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Flooding during extreme weather events damages critical infrastructure, property, and threatens lives. Hurricane María devastated Puerto Rico (PR) on 20 September 2017. Sixty-four deaths were directly attributable to the flooding. This paper describes the development of a hydrologic model using the Gridded Surface Subsurface Hydrologic Analysis (GSSHA), capable of simulating flood depth and extent for the Añasco coastal flood plain in Western PR. The purpose of the study was to develop a numerical model to simulate flooding from extreme weather events and to evaluate the impacts on critical infrastructure and communities; Hurricane María is used as a case study. GSSHA was calibrated for Irma, a Category 3 hurricane, which struck the northeastern corner of the island on 7 September 2017, two weeks before Hurricane María. The upper Añasco watershed was calibrated using United States Geological Survey (USGS) stream discharge data. The model was validated using a storm of similar magnitude on 11–13 December 2007. Owing to the damage sustained by PR’s WSR-88D weather radar during Hurricane María, rainfall was estimated in this study using the Weather Research Forecast (WRF) model. Flooding in the coastal floodplain during Hurricane María was simulated using three methods: (1) Use of observed discharge hydrograph from the upper watershed as an inflow boundary condition for the coastal floodplain area, along with the WRF rainfall in the coastal flood plain; (2) Use of WRF rainfall to simulate runoff in the upper watershed and coastal flood plain; and (3) Similar to approach (2), except the use of bias-corrected WRF rainfall. Flooding results were compared with forty-two values of flood depth obtained during face-to-face interviews with residents of the affected communities. Impacts on critical infrastructure (water, electric, and public schools) were evaluated, assuming any structure exposed to 20 cm or more of flooding would sustain damage. Calibration equations were also used to improve flood depth estimates. Our model included the influence of storm surge, which we found to have a minimal effect on flood depths within the study area. Water infrastructure was more severely impacted by flooding than electrical infrastructure. From these findings, we conclude that the model developed in this study can be used with sufficient accuracy to identify infrastructure affected by future flooding events. 

Abstract Air conditioning (AC) demand has recently grown to about 10% of total electricity globally, and the International Energy Agency (IEA) predicts that the cooling requirement for buildings globally increases by three-fold by 2050 without additional policy interventions. The impacts of these increases for energy demand for human comfort are more pronounced in tropical coastal areas due to the high temperatures and humidity and their limited energy resources. One of those regions is the Caribbean, where building energy demands often exceed 50% of the total electricity, and this demand is projected to increase due to a warming climate. The interconnection between the built environment and the local environment introduces the challenge to find new approaches to explore future energy demand changes and the role of mitigation measures to curb the increasing demands for vulnerable tropical coastal cities due to climate change. This study presents mid-of-century and end-of-century cooling demand projections along with demand alleviation measures for the San Juan Metropolitan Area in the Caribbean Island of Puerto Rico using a high-resolution configuration of the Weather Research and Forecasting (WRF) model coupled with Building Energy Model (BEM) forced by bias-corrected Community Earth Systems Model (CESM1) global simulations. The World Urban Database Access Portal Tool (WUDAPT) Land Class Zones (LCZs) bridge the gap required by BEM for their morphology and urban parameters. MODIS land covers land use is depicted for all-natural classes. The baseline historical period of 2008–2012 is compared with climate and energy projections in addition to energy mitigation options. Energy mitigation options explored include the integration of solar power in buildings, the use of white roofs, and high-efficiency heating, ventilation, and air conditioning (HVAC) systems. The impact of climate change is simulated to increase minimum temperatures at the same rate as maximum temperatures. However, the maximum temperatures are projected to rise by 1–1.5 °C and 2 °C for mid- and end-of-century, respectively, increasing peak AC demand by 12.5% and 25%, correspondingly. However, the explored mitigation options surpass both increases in temperature and AC demand. The AC demand reduction potential with energy mitigation options for 2050 and 2100 decreases the need by 13% and 1.5% with the historical periods. Overall, the demand reduction potential varies with LCZs showing a high reduction potential for sparsely built (32%), and low for compact low rise (21%) for the mid-of-century period compared with the same period without mitigation options. 

Abstract The discourse on resilience, currently at the forefront of research and implementation in a wide variety of fields, is confusing because of its multi-disciplinary/spatial/temporal nature. Resilience analysis is a discipline that allows the assessment and enhancement of the coping and recovery behaviors of systems when subjected to short-lived high-impact external shocks leading to partial or complete failure. This paper, meant for pedagogical teaching and research formulation, starts by providing an overview of different aspects of resilience in general and then focuses on communities and regions that are complex adaptive systems (CAS) involving multiple engineered infrastructures providing essential services to local inhabitants and adapted to available natural resources and social requirements. Next, for objective analysis and assessment, it is proposed that resilience be characterized by four different quantifiable sub-attributes. This paper then describes the standard technocentric manner in which different temporal phases during and in the aftermath of disasters are generally visualized and analyzed, and discusses how these relate to reliability and risk analyses. Subsequently, two prevalent types of frameworks are described and representative literature reviewed: (i) those that aim at improving general resilience via soft methods such as subjective means (interviews, narratives) and census data, and (ii) those that are meant to enhance specific resilience under certain threat scenarios using hard/objective methods such as data-driven analysis and performance-predictive modeling methods, akin to resource allocation problems in operations research. Finally, the need for research into an integrated framework is urged; one that could potentially combine the strengths of both approaches. 

Abstract As a consequence of the warm and humid climate of tropical coastal regions, there is high energy demand year-round due to air conditioning to maintain indoor comfort levels. Past and current practices are focused on mitigating peak cooling demands by improving heat balances by using efficient building envelope technologies, passive systems, and demand side management strategies. In this study, we explore city-scale solar photovoltaic (PV) planning integrating information on climate, building parameters and energy models, and electrical system performance, with added benefits for the tropical coastal city of San Juan, Puerto Rico. Energy balance on normal roof, flush-mounted PV roof, and tilted PV roof are used to determine PV power generation, air, and roof surface temperatures. To scale up the application to the whole city, we use the urbanized version of the Weather Research and Forecast (WRF) model with the building effect parameterization (BEP) and the building energy model (BEM). The city topology is represented by the World Urban Database Access Portal Tool (WUDAPT), local climate zones (LCZs) for urban landscapes. The modeled peak roof temperature is maximum for normal roof conditions and minimum when inclined PV is installed on a roof. These trends are followed by the building air conditioning (AC) demand from urbanized WRF, maximum for normal roof and minimum for inclined roof-mounted PV. The net result is a reduced daytime Urban Heat Island (UHI) for horizontal and inclined PV roof and increased nighttime UHI for the horizontal PV roof as compared with the normal roof. The ratio between coincident AC demand and PV production for the entire metropolitan region is further analyzed reaching 20% for compact low rise and open low rise buildings due to adequate roof area but reaches almost 100% for compact high rise and compact midrise buildings class, respectively.