RAINFALL RUNOFF MODELING FOR A SMALL URBANIZING SUB-WATERSHED IN THE UPPER DELAWARE RIVER BASIN

Transcription

1 RAINFALL RUNOFF MODELING FOR A SMALL URBANIZING SUB-WATERSHED IN THE UPPER DELAWARE RIVER BASIN Practical Exam APRIL 2, 2014 ALYSSA LYND Shippensburg University

2 TABLE OF CONTENTS List of tables and figures iii Introduction 1 Literature Review 2 Study Area Data and Methods 6 Results 11 Discussion Future Implications Conclusion 16 Literature Cited 17 ii

3 LIST OF TABLES Table 1. Urban land cover in 2005 and projected for 2030 in the Reeders Run watershed 6 Table 2. Percentages of soil hydrologic groups within the Reeders Run watershed 7 Table 3. Area and percentage of urban land cover within each soil hydrologic group for 2005 and Table 4. Area of land cover types within each soil hydrologic group 8 Table 5. Depth of 24-hour precipitation events with recurrence intervals from 2 to 100 years (NOAA 2014). 10 Table 6. TR-55 input data for each scenario 11 Table 7. TR-55 results for 24 hour storm events for each proposed future scenario. 11 Table 8. Peak flow from StreamStats regression estimates compared to peak flow calculated by TR-55 for LIST OF FIGURES Figure 1. The Upper Delaware River Basin and the Reeders Run watershed. 18 Figure 2. Geology of the Reeders Run watershed. 19 Figure 3. Urban land cover for the Reeders Run watershed in 2005 and projected by SLEUTH for Figure 4. Aerial photographs of the Reeders Run watershed in 2005 and Figure 5. Soil hydrologic groups of the Reeders Run watershed 22 Figure 6. Urban land cover within each soil hydrologic group. 23 Figure 7. Rainfall distribution types for the U.S. 24 Figure 8. Resulting peak discharge for each scenario 25 Figure 9. Runoff depth for each scenario. 25 iii

4 INTRODUCTION The Upper Delaware River Basin has been experiencing increases in urban growth in many counties and is expected to continue to experience urban growth into the future. Land use and Land cover changes due to increased development can have a significant impact on the ecology and hydrology of a watershed. Increases in impervious surfaces cause increased amounts of runoff within a watershed, which can have negative effects on stream hydrology and water quality. Increases in impervious surfaces in a watershed can be estimated based on urban growth projections. The SLEUTH Urban Growth Model was used to project urban growth in the Upper Delaware for 2030 by Jantz and Morlock (2011) from 2005 urban land cover. SLEUTH is a cellular automata projection model, used to forecast urban growth and land cover change. It projects land-cover change based on historical trends in development patterns (Jantz and Morlock 2011). The SLEUTH projected urban growth data can be used to make estimations of how urban growth will impact the hydrology of an area. In this study, a small subwatershed within the Upper Delaware River Basin was analyzed. A rainfall runoff model, NRCS Win TR-55, was used for three possible future land cover scenarios within the sub-watershed to predict how urban land cover change will affect runoff. The Natural Resources Conservation Service (NRCS) Win Technical Release 55 (TR-55) rainfall runoff model is used to predict runoff and peak discharge for small urban watersheds. It is a revised version of the NRCS TR-20 model and utilizes the hydrologic calculations of TR-20 for routing and hydrographs (NRCS 2009). Runoff and peak 1

5 discharge are based on changes of land use and land cover in a watershed and are calculated for individual precipitation events. The purpose of this study is to determine how changes in urban growth in a small sub-watershed of the Delaware River Basin will affect runoff and peak discharge. Also, to estimate future land cover scenarios for the sub-watershed based on projected urban growth and determine the possible implications of land cover change for the subwatershed and the Delaware Basin as a whole. LITERATURE REVIEW There are many methods and models that can be utilized to predict rainfall runoff in a watershed. The U.S. Army Corps of Engineers and U.S. Department of Agriculture (USDA) have produced models that can be used to predict peak discharges for high magnitude storm events in order to mitigate flooding. The U.S. Environmental Protection Agency also uses a rainfall runoff model to predict runoff for proposed land use changes and its implications for stormwater management (Kim et al. 2007). The USDA developed a Soil Conservation Service (SCS) curve number (CN) based on land use/cover, soil hydrologic group, treatment, and hydrologic condition. Curve numbers are used to predict direct runoff or infiltration from rainfall. They are calculated using an empirical equation based on trends observed in data from collected sites (Kim et al 2007). This method is widely used and can be applied to Geographic Information Systems (GIS). It is a major component of many rainfall runoff models such as Win TR-55. 2

6 Kim et al. (2007) utilized a rainfall runoff method for predicting long-term effects in a watershed from land use change. This method, called Long-Term Hydrologic Impact Analysis (L-THIA), uses the curve number method to calculate runoff based on land use and hydrologic soil group but also uses long-term climate records (Typically 30 years). The ultimate goal of this method was to estimate average annual runoff for each curve number. For this study, a GIS interface was utilized to calculate curve numbers based on land cover and soil data. Runoff depth was calculated for individual storm events for three different time periods. Land use and soil hydrologic group were determined for three time periods and average annual runoff was determined for each. Comparison of average annual runoff between the three time periods allowed interpretation of how land use changes over time impacted runoff depth. It was found that average annual runoff increased over time with increased development and the conversion of forested land to agriculture and impervious surfaces. Williams et al. (2012) describe the evolution of the continuous curve number method similar to the method used by Kim et al. (2007). Implementation of a soilmoisture index was proposed for the continuous curve number method by Williams and LaSeur (1976) instead of using a five-day antecedent rainfall. Williams et al. (2012) tested the ability of a revised soil-moisture index to predict runoff over a range of soil properties and conditions with two different runoff models. The two models used were the Agricultural Policy/Environmental Extender (APEX) and the Soil and Water Assessment Tool (SWAT). The APEX model is typically used for farm and small watershed management to evaluate land-management strategies 3

7 based on many factors such as erosion, water supply and quality, soil quality, and weather conditions and how they affect hydrology. The SWAT model is a watershed-scale model also used to predict the impact of land management practices on water, sediment, and agricultural chemical yields. Like the APEX model it incorporates weather conditions, crop cover, soil erosion, runoff, etc. for sub-basins within the watershed being evaluated. Both models attempt to predict impacts from changes in land management to the hydrology and environment of watersheds. The TR-55 rainfall runoff model was used by Henning (2009) to predict changes in peak flows after the implementation of permeable pavements on a college campus. Peaks flows and runoff for 24 hour storm events with return periods of 2, 5, 10, 25, 50, and 100 years were predicted for TYPE II precipitation. Composite curve numbers were calculated within TR-55 based on land cover determined by aerial photographs for delineated sub-basins. In a similar study, Holman-Dodds et al. (2003) used TR-55 and the SCS curve number method to determine changes in peak flows and runoff for three different scenarios. The first scenario was predevelopment which was characterized as a vegetated watershed (fully pervious surfaces). The second scenario was high impact developed which represented traditional storm water management of removal from impervious surfaces and piped out. The third scenario, low impact, was characterized as infiltration based storm water management. This scenario assumed runoff from impervious surfaces would be routed to flow across adjacent pervious surfaces. They concluded that the degree of impact from urbanization is dependent on soil type and properties. 4

8 STUDY AREA The area of study is a small sub-watershed within the Upper Delaware River Basin (Figure 1). The Reeders Run watershed is within the Upper Pocono Creek watershed (delineated by HUC-12). This watershed is located in Monroe County, Pennsylvania and was chosen for analysis because it was identified by Jantz and Morlock (2011) as a county that is expected to experience a significant increase in urban land cover by Monroe County is located in the Blue Mountain physiographic section as well as the Glaciated Pocono Plateau section. Because of this, the topography of the area is mountainous with many lakes, streams, and wetlands. The geology of the watershed is predominantly sandstone with some siltstone in the southern end (Figure 2). Reeders Run is a small stream that begins at the base of Camelback Mountain and flows through almost all sandstone towards Pocono Creek. Interstate 80 borders the Reeders Run watershed to the east. The city of Stroudsburg is approximately 12 km to the southeast and Camelback Mountain ski resort is about 6 km to the north. This area attracts tourism during the warm months for outdoor recreation and during the winter months for skiing. The expected growth in urban land cover will most likely be driven by tourism due to the sub-watersheds proximity to Camelback Resort. Most of the Counties within the Upper Delaware in Northeastern Pennsylvania are expected to experience urban growth due to the same circumstances. Other Counties expected to experience urban growth are those in northern New Jersey and southern New York close to New York City due to suburban sprawl. Most of the other counties in New 5

9 York are not expected to experience the same amounts of growth as those closer to the city. This is most likely because they are very rural and do not attract much tourism. DATA/METHODS Urban land cover and urban growth projections for 2030 generated using the SLEUTH urban growth model were provided as raster datasets from Jantz and Morlock (2011). The 12-digit Watershed Boundary Dataset (HUC-12) was also provided. The HUC-12 dataset delineates small watersheds for the Upper Delaware River Basin. The Reeders Run sub-watershed was chosen due to the concentration of projected urban growth adjacent to the stream (Figure 3). This sub-watershed was delineated using a Digital Elevation Model and Esri ArcGIS hydrology tools. The Reeders Run subwatershed is 9.67 km 2 and is a tributary of the Upper Pocono Creek. The Upper Pocono Creek watershed (HUC-12 watershed) is km 2. Existing urban land cover within the Reeders Run watershed was calculated from the 2005 urban land cover raster. Projected urban land cover was then calculated from the SLEUTH 2030 urban cover raster (Table 1). Existing urban land cover was classified as low density residential based on aerial photographs from 2005 (Figure 4, Google 2013). Table 1. Urban land cover (km 2 ) within the Reeders Run sub-watershed in 2005 and projected for (km 2 ) 2030 (km 2 ) Urban Non-Urban

10 Similar to the study by Holman-Dodds et al (2003), three future land cover scenarios were developed to classify all new urban land cover (approximately 0.5 km 2 ). The three scenarios tested were: all new urban land cover as low density residential (1/2 acre lots or larger), all new urban land cover as medium to high density residential (1/4 acre lots), and all new urban land cover as mixed use commercial and residential (high density). The non-urban land cover was determined to be mostly forest with some agriculture from Google Earth imagery for 2005 (Google 2013). This was assumed to remain constant for non-urban land in The Natural Resources Conservation Service (NRCS) soil series dataset was used to determine the hydrologic soil groups within the watershed and the percentage of each (Table 2, Figure 5). Table 2. Percentages of soil hydrologic groups within the Reeders Run sub-watershed. Soil hydrologic group Percentage within the watershed A 3.7 B 1.4 B/D 0.8 C 82.1 C/D 0.8 D 10.7 Water 0.4 To determine a composite curve number for 2005 and each future scenario, the area of land cover types was determined for each soil hydrologic group. The area of existing urban and future urban cover were taken from the SLEUTH rasters and the area within each soil hydrologic group was calculated using Esri ArcGIS (Table 3, Figure 6). To determine the approximate amount of other land cover types in the watershed (i.e. forest and agriculture), NOAA Coastal Change Analysis Program (C-CAP) data was 7

11 viewed for 2006 land cover (NOAA 2014). The approximate areas were determined by overlaying the soil hydrologic group layer over the C-CAP layer (Table 4). This data was also used to verify the assumption that existing urban land cover should be classified as low density. Table 3. Area and percentage of urban land cover within each soil hydrologic group for 2005 and A B C D Area % Area % Area % Area % (km 2 ) (km 2 ) (km 2 ) (km 2 ) Table 4. Calculated area of land cover types within each soil hydrologic group for each proposed scenario and for A B C D Non-urban 9.1 cultivated pasture/hay forest water Urban 0.57 low intensity developed medium intensity developed high intensity developed Scenario 1 A B C D Non-urban 8.6 cultivated pasture/hay forest water Urban 1.07 low intensity developed medium intensity developed high intensity developed

12 Scenario 2 A B C D Non-urban 8.6 cultivated pasture/hay forest water Urban 1.07 low intensity developed medium intensity developed high intensity developed Scenario 3 A B C D Non-urban 8.6 cultivated pasture/hay forest water Urban 1.07 low intensity developed medium intensity developed high intensity developed The calculated areas for each land cover type within each hydrologic soil group were entered into the land use details in TR-55 to calculate a composite curve number for each scenario. The curve number calculated for 2005 was 68, scenario one was 70, scenario two was 72, and scenario three was 73. Precipitation frequency estimates were obtained from the National Weather Service s Stroudsburg, Pennsylvania station to determine the depth of rainfall for 24 hour precipitation events with recurrence intervals of 2, 5, 10, 25, 50, and 100 years (Table 5, NOAA 2014). A Type II rainfall distribution type was assumed for the area based on the NRCS rainfall distribution map (Figure 7, NRCS 2009). A Type II rainfall distribution represents an intense short duration rainfall in which the majority of precipitation during 9

13 a 24-hour period occurs halfway through the time period with less intense rainfall leading up to and following (NRCS 2009). Table 5. Depth of 24-hour precipitation events with recurrence intervals from 2 to 100 years (NOAA 2014). 24 hour duration Recurrence (years) Depth (mm) The time of concentration was estimated using TR-55. The distance from the furthest point in the watershed to the outlet was measured as 6.2 km and the slope over that distance was determined from the Digital Elevation Model using Esri ArcGIS to be 0.21 m/m. It was assumed that most of the distance would be channel flow, about 4.7 km, with a slope of 0.04 m/m. The remaining 1.5 km was classified as sheet flow and shallow concentrated flow. Sheet flow with a manning s number of 0.8 for forest cover was measured as 20 meters. The remaining 800 meters and 680 meters were classified as shallow concentrated flow over unpaved surface and shallow concentrated flow over paved surface respectively. The time of concentration was kept constant for all three scenarios at hours. The TR-55 model was run as a single basin. The routing and sub-basin options were not utilized because the Reeders Run watershed is fairly small. The input data for each scenario can be seen in Table 6. 10

14 Table 6. TR-55 input data for each scenario. Scenario Area (km 2 ) Curve Number Time of Concentration (hr) RESULTS The results of the TR-55 models can be seen in Table 7. The peak discharge (cubic meters per second) and total runoff (millimeters) increase for each storm event across the three scenarios as expected. Each scenario represented an increase in intensity of development for projected urban land cover. The results can be graphically seen in Figures 8 and 9. Table 7. TR-55 results for 24 hour storm events for 2005 and each proposed future scenario. Scenario/storm recurrence Rainfall depth (mm) Peak discharge (cms) Total runoff volume (mm) Potential groundwater recharge (mm)

15 Potential groundwater recharge was calculated by subtracting runoff depth from the precipitation depth for each storm recurrence interval. Potential groundwater recharge decreases with increased runoff volume due to increased impervious surface area from increased intensity of development. DISCUSSION As expected, with increased density or intensity of urban development, runoff depths and peak discharge increase for all storm events. Each scenario represents a successive increase in intensity of development from 2005 conditions and the results show this. Increased amounts of impervious surface area reduces the amount of infiltration that can occur and therefore produces increased amounts of runoff and a greater peak discharge. It is noticed that the increment of increasing runoff and peak discharge for storm events gets larger with increased precipitation. This is because soil capacity to infiltrate water reduces with increased precipitation. In other words, the soil is already full of water therefore more runoff is generated. The majority of the Reeders Run Watershed is classified as hydrologic soil group C. Group C soils have a moderately high runoff potential when wet and are usually composed of 20 to 40 percent clay and less than 50 percent sand (USDA 2007). Because of this, movement of water through the soil is somewhat restricted. The presence of soil 12

16 group D is noticed to be mostly surrounding the stream channels. This is most likely because group D soils are classified as those soils in which a water impermeable layer is within 50 cm and/or a water table is within 60 cm. These soils are usually composed of greater than 40 percent clay, less than 50 percent sand and have a high runoff potential (USDA 2007). Though there is a greater percentage of group D soils within the watershed than group A, the percentage of urban land cover for 2005 on D soils compared to A soils is less. This changes for 2030 projections however, the percentage of urban cover on A soils is proportionally less for 2005 and is about the same as urban cover on D soils. A soils are characterized as having a low runoff potential therefore are capable of infiltrating more water because they are typically composed of less than 10 percent clay and more than 90 percent sand (USDA 2007). This explains the presence of agricultural land cover on A soils and not D. Increasing the impervious surface area on A soils will have a greater impact on the runoff and peak discharge of the basin as a whole compared to development on C and D soils. Covering soils with impervious surfaces increases the runoff potential of that area. If the soil type already has high runoff potential (C and D) then significant increases in runoff are not as likely. If the Reeders Run Watershed were to contain more A soils, a more significant increase in runoff and peak discharge may have been seen. Most of the projected development is expected to occur on C soils. New urban cover on A and B soils is very small but an increase of urban cover on D soils is expected. The peak discharges produced by TR-55 were greater than peak discharges calculated from USGS StreamStats for the Reeders Run Watershed (Table 8). This may 13

17 be because different methods of calculation are used. TR-55 is based on soil properties, soil condition, and land use whereas StreamStats utilizes regionalization. Because Reeders Run is an ungagged stream, a regression equation is utilized based on existing gaging stations in the region related to basin characteristics. Some basin characteristics calculated are basin area, mean elevation, slope, stream length, percent covered by bodies of water, percent forested, percent urban, mean annual precipitation, and a generalized soil drainage quality index. Table 8. Peak flow from StreamStats regression estimates compared to peak flow calculated by TR-55 for Storm recurrence cms 2005 TR-55 peak flow (cms) Future Implications After examining aerial photographs of the Reeders Run Watershed from Google Earth for 2005 through 2012, it is probably a good assumption that new urban land cover in the Reeders Run Watershed in 2030 will probably be low density residential (Figure 4, Google 2013). Therefore, the results from scenario one should be a good estimate of future hydrology. An increase in commercial areas such as hotels or shopping centers may be seen in the future because of the proximity to ski resorts however, most of that type of development seems to be occurring on the opposite side of Camelback Mountain. The 14

18 Reeders Run watershed borders several small lakes and these areas will most likely experience growth in vacation housing units. Most likely small housing developments or larger properties with single dwelling units will be the future trend. If this is the case, the hydrology of the watershed may not be as significantly affected if much of the forest cover remains. Connected impervious surface areas have a greater impact on runoff and peak discharge than impervious surfaces bordered by pervious surfaces (i.e. lawns, woods). This is the case for other counties in northeastern Pennsylvania as well. Tourism is a driving factor of urban development in the Upper Delaware. Besides ski resorts and lakes, the Delaware Water Gap also attracts many visitors for outdoor recreation. Infrastructure to support tourism will probably be the other type of urbanization in the area but not necessarily in the Reeders Run watershed. This may include new and/or wider roadways, shopping centers, restaurants, and other commercial amenities. The Upper Delaware Basin has been experiencing this type of urbanization for quite some time and it is expected to increase in the future. Urbanization due to increased sprawl from New York City has also been occurring on the opposite side of the river. Constant sprawl may have a more significant impact on the Delaware than infrastructure to support tourism however, increased impervious surface area from both types of growth can have significant impacts. Some implications this may have for the watershed as a whole may include increased runoff therefore increased discharge and more frequent flood events, decline in water quality, and increase in water temperature resulting in a lack of species and habitat diversity. 15

19 High-density development will most likely occur in many areas of the watershed and future hydrology and environmental quality will rely on storm water management. Implementations of best management and low impact development practices can be encouraged such as pervious pavement, bio swales, green roofs, rain gardens, etc. to reduce runoff and improve water quality. Local municipality regulations and zoning can also aid in reducing the density of development or sprawl and protect ecologically sensitive areas. CONCLUSION In conclusion, the Upper Delaware River Basin is expected to experience urban growth in the future that will most likely impact the hydrology of the watershed. The extent to which runoff and peak discharge will impact the watershed will depend on the intensity of development and amount of impervious surface area as seen in the Reeders Run watershed. It was estimated that the Reeders Run watershed will most likely experience low-density residential development and possibly some commercial infrastructure to support the tourism in the area. However, the rural quality of the area is what attracts tourism. This cannot be said for the entire Upper Delaware Basin but if the rate and density of development is controlled and mitigated in the future, water quality can be protected and impacts from increased runoff can be reduced. 16

20 LITERATURE CITED Google Google Earth (Version 6.1) [Software]. Available from Henning, J.L. Stormwater flooding on the UNR campus: A current and future modeling assessment. University of Nevada, Reno. Thesis Holman-Dodds, J. K., A. A. Bradley, and K. W. Potter. Evaluation of hydrologic benefits of infiltration based urban storm water management. Journal of the American Water Resources Association Jantz, C.A. and L. Morlock. Modeling urban land use change in the Upper Delaware River Basin. May pdf Kim, Y., B.A. Engel, K.J. Lim, V. Larson, and B. Duncan. Runoff impacts of land-use change in Indian River Lagoon Watershed. Journal of Hydrologic Engineering. May/June NRCS. Small watershed hydrology, Win TR-55 user guide. January NOAA. NOAA atlas 14 point precipitation frequency estimates: PA. February 24, Date accessed: March 18, NOAA. Coastal Change Analysis Program USDA. National engineering handbook: Chapter 7, hydrologic soil groups. May Williams, J.R., N. Kannan, X. Wang, C. Santhi, and J.G. Arnold. Evolution of the SCS runoff curve number method and its application to continuous runoff simulation. Journal of Hydrologic Engineering. November Williams, J.R. and W.V. LaSeur. Water yield modeling using SCS curve numbers. Journal of the Hydraulics Division, 102(9). September

21 FIGURES Figure 1. The Upper Delaware River Basin and the Reeders Run watershed. 18

22 Figure 2. Geology of the Reeders Run watershed. 19

23 Figure 3. Urban land cover for the Reeders Run watershed in 2005 and projected by SLEUTH for

24 Figure 4. Aerial photographs of the Reeders Run watershed in 2005 and 2012 (Google 2013). 21

25 Figure 5. Soil hydrologic groups of the Reeders Run watershed. 22

26 Figure 6. Urban land cover within each soil hydrologic group. 23

27 Figure 7. Rainfall distribution types for the U.S. 24

28 RUNOFF (MM) PEAK DISCHARGE (CMS) Peak Discharge for 2005 and Future Scenarios STORM RECURRENCE INTERVAL Figure 8. Resulting peak discharge for each scenario. 140 Runoff Depth for 2005 and Future Scenarios STORM RECURRENCE INTERVAL Figure 9. Runoff depth for each scenario. 25