Numerical modeling efforts in support of restoration and protection activities in coastal Louisiana have traditionally been conducted externally to any stakeholder engagement processes. This separation has resulted in planning- and project-level models built solely on technical observation and analysis of natural processes. Despite its scientific rigor, this process often fails to account for the knowledge, values, and experiences of local stakeholders that often contextualizes a modeled system. To bridge this gap, a team of natural and social scientists worked directly with local residents and resource users to develop a participatory modeling approach to collect and utilize local knowledge about the Breton Sound Estuary in southeast Louisiana, USA. Knowledge capture was facilitated through application of a local knowledge mapping methodology designed to catalog local understanding of current and historical conditions within the estuary and identify desired ecological and hydrologic end states. The results of the mapping endeavor informed modeling activities designed to assess the applicability of the identified restoration solutions. This effort was aimed at increasing stakeholder buy-in surrounding the utility of numerical models for planning and designing coastal protection and restoration projects and included an ancillary outcome aimed at elevating stakeholder empowerment regarding the design of nature-based restoration solutions and modeling scenarios. This intersection of traditional science and modeling activities with the collection and analysis of traditional ecological knowledge proved useful in elevating the confidence that community members had in modeled restoration outcomes.

中文翻译：

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通过参与式建模提高当地知识：路易斯安那州沿海地区社区积极参与恢复规划

传统上，在任何利益相关者参与过程的外部都进行了数值建模工作，以支持路易斯安那州沿海地区的恢复和保护活动。这种分离导致仅在技术观察和自然过程分析基础上建立计划和项目级别的模型。尽管具有严格的科学性，但此过程通常无法考虑经常与模型化系统相关联的本地利益相关者的知识，价值和经验。为了弥合这一差距，由自然和社会科学家组成的团队与当地居民和资源使用者直接合作，开发了一种参与式建模方法，以收集和利用有关美国东南部路易斯安那州布雷顿海峡河口的当地知识。通过应用本地知识映射方法促进知识获取，该方法旨在对河口内当前和历史条件的本地理解进行分类，并确定所需的生态和水文最终状态。映射工作的结果将有助于进行建模活动，以评估已确定的修复方案的适用性。这项工作旨在增加利益相关者对数字模型在规划和设计沿海保护与恢复项目中的效用的认可，并包括一项旨在提高利益相关者对基于自然的恢复解决方案和建模方案的设计能力的辅助成果。