Abstract
The objective of this project is to develop and test two qualitative flood risk models for use in first responder and planning roles. The first, the Obstruction Detection Model (ODM), uses Light Detection and Ranging (LiDAR) derived Digital Elevation Models (DEMs) and a slope analysis to detect changes in the free surface of the water that might indicate the presence of a sub-surface obstruction. The product of the ODM can be used as a guide for field inspection, as well as an input scenario for the Risk Assessment Model (RAM). The RAM is the second model developed and serves to create an output product that displays the risk factor of each given parcel in order to help prioritize first responder efforts, as well as planning and mitigation efforts when used as a scenario generation tool. The RAM incorporates various vector data comprised of parcels, Monroe County Critical Infrastructure (CIKR), population, and assessed value in order to generate the Risk Factor. A third model, the Flood Extent Generator (FEG), uses an input scenario from the ODM to generate vector flood extents rapidly. These extents are used with the RAM to create a map that displays the Risk Factor in the flooded parcels.
The ODM appears to pick up riverine obstructions in the various river reaches tested within New York State. The FEG flood extents have 15% spatial agreement when constrained to Monroe County and 32% when constrained upriver of the Ford Street Bridge obstruction. The over-estimated flood extents lead to the RAM over-predicting populations and infrastructure at risk.
Model results, when compared to the more complex Hazus model, suggest that the simplified approach presented needs additional predictor variables or data pre-processing to improve accuracy of each model component.
Library of Congress Subject Headings
Flood forecasting--Data processing; Flood forecasting--New York (State)--Monroe County
Publication Date
1-20-2017
Document Type
Thesis
Student Type
Graduate
Degree Name
Environmental Science (MS)
Department, Program, or Center
Thomas H. Gosnell School of Life Sciences (COS)
Advisor
Karl F. Korfmacher
Advisor/Committee Member
Jan Van Aardt
Advisor/Committee Member
Justin Cole
Recommended Citation
Carlock, Brett Edmond, "Analytical Flood Risk Models for First Responder Use: Obstruction Detection and Risk Assessment" (2017). Thesis. Rochester Institute of Technology. Accessed from
https://repository.rit.edu/theses/9383
Campus
RIT – Main Campus
Plan Codes
ENVS-MS
Comments
Physical copy available from RIT's Wallace Library at GB1399.2 .C37 2017