October 2013

NASA/TM–2013-218046

A Storm Surge and Inundation Model of the 

Back River Watershed at NASA Langley 

Research Center

Jon Derek Loftis and Harry V. Wang

Virginia Institute of Marine Science

The College of William and Mary

Gloucester Point, Virginia

Russell J. DeYoung

Langley Research Center

Hampton, Virginia
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October 2013

NASA/TM–2013-218046

A Storm Surge and Inundation Model of the 

Back River Watershed at NASA Langley 

Research Center

Jon Derek Loftis and Harry V. Wang

Virginia Institute of Marine Science

The College of William and Mary

Gloucester Point, Virginia

Russell J. DeYoung

Langley Research Center

Hampton, Virginia
Available from:

NASA Center for AeroSpace Information

7115 Standard Drive

Hanover, MD 21076-1320

443-757-5802
iii

Table of Contents Page #

List of Tables............................................................................................................iv

List of Figures..........................................................................................................iv

ABSTRACT............................................................................................................viii

Chapter 1: INTRODUCTION........................................................................................1

Chapter 2: MODEL HINDCAST FOR THE BACK RIVER ESTUARY....................................5

2.1 Results for 2003 Hurricane Isabel...........................................................................5

 2.1.1 Precipitation Comparison with and without Rainfall...............................................5

 2.1.2 Climate Change Future Sea Level Rise Scenarios...............................................9

2.2 Results for 2011 Hurricane Irene..............................................................................9

 2.2.1 Storm Tide Comparison..........................................................................9

 2.2.2 Wrack Line Comparison........................................................................16

Chapter 3: DISCUSSION AND CONCLUSIONS....................................................... 25

3.1 Discussion.........................................................................................................25

3.2 Conclusion........................................................................................................32

3.3 Future Work......................................................................................................32

Appendix A: METHODOLOGY AND MODEL SETUP .................................................34

A.1 Digital Elevation Model derived from Lidar and Incorporation into Sub-Grid Model............34

A.2 Development of Hydrological Transport Simulation with Precipitation............................39

 A.2.1 Ideal Test Case with Open Flow Basin with Precipitation...............................39

 A.2.2 Ideal Test Case for Partially Closed Basin with Precipitation...........................43

 A.2.3 Ideal Test Case for Fully Enclosed Basin with Precipitation............................43

A.3 Storm Tide and Inundation Model Forcing Functions..................................................43

A.3.1 Tidal Forcing........................................................................................43

A.3.2 Atmospheric Wind, Pressure, and Precipitation Forcing.................................44
iv

A.4 Verification of Results – Comparison with NASA-installed tidal gauge...........................44

Appendix B: COMPARISON BETWEEN WRACK LINE MEASUREMENT AND PREDICTED

MAXIMUM WATER LEVEL........................................................................................45

Tables B1 - B6........................................................................................................45

References.............................................................................................................51

LIST OF TABLES Page #

Table 3A. Wrack line GPS point data for 2011 Hurricane Irene at Site E ............................30

Table 3B. Wrack line GPS point data for 2011 Hurricane Irene at Site F.............................31

Table A1. Chart of various storm scenarios conducted in the vicinity of NASA Langley 

Research Center......................................................................................................44

Table B1. Wrack line GPS point data at Site A ..............................................................46

Table B2. Wrack line GPS point data at Site B ..............................................................47

Table B3. Wrack line GPS point data at Site C ..............................................................48

Table B4. Wrack line GPS point data at Site D ..............................................................49

Table B5. Wrack line GPS point data at Site E .............................................................50

Table B6. Wrack line GPS point data at Site F...............................................................50

LIST OF FIGURES Page #

Figure 1.1. VIMS flood modeling methodology for NASA Langley Research Center highlighting 

the utility of a large scale atmospheric and ocean prediction model with a sub-grid inundation 

model with Lidar-derived topography providing the high-resolution Langley flood map..............1

Figure 1.2. Ditches present in Lidar contour data for Langley Air Force Base and NASA Langley 

Research Center on the Back River peninsula..................................................................3

Figure 1.3A. Lidar contours for a resolved ditch following adjacent to Doolittle Rd. near Building 

1222 draining into the west end of Tabb Creek (left); 50m Base Grid (grey grid lines) with 5m 

nested Sub-grid (black grid lines) displaying elevation with superposed Lidar contours (right)....4

Figure 1.3B. Lidar contour data for a resolved ditch adjacent to Gregg Rd. leading to Eaglewood 

Golf Course draining into the south end of Tabb Creek (left); 50m Base Grid (grey grid lines) 

with 5m nested Sub-grid (black grid lines) superposed with Lidar elevation contours (right).......4
v

Figure 2.1. Precipitation input data for 2003 Hurricane Isabel from Williamsburg/Newport News 

Airport shown with a peak observed precipitation rate of 28 mm/hr on September 18, 2011, at 

20:00 GMT...............................................................................................................6

Figure 2.2. 2003 Hurricane Isabel temporal comparison in GMT of observed results (Sewells 

Point) and sub-grid results (R2 = 0.9903) with an observed peak of 2.016m above mean sea 

level........................................................................................................................6

Figure 2.3A. Inundation thickness (height of water above the topographic land surface) map in 

meters for 2003 Hurricane Isabel without precipitation over the Back River peninsula with 

Langley Air Force Base in the south end and NASA Langley Research Center in the north end 

of the map...............................................................................................................7

Figure 2.3B. Inundation thickness map in meters for 2003 Hurricane Isabel including 

precipitation input over the Back River peninsula with Langley Air Force Base in the south end 

and NASA Langley Research Center in the north end of the map........................................8

Figure 2.3C. Precipitation difference map representing thickness in meters comparing a 2003 

Hurricane Isabel precipitation scenario to one without precipitation over the Back River 

peninsula.................................................................................................................8

Figure 2.4. Time series of elevation forcing at the open boundary for four 2003 Hurricane Isabel 

sea level rise scenarios including the original storm at +00in, +15in, +30in, and +60in............10

Figure 2.5A. 2003 Hurricane Isabel sea level rise climate change scenario for Isabel +00in in 

the central region of NASA Langley.............................................................................11

Figure 2.5B. 2003 Hurricane Isabel sea level rise climate change scenario for Isabel +15in in 

the central region of NASA Langley. ............................................................................12

Figure 2.5C. 2003 Hurricane Isabel sea level rise climate change scenario for Isabel +30in in 

the central region of NASA Langley.............................................................................13

Figure 2.5D. 2003 Hurricane Isabel sea level rise climate change scenario for Isabel +60in in 

the central region of NASA Langley ............................................................................14

Figure 2.6. Precipitation input data from Williamsburg/Newport News Airport shown for the 2009 

November Nor’easter with a measured peak precipitation rate of 14.5 mm/hr on November 12, 

2009, at 11:00 GMT.................................................................................................15

Figure 2.7. 2011 Hurricane Irene temporal comparison in GMT of observed results (NASA Tide 

01) and sub-grid results with an observed peak of 1.656m above mean sea level. .................15

Figure 2.8. GPS wrack line/debris locations for observation data collected by NASA Langley 

Research Center immediately after 2011 Hurricane Irene.................................................18
vi

Figure 2.9A. Spatial comparison of maximum extent of inundation for 2011 Hurricane Irene at 

NASA Langley Research Center with GPS-recorded wrack line area A with depths 

corresponding with wrack line thicknesses in Table B1....................................................19

Figure 2.9B. Spatial comparison of maximum extent of inundation for 2011 Hurricane Irene at 

NASA Langley Research Center with GPS-recorded wrack line area A with depths 

corresponding with wrack line thicknesses in Table B2....................................................20

Figure 2.9C. Spatial comparison of maximum extent of inundation for 2011 Hurricane Irene at 

NASA Langley Research Center with GPS-recorded wrack line area A with depths 

corresponding with wrack line thicknesses in Table B3....................................................21

Figure 2.9D. Spatial comparison of maximum extent of inundation for 2011 Hurricane Irene at 

NASA Langley Research Center with GPS-recorded wrack line area A with depths 

corresponding with wrack line thicknesses in Table B4....................................................22

Figure 2.9E. Spatial comparison of maximum extent of inundation for 2011 Hurricane Irene at 

NASA Langley Research Center with GPS-recorded wrack line area A with depths 

corresponding with wrack line thicknesses in Table B5....................................................23

Figure 2.9F. Spatial comparison of maximum extent of inundation for 2011 Hurricane Irene at 

NASA Langley Research Center with GPS-recorded wrack line area A with depths 

corresponding with wrack line thicknesses in Table B6....................................................24

Figure 3.1. Land use map for the Back River watershed with developed land shown in red hues 

and vegetated land displayed with green hues (Source: National Land Cover Database, 

2006).....................................................................................................................26

Figure 3.2. Example of a spatially-varying infiltration rate in mm/hr for NASA Langley Research 

Center and Langley Air Force Base using 30m-resolution land use data with 50m base grid cells 

and 5m sub-grid cells illustrated..................................................................................27

Figure 3.3A. Spatial comparison of maximum extent of inundation for 2011 Hurricane Irene at 

NASA Langley Research Center with GPS-recorded wrack line at Site E with depths 

corresponding with wrack line thicknesses in Table 3A....................................................28

Figure 3.3B. Spatial comparison of maximum extent of inundation for 2011 Hurricane Irene at 

NASA Langley Research Center with GPS-recorded wrack line at Site F with depths 

corresponding with wrack line thicknesses in Table 3B....................................................29

Figure A.1A. Lidar for Langley Research Center displaying 30cm vertical resolution contours..35

Figure A.1B. Lidar contours focused on central Langley Research Center displaying drainage 

ditches backing up to a meandering tidal creek along Back River.......................................35

Figure A.1C. Lidar contours focused on the north end of Langley Research Center displaying 

drainage ditches near the location of the NASA Tide 01 tide gauge along Back River............ 36
vii

Figure A.1D. Peninsula contours shown for Langley Air Force Base and NASA Langley 

Research Center................................................................................................... .37

Figure A.2. 50m Base Grid shown with 5m Sub-Grid shown for the Northeast tip of Langley Air 

Force Base in the UnTRIM2 model interface.................................................................38

Figure A.3. Full Back River model domain in Google Earth with 54,057 nodes and 53,474 

elements comprising the 50m resolution base grid, yielding 4,759,788 sub-grid elements at 5m 

resolution.............................................................................................................. 38

Figure A.4. Ideal test case for precipitation at 25 mm/hr in an open flow basin with a prescribed 

0.5 m/s flow from the west.........................................................................................40

Figure A.5. Ideal test case for precipitation at 25 mm/hr in a partially enclosed basin with a wall 

along the west edge of the sloping trough basin.............................................................41

Figure A.6. Ideal test case for precipitation at 25 mm/hr in a fully enclosed basin which allows 

water volume to properly accumulate over time..............................................................42
viii

ABSTRACT

Sub-grid modeling is a novel method by which inundation on the sub-grid level can be obtained 

through the combination of water levels and velocities efficiently calculated at the coarse 

computational grid, the discretized bathymetric depths, and local friction parameters without 

resorting to solve the full set of equations. The Sub-grid approach essentially allows velocity to 

be determined rationally and efficiently at the sub-grid level. This salient feature enables coastal 

flooding to be addressed in a single cross-scale model from the ocean to the upstream river 

channel without overly refining the grid resolution. The sub-grid model is suitable for hydrologic 

transport model coupled with high-resolution lidar topography for the NASA Langley Research 

Center for use in modeling storm surge inundation including precipitation-induced flooding.

To this end, high-resolution digital elevation models (DEMs), incorporating GIS from Lidarderived topography, were used for incorporation into a sub-grid model, for research into case 

studies related to recent substantial inundation events at the NASA Langley Research Center in 

Hampton, VA. Two inundation events were modeled. The 2003 Hurricane Isabel was utilized for 

a comparison of inundation extent including and without precipitation included in the sub-grid 

model, in addition to sea level rise projections associated with global climate change for 

Isabel+00in (Hurricane Isabel’s maximum extent of inundation), Isabel+15in, Isabel+30in, 

Isabel+60in. Also the 2011 Hurricane Irene confirmed that sub-grid model results accurately 

predicted the maximum extent of inundation at Langley Research Center via spatial comparison 

of NASA-recorded GPS wrack line data at 6 different sites. The model provided accurate water 

level prediction with maximum extent of the inundation within a few tens of meters to the wrack 

line measurement. Further improvement was made when the infiltration by the pervious and 

impervious surface were taken into consideration. 
1

1. Introduction 

Located in Hampton, Virginia, Langley Research Center is adjacent to the banks of the 

Chesapeake Bay, making it susceptible to hurricanes and extreme coastal weather brought up 

from the Gulf Stream. Langley covers over 800 acres (20 acres located on the Langley Air 

Force Base) and is surrounded by the Back River, a shallow estuarine inlet of the Chesapeake 

Bay, the largest estuary in the United States.

Langley Research Center is located in one of the most vulnerable areas in the United States to 

the effects of climate change and sea level rise. The East Coast has 50% of its length in the 

"very high" or "high" vulnerability range. The highest vulnerability areas are typically coastlines 

where the regional coastal slope is low and the major landform type is a barrier island. A 

significant exception to this is found in the lower Chesapeake Bay. Here, the low coastal slope, 

vulnerable landform type (salt marsh), and high rate of relative sea-level rise combine for a high 

coastal vulnerability. This threat requires the use of high-resolution inundation modeling to 

assess the flooding damage to Langley infrastructure on a building-by-building basis for a suite 

of potential storms from nor’easters to hurricanes. This is especially relevant to the construction 

of “New Town”; the new building plan for this century.

The Chesapeake Inundation Prediction System (CIPS) has been developed and demonstrated 

to provide a capability to forecast large-scale storm surge and land area inundated in the 

Chesapeake Bay (CIPS final report, 2011, Cho et al. 2011; Roland et al. 2012). Recently, subgrid modeling capability was added to the model framework in order to incorporate fine-scale 

features (within 1-5 meters) into the coarse base grid without significantly increasing overhead 

to computing resources (Casulli and Stelling, 2011). Sub-grid modeling is a cutting-edge 

approach which is designed to incorporate Lidar topography into the sub-grid of an otherwise 

regular model framework to simulate storm surge and inundation (Figure 1.1).

Figure 1.1. VIMS flood modeling methodology for NASA Langley Research Center. The focus of 

this paper is the Flood Map Modeling using Lidar-derived topography to produce the highresolution Langley flood map. In future modeling an Atmospheric and Ocean Prediction Model 

would be added to give near real time flood maps.
2

The topographic representation (stored in the model sub-grid) will allow the effects of friction 

and total conveyance to be determined more accurately, resulting in better characterization of 

total inundation.

This new methodology is significant because it provides a rational way to combine highresolution Lidar and bathymetry data into the model, and concurrently generate storm surge and 

hydrological transport model results. At Langley a network of numerous ditches, on the order of 

2-5 meters wide, are utilized for draining excess water during weather events as shown in 

Figure 1.2. These ditches are part of the hydrological features that need to be resolved in the 

model in order to predict the extent, depth, and the timing of the flood inundation (Figure 1.1). 

Utilizing the sub-grid approach, it is possible to resolve the ditches that are on the order of a few 

meters wide as shown in Figure 1.3A-B, and at the same time be able to channel the rainfall into

runoff to simulate the water budget and inundation for the entire Back River system influenced 

via external forcing. 

This paper will describe an advanced sub-grid inundation model of NASA Langley which will 

incorporate the flowing topics:

A. Retrieve the high-resolution Lidar data and incorporate it into the sub-grid model 

B. Set up the sub-grid model and incorporate precipitation during major storm events

C. Perform calibrations and conduct hindcast for recent major inundation events

D. Incorporate sea level rise scenarios 

This work demonstrates that sub-grid modeling technology (now as part of Chesapeake Bay 

Inundation Prediction System, CIPS) can incorporate high-resolution Lidar measurements

provided by NASA Langley Research Center into the sub-grid model framework to resolve 

detailed topographic features for use as a hydrological transport model for run-off simulations

within NASA Langley and Langley Air Force Base. The rainfall over land accumulates in the 

ditches/channels resolved via the model sub-grid was tested to simulate the run-off induced by 

heavy precipitation. Possessing both the capabilities for storm surge and run-off simulations, the 

CIPS model was then applied to simulate real storm events starting with Hurricane Isabel in 

2003. It will be shown that the model can generate highly accurate on-land inundation maps as 

demonstrated by excellent comparison of the Langley tidal gauge time series data 

(CAPABLE.larc.nasa.gov) and spatial patterns of real storm wrack line measurements with the 

model results simulated during Hurricanes Isabel (2003), and Irene (2011). With confidence built 

upon the model’s performance, sea level rise scenarios from the ICCP (International Climate 

Change Partnership) were also included in the model scenario runs to simulate future 

inundation cases. 

The model methodology and setup are discussed in Appendix A. Here the development of a 

hydrological transport simulation with included precipitation is developed in detail.
3

Figure 1.2. Lidar contour data for Langley Air Force Base (right) and NASA Langley Research 

Center (Left) on the Back River peninsula. North is upward. Ditches are labeled which inpact 

innundation modeling. Elevation above NAVD88 is shown in color and indicates the near sea 

level height of the Center.
4

 

Figure 1.3A. Lidar resolved ditch contours (0-6 ft) adjacent to Doolittle Rd. near Building 1222 

draining into west end of Tabb Creek (left); 50m Base Grid (grey lines) with 5m nested Sub-grid 

(black lines) displaying elevation with superposed Lidar contours (right). (Scale as Fig. 1.2)

 

Figure 1.3B. Lidar resolved ditch contours (0-6 ft) adjacent to Gregg Rd. leading to Eaglewood 

Golf Course draining into south end of Tabb Creek (left); 50m base grid (grey) with 5m nested 

Sub-grid (black lines) superposed with Lidar elevation contours (right).
5

2. Model Hindcast for the Back River Estuary

2.1 Results for 2003 Hurricane Isabel

A peak precipitation rate of 28 mm/hr was observed during Hurricane Isabel on 

September 18, 2003, at 20:00 GMT as shown in Figure 2.1. A time series comparison of 

observed results at Sewell’s Point and sub-grid results yielded an observed peak of 2m above 

mean sea level as shown in Figure 2.2. Correlation of observation data against the model 

prediction yielded an R2= 0.9903 for 2003 Hurricane Isabel and gave confidence that the model 

was working properly.

2.1.1 Inundation Model Comparison with and without Rainfall 

Rainfall is an important parameter to consider in inundation modeling. A considerable 

gap currently exists between atmospheric modeling and hydrodynamic modeling communities. 

To appropriately address tropical and extra-tropical storm systems for both flooding extent and 

duration, precipitation is an invaluable parameter for modeling in the coastal plane. In an area 

like NASA Langley Research Center and Langley Air Force Base, where the terrain is converted 

lowlands and salt marshes, virtually no buffer exists between an impending storm surge 

intruding into the Back River estuary. 

Precipitation is useful to consider in flood modeling for considering relatively flat terrain 

like the terrain at NASA Langley where the water table is regularly high (close to the exposed 

soil surface) throughout the year. Considering inundation thickness (height of water above the 

topographic land surface) is a useful method for evaluating the importance of coding 

precipitation into a hydrodynamic model as a model input. Figure 2.3A displays the maximum 

inundation thickness around NASA Langley Research Center and Langley Air Force Base after 

the 2003 Hurricane Isabel in a simulation neglecting precipitation. In contrast, Figure 2.3B 

illustrates the maximum inundation thickness in meters for 2003 Hurricane Isabel including 

precipitation input over the Back River peninsula. 

Upon inclusion of precipitation data as an atmospheric model input, the model identified 

localized flooding non-contiguous to the storm surge flooding associated with 2003 Hurricane 

Isabel. Specific areas of localized precipitation-based flooding persist in the southwest region of 

NASA Langley and the central to southwest regions of Langley Air Force Base. There are 

interior areas along the western edge of the Langley Research Center (which are not directly 

adjacent to the storm surge-induced flooding along the edge of the Back River estuary) that are 

now shown to be inundated when precipitation is included. While some of these areas noncontiguous with the Back River estuary are local drainage infrastructure containing a water 

thickness of 25cm or less, many areas in the southwestern portion of the map near Langley Air 

Force Base (approaching the NASA Hangar) are inundated by precipitation-derived flooding 

between 1.00-1.75m. This is effectively exemplified in the difference map shown in Figure 2.3C. 

Note that Figure 2.3C is the difference of Figure 2.3B minus Figure 2.3A, generated by

ArcGIS10.1. 
6

Figure 2.1. Precipitation input data for 2003 Hurricane Isabel from Williamsburg/Newport News 

Airport shown with a peak observed precipitation rate of 28 mm/hr on September 18, 2011, at 

20:00 GMT.

Figure 2.2. 2003 Hurricane Isabel temporal comparison in GMT of observed results (Sewells 

Point) and sub-grid results (R2= 0.9903) with an observed peak of 2.016m above mean sea 

level.

0

5

10

15

20

25

30

11 12 13 14 15 16 17 18 19 20

Precipitation (mm/hr)

Day in September 2003

Williamsburg Airport

-0.5

0

0.5

1

1.5

2

2.5

11 12 13 14 15 16 17 18 19 20

Water Level above MSL (m)

Day in September 2003

NOAA Observation

Model Result
7

Figure 2.3A. Inundation thickness (height of water above the topographic land surface) map in 

meters for 2003 Hurricane Isabel without precipitation over the Back River peninsula with 

Langley Air Force Base in the south (lower) end and NASA Langley Research Center in the 

north (upper) end of the map.
8

Figure 2.3B. Inundation thickness map in meters for 2003 Hurricane Isabel including 

precipitation input over the Back River peninsula with Langley Air Force Base in the south end 

and NASA Langley Research Center in the north (upper) end of the map.

Figure 2.3C. Inundation difference map representing the influence of rainfall (Fig 2.3B – Fig. 

2.3A) in meters by comparing Hurricane Isabel precipitation scenario to one without 

precipitation.
9

2.1.2 Climate Change Future Sea Level Rise Scenarios 

Considering future sea level rise and climate change is important for coastal areas. To 

address these raising concerns, a series of sea level rise scenarios using the 2003 Hurricane 

Isabel model inundation as a base case (+00in) and then adding +15in, +30in, and +60in of 

future sea level rise were generated to observe the inundation result of this sea level rise at 

NASA Langley. In Figure 2.4, a time series of sea level rise scenarios describes the inundation 

peaks for the original storm (+00in) at 1.902m, Isabel +15in at 2.285m , Isabel +30in at 2.696m, 

and Isabel +60in at a maximum inundation of 3.460m . Spatial comparison maps of the four 

Hurricane Isabel sea level rise climate change scenarios are shown in Figure 2.5 A-D. The 

maximum inundation thickness is shown in the maps focused on the central region of NASA 

Langley Research Center as it backs up to a tidal tributary creek that feeds into the Back River 

estuary. 

In the climate change scenarios, only storm surge flooding associated with sea level rise was 

utilized with no precipitation input, as it is impossible to accurately anticipate what the future 

precipitation rates would be with a future storm system of the magnitude of 2003 Hurricane 

Isabel (Figure 2.5A) at Isabel +15in (Figure 2.5B), Isabel +30in (Figure 2.5C), and Isabel +60in 

(Figure 2.5D). Also, the desire in this simulated series is to assess the inundation threat posed 

via future sea level rise associated with climate change, and neglecting precipitation allows the 

maximum inundation maps to more clearly reflect the storm surge-induced flooding associated 

with increasing sea level. 

2.2 Results for 2011 Hurricane Irene

2.2.1 Storm Tide Comparison 

A peak precipitation rate of 46 mm/hr was observed at the Williamsburg/Newport News 

Airport during 2011 Hurricane Irene on August 28, 2011, at 05:00 GMT as shown in Figure 2.6. 

A temporal comparison of observed results at Langley Tide Gauge 1 and sub-grid results using 

the Back River Dandy Haven VIMS TideWatch observation data for 2011 Hurricane Irene yields 

a correlation of R2= 0.9714 (R2= 0.9486 around the three day peak) with an observed 

maximum inundation peak of 1.656m above mean sea level as shown in Figure 2.7. 
10

Figure 2.4. Time series of elevation forcing at the open boundary for four 2003 Hurricane Isabel sea level rise scenarios 

including the original storm at +00in, +15in, +30in, and +60in.

-1

-0.5

0

0.5

1

1.5

2

2.5

3

3.5

4

15 16 17 18 19 20 21 22 23 24 25

Water Level above MSL (m)

Day in September 2003

+00in

+15in

+30in

+60in
11

Figure 2.5A. 2003 Hurricane Isabel inundation with +00in sea level rise added scenario in the central region of NASA Langley. The 

emphasis is on the inundation extent as a function of future sea level rise.
12

Figure 2.5B. 2003 Hurricane Isabel sea level rise climate change scenario for Isabel +15in in the central region of NASA Langley. 
13

Figure 2.5C. 2003 Hurricane Isabel sea level rise climate change scenario for Isabel +30in in the central region of NASA Langley. 
14

Figure 2.5D. 2003 Hurricane Isabel sea level rise climate change scenario for Isabel +60in in the central region of NASA Langley. 
15

Figure 2.6. Precipitation input data from Williamsburg/Newport News Airport shown for 2011 

Hurricane Irene with a peak observed precipitation rate of 46 mm/hr August 28, 2011, at 05:00 

GMT.

Figure 2.7. 2011 Hurricane Irene temporal comparison in GMT of observed results (NASA Tide 

01) and sub-grid results (R2= 0.9714 and R2= 0.9486 for three days around peak) with an 

observed peak of 1.656m above mean sea level.

-1

-0.5

0

0.5

1

1.5

2

20 21 22 23 24 25 26 27 28 29 30

Water Level aboveMSL (m)

Day in August 2011

NASA Tide 01

Model Results
16

2.2.2 Wrack Line Comparison 

A wrack line vertical inundation comparison was performed utilizing the NASAcollected debris data collected from the aftermath of 2011 Hurricane Irene at six flooded sites as 

shown in Figure 2.8. These deposited debris lines were utilized as a proxy for comparison of 

sub-grid model results for maximum extent of inundation as an additional metric for evaluating 

the accuracy of the sub-grid model’s predicted spatial inundation on a 5m sub-grid. Water level 

thickness will be calculated via maximum water level elevation (maximum water surface level) -

the sub-grid topography elevations at each recorded GPS wrack line point using GIS to retrieve 

the model-computed thickness at each wrack line point. Ideally, this value should be close to 0m 

for a perfect match, although with the precipitation input, we do not exactly know how much 

water was infiltrated through the soil. Additionally, the buildings shown in Figures 2.9A-F have 

been filtered out of the Lidar topography data and are not present in the model sub-grid results. 

Provided accurate building heights, buildings may be assessed in future model simulations for 

integration with the Lidar-derived sub-grid topography. 

Site A is located near the tidal tributary to the Back River estuary in the central 

region of Langley near buildings 1256 and 1247 as shown in Figure 2.9A. The wrack line 

contains 35 points with a localized maximum observed water level of 1.802m with an average 

difference/water thickness of 0.128m (without infiltration) and 0.052m with 10% infiltration is 

considered as shown in Table B1 (Appendix B). 

The wrack line at Site B is also located near the tidal tributary to the Back River 

estuary in the central region of Langley west of Site A near buildings 1222 and 1223 as shown 

in Figure 2.9B. This wrack line consists of 25 different recorded points with a local maximum 

water level of 1.801m with an average difference/water thickness of 0.110m (without infiltration) 

and 0.070m with 10% infiltration is considered as shown in Table B2 (Appendix B). 

Site C’s wrack line is populated with 32 GPS points located adjacent to Back 

River in the north end of NASA Langley Research Center near building 1275 as shown in Figure 

2.9C. The wrack line is positioned at a location where the maximum water level is 1.766m with 

an average difference/water thickness of 0.167m (without infiltration) and 0.010m with 10% 

infiltration is considered as shown in Table B3 (Appendix B). 

Site D is the shortest wrack line consisting of 4 GPS data points located near a 

meandering tidal creek connecting the Big Bethel Reservoir to the Back River estuary in the 

north end of Langley near buildings 1158 and 1159 as shown in Figure 2.9D. The maximum 

water level is 1.780m at the wrack line where an average difference/water thickness of 0.227m 

(without infiltration) and 0.049m with 10% infiltration is considered was calculated as shown in 

Table B4 (Appendix B).

The wrack line measured at Site E is also located adjacent to the meandering 

tidal creek connecting the Big Bethel Reservoir to the Back River estuary close to the location of 

the Langley Tide Gauge 1 in the north end of Langley southwest of Site D near building 1196 

adjacent to a drainage creek running nearly parallel to building 1257 as shown in Figure 2.9E. 

This wrack line consists of 14 different recorded points with a local maximum water level of 
17

1.780m with an average difference/water thickness of 0.231m (without any infiltration) and 

0.053m with 10% infiltration is considered as shown in Table B5 (Appendix B).

Site F is located west of Site E also located parallel to the west end of building

1257 adjacent to the meandering tidal creek on the north end of Langley near building 1258 as 

shown in Figure 2.9F. The wrack line contains 7 points with a localized maximum observed 

water level of 1.802m with an average difference/water thickness of 0.168 (without any 

infiltration) and 0.011m with 10% infiltration is considered as shown in Table B6 (Appendix B). 

Site F has the best horizontal maximum inundation comparison following the wrack line within 

2.5m, followed closely by Site E (6.5m), and then site A (8.5m). 

All of the sites fit within two sub-grid cells’ length in distance (on average) for 

inundation thicknesses greater than 0.05m from the GPS-recorded wrack line data. For the sites 

with larger horizontal distances from their GPS-recorded wrack lines, these sites are located in 

very flat areas where much of the horizontal discrepancy is attributed to precipitation-induced 

inundation on the order of <0.05m. In terms of vertical maximum inundation differences with 

10% infiltration, Site C ranked the best with a difference of 0.010m, followed closely by the 

wrack line at Site F with a measured difference of 0.011m.

In summary, the wrack line measurements at NASA Langley Research Center 

provide a unique observation dataset that can be utilized to assess the maximum extent of the 

inundation during a storm event. The maximum water level computed from the model compared 

favorably with the local topography (in m above NAVD88) within 10% of error if infiltration is 

assumed to be 0 and the error is within 2-5% error if 10% infiltration is considered. This 

assessment is consistent with the rational C factor approach assuming that the infiltration is 

constant:

Q C I A   

 

Where Q is the peak runoff value, I is the average rainfall intensity, A is the drainage area and C 

is the runoff coefficient ranging from 0.1 to 0.9 depend on the land use, soil type and soil 

condition.
18

Figure 2.8. GPS wrack line/debris locations for observation data collected by NASA Langley 

Research Center immediately after 2011 Hurricane Irene.

Site A

Site B

Site C

Site D

Site E

Site F
19

Figure 2.9A. Spatial comparison of maximum extent of inundation for 2011 Hurricane Irene at NASA Langley Research Center with GPSrecorded wrack line area A with depths corresponding with wrack line thicknesses in Table B1 (blue dots).

8.5m Average Horizontal 

Difference (Over-Predict)
20

Figure 2.9B. Spatial comparison of maximum extent of inundation for 2011 Hurricane Irene at NASA Langley Research Center with GPSrecorded wrack line area A with depths corresponding with wrack line thicknesses in Table B2 (blue dots).

29m Average Horizontal 

Difference (Over-Predict)
21

Figure 2.9C. Spatial comparison of maximum extent of inundation for 2011 Hurricane Irene at NASA Langley Research Center with GPSrecorded wrack line area A with depths corresponding with wrack line thicknesses in Table B3 (blue dots).

36m Average Horizontal 

Difference (Over-Predict)
22

Figure 2.9D. Spatial comparison of maximum extent of inundation for 2011 Hurricane Irene at NASA Langley Research Center with GPSrecorded wrack line area A with depths corresponding with wrack line thicknesses in Table B4 (blue dots).

23.5m Average Horizontal 

Difference (Over-Predict)
23

Figure 2.9E. Spatial comparison of maximum extent of inundation for 2011 Hurricane Irene at NASA Langley Research Center with GPSrecorded wrack line area A with depths corresponding with wrack line thicknesses in Table B5 (blue dots).

6.5m Average Horizontal 

Difference (Over-Predict)
24

Figure 2.9F. Spatial comparison of maximum extent of inundation for 2011 Hurricane Irene at NASA Langley Research Center with GPSrecorded wrack line area A with depths corresponding with wrack line thicknesses in Table B6 (blue dots).

2.5m Average Horizontal 

Difference (Over-Predict)
25

3. Discussion and Conclusion

3.1 Discussion

One of the main assumptions of this study is that the ground is completely saturated and 

therefore there is not water infiltration. In practice, rainfall reaching the land surface can infiltrate 

into the pervious soil. Soil has a finite capacity to absorb water. The infiltration capacity varies 

not only from soil to soil, but is also different for dry versus moist conditions based upon the 

hydraulic conductivity gradient in the same soil. Upon consideration of soil infiltration rates, a 

runoff coefficient can range from 0.1 to 0.9. Thus, the inundation prediction without infiltration 

represents the most conservative (worst case scenario) estimation of the flooding which can 

occur given the observed amount of precipitation. 

If fluid is allowed to permeate through the model grid, the degree of over-prediction associated 

with the precipitation input from the model may be appropriately balanced. Preliminary tests 

employing a spatially-varying infiltration rate have shown marked improvement in wrack line 

comparison results. Provided a spatially-varying infiltration rate assigned according to the 

varying degrees of impervious nature of different land cover classifications from the National 

Land Cover Database (via percentage of land cover with vegetation available for absorbing 

flood waters and precipitation after a storm has passed), higher percentages of land cover with 

vegetation equates to a greater absorption into the soil, and a higher infiltration rate (Figure 3.1). 

In likewise fashion, less vegetation and greater percentages of urban infrastructure including 

paved surfaces (streets, some drainage structure, and runways) equates to more impervious 

surfaces for a lower infiltration rate. Land cover data were utilized in GIS as a proxy to specify 

flags in the model’s Fortran code corresponding with the areas shown in the model grid with an 

example shown in Figure 3.2, translating to improved horizontal (Figure 3.3A–B) and vertical 

(Table 3A–B) wrack line results comparisons.

Incorporation of land use classifications as a proxy for spatially-varying infiltration rates in the 

sub-grid model results in the wrack line at Site E (near the location of the NASA Tide 01 tide 

gauge in an estuarine emergent wetland classification area in Figure 3.3A) yields a decrease of 

0.084m for a water thickness of 0.147m (± 0.035m standard deviation) as shown in Table 3A.

Site F is also adjacent to an estuarine emergent wetland classified area, and incorporation of 

spatially-varying infiltration results in a decrease of 0.064m for a water thickness of 0.103m ( ± 

0.049m standard deviation) as shown in Table 3B. Spatially-varying infiltration rates may be 

further addressed in a phase II portion of this project and may better constrain the effect of the 

precipitation input utilized in the sub-grid model, thus further improving upon the wrack line 

comparison results.
26

Figure 3.1. Land use map for the Back River watershed with developed land shown in red hues 

and vegetated land displayed with green hues with north at top (Source: National Land Cover 

Database, 2006).
27

Figure 3.2. Example of a spatially-varying infiltration rate in mm/hr for NASA Langley Research 

Center and Langley Air Force Base using 30m-resolution land use data with 50m base grid cells 

and 5m sub-grid cells illustrated.
28

Figure 3.3A. Spatial comparison of maximum extent of inundation for 2011 Hurricane Irene at NASA Langley Research 

Center with GPS-recorded wrack line at Site E with depths corresponding with wrack line thicknesses in Table 3A (blue 

dots).

4m Average Horizontal 

Difference (Over-Predict)
29

Figure 3.3B. Spatial comparison of maximum extent of inundation for 2011 Hurricane Irene at NASA Langley Research 

Center with GPS-recorded wrack line at Site F with depths corresponding with wrack line thicknesses in Table 3B (blue 

dots).

1m Average Horizontal 

Difference (Over-Predict)
30

#

Wrack Line 

Point Northing Easting

Elevation 

(m)

Max Water Level 

without Infiltration 

(m)

Difference 

(m)

Max Water 

Level with SV 

Infiltration (m)

Difference with 

SV Infiltration 

(m)

1 VX558 1087664.55

7

3687772.84

6

1.531 1.780 0.249 1.696 0.165

2 VX559 1087663.20

4

3687778.58

6

1.594 1.780 0.186 1.696 0.102

3 VX560 1087663.25

5

3687781.84

0

1.618 1.780 0.162 1.696 0.078

4 a5062 1087666.59

2

3687787.50

4

1.554 1.780 0.226 1.696 0.142

5 a5061 1087668.05

7

3687788.71

2

1.528 1.780 0.252 1.696 0.168

6 a5060 1087670.65

9

3687792.35

6

1.523 1.780 0.257 1.696 0.173

7 a5059 1087671.42

3

3687797.59

1

1.521 1.780 0.259 1.696 0.175

8 a5058 1087671.84

2

3687803.58

1

1.576 1.780 0.204 1.696 0.120

9 a5057 1087672.92

6

3687806.36

4

1.579 1.780 0.201 1.696 0.117

10 a5056 1087674.57

6

3687810.67

9

1.561 1.780 0.219 1.696 0.135

11 VX557 1087676.41

1

3687815.00

2

1.563 1.780 0.217 1.696 0.133

12 VX556 1087676.87

5

3687817.39

6

1.503 1.780 0.277 1.696 0.193

13 VX555 1087676.75

8

3687820.00

6

1.501 1.780 0.279 1.696 0.195

14 VX554 1087677.14

4

3687822.44

2

1.530 1.780 0.250 1.696 0.166

Average 

Difference 0.231

Average 

Difference 0.147

Standard 

Deviation 0.035

Standard 

Deviation 0.035

Table 3A. Wrack line GPS point data for 2011 Hurricane Irene at Site E with NAD83 HARN Virginia State Plane South coordinates 

for northing and easting, sub-grid elevation, the base-grid maximum water level and the difference as inundation thickness, with and 

without 10% infiltration, including average and standard deviation statistics for verification of the sub-grid model with spatially-varying 

(SV) infiltration. 
31

#

Wrack Line 

Point Northing Easting

Elevation 

(m)

Max Water Level 

without 

Infiltration (m)

Difference 

(m)

Max Water 

Level with SV 

Infiltration (m)

Difference with 

SV Infiltration 

(m)

1 VX566 1087565.305 3687330.905 1.520 1.785 0.265 1.721 0.201

2 VX565 1087568.984 3687335.120 1.592 1.785 0.193 1.721 0.129

3 VX564 1087570.099 3687340.301 1.626 1.785 0.159 1.721 0.095

4 VX563 1087569.918 3687347.885 1.630 1.785 0.155 1.721 0.091

5 VX562 1087569.774 3687354.096 1.653 1.785 0.132 1.721 0.068

6 VX561 1087569.723 3687363.956 1.635 1.785 0.150 1.721 0.086

7 a5063 1087570.539 3687390.786 1.665 1.785 0.120 1.721 0.056

Average 

Difference 0.168

Average 

Difference 0.103

Standard 

Deviation 0.049

Standard 

Deviation 0.049

Table 3B. Wrack line GPS point data for 2011 Hurricane Irene at Site F with NAD83 HARN Virginia State Plane South coordinates

for northing and easting, sub-grid elevation, the base-grid maximum water level and the difference as inundation thickness, with and 

without 10% infiltration, including average and standard deviation statistics for verification of the sub-grid model with spatially-varying 

(SV) infiltration. 
32

3.2 Conclusions

It is demonstrated that the hydrodynamic model UnTRIM with the sub-grid capability 

can be used as a hydrological transport model to channel the rainfall into a run-off transport 

model.

The UnTRIM2 model is capable of simulating storm surge and inundation at NASA 

Langley Research Center and at Langley Air Force Base utilizing the incorporation of Lidar data 

in a hydrodynamic and hydrological transport sub-grid model. Upon inclusion of precipitation 

data as an atmospheric model input, localized flooding in the interior of Langley was simulated 

(non-contiguous from storm surge flooding along the edge of the Back River estuary). Specific 

areas of localized precipitation-induced flooding persist in the southwest interior region of 

Langley Research Center. Although buildings have been filtered out of the Lidar topography 

data and the structure itself is not modeled, the resulting topography still includes localized 

raised elevations at the buildings. That means, precipitation will fall onto these raised elevations 

and water will navigate around the buildings and subsequently accumulate in the surrounding 

low-lying areas. Therefore, we believe that we have achieved adequate building-by-building 

flood predictions for NASA Facilities at NASA Langley Research Center. 

Two simulated storm cases were compared utilizing past observation data. The 2003 

Hurricane Isabel compared the impact of modeling storm surge with and without precipitation 

input as shown in Figure 2.3 A-C. Additionally, a series of simulations involving sea level rise 

associated with climate change specifically address Hurricane Isabel at +00in, +15in, +30in, and 

+60in as shown in Figures 2.6 A-D. The 2011 Hurricane Irene was compared with GPS wrack 

line observation data at six separate sites in a comprehensive inundation comparison between 

model prediction and observed locations of collected debris immediately after the storm as 

shown in Figures 2.9 A-F.

The Langley installed tidal gauges are valuable and important for benchmarking the 

water level surrounding NASA Langley and Air Force site both for tidal forcing and the storm 

induced variation. The comparison of model results and the Langley tide gauge was very 

satisfactory achieving a correlation coefficient of R2= 0.95. 

NASA-collected GPS wrack line observation data proves to be particularly useful for 

evaluating modeled inundation extent. It can be utilized in a rigorous comparison by calculating 

the difference between observed and model-predicted maximum inundation. When no infiltration 

is considered, the difference of the maximum water elevation is approximately 10%. The 

difference reduces to between 1 - 5% when 10% infiltration was considered; a reasonable runoff 

coefficient, considering the perennially high water table at NASA Langley Research Center. 

3.3 Future Work 

Future efforts will address the assumption of ignoring percolation of water through the 

soil, as currently all model surfaces are considered impermeable. Additionally, the assumption 

of no storm water drainage loss or underground pipes potentially neglects some potential for 

precipitation sinks not currently accounted for in the model grid. Also, buildings displayed in 
33

Figures 2.9A-F have been filtered out of the Lidar topography data and are not present in the 

model sub-grid results. Provided accurate building heights, buildings potentially may be 

assessed in future model simulations for integration with the Lidar-derived sub-grid topography 

to determine their impact as barriers to maximum storm surge inundation. 

Potential coupling with a large scale ocean model for future forecast simulation is 

essential to the improvement of model simulations. An operational forecast model using a large 

scale ocean model with interpolated forecast wind and pressure fields can provide predictive 

capability up to 30 hours in advance of a major storm. The large scale model can be utilized to 

provide necessary boundary conditions to run the localized high-resolution sub-grid model 

simulations for the Back River estuary. The utility of future forecast simulation for tropical and 

extra-tropical storm systems is valuable for emergency response and protection of valuable 

infrastructure. Finally, the model can also be used to answer important management questions: 

• Do certain areas, tributaries, or small embayments tend to experience storm tide 

flooding to a greater degree or more frequently than others? 

• Can risks be mitigated through improved planning or engineering? 

• Are water-level extremes increased or locally prolonged because of increased runoff 

from modified watersheds?

• In conjunction with projected sea level rise, are particular regions of NASA Langley Research 

Center under greater threat of prolonged of more frequent inundation than others?

Acknowledgement:

The work was funded by NASA headquarters under the Climate Adaptation Science Investigator 

program administered by Jack Kaye. The Lidar data and wrack line measurement data was 

kindly provided by NASA Langley GIS team: Brad Ball and Berch Smithson. 
34

Appendix A. Methodology and Model Setup 

A1 Digital Elevation Model (DEM) derived from Lidar and Incorporation into Sub-Grid Model 

The setup and design of the model domain for the Back River estuary is based upon Lidar

topographic measurements from 2005 (Figure A.1, A – D). Lidar topography for NASA Langley 

came from 56 separate point cloud .las tiles in NAD83 HARN Virginia State Plane South in 

meters, with a vertical datum of NAVD88 in meters. The Lidar .las files were parsed as points 

and used to generate a single combined .xyz point file using las2txt from the Lastools toolset. 

The data sampled from the Lidar flyover for Langley are ample enough (at least one elevation 

value per m2) for creation of a raster at 1m resolution bereft of frequent gaps in the data. The 

.xyz point file was utilized as an IDW power 2 interpolation input to a raster Geotiff file. Using the 

Lidar point cloud data, a raster was produced at 5m resolution. The resulting interpolation 

product was then translated from NAD83 HARN Virginia State Plane South coordinates to 

NAD83 CORS 96 in UTM Zone18N with a vertical datum of NAVD88 in meters for interpolation 

onto the model grid (Figure A.2).

The 5m Digital Elevation Model (DEM) produced from the Lidar data was cast over a domain 

covering the Back River system around NASA Langley with an open boundary at the mouth of 

the river leading into the Chesapeake Bay (Figure A.3). The base grid utilizes 50m resolution 

cells, with 100 nested 5x5m sub-grid cells within each base grid cell (Figure A.2). This base grid 

resolution was chosen so that the main stem of the Back River channel would have multiple grid 

cells across the width of the river for proper calculation of volume water transport into and out of 

the system. The sub-grid scaling was chosen such that the topographic Lidar-derived DEM 

would be at the native resolution (5m) and not require further interpolation and potentially invite 

computational error due to distortion. In the future, the Lidar point cloud can be utilized to 

produce even higher resolution DEMs down to 1m resolution. However, the error associated 

with Lidar data collection methods, assuming the most accurately calibrated instrumentation,

still may include errors on the order of 0-10cm along spatially uniform terrain and 10-50cm in 

vegetated areas and urban environments.

Bathymetric .xyz point data (10m resolution) were retrieved from two NOAA bathymetric surveys 

of the Back River system, H07959 and H07185. Using ArcGIS 10.1, a power-2 inverse distance 

weighted interpolation was performed on the bathymetry data using a shoreline polyline as a 

barrier. The resulting interpolation product was then translated to NAD83 CORS 96 in UTM 

Zone18N with a vertical datum of NAVD88 in meters. With the Lidar-derived topography and 

NOAA bathymetry datasets in the same projections and datums, they are merged such that the 

bathymetric data would overlap the Lidar topographic data to resolve any issues with bridges or 

other impediments in the Lidar DEM potentially blocking proper water movement into rivers and 

streams second order and above. The resulting topography and bathymetry merged DEM was 

provided to grid-generation software, Janet v.2.9.36, to provide elevations for the model subgrid, where the model domain was constructed with a 50m base grid with a 5m resolution subgrid (Figure A.2).
35

Figure A.1A. Lidar for Langley Research Center displaying 30cm vertical resolution contours.

Figure A.1B. Lidar contours focused on central Langley Research Center displaying drainage 

ditches backing up to a meandering tidal creek along Back River.

 B

 A
36

Figure A.1C. Lidar contours focused on the north end of Langley Research Center displaying 

drainage ditches near the location of the NASA Tide 01 tide gauge along Back River.

 C

 * Langley Tide Gauge 1
37

Figure A.1D. Peninsula contours shown for Langley Air Force Base and NASA Langley 

Research Center.

 D
38

Figure A.2. 50m Base Grid shown with 5m Sub-Grid shown for the Northeast tip of Langley Air 

Force Base in the UnTRIM2 model interface.

Figure A.3. Full Back River model domain in Google Earth with 54,057 nodes and 53,474 

elements comprising the 50m resolution base grid, yielding 4,759,788 sub-grid elements at 5m 

resolution.
39

A2 Development of a Hydrological Transport Simulation with Precipitation

With the detail topography integrated into the hydrodynamic model sub-grid, as was done in the 

last section, the hydrodynamic model becomes a continuous time model that can be used to 

simulate the water budget given the landscapes in the watershed. UnTRIM2uses a two-level 

disaggregation scheme; a preliminary sub-basin identification is carried out based on 

topographic criteria, followed by further discretization using land use type considerations. When 

the precipitation is prescribed, it becomes a runoff model to describe the rainfall - runoff 

relations of a rainfall catchment area, watershed and drainage basin. More precisely, it 

produces the surface runoff hydrograph as a response to a rainfall hydrograph as input. In other 

words, the model calculates the conversion of rainfall into runoff. Often models have separate 

modules to address individual steps in the simulation process. The most common module is a 

subroutine for calculation of surface runoff, allowing variation in land use type, topography, soil 

type, vegetative cover, precipitation and land management practice (such as the application rate 

of a fertilizer). However, in this phase I approach, we will assume the land use is homogeneous 

and the soil is saturated during the storm condition. 

Ideal test simulations for precipitation will be utilized to test the input of rainfall into the model in 

three separate cases: one using an open flow basin with rainfall shown in Figure A.4, one using 

a partially enclosed basin with rainfall in Figure A.5, and a closed flow basin with rainfall in 

Figure A.6. For all three simulations an ideal ditch has been designed with sloping sides angled 

into the basin as depicted in the inset of Figure A.6. The model grid is shaped like a sloping 

trough with a depth of 2m in the channel. The north and south banks of the trough gradually 

slope into the channel in the center with a maximum elevation of 2m on each side. 

A2.1 Ideal Test Case with Open Flow Basin with Precipitation 

The parameters for the open flow basin with rainfall ideal test case include a flux boundary 

condition with a constant prescribed 0.5 m/s flow on the west edge of the grid in Figure A.4 with 

no forcing at the open boundary on the east edge. A constant 25 mm/hr precipitation input was 

designated for a 72 hour simulation. Over the three day simulation, the UnTRIM2 model’s 

particle tracking mode was utilized to place particles on the north and south banks of the ideal 

trough-shaped domain to allow precipitation to transport the particles into the channel to be 

transported out of the domain. The particles (red dots) are arbitrarily placed at a variety of 

elevations between 0-2m above the water level in the basin to ascertain if precipitation will 

gravitationally transport the particles perpendicular to the contours into the trough-shaped basin 

and out of the domain. This scenario was designed to demonstrate the model’s capability of 

transporting precipitation into an unobstructed, free-flowing drainage ditch back to the 

neighboring river system.
40

Figure A.4. Ideal test case for precipitation at 25 mm/hr in an open flow basin with a prescribed 

0.5 m/s flow from the west.

t = 1 day

Day 0: Initial Condition

Day 1

Day 2

Day 3

t = 1 day

t = 1 day

* Precipitation Transports Particles Initially 

 Placed on Land into the Ditch and out of the Basin!
41

Figure A.5. Ideal test case for precipitation at 25 mm/hr in a partially enclosed basin with a wall 

along the west edge of the sloping trough basin.

t = 1 day

Day 0: Initial Condition

Day 1

Day 2

Day 3

t = 1 day

t = 1 day

* Precipitation Transports Particles

 Initially Placed on Land into the Ditch!
42

Figure A.6. Ideal test case for precipitation at 25 mm/hr in a fully enclosed basin which allows 

water volume to properly accumulate over time.

Day 0: Initial Condition

Day 1

Day 2

Day 3

t = 1 day

t = 1 day

t = 1 day
43

A2.2 Ideal Test Case for Partially Closed Basin with Precipitation 

The parameters for the partially closed basin with precipitation as an ideal test case include a 

wall (or flux boundary condition with a prescribed 0 m/s flow) on the west edge of the grid shown 

in Figure A.5. As with the ideal test case for the open flow basin with rainfall, no forcing was 

prescribed at the open boundary on the eastern edge of the model domain with a constant 25 

mm/hr precipitation rate designated for 72 hours in the simulation. The model’s particle tracking 

mode was utilized again to arbitrarily place particles on the north and south banks of the troughshaped domain between 0-2m above the water level in the basin to confirm that precipitation 

gravitationally transports the red particles into the trough-shaped basin and out of the domain. 

This scenario was designed to effectively demonstrate the model’s capability of transporting 

precipitation into a partially obstructed drainage with an outlet ditch back to the neighboring river 

system. Unlike the previous simulation, the particles slowly collect in the channel, but only a 

small quantity of the particles exit the ditch, as virtually no current is observed in the ditch with 

one side (the west side) obstructed or otherwise blocked (Figure A.5).

A2.3 Ideal Test Case for Fully Enclosed Basin with Precipitation 

In the case of an ideal test case with precipitation in a fully enclosed basin, there are walls 

blocking transport out of the domain on both sides of the idealized sloping trough with no 

prescribed flux boundary condition on the west edge of the grid, and no forcing at the clamped 

open boundary on the east edge. The same constant 25 mm/hr precipitation input was 

prescribed over the 72 hour simulation shown in Figure A.6. This test case was designed to test 

the conservation of mass and ascertain that precipitation would accumulate in a ditch if there is 

no outlet to allow water to escape. This scenario successfully validates the model’s ability of 

collecting precipitation over time and allows the user to compute the volume of water collected 

over time in a simplistic bathtub-style simulation.

A3 Storm Tide and Inundation Model Forcing Functions 

A3.1 Tidal Forcing 

Tides are forced along the Back River open boundary on the easternmost edge of the domain at 

the mouth of Back River into the Chesapeake Bay with the north bank along the southeastern 

edge of Poquoson, and the south bank along the Grandview Park spit in Hampton shown in 

Figure A.3. Model application simulations for the 2003 Hurricane Isabel make use of NOAA 

observation data from Sewells Point, VA (Station #8638610), as the tidal boundary condition. 

This station was utilized as a tidal input at the open boundary of the Back River domain due to 

its harmonic similarity in tidal frequency relative to the mouth of the Chesapeake Bay and for its 

use in the calibration of the three recently installed Langley tide gauges (NASA Langley GIS 

Team, 2010, 2012). The tide input storm scenarios were the 2009 November Nor’easter 

(Nor’Ida), and 2011 Hurricane Irene and were collected 3km from the model’s open boundary

shown in Figure A.3. This tide gauge is located in the Back River estuary at Dandy Haven 

Marina (courtesy of VIMS TideWatch), and interpolated to a 5 minute time step (Table A1, 

Appendix A). 
44

A3.2 Atmospheric Wind, Pressure, and Precipitation Forcing 

Wind data were retrieved in m/s from NOAA observations at Sewell’s Point, VA (Station 

#8638610) and prepared as a uniform input throughout the domain for each of the storm 

scenarios. U and V wind velocities were extracted and wind fields were interpolated to 5 minute 

intervals for each of the storm scenarios with appropriate start and end times for each storm 

event included in Table A1. Atmospheric pressure data in mbars were obtained for the same 

time periods from NOAA observations at Sewell’s Point, VA as well. Pressure data were 

converted to Pascals, and prescribed as a uniform atmospheric pressure input throughout the 

domain. Precipitation inputs were interpolated from hourly measurements from the NOAA 

NGDC collection station at the Williamsburg/Newport News Airport nearby NASA Langley.

A.4 Verification of Results 

Tide stations Langley Tide1 and Back River Dandy Haven (part of a suite of VIMS TideWatch 

stations throughout the Chesapeake Bay) will be utilized to evaluate the temporal variability of 

each storm system in Table A1. The Langley Tide gauge 1 was installed in 2010, and the Back 

River Dandy Haven Gauge was installed in 2008 with their locations noted within the model 

domain in Figure A.3 (NASA Langley GIS Team, 2010). It should be noted that Langley has 

recently installed 2 additional tide gauges (NASA Tide2 and NASA Tide3) within the model 

domain in April 2012, but they are not included due to their recent installation and non-presence 

during any the storm events noted in Table A1 (NASA Langley GIS Team, 2012). An R2

correlation will be utilized to compare the observations with the model result for each scenario 

as a statistical measure of accuracy. Statistical tests for spatial verification of model coastal 

flooding results will utilize GPS wrack line data (collected via GPS using debris presence after 

each storm) to assess the maximum extent of inundation. 

Table A1. Chart of various storm scenarios conducted in the vicinity of NASA Langley Research 

Center with model start and end times in Greenwich Mean Time (GMT). 

Storm Scenario Simulation Date Range

Start Time End Time

1 2003 Hurricane Isabel 00:00 GMT 09/01/2009 00:00 GMT 10/01/2009

2

2009 November Nor’easter 00:00 GMT 11/01/2009 00:00 GMT 12/01/2009

3 2011 Hurricane Irene 00:00 GMT 08/01/2011 00:00 GMT 09/01/2011
45

Appendix B: COMPARISON BETWEEN WRACK LINE MEASUREMENT AND PREDICTED MAXIMUM WATER LEVEL

#

Wrack Line 

Point Northing Easting

Elevation 

(m)

Max Water Level 

without Infiltration 

(m)

Difference 

(m)

Max Water 

Level with 10% 

Infiltration (m)

Difference with 

10% Infiltration 

(m)

1 a5027 1086519.375 3688608.584 1.627 1.802 0.175 1.622 -0.005

2 a5028 1086517.371 3688609.014 1.679 1.802 0.123 1.622 -0.057

3 VX519 1086516.091 3688610.823 1.702 1.802 0.1 1.622 -0.080

4 VX518 1086516.126 3688611.563 1.683 1.802 0.119 1.622 -0.061

5 VX517 1086516.076 3688612.504 1.665 1.802 0.137 1.622 -0.043

6 VX516 1086515.458 3688613.648 1.695 1.802 0.107 1.622 -0.073

7 VX515 1086514.373 3688614.778 1.686 1.802 0.116 1.622 -0.064

8 VX514 1086513.578 3688616.071 1.706 1.802 0.096 1.622 -0.084

9 a5026 1086513.997 3688622.987 1.724 1.802 0.078 1.622 -0.102

10 a5025 1086516.533 3688628.9 1.739 1.802 0.063 1.622 -0.117

11 a5024 1086515.484 3688635.438 1.705 1.802 0.097 1.622 -0.083

12 a5023 1086515.647 3688637.976 1.723 1.802 0.079 1.622 -0.101

13 a5022 1086512.812 3688641.324 1.667 1.802 0.135 1.622 -0.045

14 a5021 1086508.635 3688643.482 1.717 1.802 0.085 1.622 -0.095

15 a5020 1086507.836 3688648.444 1.7 1.802 0.102 1.622 -0.078

16 a5019 1086507.545 3688655.408 1.694 1.802 0.108 1.622 -0.072

17 a5018 1086508.05 3688659.18 1.681 1.802 0.121 1.622 -0.059

18 a5017 1086508.953 3688663.616 1.699 1.802 0.103 1.622 -0.077

19 a5016 1086510.462 3688667.204 1.695 1.802 0.107 1.622 -0.073

20 a5015 1086510.789 3688670.572 1.694 1.802 0.108 1.622 -0.072

21 a5014 1086511.676 3688674.6 1.646 1.802 0.156 1.622 -0.024

22 VX513 1086515.103 3688683.796 1.634 1.802 0.168 1.622 -0.012

23 VX512 1086514.783 3688684.566 1.635 1.802 0.167 1.622 -0.013

24 VX511 1086514.213 3688685.837 1.647 1.802 0.155 1.622 -0.025

25 VX510 1086513.448 3688687.233 1.654 1.802 0.148 1.622 -0.032

26 VX509 1086513.072 3688688.397 1.666 1.802 0.136 1.622 -0.044

27 VX508 1086510.753 3688690.108 1.647 1.802 0.155 1.622 -0.025

28 VX507 1086510.896 3688691.597 1.672 1.802 0.13 1.622 -0.050
46

29 VX506 1086510.73 3688692.998 1.657 1.802 0.145 1.622 -0.035

30 VX505 1086510.577 3688694.43 1.632 1.802 0.17 1.622 -0.010

31 VX504 1086510.9 3688696.027 1.615 1.802 0.187 1.622 0.007

32 VX503 1086510.715 3688697.605 1.671 1.802 0.131 1.622 -0.049

33 VX502 1086510.801 3688699.177 1.649 1.802 0.153 1.622 -0.027

34 VX501 1086510.729 3688700.721 1.643 1.802 0.159 1.622 -0.021

35 VX500 1086510.434 3688701.786 1.635 1.802 0.167 1.622 -0.013

Average 

Difference

0.128 Average 

Difference

-0.052

Standard 

Deviation

0.032 Standard 

Deviation

0.032

Table B1. Wrack line GPS point data at Site A with NAD83 HARN Virginia State Plane South coordinates for northing and easting, subgrid elevation, the base-grid maximum water level and the difference as inundation thickness, with and without 10% infiltration, including 

average and standard deviation statistics for verification of the sub-grid model. 

#

Wrack Line 

Point Northing Easting

Elevation 

(m)

Max Water Level 

without Infiltration 

(m)

Difference 

(m)

Max Water 

Level with 10% 

Infiltration (m)

Difference with 

10% Infiltration 

(m)

1 VX532 1086594.643 3688370.591 1.750 1.801 0.051 1.621 -0.129

2 VX531 1086597.287 3688374.649 1.746 1.801 0.055 1.621 -0.125

3 VX530 1086598.288 3688378.817 1.750 1.801 0.051 1.621 -0.129

4 VX529 1086599.157 3688383.034 1.749 1.801 0.052 1.621 -0.128

5 VX528 1086600.463 3688388.673 1.759 1.801 0.042 1.621 -0.138

6 a5036 1086575.220 3688398.068 1.669 1.801 0.132 1.621 -0.048

7 a5040 1086595.261 3688399.296 1.751 1.801 0.050 1.621 -0.130

8 a5039 1086593.454 3688400.210 1.750 1.801 0.051 1.621 -0.129

9 a5038 1086590.768 3688400.983 1.755 1.801 0.046 1.621 -0.134

10 a5037 1086588.065 3688401.060 1.764 1.801 0.037 1.621 -0.143

11 a5035 1086578.106 3688405.365 1.663 1.801 0.138 1.621 -0.042

12 a5034 1086577.494 3688409.574 1.661 1.801 0.140 1.621 -0.040

13 a5033 1086578.844 3688414.090 1.674 1.801 0.127 1.621 -0.053

14 a5032 1086578.522 3688418.064 1.671 1.801 0.130 1.621 -0.050

15 a5029 1086560.682 3688421.860 1.654 1.801 0.147 1.621 -0.033

16 a5030 1086564.393 3688422.012 1.668 1.801 0.133 1.621 -0.047
47

17 a5031 1086571.994 3688422.993 1.686 1.801 0.115 1.621 -0.065

18 VX520 1086536.219 3688423.552 1.645 1.801 0.156 1.621 -0.024

19 VX521 1086540.460 3688426.264 1.669 1.801 0.132 1.621 -0.048

20 VX522 1086544.949 3688429.776 1.639 1.801 0.162 1.621 -0.018

21 VX523 1086551.865 3688434.625 1.670 1.801 0.131 1.621 -0.049

22 VX524 1086557.694 3688438.474 1.631 1.801 0.170 1.621 -0.010

23 VX525 1086560.314 3688441.591 1.654 1.801 0.147 1.621 -0.033

24 VX526 1086562.895 3688442.864 1.631 1.801 0.170 1.621 -0.010

25 VX527 1086565.371 3688443.812 1.604 1.801 0.197 1.621 0.017

Average 

Difference

0.110 Average 

Difference

-0.070

Standard 

Deviation

0.050 Standard 

Deviation

0.050

Table B2. Wrack line GPS point data at Site B with NAD83 HARN Virginia State Plane South coordinates for northing and easting, subgrid elevation, the base-grid maximum water level and the difference as inundation thickness, with and without 10% infiltration, including 

average and standard deviation statistics for verification of the sub-grid model. 

#

Wrack Line 

Point Northing Easting

Elevation 

(m)

Max Water 

Level without 

Infiltration (m)

Difference 

(m)

Max Water 

Level with 

10% 

Infiltration (m)

Difference 

with 

10% 

Infiltration 

(m)

1 VX553 1087857.664 3688508.326 1.590 1.766 0.176 1.589 -0.001

2 VX552 1087854.880 3688515.822 1.594 1.766 0.172 1.589 -0.005

3 VX551 1087853.441 3688521.385 1.574 1.766 0.192 1.589 0.015

4 VX550 1087852.618 3688525.460 1.543 1.766 0.223 1.589 0.046

5 VX549 1087853.282 3688532.202 1.580 1.766 0.186 1.589 0.009

6 VX548 1087855.684 3688536.171 1.616 1.766 0.150 1.589 -0.027

7 VX547 1087856.630 3688540.129 1.640 1.766 0.126 1.589 -0.051

8 VX546 1087855.921 3688544.541 1.639 1.766 0.127 1.589 -0.050

9 VX545 1087854.189 3688550.450 1.632 1.766 0.134 1.589 -0.043

10 VX544 1087850.881 3688556.263 1.640 1.766 0.126 1.589 -0.051

11 VX543 1087849.485 3688562.785 1.588 1.766 0.178 1.589 0.001
48

12 VX542 1087845.848 3688566.306 1.584 1.766 0.182 1.589 0.005

13 VX541 1087847.462 3688571.618 1.637 1.766 0.129 1.589 -0.048

14 VX540 1087845.286 3688573.756 1.634 1.766 0.132 1.589 -0.045

15 VX539 1087844.478 3688577.683 1.566 1.766 0.200 1.589 0.023

16 VX537 1087828.872 3688580.495 1.544 1.766 0.222 1.589 0.045

17 VX538 1087832.782 3688580.816 1.509 1.766 0.257 1.589 0.080

18 VX536 1087818.186 3688582.003 1.574 1.766 0.192 1.589 0.015

19 VX535 1087812.782 3688584.123 1.572 1.766 0.194 1.589 0.017

20 VX534 1087807.102 3688586.422 1.599 1.766 0.167 1.589 -0.010

21 VX533 1087801.790 3688588.476 1.575 1.766 0.191 1.589 0.014

22 a5051 1087815.832 3688607.961 1.473 1.766 0.293 1.589 0.116

23 a5050 1087817.645 3688609.878 1.531 1.766 0.235 1.589 0.058

24 a5049 1087819.673 3688615.755 1.720 1.766 0.046 1.589 -0.131

25 a5048 1087816.891 3688616.656 1.691 1.766 0.075 1.589 -0.102

26 a5047 1087813.098 3688617.414 1.634 1.766 0.132 1.589 -0.045

27 a5046 1087809.551 3688619.224 1.623 1.766 0.143 1.589 -0.034

28 a5045 1087808.063 3688620.189 1.625 1.766 0.141 1.589 -0.036

29 a5044 1087807.875 3688622.824 1.619 1.766 0.147 1.589 -0.030

30 a5043 1087806.676 3688624.209 1.625 1.766 0.141 1.589 -0.036

31 a5042 1087804.188 3688626.321 1.618 1.766 0.148 1.589 -0.029

32 a5041 1087800.942 3688627.558 1.595 1.766 0.171 1.589 -0.006

Average 

Difference

0.167 Average 

Difference

-0.010

Standard 

Deviation

0.049 Standard 

Deviation

0.049

Table B3. Wrack line GPS point data at Site C with NAD83 HARN Virginia State Plane South coordinates for northing and easting, subgrid elevation, the base-grid maximum water level and the difference as inundation thickness, with and without 10% infiltration, including 

average and standard deviation statistics for verification of the sub-grid model. 
49

#

Wrack Line 

Point Northing Easting

Elevation 

(m)

Max Water Level 

without Infiltration 

(m)

Difference 

(m)

Max Water 

Level with 10% 

Infiltration (m)

Difference with 

10% Infiltration 

(m)

1 a5055 1087804.297 3688174.532 1.569 1.775 0.21 1.598 0.029

2 a5054 1087802.715 3688179.124 1.572 1.775 0.20 1.598 0.025

3 a5053 1087801.440 3688184.098 1.571 1.775 0.20 1.598 0.027

4 a5052 1087802.098 3688187.626 1.482 1.775 0.29 1.598 0.116

Average 

Difference 0.227

Average 

Difference 0.049

Standard 

Deviation 0.044

Standard 

Deviation 0.044

Table B4. Wrack line GPS point data at Site D with NAD83 HARN Virginia State Plane South coordinates for northing and easting, subgrid elevation, the base-grid maximum water level and the difference as inundation thickness, with and without 10% infiltration, including 

average and standard deviation statistics for verification of the sub-grid model. 

#

Wrack Line 

Point Northing Easting

Elevation 

(m)

Max Water Level 

without 

Infiltration (m)

Difference 

(m)

Max Water 

Level with 10% 

Infiltration (m)

Difference 

with 

10% 

Infiltration (m)

1 VX558 1087664.557 3687772.846 1.531 1.780 0.249 1.602 0.071

2 VX559 1087663.204 3687778.586 1.594 1.780 0.186 1.602 0.008

3 VX560 1087663.255 3687781.840 1.618 1.780 0.162 1.602 -0.016

4 a5062 1087666.592 3687787.504 1.554 1.780 0.226 1.602 0.048

5 a5061 1087668.057 3687788.712 1.528 1.780 0.252 1.602 0.074

6 a5060 1087670.659 3687792.356 1.523 1.780 0.257 1.602 0.079

7 a5059 1087671.423 3687797.591 1.521 1.780 0.259 1.602 0.081

8 a5058 1087671.842 3687803.581 1.576 1.780 0.204 1.602 0.026

9 a5057 1087672.926 3687806.364 1.579 1.780 0.201 1.602 0.023

10 a5056 1087674.576 3687810.679 1.561 1.780 0.219 1.602 0.041
50

11 VX557 1087676.411 3687815.002 1.563 1.780 0.217 1.602 0.039

12 VX556 1087676.875 3687817.396 1.503 1.780 0.277 1.602 0.099

13 VX555 1087676.758 3687820.006 1.501 1.780 0.279 1.602 0.101

14 VX554 1087677.144 3687822.442 1.530 1.780 0.250 1.602 0.072

Average 

Difference

0.231 Average 

Difference

0.053

Standard 

Deviation

0.035 Standard 

Deviation

0.035

Table B5. Wrack line GPS point data at Site E with NAD83 HARN Virginia State Plane South coordinates for northing and easting, subgrid elevation, the base-grid maximum water level and the difference as inundation thickness, with and without 10% infiltration, including 

average and standard deviation statistics for verification of the sub-grid model. 

#

Wrack Line 

Point Northing Easting

Elevation 

(m)

Max Water Level 

without Infiltration 

(m)

Difference 

(m)

Max Water 

Level with 10% 

Infiltration (m)

Difference with 

10% Infiltration 

(m)

1 VX566 1087565.305 3687330.905 1.520 1.785 0.265 1.607 0.087

2 VX565 1087568.984 3687335.120 1.592 1.785 0.193 1.607 0.015

3 VX564 1087570.099 3687340.301 1.626 1.785 0.159 1.607 -0.019

4 VX563 1087569.918 3687347.885 1.630 1.785 0.155 1.607 -0.023

5 VX562 1087569.774 3687354.096 1.653 1.785 0.132 1.607 -0.047

6 VX561 1087569.723 3687363.956 1.635 1.785 0.150 1.607 -0.029

7 a5063 1087570.539 3687390.786 1.665 1.785 0.120 1.607 -0.059

Average 

Difference

0.168 Average 

Difference

-0.011

Standard

Deviation 0.049 Standard Deviation 0.049

Table B6. Wrack line GPS point data at Site F with NAD83 HARN Virginia State Plane South coordinates for northing and easting, subgrid elevation, the base-grid maximum water level and the difference as inundation thickness, with and without 10% infiltration, including 

average and standard deviation statistics for verification of the sub-grid model. 
51

References:

Casulli, V. and Sterling, G. S. (2011): “Semi-implicit sub-grid modeling of three-dimensional 

free-surface flows”, International journal for numerical method in fluids. Vol. 67, p441-449. 

CIPS report by Sellner, Kevin, Elizabeth Smith, Harry V. Wang, Ming Li, Jay Titlow, and Barry 

Stamey (2012): “Chesapeake Inundation Prediction System (CIPS): flood forecasts for coastalbay-estuary resiliency to storm surge”. Final report submitted to NOAA IOOS Program 

Office; award number: NOAA NA07NOS4730214. 

Cho Kyoung-Ho, Harry Wang Jian Shen, Arnoldo Valle-Levinson and Yi-cheng Teng (2012): “A 

modeling study on the response of the Chesapeake Bay to Hurricane Events of Floyd and 

Isabel” Ocean Modeling, Vol. 49-50, p22-46. 

National Land Cover Database, 2006. NOAA Coastal Change Analysis Program. 

www.csc.noaa.gov/landcover .

NASA Langley GIS Team, 2010. LaRC Prototype Tide Measurement Station. Langley Research 

Center, Hampton, VA 23681-0001, M/S 300. http://capable.larc.nasa.gov/tide-gauge/docspdf/Langley_sea_level_gauge_report.pdf .

NASA Langley GIS Team, 2012. LaRC Tide Measurement Stations. Langley Research Center, 

Hampton, VA 23681-0001, M/S 300. http://capable.larc.nasa.gov/tide-gauge/docspdf/New_stations_report.pdf .

Roland, Aron, Yinglong. Zhang, Harry. V. Wang, Yanqiu Meng, Yi-cheng Teng, Vladimir

Maderichd, Igor Brovchenkod, Mathieu Dutour-Sikirice and Ulrich Zankea (2012): “A fully

coupled 3D wave-current interaction model on unstructured grids". JGR – Oceans, Vol. 117, 

C00J33, doi:10.1029/2012
REPORT DOCUMENTATION PAGE Form Approved

OMB No. 0704-0188

2. REPORT TYPE 

Technical Memorandum

 4. TITLE AND SUBTITLE

A Storm Surge and Inundation Model of the Back River Watershed at 

NASA Langley Research Center 

5a. CONTRACT NUMBER

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Loftis, Jon Derek; Wang, Harry V.; DeYoung, Russell J.

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NASA Langley Research Center

Hampton, VA 23681-2199

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This report on a Virginia Institute for Marine Science project demonstrates that the sub-grid modeling technology (now as part of Chesapeake Bay Inundation 

Prediction System, CIPS) can incorporate high-resolution Lidar measurements provided by NASA Langley Research Center into the sub-grid model 

framework to resolve detailed topographic features for use as a hydrological transport model for run-off simulations within NASA Langley and Langley Air 

Force Base. The rainfall over land accumulates in the ditches/channels resolved via the model sub-grid was tested to simulate the run-off induced by heavy 

precipitation. Possessing both the capabilities for storm surge and run-off simulations, the CIPS model was then applied to simulate real storm events starting 

with Hurricane Isabel in 2003. It will be shown that the model can generate highly accurate on-land inundation maps as demonstrated by excellent comparison 

of the Langley tidal gauge time series data (CAPABLE.larc.nasa.gov) and spatial patterns of real storm wrack line measurements with the model results 

simulated during Hurricanes Isabel (2003), Irene (2011), and a 2009 Nor’easter. With confidence built upon the model’s performance, sea level rise scenarios 

from the ICCP (International Climate Change Partnership) were also included in the model scenario runs to simulate future inundation cases. 

15. SUBJECT TERMS

Climate change; Flood model; Hurricanes; Storm surge; Storms

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