This study reports a new and significantly enhanced analysis of US flood hazard at 30 m spatial resolution. Specific improvements include updated hydrography data, new methods to determine channel depth, more rigorous flood frequency analysis, output downscaling to property tract level, and inclusion of the impact of local interventions in the flooding system. For the first time, we consider pluvial, fluvial, and coastal flood hazards within the same framework and provide projections for both current (rather than historic average) conditions and for future time periods centered on 2035 and 2050 under the RCP4.5 emissions pathway. Validation against high-quality local models and the entire catalog of FEMA 1% annual probability flood maps yielded Critical Success Index values in the range 0.69-0.82. Significant improvements over a previous pluvial/fluvial model version are shown for high-frequency events and coastal zones, along with minor improvements in areas where model performance was already good. The result is the first comprehensive and consistent national-scale analysis of flood hazard for the conterminous US for both current and future conditions. Even though we consider a stabilization emissions scenario and a near-future time horizon, we project clear patterns of changing flood hazard (3σ changes in 100 years inundated area of −3.8 to +16% at 1° scale), that are significant when considered as a proportion of the land area where human use is possible or in terms of the currently protected land area where the standard of flood defense protection may become compromised by this time. Plain Language Summary We develop a method to estimate past, present, and future flood risk for all properties in the conterminous United States whether affected by river, coastal or rainfall flooding. The analysis accounts for variability within environmental factors including changes in sea level rise, hurricane intensity and landfall locations, precipitation patterns, and river discharge. We show that even for a conservative climate change trajectory we can expect locally significant changes in the land area at risk from floods by 2050, and by this time defenses protecting 2,200 km 2 of land may be compromised. The complete dataset has been made available via a website (https://floodfactor.com/) created by the First Street Foundation in order to increase public awareness of the threat posed by flooding to safety and livelihoods. BATES ET AL.

This study investigates the capacity of a Spartina alterniflora meadow to attenuate waves during storm events based on field observations in the Chesapeake Bay. These observations reveal that environmental conditions including the ratio between water depth and plant height (hr), the ratio between wave height (HS) and water depth, and current directions impact the wave height decay. Further, we present empirical representations of the bulk drag coefficient (Cd) as a function of the Keulegan‐Carpenter (KC) and Reynolds (Re) numbers, and the hr ratio. When applying the distinction between current directions, this representation exhibits better agreement when using the Re (ρ2 = 54%) and hr (ρ2 = 77%) than with the KC (ρ2 = 39%). Furthermore, we show that the representation of Cd can be improved by using a hr‐based modified Re and KC formulation, yielding correlations of 76% (modified Re) and 78% (modified KC). The proposed expressions are validated during another storm and predicted HS computed within the marsh results in a root‐mean‐square error of 0.014 m, overestimating the largest HS (0.22 m) by 18%. Finally, these expressions are applied to several hypothetical sea conditions. Under similar vegetation characteristics, HS of 1.55 and 0.8 m (close to a 10,000‐ and 100‐year recurrence interval storm) are attenuated by 50% and 70%, respectively, at 250 m from the marsh edge. This study provides evidence that validates the saltmarsh wave attenuation capacity during storms, quantifies this attenuation, and supports the transferability of the existing formulas in the literature across similar coastal marshes.

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Large estuaries are especially vulnerable to coastal flooding due to the potential of combined storm surges and riverine flows. Numerical models can support flood prevention and planning for coastal communities. However, while recent advancements in the development of numerical models for storm surge prediction have led to robust and accurate models; an increasing number of parameters and physical processes' representations are available to modelers and engineers. This study investigates uncertainties associated with the selection of physical parameters or processes involved in storm surge modeling in large estuaries. Specifically, we explored the sensitivity of a hydrodynamic model (ADCIRC) and a coupled wind-wave and circulation model system (ADCIRC + SWAN) to Manning's n coefficient, wind waves and circulation interaction (wave setup), minimum depth (H 0 ) in the wetting and drying algorithm, and spatially constant horizontal eddy viscosity (ESLM) forced by tides and hurricane winds. Furthermore, sensitivity analysis to Manning's n coefficient and the interaction of waves and circulation were analyzed by using three different numerical meshes. Manning's coefficient analysis was divided into waterway (rivers, bay and shore, and open ocean) and overland. Overall, the rivers exhibited a larger sensitivity, and M 2 amplitude and maximum water elevations were reduced by 0.20 m and 0.56 m, respectively, by using a high friction value; similarly, high friction reduced maximum water levels up to 0.30 m in overland areas; the wave setup depended on the offshore wave height, angle of breaking, the profile morphology, and the mesh resolution, accounting for up to 0.19 m setup inside the bay; minimum depth analysis showed that H 0 = 0.01 added an artificial mass of water in marshes and channels, meanwhile H = 0.1 partially solved this problem; and the eddy viscosity study demonstrated that the ESLM = 40 values reduced up to 0.40 m the peak of the maximum water levels in the upper side of narrow rivers.

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BackgroundThe literature indicates that chronic obstructive pulmonary disease (COPD) affects cardiac autonomic control. In this study, we conducted a literature review in order to investigate the heart rate variability (HRV) in COPD subjects.MethodsA search was performed in Medline database, using the link between the keywords: “autonomic nervous system”, “cardiovascular system”, “COPD” and “heart rate variability”.ResultsThe search resulted in a total of 40 references. Amongst these references, the first exclusion resulted in the barring of 29 titles and abstracts, which were not clearly related to the purpose of review. This resulted in a total of 11 articles that were then read and utilized in the review. The selected studies indicated that there is significant reduction of HRV in patients with COPD, characterized by reduction of indices that assess parasympathetic activity in addition to dealing with the global autonomic modulation. We also established that supervised exercise can reduce these harmful effects in COPD patients. Also, it was reported that the use of non-invasive ventilation in these patients may contribute to the improvement of respiratory symptoms, with no impairing, and may even induce positive responses in cardiac autonomic regulation.ConclusionThe studies indicate a need for further investigations to guide future therapies to improve the treatment of cardiovascular system in the respiratory diseases.

Hurricane storm surge is one of the most costly natural hazards in the United States. Numerical modeling to predict and estimate hurricane surge flooding is currently widely used for research, planning, decision making, and emergency response. Land cover plays an important role in hurricane surge numerical modeling because of its impacts on the forcing (changes in wind momentum transfer to water column) and dissipation (bottom friction) mechanisms of storm surge. In this study, the hydrodynamic model ADCIRC was used to investigate predicted surge response in bays on the central and lower Texas coast using different land cover data sets: (1) Coastal Change Analysis Program for 1996, 2001, and 2006; (2) the National Land Cover Dataset for 1992Dataset for , 2001Dataset for , and 2006 and (3) the National Wetlands Inventory for 1993. Hypothetical storms were simulated with varying the storm track, forward speed, central pressure, and radius to maximum wind, totaling 140 simulations. Data set choice impacts the mean of maximum surges throughout the study area, and variability in the surge prediction due to land cover data set choice strongly depends on storm characteristics and geographical location of the bay in relation to storm track. Errors in surge estimation due to land cover choice are approximately 7% of the surge value, with change in surge prediction varying by as much as 1 m, depending on location and storm condition. Finally, the impact of land cover choice on the accuracy of simulating surges for Hurricane Bret in 1999 is evaluated.

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