TY - JOUR
T1 - Transportation Infrastructure Protection Planning against Sea Level Rise
T2 - Analysis Using Operational Landscape Units
AU - Suh, Jonghae
AU - Siwe, Alain Tcheukam
AU - Madanat, Samer Michel
N1 - Funding Information:
Partial support for this research was provided by the National Science Foundation under the CRISP program (Grant No. 1541181). We thank Sidney Feygin and Sudatta Mohanty from UC Berkeley for providing us with the data on the San Francisco Bay Area highway network that was used in the traffic simulation. We benefited from discussions with the other participants of the research team.
Publisher Copyright:
© 2019 American Society of Civil Engineers.
PY - 2019/9/1
Y1 - 2019/9/1
N2 - This paper addresses the problem of the optimal coastal protection area against sea level rise by utilizing fine-grained homogeneous segments, namely, operational landscape units (OLUs). The approach is demonstrated through a case study application focused on San Mateo County and Santa Clara County in the San Francisco Bay Area. We use the Coastal Storm Modelling System (CoSMoS) for detailed predictions of coastal flooding and inundation of bay-shore segments. The result of these hydrodynamic interactions leads to transportation network disruptions that, in turn, lead to changes in traffic flow patterns. Specifically, under a 0.5-m sea level rise scenario that is expected to occur in 2054, we forecast transportation network disruptions due to the inundation from the sea level rise and assess the impacts of protecting OLUs in the two counties of interest in terms of travel time delay reduction over the entire San Francisco Bay Area. We use agent-based traffic simulation (MATSim) with a daily activity list for 500,000 commuters. Finally, our results identify the most critical OLUs in San Mateo County and Santa Clara County. We conclude that the optimal coastal segment protection strategies depend strongly on the hydrodynamic interactions between neighboring counties and OLUs and on the traffic flow patterns after inundations. In forthcoming studies, long-term land use pattern change should be considered to establish protection strategies of coastal areas.
AB - This paper addresses the problem of the optimal coastal protection area against sea level rise by utilizing fine-grained homogeneous segments, namely, operational landscape units (OLUs). The approach is demonstrated through a case study application focused on San Mateo County and Santa Clara County in the San Francisco Bay Area. We use the Coastal Storm Modelling System (CoSMoS) for detailed predictions of coastal flooding and inundation of bay-shore segments. The result of these hydrodynamic interactions leads to transportation network disruptions that, in turn, lead to changes in traffic flow patterns. Specifically, under a 0.5-m sea level rise scenario that is expected to occur in 2054, we forecast transportation network disruptions due to the inundation from the sea level rise and assess the impacts of protecting OLUs in the two counties of interest in terms of travel time delay reduction over the entire San Francisco Bay Area. We use agent-based traffic simulation (MATSim) with a daily activity list for 500,000 commuters. Finally, our results identify the most critical OLUs in San Mateo County and Santa Clara County. We conclude that the optimal coastal segment protection strategies depend strongly on the hydrodynamic interactions between neighboring counties and OLUs and on the traffic flow patterns after inundations. In forthcoming studies, long-term land use pattern change should be considered to establish protection strategies of coastal areas.
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U2 - 10.1061/(ASCE)IS.1943-555X.0000506
DO - 10.1061/(ASCE)IS.1943-555X.0000506
M3 - Article
AN - SCOPUS:85068205381
SN - 1076-0342
VL - 25
JO - Journal of Infrastructure Systems
JF - Journal of Infrastructure Systems
IS - 3
M1 - 04019024
ER -