Hurricane Dennis water surface elevation at landfall.
M.V. Bilskie, S.C. Hagen, D.L. Passeri, K. Alizad, S.C. Medeiros,“Modeling hurricane waves and storm surge
under climate change in the northern Gulf of Mexico.” Louisiana State University, October 10, 2014.
The vulnerability of the built and natural environment in coastal regions will increase due to the effects of global climate change in general, and sea level rise (SLR) in particular. Climate change perturbs the natural state of the environment and can create short- or long-term changes in sea level, shoreline position and profile, barrier islands, intertidal salt marsh productivity, and human-induced change such as population dynamics. The goal is to examine the vulnerability of coastal flooding in the northern Gulf of Mexico from hurricane waves and storm surge under various climate change scenarios. A large-domain, high-resolution, wave and storm surge model that spans the Florida panhandle to the western Mississippi coast was developed and applied to recreate historical events such as Hurricane Dennis, Ivan, Katrina, and Isaac. The storm surge model is modified to include projected changes to shoreline positions and profiles, coastal dune elevations, salt marsh migration, and changes in land use / land cover. Numerous simulations are carried out and are driven by a comprehensive set of synthetic wind fields that result in a large population of flooding surfaces and are statistically analyzed to project a representation of the 100-year floodplain for each SLR scenario. Comparisons between 100-year floodplain maps under present and future SLR scenarios will be used to assess the vulnerability of the northern Gulf of Mexico to coastal storm surge flooding.
Permanent link to this article: http://www.mattbilskie.com/invited-presentation-modeling-hurricane-waves-and-storm-surge-under-climate-change-in-the-northern-gulf-of-mexico/
D.L. Passeri, S.C. Hagen, M.V. Bilskie, S.C. Medeiros, (2014). “On the significance of incorporating shoreline changes for evaluating coastal hydrodynamics under sea level rise scenarios.” Natural Hazards, doi:10.1007/s11069-014-1386-y.
Abstract: The influence of including the dynamic effects of future shoreline changes associated with sea level rise into hydrodynamic modeling is evaluated for the coast of the Northern Gulf of Mexico from Mobile Bay, AL to St. Andrew Bay, FL. A two-dimensional, depth-integrated hydrodynamic model forced by astronomic tides and hurricane winds and pressures representative of Hurricanes Ivan (2004), Dennis (2005) and Katrina (2005) is used to simulate present conditions, 2050 projected sea level (0.46 m rise) with present-day shorelines, and 2050 sea level with projected 2050 shorelines. The 2050 shoreline and nearshore morphology are projected using Coastal Vulnerability Index shoreline change rates to determine the position of the new Gulf and bay shorelines, while the active beach profile is shifted horizontally according to the amount of erosion or accretion, and vertically to keep pace with rising seas. Hydrodynamic model results show that taking a dynamic approach to modeling sea level rise (as opposed to a static, or ‘‘bathtub’’ approach) increases tidal ranges and tidal prisms within the bay systems. Incorporating the projected shoreline changes does not alter tidal ranges, but some bays experience changes in tidal prisms depending on whether the planform area of the bay increases or decreases with the projected erosion or accretion. Barrier islands with projected erosion are vulnerable to increased overtopping from storm surge inundation, which impels more water into the back-bays and increases the inland inundation extent and magnitude. Inundation along barrier islands with projected accretion remains relatively the same as inundation under present-day shorelines, which prevents additional overtopping and limits more water from entering back-bays. Results demonstrate that although modeling sea level rise as a dynamic process is necessary, the incorporation of shoreline changes has variable impacts when evaluating future hydrodynamics and the response of the coastal system to sea level rise.
Permanent link to this article: http://www.mattbilskie.com/on-the-significance-of-incorporating-shoreline-changes-for-evaluating-coastal-hydrodynamics-under-sea-level-rise-scenario/
I updated an old code, Interpolation_auto.F, to a new and revamped version, DEM2GRD.F90. The utility takes in a Digital Elevation Model (DEM) and interpolates it onto an unstructured finite element mesh using the cell-area averaging (CAA) algorithm published in Bilskie & Hagen (2013).
An example input file can be found here.
I also put together a brief User Manual here.
Permanent link to this article: http://www.mattbilskie.com/updated-code-grd2dem-f90/
Permanent link to this article: http://www.mattbilskie.com/invited-presentation-discuss-sea-level-rise-and-storm-surge-to-elks-club-286/
Permanent link to this article: http://www.mattbilskie.com/2014-eeslr-ngom-workshop-apalachicola-fl/
M.V. Bilskie, S.C. Hagen, P. Bacopoulos, A. Thomas, P. Hovenga, (2014) “Sea level rise and tidal hydrodynamics in the Indian River Lagoon, Florida.” 34th International Conference on Coastal Engineering, Seoul, Korea, June 15-20, 2014.
Introduction: The 156 mile Indian River Lagoon (IRL), located on the Atlantic coast, is a collection of three individual lagoons: Mosquito Lagoon, Banana River, and the Indian River, including Cape Canaveral. The lagoon consists of five narrow-width inlets (from north to south): Ponce de León, Sebastian, Fort Pierce, Saint Lucie, and Jupiter. The system also contains a chain of causeways and tens of thousands of acres of dense submerged aquatic vegetation (SAV) that combine to constrict and dampen tidal flow and flushing of the lagoon. The offshore tide range is on the order of one meter, while the lagoon is micro-tidal, with peak tide range in some areas as low as a few centimetres as found in Haulover Canal (70 m width) that connects Mosquito Lagoon to the Indian River. The IRL system is an important resource to the region, generating an economic value of about $3.7 billion and 15,000 jobs and offers recreational activities to more than 11 million people per year (St. Johns River Water Management District, 2013).
Permanent link to this article: http://www.mattbilskie.com/icce-2014-seoul-korea/
Recently, I have been doing some heavy processing of las files to eventually generate a digital elevation model (DEM). I found myself in a dilemma of having thousands of las files and needing a way to convert them to mulitpoint shapefiles (mps). I have used lastools in the past, but typically steer away from most of the utilities due to the licensing and the introduction of artificial noise if you have not paid for a full license – I don’t want to take any chances with the end product. ArcGIS also has a tool to convert las to multipoint, but I did not want to go this route for two reasons: 1) The number of points are much too large for a single mps and 2) I don’t want a mps for each las file. This leads to the following scenario; I need to combine, say 30 las files to a single mps, which is a tedious task to by hand in ArcGIS. However, it is easily done with a little python script.
The code below combines 40 las files to a single mps.
# Import system modules
from arcpy import env
workspace = 'Input Directory'
env.workspace = workspace
odir = 'Output Directory'
ptspacing = 1.8 # Average point spacing
classcode = "2" # Ground
sr = arcpy.SpatialReference("NAD 1983 UTM Zone 17N") # Coodinate System
numFiles = 0
numshpFiles = 0
for file in glob.glob('*.las'):
numFiles = numFiles + 1
totalnumFiles = numFiles
print 'Starting to convert ' + str(totalnumFiles) + ' files...'
numFiles = 0
flist = ''
for file in glob.glob('*.las'):
numFiles = numFiles + 1
if numFiles != 1:
flist = flist + ';' + file
flist = file
if numFiles % 40 == 0 or numFiles == totalnumFiles::
numshpFiles = numshpFiles + 1
ofile = odir + "/shpGroup_" + str(numshpFiles)
arcpy.LASToMultipoint_3d(flist, ofile, ptspacing, classcode)
flist = '' # Clear file list
Permanent link to this article: http://www.mattbilskie.com/using-arcpy-to-convert-las-files-to-mulitpoint-shapefile/
Central Florida Future – “With the effects of climate change hitting close to shore, two teams tackle summers that are coming too soon and cold spells that are freezing Florida.
“It’s a great combination of strength actually,” said Michael Johnson, dean of the College of Sciences. “What we have in biology and engineering together is a real strength in what you might call coastal studies.”
One team is led by Scott Hagen, a professor of civil, environmental and construction engineering and the director ofUCF’s Coastal Hydroscience Analysis, Modeling & Predictive Simulations Laboratory.”
Continue to read here: http://bit.ly/1ppUEuG
Permanent link to this article: http://www.mattbilskie.com/ucf-works-to-research-rising-sea-levels/
Update – now available as Open Access
M.V. Bilskie, S.C. Hagen, S.C. Medeiros, D.L. Passeri (2014). “Dynamics of sea level rise and coastal flooding on a changing landscape.” Geophysical Research Letters, 927-934, doi: 10.1002/2013GL058759
Standard approaches to determining the impacts of Sea Level Rise (SLR) on storm surge flooding employ numerical models reflecting present conditions with modified sea states for a given SLR scenario. In this study, we advance this paradigm by adjusting the model framework so that it reflects not only a change in sea state, but also variations to the landscape (morphologic changes and urbanization of coastal cities). We utilize a numerical model of the Mississippi and Alabama coast to simulate the response of hurricane storm surge to changes in sea level, Land Use Land Cover (LULC), and land surface elevation for past (1960), present (2005), and future (2050) conditions. The results show that the storm surge response to SLR is dynamic and sensitive to changes in the landscape. We introduce a new modeling framework that includes modification of the landscape when producing storm surge models for future conditions.
Permanent link to this article: http://www.mattbilskie.com/dynamics-of-sea-level-rise-and-coastal-flooding-on-a-changing-landscape/
I added a new code to the ADCIRC utilities page, LULC2GRD.f90. The code creates the Manning’s n nodal attribute for an ADCIRC simulation based several Land Use Land Cover (LULC) datasets and cell averaging interpolation. Please e-mail to request a copy.
Permanent link to this article: http://www.mattbilskie.com/new-code-lulc2grd/