Waackaack Creek Preliminary Hydrologic Model Report

Transcription

1 Waackaack Creek Preliminary Hydrologic Model Report Developed by the Rutgers Cooperative Extension Water Resources Program Prepared for Holmdel Township, Monmouth County, New Jersey March 8,

2 Table of Contents List of Tables... 2 List of Figures... 2 Acknowledgements... 4 Executive Summary... 5 Introduction... 5 Model Overview... 8 Engineering Methods... 9 DEM Preprocessing... 9 HEC-GeoHMS... 9 HEC-HMS Watershed Overview Land Use and Impervious Cover Hydrologic Soil Group Curve Number Model Results Model Limitations Sources of Flooding Recommended Solutions Reduce stormwater peak flow from subbasins Reconstruct stream channel Construct a wall Conclusion Next Steps References Appendix I: Waackaack Creek Model Results Appendix II: Curve Number-Land Use Matching List of Tables Table 1: 24-Hour Rainfall Frequency (Monmouth County) Table 2: Example Curve Numbers Table 3: Prioritization of subbasins for each attribute in order

3 List of Figures Figure 1: General overview of the Waackaack Creek Subwatershed... 7 Figure 2: Elevations of Waackaack Creek Figure 3: HEC-GeoHMS Delineated Subbasins Figure 4: General Land Use Figure 5: Urban Land Use Figure 6: Waackaack Creek Land Use Figure 7: Waackaack Creek Impervious Cover Figure 8: Waackaack Creek Hydrologic Soil Groups Figure 9: Waackaack Creek Curve Numbers Figure 10: Waackaack Creek Priority Basins

4 Acknowledgements The Waackaack Creek Preliminary Hydrologic Model Report has been produced by the Rutgers Cooperative Extension Water Resources Program. The principal author was Matthew Leconey, Program Associate, under the supervision of Christopher C. Obropta, Ph.D., P.E., Extension Specialist in Water Resources. Support material and guidance was provided by Michael Nikolis, Deputy Mayor of Holmdel Township. Funding for this project was generously provided by the Township of Holmdel, Monmouth County, NJ and in part by the New Jersey Agricultural Experiment Station through the United States Department of Agriculture. 4

5 Executive Summary An existing flooding issue on Palmer Avenue led to the Rutgers Cooperative Extension (RCE) Water Resources Program developing a hydrologic model for the Waackaack Creek watershed to determine the source of the flooding and to address potential solutions. ArcGIS and HEC-HMS were used to locate critical areas responsible for the flooding in the watershed for the 2-year, 10- year, and 100-year storm events. Subbasins were delineated for each watershed, and priority subbasins were identified based on peak runoff, normalized peak runoff, runoff volume, and runoff depth. These priority subbasins are those which contribute the most runoff to downstream flooding. Disconnection of impervious cover in these priority subbasins is recommended to reduce stormwater runoff volumes from entering the stream while also improving water quality. Other options to address the flooding include reconstructing the stream channel to allow more streamflow and creating a retaining structure along the roadway to prevent stormwater from reaching the roadway. Stream monitoring is needed to refine the model. This will allow for a more accurate model, and additional modeling using HEC-RAS software would allow better prediction to determine the best actions to reduce the flooding on Palmer Avenue. Introduction In the spring of 2018, Holmdel Township in Monmouth County contacted the RCE Water Resources Program to request assistance with evaluating a flooding problem occurring on Palmer Avenue. This area adjacent to the Cherry Tree Village development and Target experiences significant flooding several times a year which requires closure of the road. The watershed faces stormwater problems associated with increased impervious cover due to urban and industrial development. Impervious cover increases the rate and volume of stormwater runoff, which can cause flooding and degrade local water quality. To evaluate the potential sources of the flooding and determine potential solutions, a hydrologic model was needed to identify critical areas responsible for runoff and to determine streamflow through the flooding area. This information can also be used to estimate future scenarios (flood management, increased or decreased 5

6 development, or implementation of flood controls) that can be assessed as to their impact on water quality and quantity. Models are mathematical representations of a system that allow researchers and resource managers to perform trial-and-error scenarios on physical structures or environmental landscapes. The ability of models to vary input parameters and provide simulation and evaluation of multiple scenarios is ideal for flood management. The method generally followed when modeling hydrology is to monitor a system to be modeled, model the system of interest, and alter the model in some way to represent changes in the system. A hydrologic model will help decision-makers understand stormwater runoff volumes from subbasins within Waackaack Creek contributing to flooding and allow for determinations of stream and flood responses to stormwater runoff under various storm conditions. The model predictions can be used to help guide future development and land preservation decisions, target specific areas for flood control projects or stormwater infrastructure upgrades, and manage emergency efforts during a flood event. The RCE Water Resources Program completed stormwater runoff modeling for the Waackaack Creek watershed (Figure 1). The modeling effort involved using a rainfall-runoff model for the watershed to identify critical areas responsible for large volumes of runoff and to determine potential solutions to alleviate flooding. The model was developed by integrating a Geographic Information System (GIS) interface, ESRI s ArcGIS version , with the Hydrologic Engineering Center s Hydrologic Modeling System (HEC-HMS) version 4.3. The 2-year, 10- year, and 100-year storm events were modeled for the watershed. 6

7 Figure 1: General overview of the Waackaack Creek Subwatershed 7

8 Model Overview A numerical hydrologic model of Waackaack Creek was built using the U.S. Army Corps of Engineers (USACOE) HEC-HMS model. HEC-HMS is a distributed hydrologic model developed in the late 1980s by the USACOE that can simulate runoff at points within a watershed given data on the physical characteristics of that watershed. HEC-HMS is a wellaccepted engineering standard for analyzing stormwater runoff in watersheds like Waackaack Creek. HEC-HMS has the advantage over other models in that it uses readily available data, can operate in large-scale basins, has the possibility of simulation for long periods of time, and has a history of successful usage. Models created using HEC-HMS also require a small number of parameters to simulate flooding effectively 1. Data layers for elevation, hydrography, soil types, and land use/land cover (LULC) were required to obtain input parameters for the model. Hydrography (HUC14) and LULC data (2012) was downloaded directly from the New Jersey Department of Environmental Protection (NJDEP) Bureau of GIS website. 2 Elevation data (2015 USGS CoNED Topobathymetric Model) was obtained through the NOAA Data Access Viewer. 3 Soils data was obtained from the United States Department of Agriculture Natural Resources Conservation Service (USDA NRCS). These data were compiled using an ArcGIS graphical interface used to generate input files for the HEC-HMS model: HEC-GeoHMS. This allows the user to employ readily available GIS layers and easily create model parameters. Field observations and measurements were done to collect data to help verify this input data. Input parameters are then extracted from HEC-GeoHMS and transferred into HEC-HMS. In HEC-HMS, additional input parameters are provided (field data was used where applicable), and statistical rainfall data for Monmouth County, provided in the Engineering Field Handbook provided by NRCS, was used to generate synthetic rainfall events. The model then generates runoff based on soil data and impervious cover, and routing for streamflow is determined from lag time data. Streamflow for each subbasin is generated, and total streamflow and any downstream point can be determined through stream routing. 1 Ogden et al., NJDEP, NOAA,

9 Engineering Methods DEM Preprocessing A DEM (Digital Elevation Model) represents the rasterized version of elevation over a spatial area. A one-meter DEM (1-m horizontal accuracy, 20-cm vertical accuracy) was utilized to delineate the subbasins. However, some preprocessing is necessary to create an elevation model that accurately represents the hydrology, as they are not typically created with hydrology in mind. The biggest issue are bridges which show high elevations where low elevations really exist. Therefore, the Whitebox GAT software, developed by the Geomorphometry & Hydrogeomatics Research Group at the University of Guelph under Dr. John Lindsay, was used as it includes a Breach Depressions tool which creates cuts in the DEM to make it hydrologically accurate. While the tool was effective in getting most of the bridges, additional manual processing was needed to remove the remaining bridges and adjust areas that were cut incorrectly. HEC-GeoHMS A GIS is a way to display a digital database that can relate different layers of geospatial information or data referenced to a set of geographic coordinates. 4 The Geospatial Hydrologic Modeling Extension for HEC-HMS (HEC-GeoHMS 10.1) and Spatial Analyst extension for ArcGIS were utilized to combine different layers and extract attributes for use as input in the HEC-HMS modeling software. Standard procedures outlined in the HEC-GeoHMS user s manual under Terrain Preprocessing and Basin Processing were followed. These processes extract data from the DEM to generate the basin delineations and physical parameters for the model. Additional hydrologic parameters are needed, and the HEC-GeoHMS software includes a way to incorporate the data to export it to HEC-HMS. The NRCS Curve Number (CN) methodology used in the Technical Review 55 (TR- 55) model was chosen for the Loss and Transform Methods. This methodology requires a Curve Number value and a basin lag time. Curve Numbers are representations of both soil and land use types that estimate the absorptive ability of the soil. Standard CN tables used in the TR-55 model were utilized for the modeling. These tables correlate land use to CN values based on the 4 Folger,

10 Hydrologic Soil Group (HSG). The HSG is contained within the soils data, so this can be used with the 2012 LULC data to generate CN values for each subbasin. The table detailing how LULC data was correlated to appropriate CN values is shown in the Appendix. Basin lag was calculated using the CN Lag Method: Lag L. S Y. S 1,000 CN 10 Where: Lag = basin lag time (hours) L = hydraulic length of watershed (feet) Y = basin slope (%) GIS data was then exported into HEC-HMS as a basin model that can be directly loaded into the program. HEC-HMS HEC-HMS simulates rainfall-runoff and routing processes using a mathematical model. 5 The outputs of the model are hydrographs and tables estimating peak discharge, time to peak, and runoff volume. Components of HEC-HMS are basin models, meteorological models, and control specifications. The basin model created from HEC-GeoHMS was loaded as a starting point for the model. The model also has options for modeling canopy, surface, and baseflow, but these were all neglected from the model for simplicity. The Soil Conservation Service (SCS) hypothetical storm was selected as the precipitation type for the meteorological model. This synthetic precipitation was based on a Type 3 storm and the 24 hour rainfall frequency per storm event. Control specifications were set at 5-minute time intervals over a period of 48 hours. From the HEC-HMS Reference Manual, the SCS curve number loss method was used to estimate precipitation excess using the following equations: 5 USACOE HEC,

11 P P I P I S I 0.2S where Pe is the accumulated precipitation excess at time t, P is the accumulated rainfall depth at time t, Ia is the initial abstraction, and S is the potential maximum retention. This method is simple, well established, and widely used, however its drawback is that rain intensity is not considered. The SCS Unit Hydrograph transform model was employed. This method draws from the properties of the time-area histogram and the storage coefficient. 6 A peak factor of 284 (Delmarva) was chosen as this value is more appropriate for coastal watersheds. The Muskinham-Kunge model was utilized as a routing method as its parameters could be easily estimated from the DEM and aerial and field observations, and it is a reliable routing method based in Manning s equation. Rectangular geometry was assumed for simplicity. For more information on the components and complete descriptions of their relationships within the model, see the Hydrologic Modeling System (HMS) User s Manual Version 4.3 September USACOE HEC, USACOE,

12 Watershed Overview The entirety of the Waackaack Creek watershed was chosen for the development of the HEC- HMS model. While it is understood that Holmdel Township does not have jurisdiction over the portions of the modeled watershed not contained within its borders, this was done to represent a complete picture of the hydrology for the watershed. The watershed s elevation ranges from feet above mean sea level (AMSL) in the northern region to feet AMSL in the southern region (Figure 2). Annual rain accumulation for the area is 45 inches, and the total storm peaks by storm event are as shown in Table 1. 8 Based on NJDEP s HUC14 layer, the total drainage area is 6,161 acres (9.6 sq. miles). Using HEC-GeoHMS, the total delineated drainage area was less at 5,221 acres (8.2 sq. miles). The differences between the HUC14 watershed and the delineated subbasins are shown in Figure 3. The delineations match well everywhere except the northeast region. This portion likely flows out of the watershed through a different pathway and is left out of the model. Table 1: 24-Hour Rainfall Frequency (Monmouth County) 9 Storm Event 24 Hour Rainfall Frequency (inches) 1 year year year year year year year Office of the NJ State Climatologist, NJ NRCS,

13 Figure 2: Elevations of Waackaack Creek 13

14 Figure 3: HEC-GeoHMS Delineated Subbasins 14

15 A portion of the key information compiled and derived as input parameters for the hydrologic models are summarized in the following sections including land use, impervious cover, hydrologic soil group, and curve number. Maps are included to allow a better understanding of the spatial variation of these variables. Refer to Appendix I for detailed information regarding individual subbasins, the properties used, and the model output. Land Use and Impervious Cover Land use and impervious cover directly affect the ability Impervious surfaces are defined of stormwater to recharge aquifers and to prevent as any surface that has been downstream flooding. Developed areas have a greater covered with a layer of material so that it is highly resistant to percentage of impervious surfaces, which increases the infiltration by water. Examples rate and volume of runoff. 10 Increasing impervious include, but are not limited to, paved roadways, paved parking surfaces associated with urbanization account for many areas, building roofs, and of the alterations to watershed hydrology. Urbanization greenhouses. converts natural habitats to land uses with impervious surfaces (such as asphalt and concrete) that reduce or prevent soil infiltration of precipitation. Large amounts of impervious surfaces have negative impacts by increasing the amount of water and associated contaminants and sediments that flow through the watershed. This runoff, when managed improperly, is a major pathway for the transportation of pollutants such as debris, fertilizer, bacteria, and/or petroleum products. Increased runoff causes flooding when flood control measures are exceeded. The Waackaack Creek watershed is dominated largely by urban land use (75%) with a high percentage of this urban area used for residential (84%). The land use is summarized in Figures 4, 5, and 6. These urban areas also have higher values of impervious cover that generate more stormwater runoff. The impervious cover for the delineated subbasins ranged from 0.4% %. Figure 7 shows the impervious cover data from the NJDEP land use layer. 10 RCE Water Resources Program,

16 1% 1% <1% General Land Use 9% 13% AGRICULTURE BARREN LAND FOREST URBAN WATER 75% WETLANDS Figure 4: General Land Use 5% 4% 3% 3% 1% Urban Land Use RESIDENTIAL COMMERCIAL TRANSPORTATION/COMMU NICATION/UTILITIES 84% OTHER URBAN OR BUILT UP LAND RECREATIONAL LAND INDUSTRIAL Figure 5: Urban Land Use 16

17 Figure 6: Waackaack Creek Land Use 17

18 Figure 7: Waackaack Creek Impervious Cover 18

19 Hydrologic Soil Group Hydrologic soil groups quantify a soil s ability to drain water. 11 Stormwater runoff volume decreases with the more infiltration a soil provides. Soil infiltration is important not only as a way to decrease flooding, but also as a way to improve water quality and recharge local aquifers. The hydrologic groups range from A, which has the highest infiltration rates, to D, which has the lowest infiltration rates. There are three dual hydrologic groups (A/D, B/D, C/D) in which the first letter applies to the drained condition and the second letter to the undrained condition. 12 For the purposes of the model, soils are assumed to be drained. Group A soils tend to be sandier, whereas Group D soils are denser clays or areas close to the groundwater table. 13 Figure 8 shows the locations of hydrologic soil groups found within Waackaack Creek. 11 USDA, USDA, USDA,

20 Figure 8: Waackaack Creek Hydrologic Soil Groups 20

21 Curve Number Curve number is used in the SCS Curve Number Method to approximate runoff. 14 The main components for determining curve number are land use and hydrologic soil group. 15 Curve numbers range from 0 to 98, with higher numbers leading to increased runoff. 16 Examples of how curve number is affected by land use and hydrologic soil group are found in Table 2. Curve numbers were calculated by combining soils data and land use data and correlating their appropriate land uses to values found in the SCS methodology. Appendix II includes the table showing the curve numbers used in the model and how the 2012 Land Use was matched to the CN tables for the NRCS methodology. Figure 9 shows the curve numbers calculated for Waackaack Creek. Table 2: Example Curve Numbers 17 Land Use Hydrologic Soil Group A B C D Paved parking lots, roofs, driveways, etc Commercial and business districts Industrial districts Residential districts 1 acre Cultivated agricultural lands Straight row crops, Good condition Woods Fair condition Meadow Open space Fair condition USDA, USDA, USDA, USDA,

22 Figure 9: Waackaack Creek Curve Numbers 22

23 Model Results Refer to Appendix I for simulation results for the 2-, 10-, and 100-year storms in Waackaack Creek. Values extracted from the model include drainage area, peak discharge, runoff volume, normalized peak discharge, and runoff depth. Model Limitations The model is not yet calibrated as there are no existing gage records for Waackaack Creek except for the one at the tide gate that is difficult to use reliably for calibration due to tidal influences. Some options are possible such as using the hydrologic model results used in the Federal Emergency Management Agency (FEMA) Flood Insurance Study. However, the assumptions and data used in these reports is unclear, so it not ideal for calibration. Ideally, stream gauges and rain gauges should be deployed and monitored to determine streamflows during storm events. Without calibration, the model is not precise enough to give accurate streamflows during storm events. However, it can be effective in allowing comparisons of contributions of streamflows as it can still be used on a relative basis. The model also does not include any dam structures that can potentially restrict streamflow in certain areas. Stormwater basins also are not included in the model but would decrease peak streamflows coming from the subbasins where they are present. The delineation of subbasins is only as accurate as the surface elevation data. The storm sewer network is not considered and may route water in ways that differ from the surface elevations, although these generally correlate well. Sources of Flooding The goal of this study is to identify the sources of the flooding issues on Palmer Avenue and identify potential solutions. The sources of flooding can be identified by looking at the contributing flows from each subbasin leading to the flooding area. This can be done by looking at a few different values. Values for drainage area, peak flows, and total runoff volume give an indication of the subbasins that are contributing the most. Since the subbasins are different areas, peak flow and total runoff volume can be normalized by dividing by the subbasin area. These will give a better indication of representative runoff per unit area. Only subbasins upstream of the flooding area (CB1-CB21) basins are considered as only they contribute to the inflow, and considering downstream effects would require additional modeling. Since flooding occurs even 23

24 during smaller storms, the 2-year storm values are considered for comparison. Priority basins were designated as those with the largest values that when added together contribute 50% to the total for drainage area, peak discharge, or volume. Prioritization for normalized peak and runoff depth were chosen for those that fell above the average value for that property. The results of this analysis are summarized in order in Table 3. Priority Level Table 3: Prioritization of subbasins for each attribute in order Drainage Peak Runoff Normalized Area Discharge Volume Peak Normalized Runoff Volume* Discharge 1 CB16 CB16 CB16 CB21 CB21 2 CB17 CB13 CB13 CB20 CB20 3 CB13 CB20 CB20 CB13 CB13 4 CB01 CB01 CB01 CB01 CB01 5 CB08 CB03 CB17 CB03 CB16 6 CB CB16 CB03 7 CB CB04 CB CB19 CB CB CB11 *Normalized runoff volume is also known as runoff depth. Anything that appears in both the peak discharge and runoff volume categories and the normalized categories as a priority subbasin both contribute a large amount to flooding and does so disproportionally to other subbasins. Cross referencing these subbasins leads to the conclusion that CB01, CB03, CB13, CB16, CB17, CB20, and CB21 are the highest priority basins. Additionally, CB04 and CB19 have high contributions for their size. Subbasins CB01, CB03, CB13, CB16, and CB17 are largely dominated by residential areas while C20 and C21 are largely commercial areas. Figure 10 highlights the priority subbasins and includes identified stormwater basins. Stormwater basins are structures such as detention basins and infiltration basins that provided stormwater controls. Stormwater basin data was gathered from the New Jersey Hydrologic Modeling Database 18, and additional stormwater basins were identified from inspection of aerial imagery. 18 NJHMD,

25 Figure 10: Waackaack Creek Priority Basins 25

26 Subbasins that have a representative number of stormwater basins should have proper stormwater management based on the NJDEP stormwater regulations put in place in 1983 for stormwater quantity controls. This means any development including these basins should have been designed in a way that did not increase downstream flooding and therefore would have a reduced peak discharge than the value generated by the model. Therefore, areas without such stormwater control structures are contributing the most to downstream flooding. The clear outliers from Figure 10 are CB01, CB03, and CB16 which contain minimal stormwater controls. The only fault in this analysis is that the timing of peak flows can be also be important since peak flows do not add in a straightforward way. The timing of the peak will affect how much each subbasin contributes to the flooding as well. The total added peak flow is cfs (cubic feet per second), but the peak flow experienced at the flooding area is only cfs. Factoring this into the analysis is difficult, but it shows why an integrated model is helpful in showing the total effects at a specific point of flooding. Recommended Solutions This report was developed to identify the potential sources of flooding occurring on Palmer Avenue and determine potential solutions to reduce flooding. The subbasins most responsible for the flooding have been highlighted, so solutions for dealing with the flooding issue are now needed. There are a few potential approaches to this problem that could be explored which include: reducing stormwater peak flows from priority basins, reconstructing the stream channel, or constructing a wall along the roadway. Reduce stormwater peak flow from subbasins The key way to reduce stormwater peak flow from the subbasins is to reduce the amount of impervious surfaces that drain directly to local waterways. This would require preventing stormwater runoff from going directly to local waterways by capturing and treating it, then infiltrating it, reusing it, or letting it out slowly, all in a cost-effective manner. By disconnecting these impervious surfaces from flowing directly into the local waterways, we can reduce the stormwater peak flow that is causing the flooding problem to occur. 26

27 The RCE Water Resources Program recommends disconnecting impervious cover within the critical subbasins. Disconnection is the process of diverting the first flush of stormwater runoff from impervious areas to: 1) pervious areas so it has an opportunity to infiltrate or 2) smaller distributed best management practices (BMPs) for stormwater control. By redirecting runoff from paving and rooftops to pervious areas in the landscape or these best management practices, the amount of directly connected impervious area in a drainage area can be greatly reduced. Best management practices include features such as bioretention systems (i.e., rain gardens), pervious pavement, and rainwater harvesting. The practice of disconnection also is referred to as implementing "Source Controls" or "controlling stormwater at the source." This is different than past stormwater management strategies that divert all the stormwater runoff to a centralized location such as a detention basin. These source control practices can be easily incorporated into existing landscapes and can have a high aesthetic value as well as a stormwater treatment benefit. The RCE Water Resources Program has been developing impervious cover reductions action plans (RAP) for municipalities across New Jersey to help identify opportunities to implement stormwater best management practices. The plans identify specific locations for BMPs, such as rain gardens and pervious pavements, at a variety of sites. Calculations are included that show the impact these practices will have on stormwater runoff and could provide a plan to reduce stormwater flows from the priority subbasins. More traditional stormwater management techniques such as detention and infiltration basins could also be used effectively to reduce peak flow. Detention basins are designed to hold stormwater and let it out slowly in a way that will not cause high discharges. Infiltration basins are designed to also allow infiltration of water into the ground which removes the water from the surface hydrology. However, space may be limited for such large scale practices to be practical in many of these areas, especially in the old residential developments where major disruption would be needed to install the practices. Smaller more distributed practices may be more practical to implement in these areas. 27

28 This solution will address the root of the problem for the long term, but may require a lot of time and dedication to make happen. Additional modeling would be suggested to determine the scale at which practices would need to be implemented to have an effect on reducing flooding. Reconstruct stream channel A clear issue of the flooding on Palmer Avenue has to do with the current shape of the stream channel at this location. The slopes of the embankment are nearly vertical while traditional stream embankments have a more gradual change in slope. This channel shape means that smaller changes in stormwater flows lead to larger increases in the depth of the stream. This essentially means the stream cannot hold as much water which leads to water flowing out into the road during more intense rainstorms. Reshaping the channel may allow for greater storage in the channel which would reduce flooding. This reshaping would also increase access of rising water to the floodplain on western side of the stream (side opposite the road). This would require some further modeling to determine how the stream channel would need to be reshaped to effectively reduce the frequency of flooding. This process may be invasive to the surrounding area but would be an effective solution. Construct a wall The most direct solution is to simply try constructing a wall or earthen berm along the side of the roadway that would prevent stormwater from reaching the roadway. Alternatively, the road itself could be raised. While this is a potential solution, it does not address the root of the problem of there being too much stormwater. Stormwater may still be able to get around the wall or berm and produce flooding. Even if this does not occur, the stormwater will be forced downstream which may result in flooding at another location. Further modeling would be suggested to determine the extent of the wall and to determine if downstream flooding could possibly occur. 28

29 Conclusion The flooding occurring on Palmer Avenue is clearly a significant problem for Holmdel as the roadway floods several times a year. The modeling produced using HEC-HMS clearly demonstrates the priority subbasins that are responsible for the majority of the downstream flooding. The development of impervious areas without proper stormwater management, largely from the residential developments, has led to increased runoff over time that increased the likelihood of flooding occurring. To address the root of the flooding problem, stormwater runoff from these subbasins would need to be reduced. The other option is to alter the area to prevent water from reaching the roadway. This can either involve reconstructing the stream channel to pass more flow through it or building a retaining structure that prevents stormwater from flowing onto the roadway. The modeling produced for this report is not yet calibrated and is limited to comparing contributions from each subbasin. While the existing model clearly identified actions to reduce the flooding, calibration of the model will allow for more specific recommendations. Next Steps Further calibration and modeling is needed to produce more specific recommendations that would help guide decision making on how to address the flooding problem. This process would involve placing continuous stream gauges in the river to monitor the change in elevation of the stream over time. This would be combined with continuous rainfall gauges and individual flow measurements to provide the data needed to calibrate the model. Once the HEC-HMS model is calibrated, a HEC-RAS (River Analysis System) model could be created which allows for better understanding of flooding by incorporating bridges and channel geometry to more accurately simulate streamflow. With this modeling, there will be a better understanding of the hydrology and flooding of the area which will aid in guiding the solution of the flooding problem. 29

30 References Folger, P Geospatial Information and Geographic Information Systems (GIS): Current Issues and Future Challenges. Congressional Research Service , R New Jersey Department of Environmental Protection (NJDEP) Bureau of GIS NJDEP Digital Data Downloads. Accessed March New Jersey Hydrologic Modeling Database (NJHMD) Data Downloads. Accessed March New Jersey Natural Resources Conservation Service (NJ NRCS) New Jersey 24 Hour Rainfall Frequency Data, August Accessed March 2019: National Oceanic and Atmospheric Administration (NOAA) Data Access Viewer. Accessed February 2019: Office of the NJ State Climatologist (ONJSC) ONJSC at Rutgers University. Accessed March Ogden, F.L., J. Garbrecht, P.A. DeBarry, and L.E. Johnson GIS and Distributed Watershed Models. II: Modules, Interfaces, and Models. Journal of Hydrologic Engineering. 6: Rutgers Cooperative Extension (RCE) Water Resources Program Hamilton Township (Mercer County) Hydrology Report. United States Army Corps of Engineers (USACOE) Hydrologic Engineering Center (HEC) Hydrologic Modeling System HEC-HMS Technical Reference Manual. USACOE HEC, Davis, CA. United States Army Corps of Engineers (USACOE) Hydrologic Engineering Center (HEC) Hydrologic Modeling System HEC-HMS User s Manual, Version 4.3. USACOE HEC, Davis, CA. United States Department of Agriculture (USDA) Natural Resources Conservation Service (NRCS) Urban Hydrology for Small Watersheds. Technical Report 55 (TR-55). Accessed March 2019: 30

31 Appendix I: Waackaack Creek Model Results 31

32 Subbasin Drainage Area (acres) Percent Impervious (%) CN Basin Lag (min) CB CB CB CB CB CB CB CB CB CB CB CB CB CB CB CB CB CB CB CB CB CB CB CB EB EB EB EB EB EB EB Subbasin Drainage Area (acres) Percent Impervious (%) CN Basin Lag (min) EB EB EB MB MB MB MB MB MB MB MB MB MB MB NEB NEB NEB NEB NEB4a NEB NWB NWB NWB NWB NWB NWB WB WB WB WB WB

33 Runoff Depth (in) Normalized Peak Runoff (cfs/acres) Runoff Volume (Ac ft) Peak Runoff (cfs) Runoff Depth (in) Normalized Peak Runoff (cfs/acres) Runoff Volume (Ac ft) Peak Runoff (cfs) Runoff Depth (in) Normalized Peak Runoff (cfs/acres) Runoff Volume (Ac ft) Peak Runoff (cfs) Drainage Area (acres) Drainage Area (Mi^2) Subbasin CB CB CB CB CB CB CB CB CB CB CB CB CB CB CB CB CB CB CB CB CB CB CB CB EB EB

34 Runoff Depth (in) Normalized Peak Runoff (cfs/acres) Runoff Volume (Ac ft) Peak Runoff (cfs) Runoff Depth (in) Normalized Peak Runoff (cfs/acres) Runoff Volume (Ac ft) Peak Runoff (cfs) Runoff Depth (in) Normalized Peak Runoff (cfs/acres) Runoff Volume (Ac ft) Peak Runoff (cfs) Drainage Area (acres) Drainage Area (Mi^2) Subbasin EB EB EB EB EB EB EB EB MB MB MB MB MB MB MB MB MB MB MB NEB NEB NEB NEB NEB4a NEB NWB NWB

35 Runoff Depth (in) Normalized Peak Runoff (cfs/acres) Runoff Volume (Ac ft) Peak Runoff (cfs) Runoff Depth (in) Normalized Peak Runoff (cfs/acres) Runoff Volume (Ac ft) Peak Runoff (cfs) Runoff Depth (in) Normalized Peak Runoff (cfs/acres) Runoff Volume (Ac ft) Peak Runoff (cfs) Drainage Area (acres) Drainage Area (Mi^2) Subbasin NWB NWB NWB NWB WB WB WB WB WB Palmer Ave Flood Area Combined Flows Watershed Outlet Combined Flows

36 Appendix II: Curve Number-Land Use Matching 36

37 2012 LULC LABEL12 TR 55 Methodology Table 2 2a Categories A B C D Agricultural Wetlands (Modified) Pasture, Grassland, or Range (Fair) Artificial Lakes Water Athletic Fields (Schools) Open Space (Fair) Beaches Natural Desert Landscaping Bridge over Water Paved Areas (No RoW) Commercial/Services Commercial Coniferous Forest (>50% Crown Closure) Woods (Fair) Cropland and Pastureland Cropland (Poor, Averaged) Deciduous Brush/Shrubland Brush (Good) Deciduous Forest (>50% Crown Closure) Woods (Good) Deciduous Forest (10 50% Crown Closure) Woods Grass Combination (Good) Deciduous Scrub/Shrub Wetlands Brush (Good) Deciduous Wooded Wetlands Woods (Good) Herbaceous Wetlands Meadow Industrial Industrial Major Roadway Paved Areas (No Row) Managed Wetland in Built Up Maintained Rec Area Open Space (Good) Mixed Deciduous/Coniferous Brush/Shrubland Brush (Good) Mixed Forest (>50% Coniferous with >50% Crown Closure) Woods (Good) Mixed Forest (>50% Coniferous with 10 50% Crown Closure) Woods Grass Combination (Good) Mixed Forest (>50% Deciduous with >50% Crown Closure) Woods (Good) Mixed Forest (>50% Deciduous with 10 50% Crown Closure) Woods Grass Combination (Good) Mixed Scrub/Shrub Wetlands (Deciduous Dom.) Brush (Good) Mixed Wooded Wetlands (Deciduous Dom.) Woods (Good) Old Field (< 25% Brush Covered) Pasture, Grassland, or Range (Good) Orchards/Vineyards/Nurseries/Horticultural Areas Commercial Other Agriculture Commercial Other Urban or Built Up Land Open Space (Fair) Phragmites Dominate Coastal Wetlands Meadow Phragmites Dominate Old Field Meadow Railroads Streets And Roads: Dirt Recreational Land Open Space (Good) Residential, High Density or Multiple Dwelling Residential 1/8 Acre Or Less Residential, Rural, Single Unit Residential 1 Acre Residential, Single Unit, Low Density Residential 1/2 Acre Residential, Single Unit, Medium Density Residential 1/4 Acre Saline Marsh (High Marsh) Pasture, Grassland, Or Range (Poor) Stormwater Basin Open Space (Good)

38 Tidal Rivers, Inland Bays, and Other Tidal Waters Water Transitional Areas Commercial Transportation/Communication/Utilities Commercial Upland Rights of Way Undeveloped Open Space (Good) Vegetated Dune Communities Pasture, Grassland, or Range (Poor) Wetland Rights of Way Open Space (Good)