CAREER:Understanding sustainable stormwater management via an Internet of Things-based green infrastructure network and a coupled Agent-Based Modeling approach

随着城市洪灾变得更加严重和频繁，社区越来越多地推动采用分布式绿色基础设施(GI)来管理雨水，如雨桶、雨水花园和绿色屋顶。然而，分布式地理信息系统对整个雨水管理系统的影响或影响这些影响的因素尚不清楚。该职业项目的总体目标是使用一个结合了基于物联网(IoT)的绿色基础设施(GI)网络和称为基于主体的耦合模型-雨水管理模型(ABM-SWMM)的计算模型的框架，更好地了解分散式可持续雨水管理。基于物联网的GI网络将允许实时收集GI维护的现场测量、时间和频率等数据。ABM-SWMM耦合模型将量化在GI安装和维护、政策、经济和气候等不同情景下对潜在洪水缓解的影响。这两种方法的结合旨在能够识别和分析在多个社区范围内接受和有效实施GI的技术、社会、经济和政策障碍，并探索克服这些障碍的潜在解决方案。该项目建立在首席调查员以前在ABM方面的经验基础上，结合基于过程的水文模型、与从业者的共同愿景规划以及利益相关者参与的在线平台。该项目围绕四个目标组织：1)通过社会调查分析当地业主接受或拒绝地理信息系统的障碍，为地理信息管理提供行为数据；2)评估通过智能家居设备和基于物联网的地理信息网络共享信息对业主维护地理信息系统勤奋程度的影响；3)使用ABM-SWMM耦合提供技术和政策见解，评估在不同场景下分散地理信息系统实施的减少径流效果；以及4)形成学术-公共-私人合作伙伴关系，以创建一个协作学习环境，允许从中学到研究生的学生参与大学、地方政府、和私营部门。人-网络基础设施框架旨在推进首席研究员的长期职业目标，即在不同的空间尺度上了解人与自然之间的复杂相互作用，通过绿色基础设施促进城市环境的可持续发展，并为所有年龄段的公民创造一种关于可持续雨水管理的学习文化。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

As urban flooding becomes more severe and frequent, communities are increasingly promoting the adoption of distributed green infrastructure (GI) to manage stormwater, such as rain barrels, rain gardens, and green roofs. However, the effects of distributed GI on the entire stormwater management system, or the factors that influence those effects, are unclear. The overarching goal of this CAREER project is to better understand decentralized sustainable stormwater management using a framework that combines an Internet of Things (IoT)-based green infrastructure (GI) network and a computational model, called the coupled agent-based model-StormWater Management Model (ABM-SWMM). The IoT-based GI network will allow data such as field measurements, timing, and frequency of GI maintenance to be collected in real-time. The coupled ABM-SWMM model will quantify effects on potential flood mitigation under various scenarios of GI installation and maintenance, policy, economic, and climate. The combination of these two approaches is designed to make it possible to identify and analyze technical, social, economic and policy barriers to acceptance and effective implementation of GI at multiple community scales, and to explore potential solutions to overcome them.This project builds on the principal investigator's previous experience in ABM coupled with process-based hydrological models, shared vision planning with practitioners, and online platforms for stakeholder engagement. The project is organized around four objectives: 1) Analyze barriers that underlie local property owners' acceptance or rejection of GI via a social survey, providing behavioral data for the ABM, 2) Assess the effect of information sharing, via smart home devices and the IoT-based GI network, on property owners' diligence in maintaining their GIs, 3) Evaluate the runoff reduction effectiveness of decentralized GI implementation at multiple scales under various scenarios using coupled ABM-SWMM to provide technical and policy insights, and 4) Form an academic-public-private partnership to create a collaborative learning environment that allows students from middle school to graduate school to participate in collaborations among the university, local government, and private sectors. The human-cyberinfrastructure framework is targeted to advance the principal investigator's long-term career goal to understand complex interactions between humans and nature at different spatial scales, advance urban environmental sustainability through green infrastructure, and create a culture of learning for citizens of all ages about sustainable stormwater management.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.