Journal of digital landscape architecture : JoDLA最新文献

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3D Morphodynamic Visualizations of Storm Impacts for Decision Support. 用于决策支持的风暴影响的三维形态动力学可视化。

Journal of digital landscape architecture : JoDLA

Pub Date : 2023-05-01 DOI: 10.14627/537740058

Peter Stempel, Ellie Nasr-Azadani, Annette Grilli, Stephan Grilli, Elin Shuh, Felix Groetsch, Isaac Ginis, Deborah Crowley, J P Walsh, Isabel Whaling, Christopher Damon, Roland Duhaime, Pam Rubinoff, Catherine Schmitt

3D flood visualizations are commonly used by coastal managers and other experts to engage the public regarding storm impacts, and to support management decisions. 3D flood visualizations do not, however, capture physical changes to the landscape, such as erosion, that result from storms and do significant damage to human habitations and change ecological systems. We address this gap by presenting novel 3D morphodynamic visualizations that depict physical changes to the coastal morphology wrought by modelled storms. We propose these visualizations may be more effective than flood visualizations as decision support tools in situations where shoreline change is a factor. We describe the process of creating the visualizations for storm, sea level, and mitigation scenarios and make observations of their possibilities and limitations. The visualizations plainly show profoundly different outcomes than flood visualizations for the same storm. These visualizations may be extremely useful in the sedimentary contexts considered. However, the lack of clear conventions and complexity of creating these visualizations means that more experimentation is required before such visualizations can be considered for wide application.

3D洪水可视化通常被沿海管理者和其他专家用来让公众了解风暴的影响，并支持管理决策。然而，3D洪水可视化并不能捕捉到景观的物理变化，例如风暴造成的侵蚀，这些变化对人类栖息地造成了重大破坏，并改变了生态系统。我们通过呈现新颖的3D形态动力学可视化来解决这一差距，该可视化描绘了模拟风暴造成的海岸形态的物理变化。我们认为，在海岸线变化是一个因素的情况下，这些可视化可能比洪水可视化作为决策支持工具更有效。我们描述了创建风暴、海平面和缓解情景可视化的过程，并观察了它们的可能性和局限性。可视化结果显然与同一场风暴的洪水可视化结果截然不同。这些可视化在所考虑的沉积环境中可能非常有用。然而，缺乏清晰的约定和创建这些可视化的复杂性意味着，在考虑将这些可视化广泛应用之前，需要进行更多的实验。

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引用次数: 0

Integrating Prediction and Performance Models into Scenario-based Resilient Community Design. 将预测和性能模型集成到基于场景的弹性社区设计中。

Journal of digital landscape architecture : JoDLA

Pub Date : 2020-01-01

Galen Newman, Youjung Kim, Karishma Joshi, Jiali Liu

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.

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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引用次数: 0

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