Implementing Physical Activity Studies During COVID-19 and Winter Storms: Lessons Learned

Patient recruitment and retention are challenging for longitudinal studies. Stay-at-home restrictions for the Galveston and Houston regions in 2020 for COVID-19 and in 2021 for the Winter Storms shut down elective healthcare activities and created additional recruitment barriers during the implementation of a 12-month study examining the physical function of older adults receiving a total knee arthroplasty. This presentation describes recruitment and retention strategies during natural disasters. Ten participants started the study during the pandemic and 6 remained through the winter storms (3 withdrew, 1 no showed). Physical activity monitors were distributed and collected through mail, patient reported outcomes were completed online or over the phone, clinician-initiated measures were only collected when clinics were open, and efforts were made to minimize staff burden and follow evolving hospital guidelines. Most importantly, regular communication and follow-up with participants, research team, and department personnel created a sense of community.

Modelling the Hydrological Effects of Woodland Planting on Infiltration and Peak Discharge Using HEC-HMS

Woodland planting is gaining momentum as a potential method of natural flood management (NFM), due to its ability to break up soil and increase infiltration and water storage. In this study, a 2.2 km2 area in Warwickshire, England, planted with woodland every year from 2006 to 2012, was sampled using a Mini Disk infiltrometer (MDI). Infiltration measurements were taken from 10 and 200 cm away from the trees, from November 2019 to August 2021. Two individual hydrological models were built using the US Hydraulic Engineering Center Hydrological Modelling System (HEC-HMS), to model the effects of infiltration change on peak flows from the site throughout the summer and winter. The models were calibrated and validated using empirical data; the Nash and Sutcliffe Efficiency (NSE) was used as an indicator of accuracy. Results from this study show that woodland planting reduced peak flow intensity compared to impermeable land cover by an average of 6%, 2%, and 1% for 6-h, 24-h, and 96-h winter storms, respectively, and 48%, 18%, and 3% for 6-h, 24-h, and 96-h summer storms, respectively. However, grassland simulations show the greatest reduction in peak flows, being 32%, 21%, and 10%, lower than woodland for 6-, 24-, and 96-h winter storms, respectively, and 6%, 3%, and 0.5% lower than woodland for 6-, 24-, and 96-h summer storms, respectively.

Geomorphologic Recovery of North Captiva Island from the Landfall of Hurricane Charley in 2004

Hurricane Charley made landfall on the Gulf Coast of Florida on 13 August 2004 as a category 4 hurricane, devastating North Captiva Island. The hurricane caused a breach to occur to the southern end of the island, which naturally healed itself over the course of three years. By 2008, the cut was completely repaired geomorphologically. LiDAR data analysis shows the northern half of the island has been subjected to persistent erosion from 1998–2018, while the southern half experienced accretion since 2004, including the complete closure of the “Charley cut”. The maximum volume of sediment erosion in the northern sector of the island (R71–R73) from 2004–2018 was −85,710.1 m3, which was the source of southern accretion. The breached area of the island (R78b–R79a) obtained 500,163.9 m3 of sediments from 2004–2018 to heal the cut made by Hurricane Charley. Along with LiDAR data analysis, Google Earth Pro historical imageries and SANDS volumetric analysis confirmed the longshore transport of sediments from the northern to the southern end of the island. Winter storms are mainly responsible for this southerly longshore transport and are hypothesized to be the main factor driving the coastal dynamics that restored the breach and helps in widening the southern end of North Captiva Island.

Cold-Water Coral Reefs in the Langenuen Fjord, Southwestern Norway—A Window into Future Environmental Change

Ocean warming and acidification pose serious threats to cold-water corals (CWCs) and the surrounding habitat. Yet, little is known about the role of natural short-term and seasonal environmental variability, which could be pivotal to determine the resilience of CWCs in a changing environment. Here, we provide continuous observational data of the hydrodynamic regime (recorded using two benthic landers) and point measurements of the carbonate and nutrient systems from five Lophelia pertusa reefs in the Langenuen Fjord, southwestern Norway, from 2016 to 2017. In this fjord setting, we found that over a tidal (<24 h) cycle during winter storms, the variability of measured parameters at CWC depths was comparable to the intra-annual variability, demonstrating that single point measurements are not sufficient for documenting (and monitoring) the biogeochemical conditions at CWC sites. Due to seasonal and diurnal forcing, parts of the reefs experienced temperatures up to 4 °C warmer (i.e., >12 °C) than the mean conditions and high CT concentrations of 20 µmol kg−1 over the suggested threshold for healthy CWC reefs (i.e., >2170 µmol kg−1). Combined with hindcast measurements, our findings indicate that these shallow fjord reefs may act as an early hotspot for ocean warming and acidification. We predict that corals in Langenuen will face seasonally high temperatures (>18 °C) and hypoxic and corrosive conditions within this century. Therefore, these fjord coral communities could forewarn us of the coming consequences of climate change on CWC diversity and function.

Archaeological and Natural Indicators of Sea-Level and Coastal Changes: The Case Study of the Caesarea Roman Harbor

Archaeological and geomorphological features, as well as traces left by tsunamis, earthquakes, and vertical earth-crust displacements, are used to identify sea-level and coastal changes. Such features may be displaced, submerged or eroded by natural processes and human activities. Thus, identifying ancient sea levels and coastal changes associated with such processes may be controversial and often leads to misinterpretations. We exemplify the use of sediment deposits and sea-level and coastline indicators by discussing the enigmatic demise of the Roman harbor of Caesarea, one of the greatest marine constructions built in antiquity, which is still debated and not fully understood. It was suggested that the harbor destruction was mainly the result of either tectonic subsidence associated with a local, active fault line, or as a result of an earthquake/tsunami that struck the harbor. Here we examine and reassess the deterioration of the harbor in light of historical records, and geological, geomorphological and archaeological studies of natural and man-made features associated with the harbor. We show that the alleged evidence of an earthquakes or tsunami-driven damage to the outer breakwaters is equivocal. There is no supporting evidence for the assumed tectonic, active fault, nor is there a reliable historic account of such a catastrophic destruction. It is suggested that geo-technic failure of the breakwater’s foundations caused by a series of annual winter storms was the main reason for the destruction and ultimate collapse of the western basin of the harbor. The breakwaters were constructed on unconsolidated sand that was later washed away by storm waves and sea currents that frequently hit the Israeli coast and undercut the breakwaters. The pounding effect of the waves could have contributed to the destruction by scouring and liquefying the sandy seabed underlying the foundations. Tsunamis that may have hit Caesarea could have added to the deterioration of the breakwaters, but did not constitute the main cause of its destruction.

Assessment of Emergency Response Preparedness in Power Plant Using FEMA Method (Case Study: South Isfahan Power Plant)

Introduction: The aim of this study was to identify all activities to be sufficiently prepared for emergencies in the power plant industries using the method of the Federal Crisis Management Organization in the south Isfahan power plant. Materials and Methods: In this research, a checklist tool of 117 questions in 9 sections based on the FEMA method has been used. Checklists were localized. To check the face and content validity of the checklists, the opinions of three technical experts were used, and to check the reliability of the research subjects, the test-retest test was used, and to measure the reliability of the checklists, Cronbach's alpha coefficient was used with an emphasis on internal correlation. The obtained alpha coefficient was 0.76. Data were analyzed using SPSS software. Results: The results showed that the power plant preparedness for general emergencies is 77.5%, winter storms and extreme cold 80%, storm 73.33%, overheating 70%, chemical storage 88.57%, earthquake 65%, Fire and explosion is 87%, flood 63.33%, and lightning 92%. The highest level of preparedness with 92% was related to the lightning checklist and the lowest level of readiness with 63.33% was related to floods. Conclusion: In general, despite the differences in the readiness of the power plant against various accidents, the average level of preparedness for all accidents is higher than average. However, a number of appropriate measures must be taken in each area and the level of preparedness must be increased in cases such as fires and explosions.

Modelling winter storm impacts on insured claim ratios of residential buildings in German administrative districts

&lt;p&gt;Severe winter storms are one of the most damaging natural hazards for European residential buildings. Previous studies mainly focused on the loss ratio (loss value / total insured sum) as a monetary value for damages. In this study the focus is on the claim ratio&amp;#160;(number of claims / number of contracts), which is derived from a storm loss dataset provided by the German Insurance Association. Due to its magnitude, the claim ratio might be a more intuitive parameter for the use in impact-based warnings than the loss ratio.&lt;/p&gt;&lt;p&gt;In a first step, loss ratios and claim ratios in German administrative districts are compared to investigate differences and similarities between the two variables. While there is no significant change in the ratio between claim ratio and loss ratio with increasing wind speeds, a tendency for lower loss ratios in urban areas can be confirmed.&lt;/p&gt;&lt;p&gt;In a second step, a generalized linear model for daily claim ratios is developed using daily maximum wind gust (ERA5) and different non-meteorological indicators for vulnerability and exposure as predictor variables. The non-meteorological predictors are derived from the Census 2011. They include information about the district-average construction years, the number of apartments per buildings and others to get a better understanding of these factors concerning the number of buildings affected by windstorms. The modelling procedure is divided into two steps. First, a logistic regression model is used to model the probabilty claim ratios larger than zero. Second, generalized linear models with different link functions are compared regarding their ability to predict claim ratios larger than zero. In a cross-validation setting a criteria for model selection is implemented and the models of both steps are verified. Both steps show an improvement over the climatological forecast and in both cases the addition of data for vulnerability and exposure leads to in decrease of the mean squared error.&amp;#160;&lt;/p&gt;

Impacts of extreme wind speeds and other factors on vegetation disturbances in the German railway network

&lt;p&gt;&lt;span&gt;Winter windstorms are among the most dangerous and costly natural hazards in Central Europe. Their ability to cause tree and branch fall leads to disruptions and damages along railway systems. &lt;/span&gt;&lt;span&gt;Along the German railway network &lt;/span&gt;&lt;span&gt;the Deutsche Bahn is &lt;/span&gt;preventively&lt;span&gt; removing about 30.000 trees per year. &lt;/span&gt;&lt;span&gt;Still&lt;/span&gt;&lt;span&gt;, each year &lt;/span&gt;&lt;span&gt;a multiplicity of&lt;/span&gt;&lt;span&gt; disturbances &lt;/span&gt;&lt;span&gt;occur&lt;/span&gt; &lt;span&gt;which may lead to delays, economic damages or even train collisions.&lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;span&gt;A&lt;/span&gt;&lt;span&gt; data set with vegetation disturbance events between 2017 and 2020 along the German railway system &lt;/span&gt;&lt;span&gt;is provided by the Deutsche Bahn&lt;/span&gt;&lt;span&gt;. &lt;/span&gt;&lt;span&gt;The aim of this study is&lt;/span&gt;&lt;span&gt; to use exploratory statistics as well as machine learning methods like regression techniques or decision trees to explore the relationship between vegetation damages and meteorological parameters like wind gusts, precipitation or temperature. Additionally, tree related factors&lt;/span&gt; &lt;span&gt;and surrounding conditions like &lt;/span&gt;&lt;span&gt;ground frost and soil moisture &lt;/span&gt;&lt;span&gt;will be taken into account. Finally, we want to derive critical thresholds and combinations of weather parameters leading to significant damage risk. &lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;span&gt;We find &lt;/span&gt;&lt;span&gt;a positive relationship between vegetation disturbance and wind speeds. Especially strong winter storms leave a very clear signal in the disturbance time series. &lt;/span&gt;&lt;span&gt;For example, t&lt;/span&gt;&lt;span&gt;he highest numbers of vegetation disturbances occurred during the winter storms Sabine (10.02.2020, 515 events) and Friderike (18.01.2018, 360 events). During winter storm days the majority of events occurs in th&lt;/span&gt;&lt;span&gt;ose&lt;/span&gt;&lt;span&gt; areas &lt;/span&gt;&lt;span&gt;affected by&lt;/span&gt;&lt;span&gt; high wind speeds. Tree fall &lt;/span&gt;&lt;span&gt;disturbance&lt;/span&gt;&lt;span&gt;s&lt;/span&gt;&lt;span&gt; pe&lt;/span&gt;&lt;span&gt;a&lt;/span&gt;&lt;span&gt;k during the winter storm season between January and March, while branch fall &lt;/span&gt;&lt;span&gt;disturbance&lt;/span&gt;&lt;span&gt;s&lt;/span&gt;&lt;span&gt; peak between June and August. &lt;/span&gt;&lt;span&gt;However&lt;/span&gt;&lt;span&gt;, a high number of events occurs &lt;/span&gt;&lt;span&gt;also &lt;/span&gt;&lt;span&gt;during times of low wind speeds. &lt;/span&gt;&lt;span&gt;Additionally, high wind speeds do not necessarily lead to vegetation disturbances.&lt;/span&gt;&lt;span&gt; It is clear that other meteorological and tree related factors need to be taken into account. Compound events as well as previous weather and soil conditions are expected to affect wind throw risks.&lt;/span&gt;&lt;/p&gt;