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Urban stormwater managers have traditionally used pipes, ditches, ponds and other gray infrastructure elements to quickly divert runoff away from its main sources—buildings and roadways. In contrast, proponents of green infrastructure attempt to manage stormwater near its origin, utilizing natural drainage pathways and best management practices (BMPs) to reduce runoff and increase infiltration. In doing so, stormwater is retained where it is needed to support urban vegetation. This vegetation, in turn, helps reduce future runoff, while producing a whole range of environmental, economic, and social/human health-related benefits. Despite the many advantages of green infrastructure, retrofitting the infrastructure of a city is a costly process that requires careful planning. The transition from gray to green infrastructure requires communication between managers from different disciplines and a willingness to stray from management strategies that have defined stormwater management for centuries. The Gray to Green (G2G) green infrastructure planning tool is designed to facilitate these conversations—showing both technical and non-technical users how green infrastructure BMPs can work within the urban forest to manage stormwater on existing or proposed development sites. This paper details the data sources and research at the core of G2G—documenting all methods, equations, and assumptions used in its creation to provide users with a fully-transparent and peer-reviewed planning tool. The paper concludes with descriptions and user insights from two case studies from Tampa, Florida (United States) and Milwaukee, Wisconsin, (United States). [ABSTRACT FROM AUTHOR]

[Display omitted] • The trends of surface runoff and flood area changes were different. • Rainfall change is the dominant driver compared with land use change. • There are coupled effects from rainfall and land use changes on both surface runoff and flood area. • The easily flooded areas would experience negative coupled effects under future rainfall and land use conditions. • The areas with inadequate drainage and low elevation variation would be of high probability to suffer flooding issues. Future rainfall and land use are two important factors for flood management since they both directly and indirectly affect the functionality and performance of urban stormwater drainage infrastructures. Although some studies have already examined the coupled effects of future rainfall and land use conditions, they have not concluded how such effects on both surface runoff and flood areas would change with regional surface elevation variation and infrastructure conditions. This paper analyzed the coupled effects of future rainfall and land use on urban drainage systems in terms of surface runoff quantity and flood area changes using EPA SWMM. Future downscaled and bias-corrected precipitation projections for 2040–2060 and 2080–2099 from "Downscaled CMIP3 and CMIP5 Climate and Hydrology Projections" Archive and future land use for 2050 s and 2090 s from EPA ICLUS project were used for the City of Tampa in Florida (USA). It was shown that potential runoff volume and flood area changes ranged from −40% to 160%, and −40% to 400% due to rainfall change, while potential changes induced by land use change ranged from 0% to 3.5%, and 0% to 18% respectively. Additionally, this study examined the coupled effects of future rainfall and land use changes on flood area variations, considering the capacity of drainage infrastructure and elevation variation of study site. Results showed that flood area variations are not solely influenced by runoff quantity changes due to the two external drivers, but also by other factors. Specifically, in low-relief areas with inadequate drainage infrastructure and less elevation variation, these two drivers have no additive effects on the percentage of flood area changes. In contrast, in areas with adequate drainage infrastructure and greater surface elevation variation, there are additive effects from rainfall and land use changes on flood area expansions. These findings have important implications for stakeholders involved in city planning and flooding control, particularly for urban areas facing future precipitation and urbanization challenges. [ABSTRACT FROM AUTHOR]

• The spatial and temporal evolution of traffic flow reconstructed for all highways in Florida for hurricane Irma evacuation. • A simplified framework is built to reconstruct evacuation traffic flow based on limited highway camera data. • The data reconstructed could improve survey-based evacuation demand simulators. Hurricane evacuation has long been a difficult problem perplexing local government. Hurricane Irma in 2017 created the most extensive scale of evacuation in Florida's history, involving about 6.5 million people in a mandatory evacuation order and an estimated 4 million evacuation vehicles. Traffic jams emerged in mid-Florida and rapidly spread to involve the entire state. To understand the hurricane evacuation process, the spatial and temporal evolution of the traffic flow is a critical piece of information, but it is usually not fully observed. Based on game theory, this paper employs the available traffic observation of main highways to reconstruct the traffic flow on all highways in Florida during Irma. The reconstructed traffic conditions compare well with those simulated by dynamic models while the reconstruction model is computationally much cheaper to use. Validation with smartphone data further confirms that the reconstruction model captures the traffic conditions for real evacuation processes. The reconstructed data show that the evacuation rates for 5 representative cities -- Key West, Miami, Tampa, Orlando, and Jacksonville-- in Florida were about 90.1%, 38.7%, 52.6%, 22.1%, and 7%, respectively. The peak evacuation traffic flows from Tampa and Miami arrived in the Orlando region at almost the same time, triggering the catastrophic congestion through the entire state. Also, the evacuation for Hurricane Irma was greater than that predicted by an evacuation demand model developed based on previous event and survey data. The detailed evacuation traffic flow reanalysis accomplished in this article lays a foundation for studying evacuation demand as well as developing evacuation management policies. [ABSTRACT FROM AUTHOR]