Role of Wetlands in Reducing Structural Loss is Highly Dependent on Characteristics of Storms and Local Wetland and Structure Conditions

Journal Article Resource
March 2021

Abstract

Coastal communities in New Jersey (NJ), New York (NY), and Connecticut (CT) sustained huge structural loss during Sandy in 2012. We present a comprehensive science-based study to assess the role of coastal wetlands in buffering surge and wave in the tri-state by considering Sandy, a hypothetical Black Swan (BS) storm, and the 1% annual chance flood and wave event. Model simulations were conducted with and without existing coastal wetlands, using a dynamically coupled surge-wave model with two types of coastal wetlands. Simulated surge and wave for Sandy were verified with data at numerous stations. Structural loss estimated using real property data and latest damage functions agreed well with loss payout data. Results show that, on zip-code scale, the relative structural loss varies significantly with the percent wetland cover, the at-risk structural value, and the average wave crest height. Reduction in structural loss by coastal wetlands was low in Sandy, modest in the BS storm, and significant in the 1% annual chance flood and wave event. NJ wetlands helped to avoid 8%, 26%, 52% loss during Sandy, BS storm, and 1% event, respectively. This regression model can be used for wetland restoration planning to further reduce structural loss in coastal communities.

About this article

This article, published in the open access jounal Scientific Reports in 2021, describes work done as part of a 2016-2020 collaborative research project conducted at Hudson River Reserve in New York. The regional modeling explained in this article informed an analysis of the buffering services provided by a single wetland, Piermont Marsh.

Citation: 

Sheng, Y.P., Rivera-Nieves, A.A., Zou, R., Paramygin, V.A., 2021. Role of wetlands in reducing structural loss is highly dependent on characteristics of storms and local wetland and structure conditions. Scientific Reports 11, 5237. https://doi.org/10.1038/s41598-021-84701-z