M. Babbar‐Sebens, Kenneth R. Cannady-Shultz, S. Mukhopadhyay
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引用次数: 0
摘要
一个地理区域的流域规划是一项艰巨的任务,主要是因为存在大量的利益相关者和决策者,他们内在的冲突和/或主观偏好往往导致规划决策的感知适应性的不确定性。如果采用景观决策对成功至关重要,那么决定在什么地点实施哪种流域战略需要采用参与式的设计和决策方法。分析参与式设计(APD)方法旨在使农民、环保人士、政府机构和其他利益相关者能够可视化景观,探索和设计在景观上实施某些管理实践的竞争性方案。由于这些方法提高了决策者对共存的物理和人类系统中的机会和约束的认识,因此假设它们可以用于生成可接受的决策,这些决策对利益相关者偏好的不确定性具有鲁棒性。本文描述了一种基于交互优化的APD方法,并在印第安纳州的一个研究流域(Eagle Creek watershed)进行了湿地设计试验。然后,该方法通过涉及多个虚拟利益相关者作为不同人类用户及其偏好的代理人来测试研究假设。结果表明,正如预期的那样,交互优化方法导致财务和环境客观标准的值较低(这是与用户多样化的主观个人标准相权衡的),但它也导致了相对较高的用户共识程度,表明利益相关者采用生成的解决方案的可能性很高。
Interactive Watershed Optimization in the Presence of Spatially-varying and Uncertain Stakeholder Preferences
Watershed planning over a geographic area is a difficult task primarily due to the presence of large number of stakeholders and decision makers whose intrinsic conflicting and/or subjective preferences often lead to uncertainty in perceived fitness of planning decisions. Deciding which watershed strategy should be implemented at what location requires a participatory approach to design and decision making, if adoption of landscape decisions is critical to success. Analytical participatory design (APD) approaches aim to enable farmers, environmentalists, government agencies, and other stakeholders to visualize the landscape, explore and design competitive scenarios of implementing certain management practices on the landscape. Since these approaches improve decision makers’ awareness of opportunities and constraints in the co-existing physical and human systems, it is hypothesized that they can be used to generate acceptable decisions that are robust to uncertainties in stakeholder preferences.An APD method based on Interactive optimization is described in this paper and tested for design of wetlands in a study watershed site (Eagle Creek Watershed) in the state of Indiana. The method is then used to test research hypothesis by involving multiple virtual stakeholders as surrogates to diverse human users and their preferences. The results indicate that, while, as expected, the interactive optimization approach results in lower values of the financial and environmental objective criteria (which are being traded off against users’ diverse subjective personal criteria), it also results in a relatively high degree of user consensus, indicating high likelihood of adoption of the generated solutions by the stakeholders.