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

随着城市洪水变得越来越严重和频繁，社区越来越多地推广采用分布式绿色基础设施（GI）来管理雨水，如雨水桶、雨水花园和绿色屋顶。然而，分布式GI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CAREER项目的总体目标是使用一个框架更好地理解分散的可持续雨水管理，该框架结合了基于物联网（IoT）的绿色基础设施（GI）网络和计算模型，称为基于代理的耦合模型-雨水管理模型（ABM-SWMM）。基于物联网的GI网络将允许实时收集GI维护的现场测量、定时和频率等数据。耦合ABM-SWMM模型将量化在地理信息系统安装和维护、政策、经济和气候等各种情况下对潜在洪水缓解的影响。这两种方法的结合旨在识别和分析在多个社区尺度上接受和有效实施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。该项目建立在首席研究员先前在ABM方面的经验基础上，再加上基于过程的水文模型，与从业人员共同的愿景规划，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标志的障碍，为ABM提供行为数据，2）通过智能家居设备和基于物联网的地理标志网络评估信息共享对业主维护地理标志的努力的影响，3）使用耦合ABM-SWMM在各种情景下评估分散式GI实施的多尺度径流减少效果，以提供技术和政策见解，（4）形成学术-公共-私人的伙伴关系，创造一个合作学习的环境，让从中学到研究生院的学生参与大学、地方政府和私营部门之间的合作。人类-网络基础设施框架旨在推进首席研究员的长期职业目标，以了解不同空间尺度上人与自然之间的复杂互动，通过绿色基础设施促进城市环境可持续性，并为所有年龄段的公民创造一种学习可持续雨水管理的文化。该奖项反映了NSF的法定使命，并通过评估被认为值得支持使用基金会的知识价值和更广泛的影响审查标准。

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.