Published electronically August 9, 2017
DOI:
10.1137/17S01580XM3 Challenge IntroductionAuthors: Deepak Moparthi, Albert Cao, Andrew Hwang, Joshua Yoon, and Haoyang Yu (Adlai E. Stevenson High School, Lincolnshire, IL)
Sponsor: Paul Kim (Adlai E. Stevenson High School, Lincolnshire, IL)
Summary: The National Park Service (NPS) is committed to preserving the beauty of America in order to provide everyone amazing interactions with nature. For over 100 years, the NPS has maintained these wonders of America; however, as it begins its second century of operation, one of the NPS's greatest concerns is the issue of climate change. Climate change greatly influences actions the NPS takes to protect parks and events such as flooding or other disasters can affect how many people visit the park.
In particular, rising sea levels are one of the imminent problems that the United States is faced with because of its impact on flooding, and it is necessary for the NPS to identify which National Parks are at risk. We were initially tasked with developing a model to classify 5 particular parks as having either high, medium, or low risk of sea level change. For each location, we created a probabilistic model of the sea level height in the next
t years. We determined whether a site had high, medium, or low risk levels based on the damage that we would expect to occur based on the change in sea level. We calculated the probability of risk associated with each region in 10, 20, 50, and even 100 years from now. Our findings show that Cape Hatteras and the Padre Island possess the greatest risk of all 5 national parks.
After classifying these parks as high, medium, or low risk based on sea level change alone, we sought to determine a set of additional criteria to build a model that would assign each site a "vulnerability score." The vulnerability score is based off of the likelihood and severity of climate related events occurring. We selected our criteria to be the Heat Index, which consisted of temperature and humidity, hurricane intensity and frequency, and the Air Quality Index. These criteria were then used to construct a model that generated the Vulnerability score by first assigning a subscore for each of the individual criteria and then taking a weighted average of these subscores. We found that Padre Island National Seashore and Acadia National Park are in critical condition, with Padre Island being in a worse condition than Acadia National Park. Furthermore, Olympic National Park and Cape Hatteras National Seashore are still safe but almost in a critical condition, and Kenai Fjords National Park is the safest of all five.
Finally, we created a model to determine how to allocate limited funds to the parks based off of factors including the adjusted vulnerability score we calculated in part two, as well as the number of visitors for each park. We accomplished this by first determining the expected number of visitors for the future based on data from previous years and the vulnerability score. We then used the results of our model to convert our predictions of the number of visitors and the vulnerability scores into indices that would calculate the overall Financial Utility index. We used the financial utility indices for each site to decide the optimal distribution of funds between the 5 parks. Based on our results, we found that the percentage of funds should be allocated as follows from most to least: Acadia National Park (30:48%), Olympic National Park (28:27%), Cape Hatteras (21:49%), Padre Island (10:94%), Kenai Fjords (8:82%).