform effective rainfall to a hydrograph of the rainfall event. The second event based runoff estimation method is the Green-Ampt for runoff depth estimation and a Snyder unit hydrograph approach to estimate the hydrograph from the depth of runoff. (b) Continuous simulation runoff module: The continuous simulation module within site scale i-DST includes a method for soil moisture accounting, surface depression storage, infiltration, and evapotranspiration. The continuous simulation model is operated over a longer period of time, which includes time series of rainfall events and inter-storm conditions. The model accounts for changes in soil moisture and its impact on infiltration. The time interval in the continuous simulation model can be varied; daily, hourly, subhourly, or variable. Models that provide only daily simulation are not useful for stormwater applications (Knapp et al. 1991). Two alternative methods are built into site scale i-DST; a modified SCS curve number and a Green-Ampt approach. In both methods, the soil moisture is updated every time step in terms to account for wet and dry conditions. The soil moisture updating includes an option where soil moisture content is set back to dry condition if water input ceases for a longer duration of time. The continuous simulation model is developed based on conservation of mass. The change in runoff depth is calculated using a mass balance approach considering precipitation, infiltration rate, evaporation rate and runoff rate. The rate of change of depth of flow is given by: dv dd (Eqn.1) A  A *(i  e  f )  Q dt dt 1 5 dd 1.49* w * s 2  ie f  (d  d p ) 3 (Eqn.2) dt A* n Where, v is volume of water on the site ( ft 3 ) , A is surface area of site ( ft 2 ) , i is intensity of rainfall (ft/s), e is evapotranspiration rate (ft/s), f is infiltration rate (ft/s), Q is discharge rate (cfs), w is width of site (ft), s is slope of site (ft/ft), n is manning’s roughness coefficient, t is time step (s), d is depth of runoff (ft), and d p is depth of depression storage (ft). Overland flow is generated from pervious and impervious area is approximated as non-linear reservoirs, as shown in Figure 2. The depth of runoff is used to estimate the runoff discharge from the site. Calculation of infiltration and depth of runoff involves implicit equation requiring an iterative process. Initially, during the development of the continuous runoff simulation module implicit equation were implemented. However, for extended simulation periods, longer simulation time was needed for implicit formulation. After extensive review, a method developed presented in Barry (2005) was adopted. The results of this method were very similar to the implicit equations for different soil types (Ali et al. 2016). This explicit method is using the W-Lambert function to solve the Natural Logarithm equation involved in the Green-Ampt infiltration equation. The result of this method is close to the implicit form for most soil types. Thus, computationally less intensive explicit methods were evaluated and compared to the implicit methods for both infiltration rates and depth runoff. It was demonstrated via observed runoff data that the two approaches resulted in similar runoff outputs (Figure 3).

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Figure 2. The non-linear reservoir sketch by coupling the continuity equation with Manning’s equation 2.2 Water quality database The site scale i-DST has a water quality module. The water quality module includes a database of stormwater quality. The stromwater quality data is needed for selection of suitable BMPs capable of providing treatment. Two options are available for the user. The user can use NCDC database based on climatic regions where the user can select a region and obtain water quality data from the data base. Alternatively, the user can manually enter water quality data specific to the site. Pollutants included in the water quality database include TSS, TN, TP, Zn, Cu, Pb, NO3, PO4 and Bacteria. 2.3 BMP efficiencies Each BMP(s) has a specific removal capability for specific pollutants or flow reduction efficiency. The removal efficiency is calculated based on input water quality, target water quality defined as standard water quality. Site scale i-DST is developed for small site. Thus, it is assumed that BMP(S) are placed in series and whole runoff passes through each BMP in series where the output from the first BMP is an input to the second BMP and so on. The removal efficiency for a single BMP is calculated as: water quality(%)  standard (%) (Eqn.3) Removal goal  water quality(%) And the removal efficiency for multiple BMPs is calculated as: RE  1  1  RE of BMP1*x1  *1  RE of BMP2 *x2  *1  RE of BMPn *xn  (Eqn.4) Where RE is the combined removal efficiency, BMP1, BMP2, BMPn represent alternative BMPs and X1, X2, ..Xn represent decision variables. X1, X2, ..Xn become 1 if a BMP is selected and zero otherwise. 2.4 Capital, operation and maintenance costs For cost analysis, there are two options. The user can choose either annual capital cost and operation and maintenance cost or apply a life cycle cost analysis (LCCA), the development of which is currently in progress. The site scale i-DST optimization module minimizes the objective function while meeting the required level of water quality and quantity. Facility capital costs as well as O&M costs are calculated for each best management practices. The capital costs for each BMP are calculated as a function of size of BMP or flow rate. The capital costs are amortized to annual costs based on interest rate and user defined period of service for each technology.

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Annual O&M costs include costs for energy, labor, chemicals, treatment supplies, and for leasing public land. The total annual cost is calculated as the sum of annualized capital costs and O&M costs.

Figure 3. (a) Runoff hydrograph for continuous simulation and (b) Coefficient of determination between observed and simulated data 2.5 Optimization tool The optimization module has defined objective function and constraints. The objective function is minimized while satisfying the constraints. The objective function includes several criteria including technical and economic. The optimization tool has constraints that should be met when finding the optimal solution including target flow and water quality constraints. User can do include or exclude a BMP based the feasibility of the specific BMP(S) for a specific place. The objective is to minimize the cost while satisfying the technical constraints. The decision variables are the list of BMP(s) which are assigned to be binary value of one

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corresponding to BMP being selected and/or zero corresponding to a BMP being not selected

Figure 4. Graphical user interface (GUI) of site scale i-DST 3. THE GRAPHICAL USER INTERFACE (GUI) The graphical user interface design and the level of interactivity are important factors for broader use of any decision support tool. A user interface should facilitate easy quantitative data inputting in addition to allowing user intervention to change alternatives (Kao et al. 1993; Druzdzel and Flynn 2002). Usually, little attention is given to the user interface when a decision support tool is intended as a conceptual demonstration or evaluation of approaches (Flores et al. 2007), or when it is intended for a highly specific use or for expert users who are more concerned with the theory behind the decision process (Rodriguez-Roda et al. 2000; Gachet and Sprague 2005). For a decision support tool that is intended to be used by a wide range of utilities or users who may not be modelers, it is preferred that the user interface allows easy and active interaction. Interactivity can be in the form of adding the ability to monitor the decision process, and/or set constraints or rules that reflect the user’s preferences, or giving a warning message if any design standards are violated (Krovvidy et al. 1991; Kao et al. 1993; Freitas et al. 2000). It is important that the user interface integrates the various underlying modules. Often it is also important to have a help tool to guide the user through the system (Krovvidy et al. 1991; Heller et al. 1998). The design of the site scale i-DST shown in Figure 4 is organized in a manner that includes the attributes of a simple-to-use user interface. As shown in Figure 4, the user will be able to easily modify the input including such as water quality inputs, runoff, removal efficiency, cost, and more. Within each input, the user has the ability to change and modify the various factors that affect the outcome of the site scale i- DST. User can then run site scale i-DST and visualize the outputs also from the user interface. 4. SUMMARY AND CONCLUSION The site scale i-DST has several modules integrated into one including runoff estimation tool, water quality, BMP efficiency and cost module. Site scale i-DST is a user-friendly tool

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developed for small sites. Decision support tools in stormwater management become more useful to the users when they integrate multiple criteria and objective functions. The site scale i-DST developed in this study is an integrated and comprehensive tool that considers multiple factors in the selection of best management practices. It is an integrated tool that includes multiple technical and economic factors while focusing mainly on contaminant removal as required by discharge water quality standards or intended beneficial reuse. Most decision support tools involve a limited number of criteria particularly cost. In contrast, site scale i-DST includes technical, environmental and economic criteria that are quantifiable and non-quantifiable in the BMP selection process. The tool has a built-in water quality database but it also allows users to input their own feed and target water quality data. The technical, economic and environmental criteria are used in the selection of BMPs using a constrained multi-objective optimization approach with a graphical user interface for users to change inputs such as weights, cost and water quality allowing a higher level of interactivity. The graphical user interface allows altering constraints that may result in a different set of BMPs. The tool allows users to include or exclude BMPs based on site specific conditions. The tool can help decision makers in analyzing various stormwater scenarios. REFERENCES 1. USEPA (2011), User’s Guide Spreadsheet Tool for the Estimation of Pollutant Load (STEPL) Version 4.1. Prepared by Tetra Tech, Inc. Tetra Tech, Inc. 10306 Eaton Place, VA 22003 2. Grimm NB, Faeth SH, Golubiewski NE, Redman CL, Wu J, Bai X, et al. (2008). Global Change and the Ecology of Cities. Science. 319(5864):756–60. 3. Dietz, M. E. (2007). Low impact development practices: a review of current research and recommendations for future directions. Water, Air, and Soil Pollution, 186, 351–363. 4. Brabec, E., Schulte, S., Richards, P. L. (2002). Impervious surfaces and water quality: A review of current literature and its implications for watershed planning. Journal of Planning Literature. Sage Publications, Thousand Oaks, CA. Volume 16, Number 4. Page 499 5. Paul MJ, Meyer JL. (2001). Streams in the urban landscape. Annu. Rev. Ecol. Syst. 32:333–65 6. Parkinson, J. (2003). Drainage and stormwater management strategies for low-income urban communities. Environ. Urban. 15, 115–126. 7. Medina F. M. et al. (2011). A global review of the impacts of invasive cats on island endangered vertebrates. Global Change Biol. 17, 3503–3510 8. Dietz, M. E., and J. C. Clausen. (2008). Stormwater runoff and export changes with development in a traditional and low impact subdivision Exit. Journal of Environmental Management 87:560–566. 9. Khader O and Montalto F A (2008). Development and calibration of a high resolution SWMM model for simulating the effects of LID retrofits on the outflow hydrograph of a dense urban watershed, ASCE, Low Impact Development for Urban Ecosystem and Habitat Protection (Reston, VA: ASCE) pp 1–9 10. Montalto, F., Behr, C., Alfredo, K., Wolf, M., Arye, M., Walsh, M. (2007). Rapid assessment of the cost-effectiveness of low impact development for CSO control. Landscape and Urban Planning. 82:117–131. 11. Knapp, H. V., Durgunoglu, A., and Ortel, T. W. (1991). “A review of rainfall-runoff modeling for stormwater management.” Illinois State Water Survey, Contract Rep. No. 516, Champaign, Ill. 12. Barry, D. A., Parlange, J. Y., Li, L., Jeng, D. S., Crapper, M., (2005). Green–Ampt

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