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How does household exposure to a natural disaster affect higher education investments? Using variation in flooding from Hurricane Harvey (2017), we find that college-aged adults from flooded blocks in Houston are 7% less likely than counterparts to have student loans after Harvey, with larger effects in areas with more potential first-generation students. We find a similar relative decline in enrollment at more exposed Texas universities and colleges and a shift toward majors with higher expected earnings. Our results highlight a decrease in the quantity but an increase in the intensity of investments in human capital after the storm. Authors have furnished an Internet Appendix , which is available on the Oxford University Press Web site next to the link to the final published paper online. [ABSTRACT FROM AUTHOR]

In 2022, Houston, TX became a nexus for field campaigns aiming to further our understanding of the feedbacks between convective clouds, aerosols and atmospheric boundary layer (ABL) properties. Houston's proximity to the Gulf of Mexico and Galveston Bay motivated the collection of spatially distributed observations to disentangle coastal and urban processes. This paper presents a value-added ABL dataset derived from observations collected by eight research teams over 46 days between 2 June - 18 September 2022. The dataset spans 14 sites distributed within a ~80-km radius around Houston. Measurements from three types of instruments are analyzed to objectively provide estimates of nine ABL parameters, both thermodynamic (potential temperature, and relative humidity profiles and thermodynamic ABL depth) and dynamic (horizontal wind speed and direction, mean vertical velocity, updraft and downdraft speed profiles, and dynamical ABL depth). Contextual information about cloud occurrence is also provided. The dataset is prepared on a uniform time-height grid of 1 h and 30 m resolution to facilitate its use as a benchmark for forthcoming numerical simulations and the fundamental study of atmospheric processes. [ABSTRACT FROM AUTHOR]

Day-labor worker centers are labor market intermediaries that target their interventions to underregulated segments of residential construction and allied industries. As sites of rulemaking in the informal economy, worker centers raise standards and enforce worker protections in sectors that lie beyond the reach of government enforcement. In addition to strengthening wage floors, worker centers are now acting as "disaster recovery hubs" that can help local communities following natural disasters. As the economy was shuttered by the COVID-19 pandemic, worker centers pivoted to provide emergency assistance to unemployed workers. This paper assesses these two emerging areas of worker center activity through a survey of disaster-recovery workers in Houston in the aftermath of Hurricane Harvey and a national survey of worker centers that administered emergency assistance to immigrant workers during the COVID-19 pandemic. These case studies reveal promising new interventions that could lead to more inclusive forms of workforce development. [ABSTRACT FROM AUTHOR]

In view that cities will continue to house the majority of the world's population at an increasing rate in the face of climate change, this paper studies urban resilience by examining the response history of the mean-square displacement of the citizens of large cities prior to and upon historic natural hazards strike. The recorded mean-square displacements of large numbers of cellphone users from the cities of Houston, Miami, and Jacksonville when struck by hurricanes Harvey 2017, Irma 2017, and Dorian 2019 together with the recorded mean-square displacements of the citizens of Dallas and Houston when experiencing the 2021 North American winter storm suggest that large cities of average population density when struck by natural hazards are inherently resilient. The recorded mean-square displacements presented in this study also validate a mechanical model for cities, previously developed by the authors, that is rooted in Langevin dynamics and predicts that following a natural hazard, large cities revert immediately to their initial steady-state behavior and resume their normal, preevent activities. The inherent ability of large American cities to revert to their normal, preevent, steady-state response as evidenced in this study by the recorded mean-square displacement of their citizens needs to be further explored for other cities around the world with different resources, and socioeconomic structures. [ABSTRACT FROM AUTHOR]

Addicks and Barker reservoirs were built in the 1940s to protect downtown Houston from flooding and have generally worked very well until 2017 when Hurricane Harvey devastated much of Houston and surroundings with up to 40 inches (102 cm) of rainfall causing flooding of 154,000 homes in over 22 watersheds in Houston/Harris County alone. However, the story of how Addicks and Barker flooded upstream residential areas from a hydrologic standpoint is a harsh lesson in flood infrastructure policy and funding. This failure to protect both downstream properties in Buffalo Bayou and upstream areas behind the dams ended up with tens of thousands of flooded homes and properties, with many having flood waters for over 10 days. This paper explores the main causes for the flooding and addresses the hydrologic issues upstream in both reservoirs. The main causes of flooding were not just related to a massive rainfall event, but also explosive urban expansion of land use upstream of reservoirs, altered and updated reservoir design issues, and lack of governmental action in the years leading up to the disaster. Potential long‐term solutions to the flooding and design problems are addressed in this article as well. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to examine the community recovery efforts undertaken by Houston, Texas, sport organizations following Hurricane Harvey in 2017. Design/methodology/approach: Forty-eight media articles, 138 social media posts from Houston athletes and five semi-structured interviews with Houston sport organization executives underwent a content analysis to categorize responses of disaster relief activities. All eleven categories were identified. Three themes emerged from additional analysis: organizations serving as communication hubs, earned trust and internal organizational support. Benchmark examples in key categories are also discussed. Findings: This paper provided focused analysis of the reactions of several Houston area sport organizations during the immediate disaster recovery period. Organizations participated in both tangible and emotional recovery efforts. The long-term impacts of these efforts will require additional investigation. The findings of this case study are specific to the relief efforts in Houston, Texas, following Hurricane Harvey in 2017 and may not be generalizable beyond this scope. Practical implications: Sport organizations and community leaders can better prepare for future disaster responses by gaining insight into the roles and procedures enacted by the Houston teams following the Hurricane in 2017. Originality/value: This study provides a detailed examination of the responses of several Houston sport organizations following Hurricane Harvey, including perspectives from executives inside of the organizations. Utilizing social anchor theory, this paper expands our understanding of the impacts sport organizations may produce in their roles as social anchors during disaster relief and recovery. [ABSTRACT FROM AUTHOR]

Increasing resilience to flooding is a complex process that requires horizontal and vertical coordination between institutions in policy making and implementation. This paper explores the effect of institutional coordination on managing flood risk in two cities plagued by flooding. Our results show that efforts on building urban flood resilience can be undermined by lack of proper coordination between urban development, water management and land use planning. We find that this complexity is magnified by the emergence of the concept of resilience as an urban development goal that is increasingly pursued by various authorities, but that is inherently contested in practice. [ABSTRACT FROM AUTHOR]

Disasters are increasing in frequency and intensity. Much of the current disaster literature adopts a social vulnerability perspective, which considers how political, social, and economic factors influence pre-disaster preparation and post-disaster recovery. Even with this focus, however, there remains a dearth of literature on immigrant populations and their long-term recovery trajectories. This paper applies a racial formation framework to a disaster context. I seek to show how service providers from community-based organizations (CBOs) navigate racialized anti-immigrant disaster recovery policies to help the Mexican immigrant community in Houston, Texas with their long-term housing recovery after Hurricane Harvey. I conducted semi-structured interviews and ethnographic observations with service providers from CBOs located in Houston that serve this population with post-disaster housing. I argue that the disaster recovery system is comprised of racial structures and racialized anti-immigrant policies, passively and actively limiting the access to resources for the Mexican immigrant community. I found that to challenge the racial structures and racialized anti-immigrant policies of the disaster recovery system, service providers assist the community through direct assistance to Mexican immigrants excluded from other programs; collaboration with other organizations to combine limited resources; helping the community navigate racialized anti-immigrant bureaucracy; and building trust by embedding themselves in the victimized community. However, findings also show that these organizations face significant challenges in conducting their work. This research brings a much-needed theoretical expansion of race and racialization theories to disaster research. [ABSTRACT FROM AUTHOR]

This paper examines the vulnerability of road networks to two types of disruptions by modeling the percolation dynamics in road networks under different disruption scenarios. The objective of this paper is threefold: (1) to examine if the theoretical network robustness measure proposed in the literature is applicable for measuring the integrity of road networks during disruptions; (2) to unveil the impacts of network size on the overall vulnerability of road networks; and (3) to compare the performance profile of road networks to random and nonrandom types of disruptions. To that end, this study first modeled the road system in a community as a planar graph. Then, the percolation dynamic in the road network during the flood is captured by assigning different removal probabilities to nodes in the road network according to Bayes' rule that take floodplain types, node-elevation, and street-grade as inputs. In the end, an overall road network robustness measure and its temporal changes were obtained and for random and nonrandom scenarios, using road networks with different sizes. The results were compared in order to characterize the vulnerability of road networks under different scenarios. The proposed method was applied to the road network in central Houston during Hurricane Harvey. The results show that: (1) the theoretical network robustness measure is applicable to assess the road network robustness; (2) compared to the random percolation model, the probability (Bayes' rule) based percolation could lead to a greater decrease in the network robustness; and (3) the percolation profiles of the road networks with different sizes are not significantly different. The findings of this study could not only inform resilience enhancing decisions by the stakeholders but also could serve as a foundation for future vulnerability related research. [ABSTRACT FROM AUTHOR]

Over the past years, the frequency and scope of disasters affecting the United States have significantly increased. Government agencies have made efforts in improving the nation's disaster response framework to minimize fatalities and economic loss due to disasters. Disaster response has evolved with the emergency management agencies incorporating systematic changes in their organization and emergency response functions to accommodate lessons learned from past disaster events. Technological advancements in disaster response have also improved the agencies' ability to prepare for and respond to natural hazards. The transportation and logistics sector has a primary role in emergency response during and after disasters. In this light, this paper seeks to identify how effective policy changes and new technology have aided the transportation and logistics sector in emergency response and identify gaps in current practices for further improvement. Specifically, this study compares and contrasts the transportation and logistical support to emergency relief efforts during and after two major Hurricane events in the U.S., namely Hurricane Katrina (which affected New Orleans in 2005) and Hurricane Harvey (which affected Houston in 2017). This comparison intends to outline the major steps taken by the government and the private entities in the transportation and logistics sector to facilitate emergency response and the issues faced during the process. Finally, the paper summarizes the lessons learned from both the Hurricane events and provides recommendations for further improvements in transportation and logistical support to disaster response. [ABSTRACT FROM AUTHOR]

Viruses are the dominant biological entity in the ocean, play a vital role in biogeochemical cycles, and provide their hosts with novel metabolic capabilities through auxiliary metabolic genes (AMGs). Hurricane Harvey was a category 4 hurricane that made landfall on the Texas coast in 2017 and lashed the Houston area with 1.4–1.7 × 1010 m3 of rainfall. In this paper, we aim to characterize how the changes in abiotic conditions brought by Hurricane Harvey altered the viral assemblages of Galveston Bay at the taxonomic level and determine how viral ecosystem functions were altered. Metagenomes of the viruses and their hosts were sequenced from a transect in Galveston Bay over the five weeks following the storm. Our results show that the viral assemblages of Galveston Bay dramatically changed following Hurricane Harvey's landfall. Of the abiotic parameters measured, salinity had the strongest effect on shaping the viral assemblages. In the five weeks following Hurricane Harvey, there was a steady increase of metabolic genes and putative viral infections. Our study provides the first in-depth look at how marine viral assemblages respond and recover from extreme rainfall events, which models predict will become more frequent and intense with climate change. [ABSTRACT FROM AUTHOR]

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As demonstrated by recent tropical cyclone events, including U.S. Hurricanes Harvey, Irma, and Maria (2017), and Florence (2018), the destructive potential of flooding driven by wind, precipitation, and coastal surge coupled with growing exposure of people and property along coastlines is leading to unprecedented damage from coastal storms. In this paper, we demonstrate the ability of the recently developed Super-Fast INundation of CoastS (SFINCS) model to delineate the depth and extent of flooding during Hurricane Harvey in Houston, Texas. The model was validated against water level time-series at twenty-one United States Geological Survey (USGS) observation points and 115 high water mark locations. FEMA depth-damage curves were used to estimate building and content damages from the combined flood sources (e.g., pluvial, fluvial, and marine) and total losses are compared against insurance claims registered with the U.S. National Flood Insurance Program (NFIP) and a depth grid produced during the U.S. Federal Emergency Management Agency's (FEMA) Preliminary Damage Assessment (PDA). The results suggest that Harvey may have caused upwards of $8.3 billion USD in uninsured residential loss within the model domain. Comparison against FEMA's PDA indicates that the SFINCS model predicts much larger total losses, indicating that the incorporation of spatially-distributed pluvial hazards into the modeling method is critical for identifying high-risk areas and supports the need for further flood risk analyses in the region. [ABSTRACT FROM AUTHOR]

While conceptual definitions provide a foundation for the study of disasters and their impacts, the challenge for researchers and practitioners alike has been to develop objective and rigorous measures of resilience that are generalizable and scalable, taking into account spatiotemporal dynamics in the response and recovery of localized communities. In this paper, we analyze mobility patterns of more than 800,000 anonymized mobile devices in Houston, Texas, representing approximately 35% of the local population, in response to Hurricane Harvey in 2017. Using changes in mobility behavior before, during, and after the disaster, we empirically define community resilience capacity as a function of the magnitude of impact and time-to-recovery. Overall, we find clear socioeconomic and racial disparities in resilience capacity and evacuation patterns. Our work provides new insight into the behavioral response to disasters and provides the basis for data-driven public sector decisions that prioritize the equitable allocation of resources to vulnerable neighborhoods. Understanding how cities respond to extreme weather is critical; as such events are becoming more frequent. Using anonymized mobile phone data for Houston, Texas during Hurricane Harvey in 2017, the authors find that mobility behavior exposes neighborhood disparities in resilience capacity and recovery. [ABSTRACT FROM AUTHOR]

Post event flooding maps are currently extracted from synthetic‐aperture radar (SAR) and/or optical satellite images or developing using hydraulic model simulations. Several sources of uncertainties impact the accuracy of such flood maps constructed from each method, especially in urban areas. An integrated approach that combines satellite imagines of flooded areas, hydraulic models, and markers from social media that should reduce these uncertainties and allow a more accurate reconstruction of flooded urban areas, is presented in this paper. The flooding associated with Hurricane Harvey in Houston, TX was chosen as a case study. Model validations demonstrate the effectiveness of our integrated approach in reconstructing an accurate flooding map, as well as the temporal and spatial patterns of flooding. Using the experience from this case study we discuss the possibility to use satellite data, instead of ground‐based rainfall gauge measurements as precipitation inputs to the hydraulic model; and possible error sources in simulating flooding in urban areas using the hydraulic model. [ABSTRACT FROM AUTHOR]

One measurement modality for rainfall is a fixed location rain gauge. However, extreme rainfall, flooding, and other climate extremes often occur at larger spatial scales and affect more than one location in a community. For example, in 2017 Hurricane Harvey impacted all of Houston and the surrounding region causing widespread flooding. Flood risk modeling requires understanding of rainfall for hydrologic regions, which may contain one or more rain gauges. Further, policy changes to address the risks and damages of natural hazards such as severe flooding are usually made at the community/neighborhood level or higher geo-spatial scale. Therefore, spatial-temporal methods which convert results from one spatial scale to another are especially useful in applications for evolving environmental extremes. We develop a point-to-area random effects (PARE) modeling strategy for understanding spatial-temporal extreme values at the areal level, when the core information are time series at point locations distributed over the region. [ABSTRACT FROM AUTHOR]

Late Dr. Sam Mannan promoted in his last year the concept of the Safety Triad as a basis for effective process safety. As he mentioned himself, nobody will be surprised that this triad consists of Prevention, Mitigation, and Response. If everything were perfect an accident would not occur, but in hindsight after an accident experience teaches that at least one of these pillars of the triad is missing or defective. Also, given the recent hurricane Harvey experience in the Houston region, socio-technical associated hazard threats emerge not only from inside a plant but can be external: NaTech or technological accidental occurrences evoked by natural forceful events. Hence to be acceptably safe, the robustness and reliability of the triad components must be well designed, and their performance over time must be periodically verified. This objective supposes a risk-based approach both for design and for reliable operation. However, risk assessment itself is fallible. Over the years it has been shown that there are many limitations, but fortunately during the last few years we have seen an advent of new approaches, methods, and techniques to perform a more realistic scenario definition of what can go wrong, enabling to cope with uncertainties in models and parameter values, to analyze the risk dynamics of situations, such as reliability and availability degradation, but also process risk evolving in continuous processes. In all this, not only the technical aspects but also the associated human and organizational factors must be included. The latter dominate the scene in many situations. Last but not least is the concept of resilience in case risks are overlooked due to lack of knowledge or even to the notorious "black swan" incidents. Preparing for unexpected events should provide not only error tolerant design but early warning agility, capability to improvise, and means to recover operations. It is business continuity that will be at stake! The paper will elaborate both the triad and Sam Mannan's view on risk assessment. [ABSTRACT FROM AUTHOR]

Synthetic Aperture Radar (SAR) remote sensing has been widely used for flood mapping and monitoring. Nevertheless, flood detection in urban areas still proves to be particularly challenging by using SAR. In this paper, we assess the roles of SAR intensity and interferometric coherence in urban flood detection using multi-temporal TerraSAR-X data. We further introduce an active self-learning convolution neural network (A-SL CNN) framework to alleviate the effect of a limited annotated training dataset. The proposed framework selects informative unlabeled samples based on a temporal-ensembling CNN model. These samples are subsequently pseudo-labeled by a multi-scale spatial filter. Consistency regularization is introduced to penalize incorrect labels caused by pseudo-labeling. We show results for a case study that is centered on flooded areas in Houston, USA, during hurricane Harvey in August 2017. Our experiments show that multi-temporal intensity (pre- and co-event) plays the most important role in urban flood detection. Adding multi-temporal coherence can increase the reliability of the inundation map considerably. Meanwhile, encouraging results are achieved by the proposed A-SL CNN framework: the к statistic is improved from 0.614 to 0.686 in comparison to its supervised counterpart. [ABSTRACT FROM AUTHOR]

Mechanisms for high offshore ozone (O3) events in the Houston area have not been systematically examined due to limited O3 measurements over water. In this study, we used the datasets collected by three boats deployed in Galveston Bay and the Gulf of Mexico during the Tracking Aerosol Convection Interactions ExpeRiment – Air Quality (TRACER-AQ) field campaign period (September 2021), in combination with the Weather Research and Forecasting (WRF) coupled Comprehensive Air quality Model with Extensions (CAMx) modeling system (WRF–CAMx), to investigate the reasons for high offshore O3. The model can capture the spatiotemporal variability in the daytime (10:00–18:00 central daylight time, CDT) O3 for the three boats (R > 0.7) but tends to overestimate O3 by ∼ 10 ppb on clean days and underestimate O3 by ∼ 3 ppb during high- O3 events. The process analysis tool in CAMx identifies O3 chemistry as the major process leading to high- O3 concentrations. The region-wide increase in the long-lived volatile organic compounds (VOCs) through advection transits O3 formation to be more sensitive to NOx , leading to more O3 production under a NOx -limited regime. In addition, the VOC-limited O3 formation is also boosted along western Galveston Bay and the Gulf Coast under high- NOx conditions brought by the northeasterly winds from the Houston Ship Channel. Two case studies illustrate that high offshore O3 events can develop under both large- and mesoscale circulations, indicating both the regional and local emissions need to be stringently controlled. Wind conditions are demonstrated to be important meteorological factors in such events, so they must be well represented in photochemical models to forecast air quality over the urban coastal regions accurately. [ABSTRACT FROM AUTHOR]

Houston, Texas, has highly engineered its waterways to reduce flooding. However, this has been shown to be inadequate during recent storms in 2015 through 2017, including Hurricane Harvey. This study analyzed the efficacy of a large-scale structural mitigation project, Project Brays, on reducing flood levels in the Brays Bayou watershed given updated rainfall standards released in 2018. In addition, we investigated the water surface elevation (WSE) reduction of three detention basins that were constructed as a part of this mitigation project. We propose other possible detention basins to mitigate flood hazard in the highly flood-prone regions of the watershed. We found that Project Brays will decrease WSE in the upstream half of the watershed by around 1.2 m at the expense of increasing WSE by 0.52 m downstream. Additional detention basins could further decrease WSE by an average of 0.1 m over the area impacted during the Atlas 14 100-year storm. These impacts are very localized directly downstream of the detention locations and are no longer seen after approximately 300 m. Future mitigation should contain more localized detention directly upstream of flood-prone areas to provide additional targeted reductions in floodplain extent. Project Brays is a case study that demonstrates how future climate scenarios may be necessary for the large-scale design works of the future, given that such projects often take decades to construct and it is not typically standard practice to design for climate conditions potentially existing upon completion. [ABSTRACT FROM AUTHOR]

Resiliency measurement is a great tool for evaluating system performance and proposing solutions to prevent damage and to recover from disruptive events. This study proposes an analytic approach to quantify narrow waterway systems' resiliency during disasters. First, metrics are introduced to quantify the resiliency before, during, and after a disruption. The existing Key Performance Indicators (KPIs) for Maritime Transportation Systems (MTS) are examined, and two metrics, 1) the number of inbound and outbound vessels and 2) Total Stopped Vessel-Hours, are selected to measure the resiliency of a waterway system. Second, a heuristic method is developed to derive the KPIs from the Automatic Identification System (AIS) data. Finally, the proposed methodology is performed for the Houston Ship Channel (HSC) AIS data before, during, and after Hurricane Harvey, in August 2017. The results are presented for the entire channel and highlight useful information about the performance of individual docks, terminals, and waterway zones within HSC. This study helps decision-makers identify the weaknesses and potential bottlenecks in a waterway confronting a disruption and come up with remedies. [ABSTRACT FROM AUTHOR]

The article discusses the devastation caused in Houston, Texas from Hurricane Harvey in August 2017 and outlines the efforts of the U.S. Army Corps of Engineers and volunteers to provide relief and rebuild the area. The efforts of the volunteers discussed include provision of temporary housing to the victims and development of mobile home parks. Details on the Oak Homes Park refurbished mobile home park are provided.

In studying resilience in temporal human networks, relying solely on global network measures would be inadequate; latent sub-structural network mechanisms need to be examined to determine the extent of impact and recovery of these networks during perturbations, such as urban flooding. In this study, we utilize high-resolution aggregated location-based data to construct temporal human mobility networks in Houston in the context of the 2017 Hurricane Harvey. We examine motif distribution, motif persistence, temporal stability, and motif attributes to reveal latent sub-structural mechanisms related to the resilience of human mobility networks during disaster-induced perturbations. The results show that urban flood impacts persist in human mobility networks at the sub-structure level for several weeks. The impact extent and recovery duration are heterogeneous across different network types. Also, while perturbation impacts persist at the sub-structure level, global topological network properties indicate that the network has recovered. The findings highlight the importance of examining the microstructures and their dynamic processes and attributes in understanding the resilience of temporal human mobility networks (and other temporal networks). The findings can also provide disaster managers, public officials, and transportation planners with insights to better evaluate impacts and monitor recovery in affected communities. [ABSTRACT FROM AUTHOR]

Twitter has significant potential as a source of Volunteered Geographic Information (VGI), as its content is updated at high frequency, with high availability thanks to dedicated interfaces. However, the diversity of content types and the low average accuracy of geographic information attached to individual tweets remain obstacles in this context. The contributions in this paper relate to the general goal of extracting actionable information regarding the impact of natural hazards on a specific region from social platforms, such as Twitter. Specifically, our contributions describe the construction of a model classifying whether given spatio-temporal coordinates, materialized by raster cells in a remote sensing context, lie in a flooded area. For training, remotely sensed data are used as the target variable, and the input covariates are built on the sole basis of textual and spatial data extracted from a Twitter corpus. Our contributions enable the use of trained models for arbitrary new Twitter corpora collected for the same region, but at different times, allowing for the construction of a flooded area measurement proxy available at a higher temporal frequency. Experimental validation uses true data that were collected during Hurricane Harvey, which caused significant flooding in the Houston urban area between mid-August and mid-September 2017. Our experimental section compares several spatial information extraction methods, as well as various textual representation and aggregation techniques, which were applied to the collected Twitter data. The best configuration yields a F1 score of 0.425, boosted to 0.834 if restricted to the 10% most confident predictions. [ABSTRACT FROM AUTHOR]

Within 24 months (2015–2017), Houston was struck by three "500-year flood" events, including Hurricane Harvey, the largest rainfall event in US history. In this article we explore how this wave of catastrophic flooding has impacted Houstonians' emotional and epistemic attachments to their homes, neighborhoods, and city. In dialogue with the anthropology and science and technology studies literature on disasters and its focus on technopolitical regimes of disaster anticipation and risk mitigation, we offer an analysis of the "affective publics of slow catastrophe" that have emerged in Houston in response to a situation that experts and citizens alike fear represents a "new normal" in the context of climate change. We focus on three affective orientations around which floodies are clustering: diluvial individualism (a wounded retreat from public engagement in favor of highly individualized recovery strategies), hydraulic citizenship (an activist political subjectivity oriented around creating better infrastructures of water management), and amphibious acceptance (an emergent affective orientation oriented to learning to live with rather than against floodwater). Although we ultimately argue that amphibious acceptance's time has not yet come in Houston, our fieldwork suggests that the repetitive experience of catastrophic flooding is changing the affective presence of water in Houston. [ABSTRACT FROM AUTHOR]

The number and intensity of flood events have been on the rise in many regions of the world. In some parts of the U.S., for example, almost all residential properties, transportation networks, and major infrastructure (e.g., hospitals, airports, power stations) are at risk of failure caused by floods. The vulnerability to flooding, particularly in coastal areas and among marginalized populations is expected to increase as the climate continues to change, thus necessitating more effective flood management practices that consider various data modalities and innovative approaches to monitor and communicate flood risk. Research points to the importance of reliable information about the movement of floodwater as a critical decision-making parameter in flood evacuation and emergency response. Existing flood mapping systems, however, rely on sparsely installed flood gauges that lack sufficient spatial granularity for precise characterization of flood risk in populated urban areas. In this paper, we introduce a floodwater depth estimation methodology that augments flood gauge data with user-contributed photos of flooded streets to reliably estimate the depth of floodwater and provide ad-hoc, risk-informed route optimization. The performance of the developed technique is evaluated in Houston, Texas, that experienced urban floods during the 2017 Hurricane Harvey. A subset of 20 user-contributed flood photos in combination with gauge readings taken at the same time is used to create a flood inundation map of the experiment area. Results show that augmenting flood gauge data with crowdsourced photos of flooded streets leads to shorter travel time and distance while avoiding flood-inundated areas. [ABSTRACT FROM AUTHOR]

In the Houston-Galveston-Beaumont (HGB) region considerable scientific effort has been directed at elucidating the relationships among atmospheric circulations and urban mixed-layer ozone concentrations. These studies of the HGB region have provided guidance on the conditions that are used herein to identify specific meteorological parameters that relate with observed exceedances of the National Ambient Air Quality Standard for ozone. These parameters were developed using 15 years of ozone concentrations and localized wind conditions enhanced by incorporating data from a private monitoring network. Using these data, several key parameters were found that described the most common meteorological conditions for an exceedance day in HGB. The most relevant parameters included: the wind direction at midnight, wind speeds from 0 to 6 LST, and the extent of wind direction rotation in a 24-hour period. These parameters, and the meteorological conditions they describe, were also found to occur in an analysis of observational data throughout the state of Texas suggesting large scale forces beyond the influence of a sea breeze. A mixed layer model was developed and shown to illustrate the large-scale synoptic forces found in the observational data. The meteorological parameters, and conditions they describe, could be part of a diagnostic model performance evaluation to assure that accurate predictions of ozone for Texas were not the result of compensating errors. Implications: This study identified meteorological-based parameters that coincided with observed exceedances of the National Ambient Air Quality Standard for ozone across the state of Texas. These parameters can be used in support of regulatory model performance evaluations to assure accuracy in predicting ozone conducive conditions. In Houston, the vast majority of meteorlogical ozone conducive days did not produce an exceedance, suggesting other as yet unidentified conditions that are necessary such as an intermittent emission of precursors. [ABSTRACT FROM AUTHOR]

Hurricanes can have adverse effects on residential communities and pose a significant risk to their economic prosperity. The ingress of water into a building due to wind-driven rain (WDR) and inland flooding can cause significant damage leading to downtime or temporary loss of housing. Existing frameworks focus on estimating the amount of water ingress due to WDR and inland flooding separately. This paper provides a comprehensive framework that considers both WDR and inland flooding when estimating the amount of water ingress into residential buildings due to hurricane rainfall. The framework estimates the water ingress due to WDR by combining the WDR intensity with the perforated area of the building envelopes. The intensity of the WDR is quantified using an Eulerian Multi-phase Model. The buildings' envelope is considered susceptible to damage from the impact of windborne debris and excessive dynamic wind pressure. The framework to characterize and quantify inland flooding uses a coupled hydrologic-hydrodynamic model to estimate the inundation depth at each building. A case study consisting of a residential community in Houston, TX, which is subject to Hurricane Harvey illustrates the ability of the framework to capture the influence of WDR and inland flooding when quantifying water ingress. • A framework is presented for building water ingress estimation due to hurricane rainfall. • Both wind driven rain and inland flooding are considered simultaneously. • Wind driven rain is modeled through an Eulerian multiphase model. • Inland flooding is estimated using a coupled hydrologic-hydrodynamic model. • The importance of both WDR and inland flooding when estimating losses is shown. [ABSTRACT FROM AUTHOR]

High resolution and accurate rainfall information is essential to modeling and predicting hydrological processes. Crowdsourced personal weather stations (PWSs) have become increasingly popular in recent years and can provide dense spatial and temporal resolution in rainfall estimates. However, their usefulness could be limited due to less trust in crowdsourced data compared to traditional data sources. Using crowdsourced PWSs data without a robust evaluation of its trustworthiness can result in inaccurate rainfall estimates as PWSs are installed and maintained by non‐experts. In this study, we advance the Reputation System for Crowdsourced Rainfall Networks (RSCRN) to bridge this trust gap by assigning dynamic trust scores to PWSs. Based on rainfall data collected from 18 PWSs in two dense clusters in Houston, Texas, USA as a case study, we found that using RSCRN‐derived trust scores can increase the accuracy of 15‐min PWS rainfall estimates when compared to rainfall observations recorded at the city's high‐fidelity rainfall stations. Overall, RSCRN rainfall estimates improved for 77% (48 out of 62) of the analyzed storm events, with a median root‐mean‐square error (RMSE) improvement of 27.3%. Compared to an existing PWS quality control method, results showed that RSCRN improved rainfall estimates for 71% of the storm events (44 out of 62), with a median RMSE improvement of 18.7%. Using RSCRN‐derived trust scores can make the rapidly growing network of PWSs a more useful resource for hydrologic applications, greatly improving knowledge of rainfall patterns in areas with dense PWSs. Key Points: We present a reputation system framework to measure the trustworthiness of crowdsourced personal weather stations (PWSs)PWSs are assigned a trust score based on their agreement with rainfall measured at neighboring stationsThe accuracy of rainfall estimates based on crowdsourced PWSs can be improved by excluding PWSs with low trust scores [ABSTRACT FROM AUTHOR]

In August 2017, Hurricane Harvey inundated Houston, Texas, where flooding already was a persistent and growing challenge. Coordinated, proactive land-use planning has been shown to help mitigate flooding hazards, whereas conflicting guidance can exacerbate the problem. This study used the Plan Integration for Resilience Scorecard (PIRS) method to spatially evaluate a network of plans guiding land use and development in western Houston when Harvey struck, assessing their integration and effects on flood vulnerability. Despite generally positive results, we found important variations and conflicts across plans and across the study area. By encouraging development without sufficient attention to flood risk, some plans and policies increased vulnerability, especially in places outside the official 100-year (1% annual chance) floodplain but still in danger of flooding. A false sense of security provided by local flood control structures may have amplified the problem by enabling more intense development—an example of the safe development paradox—and making the area even more vulnerable to cascading effects from a massive and sustained precipitation event such as Harvey. [ABSTRACT FROM AUTHOR]

Flooding impacts are on the rise globally, and concentrated in urban areas. Currently, there are no operational systems to forecast flooding at spatial resolutions that can facilitate emergency preparedness and response actions mitigating flood impacts. We present a framework for real‐time flood modeling and uncertainty quantification that combines the physics of fluid motion with advances in probabilistic methods. The framework overcomes the prohibitive computational demands of high‐fidelity modeling in real‐time by using a probabilistic learning method relying on surrogate models that are trained prior to a flood event. This shifts the overwhelming burden of computation to the trivial problem of data storage, and enables forecasting of both flood hazard and its uncertainty at scales that are vital for time‐critical decision‐making before and during extreme events. The framework has the potential to improve flood prediction and analysis and can be extended to other hazard assessments requiring intense high‐fidelity computations in real‐time. Plain Language Summary: Currently, we cannot forecast flooding depths and extent in real‐time at a high level of detail in urban areas. This is the result of two key issues: detailed and accurate flood modeling requires a lot of computing power for large areas such as a city, and uncertainty in precipitation forecasts is high. We present an innovative flood forecasting method that resolves flood characteristics with enough detail to inform emergency response efforts such as timely road closures and evacuation. This is achieved by performing complex analysis of information on flooding impacts well before a future storm event, which subsequently allows much faster predictions when flooding actually happens. This approach completely changes the demand for required resources, replacing the nearly impossible burden of computation in real‐time with the easy problem of data storage, feasible even with a low‐end computer. Example results for Hurricane Harvey flooding in Houston, TX, show that predictions of both flood hazard and uncertainty work well over different areas of the city. This approach has the potential to provide timely and detailed information for emergency response efforts to help save lives and reduce other negative impacts during major flood events and other natural hazards. Key Points: There is presently no means to forecast urban flooding at high resolution due to prohibitive computational demands and data uncertaintiesProposed framework combines high‐fidelity modeling and probabilistic learning to forecast flood attributes with uncertainty in real‐timeThe framework can be extended to other real‐time hazard forecasting, requiring high‐fidelity simulations of extreme computational demand [ABSTRACT FROM AUTHOR]

As part of a larger study into the influence of a Writers in the Schools (WITS) professional development consultancy, this narrative inquiry began just as Hurricane Harvey, the second most costly hurricane to hit the United States, devastated the Texas Gulf Coast in August 2017 and drew to a close in late 2020 during the COVID-19 global pandemic. This chapter explores the 2017-2018 school-year interactions between WITS Collaborative writer, Mary Austin (pseudonym), and six writing teachers with whom she worked at McKay High School (pseudonym) in the aftermath of Hurricane Harvey. With record flooding and widespread damage causing school-opening delays, teachers, students, and WITS consultants navigated a rip tide of emotions as they strived to balance educational/professional needs and duties with personal loss and unexpected financial burdens. This inquiry examines how WITS teacher professional development was carried out in the midst of these trying circumstances. [ABSTRACT FROM AUTHOR]

While increasing physical activity is a public health priority in the United States and is known to improve health and wellbeing, little is known about how disasters influence physical activity among members of impacted communities. This qualitative study examines the experiences and activities of 17 representatives of fitness, parks, and active transportation organizations in Houston, Texas following Hurricane Harvey and in Santa Rosa, California following the Tubbs Wildfires. Interview transcripts were thematically analyzed using a combined inductive and deductive approach. Our findings suggest that factors on the individual, social and organizational, built environment, and natural environment levels influence participation in physical activity post-event. Fitness, parks, and active transportation organizations support activities that promote social and physical wellbeing during the disaster recovery process and would benefit from tailored resources and technical assistance to support their activities during disaster recovery. [ABSTRACT FROM AUTHOR]

We examine the potential role of aerosol pollution on the rainfall and intensity of Hurricane Harvey. For this study, we use the global model, Ocean–Land–Atmosphere Model (OLAM), with aerosol estimates from the global atmospheric chemistry model GEOS-Chem. Two sets of simulations of Hurricane Harvey were performed. Simulations in the first set cover the intensification phase of Harvey until initial landfall in Texas and focus on the sensitivity of storm track and intensity, while simulations in the second set examine the sensitivity of storm track and precipitation during the period after initial landfall when record flooding occurred near Houston. During each period, simulations were performed with no anthropogenic sources of aerosol, with both natural and anthropogenic aerosol sources, and with both sources enhanced 10 times. During the rapid intensification phase, the results indicate that aerosol amounts had very little impact on storm motion. Moreover, very little difference was found on the intensity of the simulated storm to aerosol amounts for the no-anthropogenic versus the GEOS-Chem estimated amounts with anthropogenic sources. However, when both natural and anthropogenic aerosol amounts were enhanced 10 times, the simulated storm intensity was enhanced appreciably in terms of minimum sea level pressure. During the second period of the simulation, through which Harvey remained a tropical storm, the main result was that very little sensitivity was found in precipitation or any other tropical cyclone (TC) characteristic to aerosol concentrations. We cannot definitively state why the individual convective cells did not respond to high aerosol concentrations during this phase of the storm. However, the abundant precipitation in all three simulations scavenged the vast majority of aerosols as it flowed radially inward, and we speculate that this modulated the potential impact of aerosols on the inner TC and eyewall. Overall, the simulated response of Hurricane Harvey to aerosols was far less spectacular than what has been simulated in the past. We conclude that this is because Hurricane Harvey was a strongly dynamically driven storm system that as a result was relatively impervious to the effects of aerosols. [ABSTRACT FROM AUTHOR]

This case study tests the frameworks of the discourse of renewal theory and social legitimacy theory through an examination of the Fort Bend Independent School District's (Texas) communication strategies and tactics before, during and after Hurricane Harvey struck the Houston area in 2017. A focus of this case study is one characteristic of the discourse of renewal theory: the showcasing of leaders as "instrumental forces for renewal and overcoming crises" (Ulmer, Seeger & Sellnow, 2007, pp. 131–132), especially related to messages by the district's superintendent. Both the superintendent's and Fort Bend ISD's communication efforts aligned with the tenets of renewal discourse and social legitimacy theory, with empathy an ingredient in many messages. Another important finding of this study is that the district used a discourse of renewal before, during, and after the storm, and not simply as a post‐crisis strategy. Overall, this strategy may have played a role in the district's organizational resilience—as shown through its sustained enrolment and continuing leadership team—after the second‐costliest hurricane in U.S. history. [ABSTRACT FROM AUTHOR]

In the wake of Hurricane Harvey, multiple media sources claimed the event was an "equal opportunity" storm. These claims challenge existing social vulnerability research that finds marginalised groups have both unequal risk exposure and subsequent differential impacts from disasters (Cutter, Boruff, and Shirley 2003, "Assessing Current and Future Freshwater Flood Risk from North Atlantic Tropical Cyclones via Insurance Claims." Scientific Reports 7 (February): 41609; Faber 2015, "Superstorm Sandy and the Demographics of Flood Risk in New York City." Human Ecology 43 (3): 363–378. ; Thomas et al. 2013, Social Vulnerability to Disasters. Boca Raton, FL: CRC Press). To understand the accuracy of this "equal opportunity" assertion, we use ordinary least squares, simultaneous autoregressive, and geographically weighted regression techniques to investigate the relationships between indicators of social vulnerability and FEMA-approved housing damages from Hurricane Harvey across five cities in the Houston area. Findings suggest Harvey had disproportionate impacts on housing damages for Black, Latinx, and mobile home residents. These results serve as a foundational analysis for the broader purpose of informing policy decisions regarding recovery efforts and future approaches to improving flooding resilience in the Houston area. [ABSTRACT FROM AUTHOR]

Background: In August 2017, Hurricane Harvey caused unprecedented flooding across the greater Houston area. Given the potential for widespread flood-related exposures, including mold and sewage, and the emotional and mental toll caused by the flooding, we sought to evaluate the short- and long-term impact of flood-related exposures on the health of Houstonians. Our objectives were to assess the association of flood-related exposures with allergic symptoms and stress among Houston-area residents at two time points: within approximately 30 days (T1) and 12 months (T2) after Hurricane Harvey's landfall.Methods: The Houston Hurricane Harvey Health (Houston-3H) Study enrolled a total of 347 unique participants from four sites across Harris County at two times: within approximately 1-month of Harvey (T1, n = 206) and approximately 12-months after Harvey (T2, n = 266), including 125 individuals who participated at both time points. Using a self-administered questionnaire, participants reported details on demographics, flood-related exposures, and health outcomes, including allergic symptoms and stress.Results: The majority of participants reported hurricane-related flooding in their homes at T1 (79.1%) and T2 (87.2%) and experienced at least one allergic symptom after the hurricane (79.4% at T1 and 68.4% at T2). In general, flood-exposed individuals were at increased risk of upper respiratory tract allergic symptoms, reported at both the T1 and T2 time points, with exposures to dirty water and mold associated with increased risk of multiple allergic symptoms. The mean stress score of study participants at T1 was 8.0 ± 2.1 and at T2, 5.1 ± 3.2, on a 0-10 scale. Participants who experienced specific flood-related exposures reported higher stress scores when compared with their counterparts, especially 1 year after Harvey. Also, a supplementary paired-samples analysis showed that reports of wheezing, shortness of breath, and skin rash did not change between T1 and T2, though other conditions were less commonly reported at T2.Conclusion: These initial Houston-3H findings demonstrate that flooding experiences that occurred as a consequence of Hurricane Harvey had lasting impacts on the health of Houstonians up to 1 year after the hurricane. [ABSTRACT FROM AUTHOR]

Hurricane Harvey was social media's first real stress test as a disaster response and recovery mechanism. A confluence of conditions makes it an ideal case study of social media's role in disaster recovery: the lack of a government-issued evacuation order, a call from government leadership for willing and able volunteers with a boat or high-water vehicle to perform life-saving rescues, and wide-spread adoption of social media platforms in the Houston area. While research on online social networks and disasters continues to grow, social scientists know little about how these online networks transform during a crisis and, further, how they drive disaster outcomes. With two original datasets, this study investigates how Houston's online social network transformed during Hurricane Harvey (2017), and the relationship between social media activity and post-Harvey recovery. The findings of a social network analysis (N= 2,387,610) and subsequent statistical analyses reveal the Houston-area online social network grew denser, clustered, and more efficient during the disaster. A spatial analysis and three separate regression models of activity before, during, and after Hurricane Harvey reveal that among 333 Nextdoor Neighborhoods, hyperlocal social media activity was a statistically significant predictor of the rate of rebuilding in these geographically based online communities. These findings suggest that policy and decision-makers should invest into online and offline hyperlocal social networks well before a disaster strikes, and leverage resources and legislation to maintain and strengthen the telecommunications and energy infrastructure that supports access to social media and telecommunications infrastructure during a time of crisis. [ABSTRACT FROM AUTHOR]

The destructive power of tropical cyclones is driven by latent heat released from water condensation and is inevitably linked to the abundance of aerosols as cloud condensation nuclei. However, the aerosol effects are unaccounted for in most operational hurricane forecast models. We combined multisource measurements and cloud‐resolving model simulations to show fundamentally altered cloud microphysical and thermodynamic processes by anthropogenic aerosols during Hurricane Harvey. Our observational analyses reveal intense lightning and precipitation in the proximity of Houston industrial areas, and these hot spots exhibit a striking geographic similarity to a climatological maximum of lightning flash density in the south‐central United States. Our ensemble cloud‐resolving simulations of Hurricane Harvey indicate that aerosols increase precipitation and lightning by a factor of 2 in the Houston urban area, unraveling the key anthropogenic factor in regulating flooding during this weather extreme. Plain Language Summary: The catastrophic flooding during Hurricane Harvey has received major attention, but the cause remains mysterious. The destructive power of tropical cyclones is produced by the latent heat release from phase change of water, which is linked to airborne particles emitted from vehicles and petrochemical plants. By combining observation and model simulations, our work provides microphysical and thermodynamic insights into the cause of the catastrophic flooding during Hurricane Harvey by the aerosols from industrial sources. Our discovery underscores the importance of representing the effects of anthropogenic aerosols for accurate short‐term forecast and climate projection of tropical cyclones to minimize future catastrophic destruction along the highly industrialized Gulf of Mexico region. Key Points: Aerosol increases accumulative precipitation by a factor of 2T and invigorates lightning activities in Houston during Hurricane HarveyObservations show intense lightning over Houston which exhibits geographic similarity to climatological maximum lightning flash densityTo better forecast extreme weather events, it is essential to account for aerosol effects in operational weather forecast models [ABSTRACT FROM AUTHOR]

This study is focused on social cognitive variables that motivate information seeking and information sharing related to Hurricane Harvey. Survey results from a nationally representative sample and a quota sample of Houston residents indicate that climate change beliefs and issue salience are consistent predictors of risk perception, which increases individuals' negative emotions and information insufficiency. This need for information subsequently motivates information seeking and information sharing. Informational subjective norms are significantly related to seeking and sharing in the Houston sample, whereas perceived information gathering capacity and trust in media are significant predictors in the national sample. [ABSTRACT FROM AUTHOR]

Hurricane Harvey heavily impacted Texas in August 2017 due to an extreme amount of rainfall, especially in the large metropolitan area in and around Houston. There was an offshore storm surge associated with Harvey, and while it raised the water level in the bay, possibly prolonging flooding in the Houston area by slowing drainage, it was not responsible for flooding, as water flowed continuously out of the bay during peak flooding. Salinity measured near the mouth of the San Jacinto river dropped to 0 from 15 psu in 1.5 days after the start of storm-related outflow from the bay; the whole bay was fully freshened in 3.6 days. Depth-averaged outflow from the entrance channel reached 2 m/s. Using publicly available oceanographic data within Galveston Bay, we estimate the amount of freshwater that flowed into the bay from this rainfall to be 17 ± 5 km3 (14 million acre feet), or about 5 times the volume of Galveston Bay itself. This is less than, but close to, the freshwater input source: 20 km3 of rain that was estimated from Doppler radar to have accumulated in the drainage basins contributing to the bay. By comparison, the freshwater inflow estimates by the Texas Water Development Board (TWDB) predicts 13 km3 (11.5 million acre feet) of inflow to Galveston Bay during Hurricane Harvey. [ABSTRACT FROM AUTHOR]

Rainfall extreme value analysis provides information that has been crucial in characterizing risk, designing successful infrastructure systems, and ultimately protecting people and property from the threat of rainfall-induced flooding. However, in the Houston region recent events (such as the unprecedented rainfall wrought by Hurricane Harvey) have highlighted the inability of existing analyses to accurately characterize current climate conditions. Specifically, there has been little research investigating how spatial patterns of extreme precipitation have shifted through time in the Texas Gulf Coast region, which has led to mis-characterization of existing intensity–duration–frequency curves. This study investigates spatiotemporal trends in extreme precipitation in southeast Texas using a statistical approach for peaks-over-threshold modeling that employs a generalized Pareto distribution. Precipitation data from over 600 rain gauges across the region are analyzed in 40-year time windows to evaluate shifts in distribution parameters and extreme rainfall levels through time. Spatial analysis of these trends focuses on highlighting regions with increasing, stationary, and decreasing extreme rainfall through time. Results demonstrate heterogeneity in spatiotemporal trends across the entire study region, but significant increases in extreme rainfall over the Houston urban area. Spatial analysis of these trends focuses on how extreme rainfall has changed within different watersheds. Return level estimates of extreme rainfall values are also compared to the current standards for Harris County. Results from this study identify areas that have experienced significant shifts in extreme rainfall, and can help inform where design standards may be inaccurate or outdated. [ABSTRACT FROM AUTHOR]

Hurricane Harvey was the wettest hurricane in US history bringing record rainfall and widespread flooding in Houston, TX. The resulting storm- and floodwaters largely emptied into the Galveston Bay. Surface water was collected from 10 stations during five cruises to investigate the concentrations and sources of 16 priority polycyclic aromatic hydrocarbons (PAHs), and relative abundances of PAH-degrading bacteria. Highest PAH levels (102–167 ng/L) were detected during the first sampling event, decreasing to 36–69 ng/L within a week. Four sites had elevated concentrations of carcinogenic benzo[a]pyrene that exceeded the Texas Standard for Surface Water threshold. The highest relative abundances of known PAH-degrading bacteria Burkholderiaceae, Comamonadaceae, and Sphingomonadales were detected during the first and second sampling events. PAH origins were about 60% pyrogenic, 2% petrogenic, and the remainder of mixed sources. This study improves our understanding on the fate, source, and distributions of PAHs in Galveston Bay after an extreme flooding event. [ABSTRACT FROM AUTHOR]

Analyses of disaster resilience have focused increasingly on the role of social capital and online social networks in recovery. This study complements this field of work by investigating three key issues. First, it examines how a social messaging application, WeChat, helped individuals to access and to mobilise three types of social capital—bonding, bridging, and linking—during Hurricane Harvey, a Category 4 storm that made landfall in Louisiana and Texas in the United States in August 2017, resulting in significant flooding and loss of life. Second, it pinpoints and assesses quantitatively how individuals' WeChat group usage and social capital influenced their post‐disaster well‐being. Third, it demonstrates how a minority and immigrant community in Houston, Texas, overcame the disadvantages commonly observed in other disaster research through the utilisation of social media. The findings of this study should aid governmental and community efforts to foster resilience in the face of natural and human‐induced hazards. [ABSTRACT FROM AUTHOR]

The objective of this study is to examine the properties of actor collaboration networks and to analyze how they influence the coordination of hazard mitigation in resilience planning in Harris County, Texas. Effective resilience planning can only be achieved through the collective actions of various actors and the network structures unfold the collaboration among the actors. Understanding the structural properties of actor collaboration networks for hazard mitigation may hold the key to understanding and improving the resilience planning process. To this end, after Hurricane Harvey, we administered a stakeholder survey to actors in various urban sectors involved in hazard mitigation (e.g., flood control, transportation, and emergency response). The survey aimed to capture actor collaboration networks for hazard mitigation in Harris County, Texas prior to Harvey. The collaboration represents that the survey respondents worked with the actors in the survey roster for hazard mitigation. We asked the respondents the frequency of the collaboration in the survey (e.g., yearly, monthly, weekly and daily). We examined three network structural properties to study actor positions in the network: degree centrality, boundary spanners, and core-periphery structure, because degree centrality could indicate what actors had more collaborations; boundary spanners could reveal what actors were in strategic positions to connect otherwise separate actors; and core-periphery structure could identify what actors formed the core of actor collaboration network for hazard mitigation and whether the core was composed of actors from diverse sectors. The results showed: (1) governmental actors from different sectors had high degree centrality and betweenness centrality, which indicated that governmental actors had a more influential role in coordination and information dissemination in hazard mitigation planning and implementation; and (2) fewer flood control and non-governmental actors were at the core of the actor collaboration networks, which reduced the extent of hazard mitigation coordination. The results identify potential influential actors (such as City of Houston, Harris County, and Houston–Galveston Area Council) in coordination of hazard mitigation and yield recommendations for increased actor network cohesion for better coordination of hazard mitigation across diverse sectors in resilience planning. [ABSTRACT FROM AUTHOR]

For more than four decades now, social scientists have understood disasters as temporally prolonged processes in which human practices enhance the socially disruptive and materially destructive capacities of geophysical phenomena, technological "accidents," and epidemics. This approach has come to be known as vulnerability theory in the realm of disaster risk management and it is closely related to the political-ecological analytical approach in the social sciences. Because of the analytical power of vulnerability theory and political ecology, some social scientists have gone so far as to call disasters "revelatory crises" that illuminate the political economic conditions that give catastrophes their form and magnitude. Although vulnerability theory and political ecology are certainly powerful analytical vantage points, they are not necessarily the perspectives through which the various social actors interpellated by catastrophes interpret calamity. This article explores the question "what does Hurricane Harvey reveal for whom?" in Houston Texas, and examines the implications the various responses to this question on the part of Houstonians of various socio-economic backgrounds and political positioning have for disaster risk reduction in the U.S. Gulf Coast. [ABSTRACT FROM AUTHOR]

This research examines the environmental and storm-scale characteristics of the extreme rainfall and flooding in the Houston, Texas, area on 18 April 2016, known as the ''Tax Day'' flood. Radar and local mesonet rain gauge observations were used to identify the locations and structures of extreme rain-rateproducing cells, with special attention given to rotating updrafts. To supplement this observation-based analysis, a WRF-ARW simulation of the Tax Day storm in 2016 was examined for the influence of any attendant rotation on both the dynamics and microphysics of the cells producing the most intense short-term (i.e., subhourly to hourly) rainfall accumulations. Results show that the most intense rainfall accumulations in the model analysis, as in the observational analysis, are associated with rotating convective elements. A lowering of the updraft base, enhancement of the low-level vertical velocities, and increased low-level rainwater production is seen in rotating updrafts, compared to those without rotation. These differences are also maintained despite increased hydrometeor loading. The results agree with the findings of previous idealized model simulations that show dynamical accelerations associated with meso-g-scale rotation can enhance convective rainfall rates. [ABSTRACT FROM AUTHOR]

The article highlights the impact of Hurricane Harvey in Houston, Texas and the impact of climate change on environment. Topics include that social and environmental determinants of health are affected by climate change; that reductions in greenhouse gases may improve air pollution; and mitigation strategies should be implemented for long-term results.

Hurricane Harvey caused at least 70 confirmed deaths, with estimated losses in the Houston urban area of Texas reaching above US$150 billion, making it one of the costliest natural disasters ever in the United States. The study tests two types of forecast index to provide surface flooding (inundation) warning over the Houston area: a meteorological index based on a global numerical weather prediction (NWP) system, and a new combined meteorological and land surface index, the flood hazard risk forecasting index (FHRFI), where land surface is used to condition the meteorological forecast. Both indices use the total precipitation extreme forecast index (EFI) and shift of tails (SoT) products from the European Centre for Medium‐Range Weather Forecasts (ECMWF) medium‐range ensemble forecasting system (ENS). Forecasts at the medium range (3–14 days ahead) were assessed against 153 observed National Weather Service (NWS) urban flood reports over the Houston urban area between August 26 and 29, 2017. It is shown that the method provides skilful forecasts up to four days ahead using both approaches. Moreover, the FHRFI combined index has a hit ratio of up to 74% at 72 hr lead time, with a false‐alarm ratio of only 45%. This amounts to a statistically significant 20% increase in performance compared with the meteorological indices. This first study demonstrates the importance of including land‐surface information to improve the quality of the flood forecasts over meteorological indices only, and that skilful flood warning in urban areas can be obtained from the NWP using the FHRFI. [ABSTRACT FROM AUTHOR]

This study analyzes Ludwig Mies van der Rohe’s two additions to Houston’s Museum of Fine Art (MFAH), completed in 1958 and 1974. Enigmatic projects within the renowned architect’s oeuvre, these designs by Mies are not only unique as additions to an existing building, but the second also involves a partial demolition of his own work. The formal aspects of both additions with curved north façades, uncommon for the architect, have only been sparingly considered in previous writings. Given this two-part project encompasses both the architect’s first completed museum and, by some accounts, his final built work, this study aims to position the MFAH additions as potentially the most interesting and complex post-World War II work within Mies’s oeuvre. This research is mainly based on site and archival visits as well as mining the vast published literature dedicated to the architect. That the first addition might be understood as a sacrificial armature for the second is an interpretation apparently not previously explored but may be concluded from synthesizing archival evidence. [ABSTRACT FROM AUTHOR]