A Decision Support Tool for Evaluating Pervious. Pavements for Parking Lots

Transcription

1 A Decision Spport Tool for Evalating Pervios Pavements for Paring Lots Ken Harrison, Assistant Professor, University of Soth Carolina, Department of Civil and Environmental Engineering, 300 Main Street, Colmbia, SC 9169 Abstract The se of pervios pavements, among U.S. EPA s Best Management Practices (BMPs) for stormwater management, increases infiltration and decreases rnoff. Here, the design of a system that incldes contribting impervios areas, a paring lot, and a detention pond is considered. This paper describes the development of a decision spport tool, the Pervios-Impervios Tradeoff (PIT) model, for evalating tradeoffs between the se of pervios pavements and impervios pavements for paring while considering the related decision of detention pondsizing. The tool incldes a solver to aid in determining the paring lot size, pervios fraction of the paring area, and the detention pond size, while considering cost, an infiltration target, a postdevelopment pea flow restriction, and a range of site-specific conditions. The model incldes an atomated search method that allows for several tradeoffs to be qicly evalated, e.g., between detention ponds and pervios pavements for meeting pea flow restrictions, between cost savings and paring area, and cost savings and grondwater recharge. General conclsions are drawn regarding the hydrologic effects and economics of pervios pavements. The limitations of the tool and possible extensions are also discssed. Keywords: Best Management Practice (BMP), Low impact development (LID), poros pavement, rban rnoff, infiltration, storm water.

2 1 Introdction Poros, or pervios, pavements are among the U.S. EPA s Best Management Practices (BMPs) for stormwater management (Hber et al., 006). Pervios pavements, which provide temporary storage of stormwater in the pores of the pavement and nderlying gravel base, allow for direct infiltration into the grondwater system, which redces rnoff and increases grondwater recharge, meeting the broader objectives of water spply and flood control. A decision spport tool (DST) is described here that can aid in the decisions on the se of pervios pavements for paring lots. Inclding pervios pavements in the design for a paring lot can lessen the need to provide space on site for a detention pond (Fergson, 005). Detention ponds are generally reqired of impervios paring for flood prevention. The selection of a pervios pavement can allow for more paring area within the same site footprint. The DST helps to assess the tradeoffs between pervios pavements, which tae p no more additional area bt can be considerably more expensive than impervios pavements on a nit area basis, and detention ponds, which are efficient at redcing pea rnoff bt can occpy valable land. By incorporating tools to assess this tradeoff, the DST meets the need identified by Sample et al. (003) to identify the opportnity costs of BMPs. Impervios/pervios pavement selection is typically framed as a binary choice, the se or not of pervios pavements. Here, however, the design problem allows consideration of a hybrid design involving allocation of some paring lot area to pervios pavement and the remaining fraction to impervios pavement. In addition, gidance on BMPs inclding pervios concrete and other infiltration practices often assmes exclsive se of the BMP for hydrologic control, i.e., no detention pond on site or other hydrologic control. Here, with inclsion of the detention pond and se of impervios pavements a broader system is considered.

3 Some existing models do inclde simlation capabilities for pervios pavements. The focs of the Sorce Loading and Management Model (SLAMM) is to relate rnoff water qality to sorces of rban rnoff polltants and incldes several otfall controls, inclding pervios pavements (Pitt and Voorhees, 00). The model does not inclde pond roting and the crrent version of SLAMM does not incorporate rnoff from contribting impervios areas. As sch, it is not directly sited to the modeling of a joint impervios srface/pervios pavement/detention pond system. Hber et al. (006) describes how pervios pavements (and other BMPs) may be simlated within the USEPA Storm Water Management Model (SWMM), which does inclde standard pond roting procedres. Pervios pavements may be modeled as a pervios srface throgh specification of varios parameters that the ser wold compte from the properties of pervios (e.g., porosity and thicness of pavement and nderlying gravel base, exfiltration rate, etc.). The Pervios Concrete Hydrological Analysis Program (PCHAP), a tool available from the Portland Cement Association, allows sers to examine the hydrology of pervios concrete, bt a detention pond is not considered a part of the system (Leming et al., 007). Distinct from these simlation models, the DST incldes search capabilities to optimize the extent of se of pervios and the detention pond size to meet pea rnoff and infiltration targets. Others have developed optimization models for watershed management. Perez-Pedini et al. (005) investigated the optimal location of infiltration-based BMPs to control pea flow at the watershed basin otlet; detention basins were not considered. Harrell and Ranjithan (003) considered simltaneosly the optimal location of detention basins and land-se allocation planning for meeting system-wide polltant redction targets; infiltration BMPs sch as pervios pavements were not considered. Here, infiltration-based BMP (pervios pavement) and storage-based BMPs (detention pond) are simltaneosly considered at a smaller scale. Lee et al. (005) present an optimization method for rban wet-weather control strategies while considering on-site controls and centralized storage-release systems. All of these stdies address the need identified by Hber 3

4 et. al (006) for methodologies to optimize the cost and performance of BMPs within a broader system context. The tool is designed to be sefl to researchers and reglators, contractors and their potential clients. In addition to being able to manally explore the relationships between varios qantities detention pond size, pervios fraction of the paring lot, paring lot size, pea rnoff, infiltration, system cost, and site-specific parameters the DST ser can invoe a solver that retrns a design that meets ser-specified infiltration and rnoff targets. In addition, the ser of the DST can reqest a report that graphically displays the pervios pavement/detention pond tradeoffs, cost as a fnction of infiltration, and cost and design as a fnction of paring area. The framewor is similar to other optimization-based DSTs in the field of environmental and water resorces management (e.g., Westphal et al., 003; Sample et al., 001; Harrison et al., 001). Sch DSTs inclde decision search engines, databases, process models, model interfaces, and graphical ser interfaces. Here, the specific challenges that were presented in the development of a DST for the pavement/detention pond system are addressed. Among these challenges were the definition of meaningfl system bondaries and appropriate levels of analysis sitable for the screening tool, the design of an atomated search method that cold accommodate the discrete modeling of the pervios concrete and the nmerical oscillations in the detention pond roting that prevented the reliable se of canned nonlinear programming solvers, and the development of a measre for annally-averaged infiltration to the grondwater system. The organization of the paper is as follows. In Section, the design problem and associated mathematical programming model are described. In Section 3, details on the implementation of the DST are given. In Section 4, an example se of the DST is shown and general conclsions are drawn. A smmary and conclsions is provided in Section 5. 4

5 Design problem Figre 1 is a schematic of the system nder consideration. The total site area, A T, reqiring hydrologic control incldes contribting impervios areas sch as bildings and sidewals (A contrib ), the paring area (A P ), area for a detention pond (A det ), and area left ndeveloped (A ndev ). The paring area is broen down frther into a pervios paring srface (A perv ) and impervios paring srface (A imp ),. Precipitation, of corse, falls on all srfaces. The rnoff from the contribting impervios and the impervios paring area flows onto the pervios pavement and, along with the direct precipitation, rapidly infiltrates into the pervios pavement and nderlying gravel base. Water stored in the pervios ltimately will exfiltrate into the nderlying soil. Shold the pervios storage capacity be exceeded, there will be rnoff into the detention pond. This rnoff will be combined with the direct precipitation and any rnoff from the ndeveloped area. The storage in the pond will be governed by these inpts and the otlet strctre and spillway of the detention pond. The flow ot of the pond is denoted by Q(x p,x d ). 5

6 Figre 1 Schematic of the system nder consideration Design storm precipitation Pervios Detention pond GW( x p ) Q( x p, x d ) Acontrib Aimp Aperv Adet A ndev A P Paring area ( ) Impervios areas Pervios areas Site area ( A S ) Total area ( A T ) The decision problem, as framed, is to allocate the area A T -A contrib to each of A perv, A imp, A det and A ndev. Given a desired paring area (A P ), an eqivalent way of framing the problem is to determine the fraction of the paring area that will be pervios, x p and the fraction of the area available for a detention pond, A T -A contrib - A P., that will actally be allocated for a detention pond, x d ; the fractions are bonded by zero and 1. All areas can be compted: A A A A perv imp det ndev = A = A = P P x ( 1 x ) ( AT Acontrib AP ) xd = ( A A A )( 1 x ) T p p contrib P d Redcing the nmber of decision variables from for to two facilitates a manal search and atomated search for designs. 6

7 Cost fnction A goal of the allocation is to minimize the total system cost: Min C x p, xd ( x, x ) p d (1) The cost fnction, C(x p,x d ) incldes paring lot and detention pond costs and can be modified by the ser throgh varios parameters: nit constrction costs for each pavement type (pervios/impervios) on a cbic yard and sqare foot basis, nit constrction costs for the detention pond are on a volmetric basis (dollars/cbic ft capacity), and nit maintenance costs. Infiltration from the pervios pavement Increasing infiltration spports the water spply and flood control objectives. The hydrologic modeling of the pervios pavement was informed by the wor of Leming et al. (007) in the development of the Pervios Concrete Hydrological Analysis Program. Their simlation tool can be sed interactively to find the thicness of the pervios pavement and that of the nderlying gravel base reqired to infiltrate all (or some fraction thereof) of a design storm rainfall falling onto the pervios pavement and hydralically connected impervios areas; an effective crve nmber (CN) is calclated and can be sed in hydrological stdies employing the USDA SCS method. Key inpts are the porosities of the pervios pavement and nderlying gravel base in addition to parameters related to the design storm. Effectively, Leming et al. model the sbsystem represented to the left of the detention pond in Figre 1. The following pervios pavement modeling assmptions were adopted from the Pervios Concrete Hydrological Analysis Program as described by Leming et al. (007). The pervios pavement is placed level. There is negligible evaporation and negligible capillarity. There is rapid vertical flow into the pervios pavement. An exfiltration rate governs infiltration into the nderlying soil; it is constant while water is available. Finally, there is immediate rnoff from impervios areas into the pervios area. The assmption of immediate rnoff from 7

8 impervios areas is conservative, thogh for impervios areas on the sites for which the tool is designed, times of concentration are expected to be small. Exclsive se of pervios for hydrologic control of large design storms is typically assmed. Sch designs will infiltrate the smaller storms. Here, however, hybrid designs, ones for which the pervios pavement does not store the fll pea-rnoff design storm, are also considered. Most of the water that is available for grondwater recharge, stream base flow, and rooting-zone soil moistre comes from small, freqent storms, while large storms, despite their size, contribte relatively little (Fergson, 005). Conseqently, hybrid designs may, at mch lower cost, secre considerable water spply benefits. For the DST, a measre for annally averaged infiltration from the pervios pavement was developed that incorporates consideration of a time series of storms instead of a design storm for pea-flow concerns. TD 360 US 15-Minte Precipitation Data is tilized. This data incldes the precipitation amonts for each 15-minte time period for which there was precipitation. The data for a fifteen-year period are fed into a simple pervios infiltration model based on the above assmptions. The se of the fifteen-minte data allows for the modeling of the overflow of the pervios storage and acconts for the draining between precipitation events. Initial losses were assmed to have occrred had there been no precipitation in the previos 4 hors; the defalt for initial losses, in inches, was set to 0.1. The constraint for meeting an infiltration target, is given by GW ( ) * x p GW () where GW * is an lower limit on the fraction of the contribting and paring area rainfall that is infiltrated by the pervios. This constraint translates into a lower bond on x p, x p. The vale of x p can be fond with the bisection method. 8

9 Post-development pea rnoff Increasing infiltration can redce rnoff and help to redce the extent of flooding. To prevent downstream flooding and erosion, however, the focs is typically on the pea rnoff, Q* (Fergson, 1995). It is typically reqired that post-development pea rnoff not exceed predevelopment pea rnoff, Q *. Modeling of the post-development pea rnoff Q( x, ) carried ot sing a specific design storm that is considered protective. The resltant constraint is: p x d is Q * ( x, x ) Q p d (3) The rnoff into the detention pond from the pervios pavement is yielded by the pervios concrete infiltration modeling as applied to the pea-rnoff design storm. As implied in the schematic drawing of the system (Figre 1), rnoff from the pervios area into the detention pond occrs when the pervios storage capacity is exceeded. To estimate the pea flow ( x, ) Q as a fnction of the detention pond area, a detention pond p x d shape that scales p with increasing A det is assmed. The shape reflects varios restrictions. To prevent accidental drowning, for slope stability, and to allow for safe mowing, a maximm side slope (ft laterally/ft of rise) is specified, e.g., one foot of rise for every three feet of rn. In addition, to eep the otlet strctre free of sediment, a long flow path is generally recommended. Given these considerations, the detention pond is modeled as rectanglar in shape with a constant side slope on all faces, and a fixed length-to-width ratio; both qantities are ser inpts. In addition, other considerations can limit the depth of the detention pond. The otfall cannot be too low as flow from the pond is by gravity. Frther, the elevation of the bottom of the pond mst be above the grondwater table. For these reasons, a maximm height of the pond is a ser inpt. If the detention pond area A det is small, the side slope restrictions can limit the depth of the pond to vales less than the ser-specified maximm depth. 9

10 Given A det, the inflow to the pond can be roted throgh the pond to allow determination of Q*, the pea rnoff ot of pond. Several approximate relationships, e.g., as given by Paine and Aan (001), are available for determining reqired detention storage to meet pea-rnoff reqirements. While these relationships wold have been an appropriate level of analysis for the screening tool, they did not captre the specific inflow hydrograph of the pervios pavement flow into the pond. The pervios pavement storage dramatically changes the shape of the inflow hydrograph, effectively storing the early part of the design storm and ths no longer resembling the shape of the storms (e.g., SCS design storms) on which the methods are based. The trncated natre of the inflow hydrograph is an important factor to captre in the modeling of infiltration designs for pea flow control (Fergson, 1995). De to the inapplicability of the approximate methods for relating pea otflow to detention pond size, level pool roting was applied. The eqation for level-pool roting is dv dt () t Q ( V ) = Q (4) in ot where V is the volme stored in the detention pond, Q in (t) and Q ot (t) are the inflow and otflow from the pond as a fnction of time. The pea rnoff, Q(x p,x d ), is the maximm vale of Q ot (t) over the dration of the design storm. There are a nmber of standard nmerical methods for solving for the otflow as a fnction of time. However, problems with nmerical oscillations were encontered that hampered the decision search process implementation. As it was a goal for the search method to wor for a large range of detention pond sizes, a different method that avoided the nmerical oscillation was developed for the specific assmed shape of the detention pond. The roting method is detailed in the appendix. The roting assmes the most common 1 otlet control, a single orifice otlet, where the otflow is ch ; c is the otlet coefficient and h is the height of the water in the pond (above the orifice). 10

11 Mathematical programming model Eqations 1-3 constitte an optimization model that specifies that a design is soght that minimizes cost while meeting the infiltration target GW * and pea rnoff limit Q *. 3 Implementation The DST consists of inpt databases, a graphical interface, a simlation model, and optimizationbased tools. It was implemented in Microsoft Excel and Visal Basic for Applications (VBA). This implementation was selected as existing tools in Excel offer fnctionality with little or no additional programming reqired. For example, the data validation capability of Excel ensres that appropriate inpt vales are assigned, while conditional formatting can be sed to alert the ser to problems, for example, with the feasibility of the design. In addition, se of Excel met the goals of model transparency and model availability. The ser can explore designs sing the simlation model throgh a process of trial-and-error or can invoe the optimization-based tools. Figre and Figre 4 are schematic diagrams of the simlation model and optimization models, respectively. Simlation model Figre indicates the interface between the model ser and the simlation model. The economic, pervios pavement, and detention pond hydrologic models are shown on the left side. The ser assigns vales to these inpts or accepts the defalt vales provided. The ser can evalate a particlar design by specifying the area allocation with x p and x d (located on the right side of Figre ) and viewing the otpts of the hydrologic and economic models, which inclde the cost, infiltration, and the pea rnoff. If the vales are nacceptable, the ser can carry ot a manal search, iteratively changing the vales of the decision variables. 11

12 Figre Schematic overview of the simlation model Model User Simlation Model C( x p, x d ) Unit costs, Pavement lifetimes, Interest rate Economic Model Depth -pervios -gravel Pond volme A, A imp perv A, A, A T P contrib x p, x d Design storm Hydrologic model Exfiltration rate Porosity & Depth -Pervios -Gravel GW( x p ) Pervios Rnoff into pond A, A, A contrib imp perv Side slope, Length-to-width ratio, Max depth Detention Pond Q( x p, x d ) A det, A ndev Optimization model A search method is reqired to solve the mathematical programming model (Eqations 1-3) to determine the design that minimizes cost while meeting the infiltration target GW * and pea rnoff limit Q *. As there are only two decision variables, x d and x p, an exhastive search method cold easily be sed to solve the model. However, for efficiency in developing tradeoff crves, an optimization approach is desired. The discrete natre of the modeling prohibited the reliable se of a gradient-based nonlinear programming solvers that for reliable se typically reqire that the model be continos and differentiable. There is an abrpt change in Q x p when the pervios capacity is exceeded. In 1

13 addition, there is an abrpt change in Q xd when the increase in A det cases the detention pond to become constrained by the maximm depth limitation. Testing with the GRG solver inclded in Excel revealed that it cold not be sed reliably to identify optimal soltions de to this lac of smoothness. While it was sccessfl in the majority of cases, with some freqency trial soltions were infeasible and the solver halted. Changes in step size (achieved with re-scaling the decision variables) sed for the nmerical differentiation did not correct the problem. Instead, the search strategy given in Figre 3 was developed. The infiltration target translates into a lower bond on the percent of the paring lot that is pervios. An assmption of the method for optimality to be garanteed is that, to meet the pea rnoff limit, it is always more cost-effective to increase the size of the detention pond than to increase the pervios fraction of the paring lot. This assmption is reasonable becase the cost per nit volme water storage provided is mch higher for pervios pavements than detention pond storage and, moreover, the pervios pavement generally has no otlet strctre. It is for this reason that the model is rn with the pervios fraction set at the minimm necessary for meeting the infiltration target and the detention pond area is set at 100% of the sable area: if the pea flow target is met, than the detention pond area is redced ntil the pea flow target is exactly met; otherwise the pea flow limit is violated and therefore the fraction of pervios is increased ntil the point at which the pea flow target is exactly met. The bisection method is sed as there is a single root that falls between two nown bonds: addition of pervios and a larger detention pond both monotonically lower the pea flow ot of the pond. 13

14 Figre 3. Search method to identify optimal vales of decision variables (xp,xd) Apply bisection method (bonds=[0,1]) to identify root x of: GW p p ( x ) GW * = 0 Set x = x p Set x = 100% d p Q * () Q? no yes Apply bisection method (bonds=[0,1]) to identify root of: Q x, x Q * = ( p d ) 0 Apply bisection method (bonds=[ x,1]) to identify root of: Q p ( x, x = 100% ) Q * = 0 p d * x p = x p * x d = root * p x = root x * d = 100% Systems analysis tools Figre 4 shows how the systems tools interact with the simlation model. A simplified schematic of the simlation model is shown on the left side of the figre. On the right side is a box indicating the ser interface to the optimization model. The ser inpts pper limits on the pea rnoff, Q*, the infiltration target, GW*, and enters the reqired paring area. When the ser invoes the Solver, the iterative search procedre is rn, which retrns the area allocation that minimizes the total system cost while meeting the limits. 14

15 In addition, the ser can invoe a tool that retrns a report. A plot is retrned showing the tradeoff between the detention pond and pervios paring area reqired to meet Q * and GW *. A plot is also prodced showing the cost of varying the infiltration target GW *. Finally, a plot is retrned that shows how the design and minimm cost vary with increasing paring area. Figre 4 Schematic overview of the DST Model ser Simlation model C( ) Model ser Optimization tools Inpts Economic Model Q *,GW * Hydrologic model x p, x d Solver * C, * * x p, xd Inpts Cost ($) # Paring spaces GW( ) Pond size Pervios paring Q( ) 4 Demonstration of the DST To demonstrate the capabilities of the DST and to draw basic conclsions abot the se of pervios, the siting of a hypothetical paring lot on an ndeveloped site in a coastal region in the Sotheastern United States is considered. The total site area is 15,000 sq ft, 5,000 sq ft of which is connected impervios areas (roofs, sidewals). The paring lot and any detention pond mst fit within the remaining available land, 10,000 sq ft. The goal is to have 3 paring spaces, which at 350 sq ft per space (inclding driving area and entry/exit ways), wold be met with 8,050 sq ft 15

16 of paring area. The percent of the paring area that is pervios concrete and the size of the detention pond are soght. A 10-yr type II SCS 4 hor design storm is sed for the pea rnoff modeling. The 10-yr rainfall amont is 6.3 inches. An exfiltration rate of 0.8 in/hr is assmed, which is reflective of a sandy, well-draining soil. The pervios concrete thicness is 6 inches, which is a typical vale set for the drability reqired of a paring lot; a 10-inch nderlying gravel base provides additional water storage capacity. These and other inpts are given in Figre 5. 16

17 Figre 5 Inpts for the demonstration case Design Site areas Total site area (with contribting) (sq-ft) 15,000 Contribting connected impervios (sq ft) 5,000 Area per paring space (sq ft/space) 350 Impervios pavement Thicness (in) Initial losses (in) 0.1 Pervios pavement Thicness (in) 6.0 Porosity (nitless) 0% Thicness gravel (in) 10.0 Porosity gravel (nitless) 40% Crb and gtter (linear ft/sq-ft) Impervios 0.04 Pervios 0.00 Detention pond Side slope (ft horiz/ft vertical) 4.00 Ratio of length to width (nitless) 3.00 Maximm depth (ft).00 Hydrology Max soil exfiltration rate (in/hr) 0.80 Design storm Clic here to edit Cost Unit cost to spply ($/c-yd) Impervios 0 Pervios 140 Gravel (placed nder pervios) 35 Unit cost to place ($/sq-ft) Impervios.5 Pervios 5.0 Gravel (placed nder pervios) 0.0 Crb and gtter Unit cost ($/linear ft) Detention pond Unit cost detention pond ($/c-ft) 1.0 Annal O&M costs ($/sq-ft/yr) Impervios 0.33 Pervios 0.7 Financial Impervios paring lot lifetime (yr) 30 Pervios paring lot lifetime (yr) 30 Detention pond lifetime (yr) 30 Annal interest rate 5.0% 17

18 Design page Higher level inpts are located on the design page of the tool, a screen captre of which is shown in Figre 6. These inpts inclde the reqired paring area, the pea rnoff limit, Q*, and the infiltration target, GW*. A paring area of 8,050 sq ft is inpt. The pre-development pea rnoff is 1 cfs and therefore the limit on the post-development pea rnoff, Q*, is set at 1 cfs. No infiltration lower limit is set. Figre 6 Screen captre of the DST design page 18

19 The decision variables inclde the fraction of paring that is pervios paring (x p ) and the fraction of the remaining area that is available to the detention pond that is allocated to the detention pond (x d ). In the screen captre (Figre 6), the reslts of a hybrid design are shown, one with both pervios paring and a detention pond. Gidance on pervios pavement design has typically assmed exclsive se of pervios pavements for stormwater management. Here, 40.0% of the 8,050 sqare feet paring area is pervios, with the remaining 60% being impervios paring. Of the land available to the detention pond, 40.0% is occpied by the detention pond, with the remainder left ndeveloped. The figre on the lower left graphically displays the land allocation. The annalized cost of the design is approximately $5,000/yr, or approximately $18/space/year. The flow into and ot of the detention pond as a fnction of time for the pea flow design storm is shown in the lower right of the screen captre. As a point of reference, the total precipitation flx (cfs) onto the entire site area is also shown. The inflow hydrograph is the sm of the direct precipitation into the pond and the rnoff into the pond from the paring and ndeveloped areas. The area between the precipitation flx crve and the inflow hydrograph reflects the water stored/infiltrated by the pervios. The effect of the pervios concrete on the inflow hydrograph can be seen. The large jmp in the inflow hydrograph at 11.8 hrs occrs when the pervios storage capacity is exceeded and rnoff from the paring area into the detention pond begins. Before 11.8 hrs, the pervios accommodates mch of the rainfall throgh storage and infiltration; only the rnoff from the ndeveloped area and direct precipitation onto the pond area is not captred. After 11.8 hrs, the entire rainfall is roted throgh the detention pond less the amont of infiltration by the pervios. The detention pond, the otlet strctre of which is sized to release the maximm pea flow allowed (Q*), delays and dampens the inflow hydrograph, bt ltimately cannot accommodate all of the inflow and the pond overtops, mared by the jmp in the otflow hydrograph. The pea rnoff is jst over cfs, well over the 1.00 cfs target. 19

20 Visally, the lac of feasibility is indicated by the box to the right of the respective constraints that is conditionally formatted (green for feasible; red for infeasible). The annally-averaged fraction of precipitation falling onto the contribting and paring areas that infiltrates into the soil below the pervios is estimated at approximately 84%. The pervios does not captre the entire pea-flow design storm. Other model otpt available to the ser indicates that the pervios stores and infiltrates approximately 68% of the design storm precipitation falling onto the contribting impervios and paring areas. The annally averaged fraction infiltrated is higher becase most precipitation over the corse of a year comes from smaller storms, many of which can be effectively captred. Manal search The ser can search for designs manally. Initially, the ser might explore the exclsive se of pervios concrete or the exclsion of pervios concrete from the design. By inptting a 100% pervios design (x p =100%) with no detention pond (x d =0%), the cost is 6,13 $/yr. The fraction infiltrated on an annally averaged basis is 90%. The pea flow rnoff for the design storm is 0.39 cfs, which more than meets the 1.00 cfs limit,. At the other extreme, a design involving no pervios (x p =0%) and assignment of the entire available area to the detention pond (x d =100%) costs 4,361 $/yr. This design is considerably less expensive. With this design, however, there is no infiltration of the paring area rnoff. The pea flow rnoff is 0.93 cfs, which too meets the 1.00 cfs limit. The ser can bac off each of these extreme designs ntil the pea flow limit is exactly met. The ser, throgh an iterative process, wold find that pervios can be applied to only 7% percent of the paring lot and still meet the pea rnoff limit withot se of the detention pond. Unlie the design depicted in Figre 6 in which the pervios did very little to redce the paring area pea rnoff, with this design the pervios stores/infiltrates the heart of the design storm and, by doing 0

21 so, does redce the pea rnoff. For the other extreme design, where pervios is avoided, the ser can find that the pea flow limit can be reached with se of 78% of the detention pond area, or a 1,54 sq ft pond. For both of these designs, there are cost savings: the pervios design withot a detention pond costs approximately $5,600, while the detention pond design costs 4,300 $/yr. Solver As there are only two decision variables and two constraints, the ser can condct an effective manal search. In the process, the ser can learn the interactions in the system, and withot mch difficlty, find a least cost design. The effects of increasing the detention pond size, inclding the dampening of the rnoff and delay of the pea, can be observed by the ser. Moreover, the effect of the infiltration on the inflow hydrograph to the detention pond can also be observed, as can the cost fnction sensitivity to the fraction pervios and detention pond size. However, the process is considerably sped p with the solver. The procedre shown in Figre 3 retrns the least cost design for the 8,050 sq ft paring lot. One rn taes approximately five seconds on an Intel Pentim M processor 1700MHz with 1 GB of RAM rnning Microsoft Windows XP. The design incldes no pervios pavement and the pea rnoff limit is met with a detention pond sing approximately 78% of the land available for it. As there is no pervios, there is no infiltration of the contribting and paring area rnoff. The main advantage of the solver is that it can be rn repeatedly to investigate changes in the optimal design when parameters are changed. For example, the infiltration target can be varied and the change in the minimm cost can be observed. The report capability of the DST can help to answer some typical qestions abot the design that wold otherwise be time-consming with a manal approach to the design. 1

22 Infiltration/Cost savings tradeoff For the report, a crve (Figre 7) is generated that shows how cost varies when changing the infiltration target. The crve shows that only a modest increase in cost is needed to secre a very large increase in annal infiltration. To increase the fraction infiltrated from zero to 40% costs approximately $160/yr, which is 3.6% of the original cost. The 40% infiltration design reqires 8.% pervios paring. To frther increase the fraction infiltrated to 80% costs an additional $440/yr, which is 10% of the original cost; the design reqires 3% pervios paring. These reslts demonstrate that the water spply objective can be met with a hybrid design withot the expense of a 100% pervios paring lot. Figre 7 Cost as a fnction of infiltration target for demonstration case $5,000 $4,900 $4,800 Annalized Cost ($/yr) $4,700 $4,600 $4,500 $4,400 $4,300 $4,00 0.0% 10.0% 0.0% 30.0% 40.0% 50.0% 60.0% 70.0% 80.0% 90.0% 100.0% Fraction infiltrated

23 Pervios/Detention pond tradeoff Inclded in the report is a crve showing the tradeoff between detention pond area and pervios paring area reqired to meet the pea rnoff target Q* (and the infiltration target shold one be specified). The crve shows varios ways of meeting Q* with different combinations of detention pond area and pervios paring area, irrespective of cost. The crve shows the degree to which the detention pond area can be redced when the fraction of pervios paring is increased. Any area freed p by having a smaller detention pond area is land available for other ses. Initially, addition of pervios area does little to decrease the reqired detention pond area. The small redction in reqired detention pond area is attribted to the small amont of water that is stored/infiltrated by the pervios had there been no pervios, this same water wold largely have been processed throgh the pond before the arrival of the heart of the storm. However, as more pervios is added, part of the rn-p to the storm pea can be stored in the pervios and this storage does begin to offset detention pond storage. 3

24 Figre 8 Detention pond/pervios tradeoff for demonstration case 1,600 1,400 1,00 Detention pond area (sq ft) 1, ,000,000 3,000 4,000 5,000 6,000 7,000 Pervios paring area (sq ft) Cost of adding more paring spaces A crve (Figre 9) showing the cost and design changes as more paring spaces are sqeezed into the site footprint is also generated in the report. For each data point, the area allocation is shown. Several conclsions can be drawn for the demonstration case from the figre. No pervios concrete is reqired for fewer than 5 spaces; a detention pond occpying approximately 1,500 sqare feet is sfficient to meet the pea rnoff target. If 5 spaces are reqired, however, only 1,50 sq ft are available for the detention pond and the pervios concrete option is needed to meet the pea rnoff limit. When first having to resort to pervios concrete, there is a prononced jmp in cost. The cost per space p ntil the 4 th space is approximately $183/yr. The cost of adding the 5 th space is 4

25 $807/yr. Additional spaces are approximately $430/yr. The large jmp when first resorting to pervios concrete can be explained with the nderstanding of the pervios/detention pond tradeoff presented earlier (Figre 8). The initially shallow slope of the tradeoff crve indicates that mch pervios paring area is needed to decrease the reqired detention pond area by a small amont. Beyond the sholder of the tradeoff crve, the addition of pervios redces the reqired detention pond area mch more significantly, in an approximately linear relationship. The lac in convexity in the cost crve has implications for paring lot sizing. It may be (bt is not necessarily the case) that there are diminishing retrns for paring spaces. Becase the marginal costs are not continally increasing in paring spaces, the optimal size may not be fond simply by eqating marginal costs with marginal retrns. Figre 9 Cost and design as a fnction of paring area 14,000 $7,000 $6,000 1,000 Area allocation (sq ft) 10,000 8,000 6,000 4,000 $5,000 $4,000 $3,000 $,000 Annalized Cost ($/yr) Contribting Impervios Pervios Det. Pond Undeveloped Cost,000 $1, Nmber of paring spaces $0 Sensitivity to exfiltration rate The exfiltration rate is a ey parameter, as it governs the infiltration into the soil nderlying the pervios pavement. The above analysis was repeated above with an exfiltration rate of one order of magnitde less, 0.08 in/hr instead of 0.8 in/hr. 5

26 The cost of increasing infiltration is greater with a lower exfiltration rate. The cost crve for the original 8,050 sq ft paring lot is given for both exfiltration rates in Figre 10. Given a rate of 0.8 in/hr, the increases in cost were 160 $/yr and 440 $/yr to increase the fraction infiltrated from zero to 40% and then 40% to 80%, respectively. With the lower rate, the corresponding increases in costs are 351 $/yr and 969 $/yr, respectively. Figre 10 Effect of decreasing exfiltration from 0.8 in/hr to 0.08 in/hr: Cost as a fnction of increasing fraction $6,000 $5,000 Annalized Cost ($/yr) $4,000 $3,000 $,000 Exfiltration rate=0.08 in/hr Exfiltration rate=0.8 in/hr $1,000 $0 0.0% 10.0% 0.0% 30.0% 40.0% 50.0% 60.0% 70.0% 80.0% 90.0% 100.0% Fraction infiltrated The sensitivity of the pervios/detention pond tradeoff to the exfiltration rate is given in Figre 11. Significantly more pervios is needed to offset the reqired detention pond area. In addition, within the same site footprint, pervios alone was nable to store a sfficient amont of the design storm so as to redce the pea rnoff to the maximm allowed; this is indicated by the tradeoff crve not intersecting the x-axis. With the lower exfiltration rate, the time at which the pervios storage capacity was exceeded and rnoff into the pond begins occrs sooner. For 6

27 example, if one sets the pervios fraction to 10% (750 sq ft), rnoff into the pond begins at 7.6 hrs given the higher rate bt mch earlier, 4.5 hrs, given the lower rate. Figre 11 Pervios/Detention pond tradeoff sensitivity to exfiltration rate 1,600 1,400 Exfiltration rate=0.08 in/hr Exfiltration rate=0.8 in/hr 1,00 Detention pond area (sq ft) 1, ,000,000 3,000 4,000 5,000 6,000 7,000 8,000 9,000 Pervios paring area (sq ft) Figre 1 shows the pdated relationship of cost and design to paring lot size. Mch more pervios is needed to sqeeze in additional paring spaces and this increases the cost. The provision of 8 spaces had cost $6,600/yr given an exfiltration rate of 0.8 in/hr, whereas with the lower rate of 0.08 in/hr the cost increases to approximately $7,400. This is a cost increase of 1%. 7

28 Figre 1 Effect of decreasing exfiltration from 0.8 in/hr to 0.08 in/hr: Cost and design as a fnction of paring area 14,000 $8,000 $7,000 Area allocation (sq ft) 1,000 10,000 8,000 6,000 $6,000 $5,000 $4,000 $3,000 Annalized Cost ($/yr) Contribting Impervios Pervios Det. Pond Undeveloped Cost 4,000 $,000,000 $1, Nmber of paring spaces $0 Limitations and possible extensions If not properly maintained, for example with periodic vacming, pervios srfaces can clog. (It shold be noted that detention ponds also tend to fail over time from improper maintenance; maintenance in general is an isse with BMPs). If the pervios srface becomes sfficiently clogged, the infiltration rate into the top srface of the pervios cold become limiting and not the exfiltration rate into the nderlying soil; this condition wold negate the vale of the pervios storage bt wold still permit infiltration at the top rate. This condition cold be modeled with the DST by eliminating the pervios storage (by setting the pervios and base porosities to near zero) and setting the exfiltration rate eqal to the rate at the top srface. However, a change in the hydrologic model wold be reqired to captre the gradal clogging over time. In the present DST, the ser is limited to modifying the sefl lifetime of the pervios concrete. A hybrid design may impose additional costs that are not crrently captred in the DST. Bilding a hybrid design may involve having to deal with mltiple contractors, one for the impervios pavement, pervios pavement, and for the detention pond, all of which may impose additional 8

29 costs. In addition, as the areas of each wold necessarily be smaller, there may be lost economies of scale. In the crrent version, if a hybrid design is retrned, the ser shold revisit the nit costs to see that they are appropriate. The explicit incorporation of fixed costs into the search method wold reqire a more comptationally expensive search method. The crrent DST assmes the most common stormwater control, a detention pond. Among the other options are a wet retention pond, dry extended detention pond, and ndergrond retention/detention system. A wet retention pond wold captre infiltration benefits bt wold reqire more area than a dry pond for the same pea flow control, as the pond will be partially fll prior to the arrival of the pea storm. Undergrond retention/detention systems, lie pervios pavements, can help in pea flow control withot sacrificing paring area and can be designed for infiltration prposes. These systems may be more expensive and can be difficlt to maintain, however. Extension of the DST to inclde these alternatives is being considered. In the crrent version of the DST, it is assmed that there is no ponding of water on the paring area. Considerable storage can be provided by bilding ponding into the design on both the flat impervios and flat pervios paring areas. For the pervios, this wold reqire additional crbing. Sch an extension to the DST is being considered. Pervios pavements direct polltants to the grondwater system instead of the srface water system. The effectiveness of pervios pavement infiltration systems is being investigated (e.g., Kwiatowsi, 004; Rshton, 001). Infiltration systems can act as effective polltant traps for a range of polltants (Mielsen et al., 1996a). However, Mielsen et al. (1996b) note that major problems remain and that simplistic modeling approaches are still needed for assessing the impact on soil and grondwater in local areas. The assessment of BMP polltant removal rates is an active area of research. The addition of water qality constraints to the DST wold increase its vale, particlarly if other stormwater control options sch as wet detention ponds can be inclded. 9

30 Reglatory considerations A hybrid design with a small amont of pervios may provide considerable water spply benefit de to the sbstantial infiltration. A small amont of pervios can infiltrate a sizeable fraction of many small storms. In addition, it can help to redce the size of downstream detention storage. These benefits are not captred by pea-rnoff reglations.. Simply conting pervios pavement as a pervios srface in a program of limits on percent imperviosness does not captre its benefits. Jones et al. (005) arge that the natre of connections of impervios areas to pervios srfaces is of paramont importance to assessing water qality, water spply and flood control benefits. The connections in the system nder consideration here connected impervios to impervios paring to pervios paring to detention pond spport this point. For example, the design for 5 paring spaces incldes 55% imperviosness for the site, which is considerably higher than typical site imperviosness limits. Nevertheless, the design provides considerable water spply benefits and is protective of flooding. 5 Smmary and conclsions A decision spport tool for the evalation of the se of pervios pavements for paring lot applications has been described. The Pervios-Impervios Tradeoff tool incorporates a hydrologic model of a system that may inclde contribting impervios area, a paring area consisting of impervios and pervios pavements, and a detention pond. Most gidance on stormwater best management practices (BMPs) assme exclsive se of a stormwater control option and not two options as are considered here. In addition, the tool incorporates systems analysis methods, inclding a search capability to identify cost-effective designs that meet rnoff and infiltration targets, and methods for the graphical display of tradeoffs. The tool is designed as a screening level tool; more advanced analysis shold be sed to evalate interesting designs. 30

31 The tool was demonstrated for a particlar hypothetical site. While reslts were specific to the hypothetical site, the following general conclsions were drawn from the demonstration: Exclsive se of pervios pavements for a paring area may be more costly than is reqired to meet infiltration and pea rnoff limits. A hybrid paring lot/stormwater control design that tilizes pervios and impervios pavements, and a detention pond, may be the most cost-effective design for meeting water spply and flood control objectives, and paring demands for a specific site. It may also be easier to design hybrid paring lots de to site topography. Increasing the fraction of the paring area that is pervios by a small amont can considerably increase infiltration to the grondwater system, which helps to spport water spply and flood control objectives. Increasing the fraction of the paring area that is pervios by a small amont has little effect on the pea rnoff from the paring area; the detention pond size reqired to meet the pea rnoff target changes little. The explanation is that water stored by the pervios wold anyway have been processed throgh the detention pond prior to the arrival of the heart of the design storm. Increasing the fraction of the paring area that is pervios frther can, however, redce pea rnoff, as a significant amont of the pea rnoff can be stored/infiltrated by the pervios, thereby offsetting detention pond storage. Relying exclsively on an on-site detention pond for stormwater control limits the maximm size of the paring area. Becase of the detention pond offset, increasing the fraction of paring area that is pervios allows for a larger paring area within the same site footprint. The reslts are highly site-specific. 31

32 6 Acnowledgements The athor wold lie to than members of the Carolina Ready Mixed Concrete Association. The athor wold lie to acnowledge the research assistance of Hiying Zh early in the project. The athor is gratefl for fnding early in the project from the Center for Manfactring and Technology at the University of Soth Carolina. 7 List of references 1. Fergson, B.K. Storm-Water Infiltration for Pea-Flow Control, Jornal of Irrigation and Drainage Engineering, vol. 11, no Fergson, B.K. Poros Pavements. CRC Press Harrell, L.J. and S.R. Ranjithan, Detention Pond Design and Land Use Planning for Watershed Management, Jornal of Water Resorces Planning and Management, vol. 19, no., p Harrison, K. W., R D. Dmas, E. Solano, M.A. Barlaz, E. D. Brill Jr., and S. Ranjithan. A Decision Spport Tool for Life-Cycle-Based Solid Waste Management. Jornal of Compting in Civil Engineering. vol. 15, no. 1, pp Hber, W.C., Cannon, L. and M. Stoder. BMP Modeling Concepts and Simlation, Report EPA/600/R-06/033. Environmental Protection Agency, Water Spply and Water Resorces Division, National Ris Management Laboratory, Edison, NJ Jones, J.E., T.A. Earles, E.A. Fassman, E.E. Herrics, B. Urbonas, and J.K. Clary. Urban Storm-Water Reglations Are Impervios Area Limits a Good Idea? Jornal of Environmental Engineering, vol. 131, Isse, p Kwiatowsi, M. Water Qality Stdy of a Poros Concrete Infiltration Best Management Practice, M.S. Thesis, Villanova University, Lee, J.G., J.P. Heaney, and F. Lai. Optimization of Integrated Urban Wet-Weather Control Strategies, Jornal of Water Resorces Planning and Management, Vol. 131, No. 4, p

33 9. Leming, M.L., H.R. Malcom, and P.D. Tennis. Hydrologic Design of Pervios Concrete, R&D Serial No. 89, National Ready Mixed Concrete Association, Silver Spring, Maryland and Portland Cement Association, Soie, Illinois, USA Mielsen, P. S., M. Hafliger, M. Ochs, J. C. Tjell, P. Jacobsen, and M. Boller. Experimental assessment of soil and grondwater contamination from two old infiltration systems for road rn-off in Switzerland. The Science of the Total Environment, vol , p a. 11. Mielsen, P. S., P. Jacobsen, and S. Fjita Infiltration Practice for Control of Urban Stormwater. Jornal of Hydralic Research, vol. 34, no. 6, p b. 1. Paine, J.N. and A.O. Aan. Design of Detention Systems, Chapter 7 in Stormwater Collection Systems Design Handboo, ed. L.W. Mays, McGraw-Hill, New Yor, NY Perez-Pedini, C., J.F. Limbrnner, and R.M. Vogel. Optimal Location of Infiltration-Based Best Management Practices for Storm Water Management, Jornal of Water Resorces Planning and Management, vol. 131, no. 6,, p Pitt, R. and J. Voorhees. SLAMM, the Sorce Loading and Management Model. In: Wet- Weather Flow in the Urban Watershed (Edited by Richard Field and Daniel Sllivan). CRC Press, Boca Raton. p Rshton, B.T. Low-Impact Paring Lot Design Redces Rnoff and Polltant Loads, Jornal of Water Resorces Planning and Management, vol. 17, no. 3., p Sample, D.J., J.P. Heaney, L.T. Wright and R. Kostas. Geographic Information Systems, Decision Spport Systems, and Urban Storm-Water Management, Jornal of Water Resorces Planning and Management, vol. 17, no. 3, p Sample, D.J., Heaney, J.P., Wright, L.T., Fan, C-Y, Lai, F-H, Field, R. Cost of Best Management Practices and Associated Land for Urban Stormwater Control, Jornal of Water Resorces Planning and Management, vol. 19, no. 1, p Westphal, K.S., R.M. Vogel, P Kirshen, and S.C. Chapra. Decision Spport System for Adaptive Water Spply Management. Jornal of Water Resorces Planning and Management, vol. 19, no. 3, p