将预测和性能模型集成到基于场景的弹性社区设计中。

Galen Newman, Youjung Kim, Karishma Joshi, Jiali Liu
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引用次数: 0

摘要

城市扩张会恶化气候变化条件,扩大危险区。气候变化导致的海平面上升使沿海人口更容易受到洪水风险的影响。与单一的综合规划相比,利用土地变化预测模型为基于情景的规划提供信息,有助于提高处理城市化不确定性(如城市增长和洪水风险)的能力。本研究使用土地转型模型来预测佛罗里达州坦帕市三种不同的城市增长情景,以确定当前的综合规划在适应城市增长以减少洪水风险和污染物负荷方面的有效性。为了实现这一目标,该研究根据每种情况制定了总体规划,然后使用长期水文影响分析低影响开发电子表格作为绩效模型评估其可能的影响。研究结果表明,坦帕目前的未来土地利用计划,虽然看起来比目前的发展模式更好,但与目前的条件相比,洪水、雨水径流和污染物排放的风险更高,但对未来的增长来说,这不仅仅是一种纯粹的弹性方法。
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Integrating Prediction and Performance Models into Scenario-based Resilient Community Design.

Urban expansion can worsen climate change conditions and enlarge hazard zones. Sea level rise due to climate change makes coastal populations more susceptible to flood risks. The use of land change prediction modelling to inform scenario-based planning has been shown to help increase capabilities when dealing with uncertainties in urbanization such as urban growth and flood risk, when compared to singular comprehensive plans. This research uses the Land Transformation model to predict three different urban growth scenarios for Tampa, FL to determine how effective the current comprehensive plan is in adapting urban growth to decreasing flood risk and pollutant load. To achieve this, the research develops master plans according to each scenario then assesses their probable impact using the Long-Term Hydrologic Impact Analysis Low Impact Development Spreadsheet as a performance model. Findings show that the current future land use plan for Tampa, while it appears to be better than current patterns of development, has higher flood exposure, stormwater runoff, and pollutant discharge that current conditions but more than a purely resilient approach to future growth.

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Integrating Prediction and Performance Models into Scenario-based Resilient Community Design.
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