4.6 Article

Near real-time prediction of wind-induced tree damage at a city scale: Simulation framework and case study for Tsinghua University campus

Journal

Publisher

ELSEVIER
DOI: 10.1016/j.ijdrr.2020.102003

Keywords

Wind-induced tree damage; Near real-time prediction; Scenario bank; Urban disaster preparedness

Funding

  1. National Natural Science Foundation of China [U1709212]
  2. Tencent Foundation

Ask authors/readers for more resources

This study proposes a high-efficiency simulation framework by coupling computational fluid dynamics and mechanistic tree damage modeling to realize the near real-time prediction of wind damage to urban trees. The methods used in each step are validated, applied in a case study at Tsinghua University campus in Beijing, and a user-friendly program is developed for evaluating wind-induced damage risk. Hypothetical strong wind events are used to exemplify the practicality of the proposed framework.
During typhoon events, wind damage to trees in urban areas may have various adverse impacts on urban functions and cause direct and indirect economic losses. To realize the near real-time prediction of wind damage to urban trees, this study proposes a high-efficiency simulation framework by coupling computational fluid dynamics and mechanistic tree damage modeling. The proposed framework involves four key steps: modeling effects of trees on urban airflow, constructing a scenario bank, near real-time predicting urban airflow, and simulating wind-induced tree damage. The accuracy and efficiency of the methods used in each step are validated. A real-world, complex urban area in Beijing, China, namely the Tsinghua University campus, is used as a case study to showcase the workflow. A user-friendly program, THU-NEWDRT, is developed to help managers efficiently evaluate the wind-induced damage risk of campus trees. Finally, a set of hypothetical strong wind events are used to exemplify the practicality of the proposed framework.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available