Date of Award

8-2022

Document Type

Thesis

Degree Name

Master of Science (MS)

College/School

College of Science and Mathematics

Department/Program

Earth and Environmental Studies

Thesis Sponsor/Dissertation Chair/Project Chair

Josh Galster

Committee Member

Melissa Hansen

Committee Member

Clement Alo

Abstract

The purpose of this research is to quantify the flood risks of rivers in various locations in New Jersey and how they have changed over time. This is important because the change is likely to continue over time as climate change continues. ArcGIS, HEC-SSP, and online sources such as Trulia (www.trulia.com) were used to understand where flooding is most likely to occur, which streets, and how many homes will be affected and estimate the cost of damages from a potential 100-year flood. I compiled information such as annual peak river discharge from the USGS river gages on the Delaware River in Trenton, Raritan River in Manville, Ramapo River in Pompton Lakes, Hackensack River in New Milford, and the Musconetcong River in Lake Hopatcong. I analyzed either a 1/9 or 1/3 arc-second Digital Elevation Model (DEM) to map the floodplains. These DEMs allowed for the area covered by floods to be mapped. HEC SSP was used to calculate the discharges for various flood frequencies over three time periods: 1959-1988, 1989-2018, and then the overall time period of 1959-2018. I compared the differences in flood magnitudes to see if there was a change in flooding over time.

Based on the information from HEC-SSP, I mapped the 1% annual exceedance chance floodplain using ArcGIS for the new 30-year data and the total 60-year data. I was then able to compare where the flood water extended against a map from the real estate website, Trulia, to see how many homes would be flooded during a 1% flood and the total cost of potential damage. Due to the influence of climate change and a rise of impervious surfaces over the past 30 years, the recent 30-year data showed a total of 1,369 homes are at risk of flooding with potential damages of $456,482,000. This number is almost double that of the 60-year data which is at 820 homes totaling $273,087,000 in damage.

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