In this study, we compare the ability of two riverine flood control approaches: channelization and stream preservation/setbacks, to alleviate the adverse impacts of rapid urbanization. To study the effects of structural intervention and urban development on the evolution of the floodplain, we have chosen two neighboring urban watersheds in Houston, TX: Brays Bayou and Buffalo Bayou. While the two watersheds are similar in size, topography, and development level, they have contrasting riverine flood management approaches. Brays Bayou is channelized, whereas Buffalo Bayou remains mostly unchannelized. We use the distributed hydrologic model, Vflo®, and the hydraulic model, HEC-RAS, to analyze channel hydraulics and floodplain extent in the two watersheds under the 10- and 100-year rainfall scenarios at three points in time: 1970s (early development), 2011 (current development), and 2040 (future development). We find that, while floodplain extent in both watersheds increases over time, the relative change in floodplain extent for Brays Bayou (channelized) is substantially larger than that for Buffalo Bayou (unchannelized). The results in this study contribute to a better understanding of the long-term performance of two flood mitigation approaches (channelization and setbacks) on riverine flood risk and provide insight into best management practices for cities experiencing rapid urban growth.

As there is increasing emphasis on transformative education and authentic learning in interdisciplinary research projects, it is meaningful to investigate how to effectively design a multidisciplinary research and education program to ensure beneficial outcomes for participating students. This is especially important for ocean and coastal engineering programs that are likely the most multidisciplinary engineering programs. The NSF PIRE Coastal Flood Risk Reduction Program is an international place and problem-based research education program in which students conduct case studies across the Houston-Galveston metropolitan area in the U.S. and in the Netherlands. There are three to four designated case studies (place-based) annually in each country, covering both surge-based and precipitation-driven flood problems (problem-based). From 2016 to 2018, there were three student research trips to the Netherlands (one each year, after the spring semesters). A total of 42 U.S. students, graduate and undergraduate were selected from four participating U.S. campuses apply for a designated Dutch case study. The three to four case studies change every year. Students from diverse disciplines, including engineering, planning, economics, hydrology, biology, architecture, geography, communications, and computational hydraulics, interested in flood risk reduction can apply. Those accepted into the Program are placed in interdisciplinary research teams composed of 5-6 students: 1-2 PhD, 2-3 Masters, and 2-3 undergraduate students. The teams are guided by project faculty mentors from both U.S. and Dutch partner institutions. A two-week long research trip to the Netherlands provides transformative education and an authentic learning environment through field trips, meetings with Dutch flood experts, lectures, and participation in design workshops. Students are required to present their research work three times while they are in the Netherlands: 5-minute research plan; 10-minute research progress; and 15-minute final presentation. By preparing these presentations, students learn how to collect data, interview stakeholders, lead/participate in brain-storming discussions, and adjust/improve their research products. Students also learn how to interact with people from different disciplines and look at the issues from diverse perspectives. This article describes the design process of the Program, from initial development through implementation. Reflections and lessons learned from the first three years of the Program are shared.

Rescue requests during large-scale urban flood disasters can be difficult to validate and prioritise. High-resolution aerial imagery is often unavailable or lacks the necessary geographic extent, making it difficult to obtain real-time information about where flooding is occurring. In this paper, we present a novel approach to map the extent of urban flooding in Harris County, Texas during Hurricane Harvey (August 25–30, 2017) and identify where people were most likely to need immediate emergency assistance. Using Maximum Entropy, we predict the probability of flooding based on several spatially-distributed physical and socio-economic characteristics coupled with crowdsourced data. We compare the results against two alternative flood datasets available after Hurricane Harvey (i.e., Copernicus satellite imagery and riverine flood depths estimated by FEMA), and we validate the performance of the model using a 15% subset of the rescue requests, Houston 311 flood calls, and inundated roadways. We find that the model predicts a much larger area of flooding than was shown by either Copernicus or FEMA when compared against the locations of rescue requests, and that it performs well using both a subset of rescue requests (AUC 0.917) and 311 calls (AUC 0.929) but is less sensitive to inundated roads (AUC 0.721).

The application of risk-based approaches for the design of flood infrastructure has become increasingly common in flood management. This approach, based on risk reduction and reliability, is used to assess the performance of conventional interventions (e.g., flood defences and dams) and to support decisions regarding their implementation. However, for more innovative solutions, performance has often not been quantified by means of these metrics and, therefore, end-users are hesitant to implement them in existing flood risk reduction systems. To overcome the gap between innovators and end-users, we present a framework based on four performance indicators, to ensure the required insights in risk and reliability are provided. The four indicators: effectiveness, durability, reliability and costs, allow end-users to evaluate, select, and implement flood adaptation innovations, and provide innovators with insight into the performance of the technology and the criteria and information necessary for successful market uptake of their innovation. The practical application of the framework is demonstrated for a (hypothetical) case of a hospital complex built in an area that has subsided below the surrounding area, which is subject to tropical rain showers. The following innovations are considered: an early flood warning system, a green roof, and a temporary flood barrier.

During August 25-30, 2017, Hurricane Harvey stalled over Texas and caused extreme precipitation, particularly over Houston and the surrounding area on August 26-28. This resulted in extensive flooding with over 80 fatalities and large economic costs. It was an extremely rare event: the return period of the highest observed three-day precipitation amount, 1043.4 mm 3dy^-1 at Baytown, is more than 9000 years (97.5% one-sided confidence interval) and return periods exceeded 1000 yr (750 mm 3dy^-1) over a large area in the current climate. Observations since 1880 over the region show a clear positive trend in the intensity of extreme precipitation of between 12% and 22%, roughly two times the increase of the moisture holding capacity of the atmosphere expected for 1 °C warming according to the Clausius-Clapeyron (CC) relation. This would indicate that the moisture flux was increased by both the moisture content and stronger winds or updrafts driven by the heat of condensation of the moisture. We also analysed extreme rainfall in the Houston area in three ensembles of 25 km resolution models. The first also shows 2 × CC scaling, the second 1 × CC scaling and the third did not have a realistic representation of extreme rainfall on the Gulf Coast. Extrapolating these results to the 2017 event, we conclude that global warming made the precipitation about 15% (8%-19%) more intense, or equivalently made such an event three (1.5-5) times more likely. This analysis makes clear that extreme rainfall events along the Gulf Coast are on the rise. And while fortifying Houston to fully withstand the impact of an event as extreme as Hurricane Harvey may not be economically feasible, it is critical that information regarding the increasing risk of extreme rainfall events in general should be part of the discussion about future improvements to Houston's flood protection system.