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In recent years, the United Arab Emirates (UAE) has experienced a marked increase in extreme rainfall events, challenging urban planning and infrastructure. This study investigates four extreme rainfall events in Al Ain, UAE, between 2007 and 2020, using data from 11 rain gauges and estimates from three satellite precipitation products. These events set new rainfall records, with some gauges recording up to 195.7 mm and intensities exceeding 175 mm/hr. Comparisons revealed significant discrepancies among satellite products, which underestimated three events and overestimated one. A watershed encompassing Al Ain was delineated, and runoff from these events was simulated using the fully distributed, physically based GSSHA hydrologic model. The model provided detailed, spatially explicit runoff estimates, highlighting urban areas of Al Ain as particularly vulnerable to flooding. Despite low runoff ratios (0.11% to 3.14%) due to high infiltration rates, significant flooding occurred in urban regions, emphasizing compounded flood risks from intense rainfall and rapid urban expansion. The study discusses general mitigation strategies that can be considered to enhance Al Ain’s resilience, ensuring the safety of residents and infrastructure and managing escalating flood hazards amid increasingly extreme weather patterns. Thoroughly evaluated strategies are essential for adapting to the dynamic climate and safeguarding urban areas from future extreme weather events.

Nitrate (NO3−) is a vulnerable natural contaminant that can be found in groundwater. The estimated nitrate concentrations for four categories of wells in the northeastern arid regions of Saudi Arabia—commercial treated water stations for drinking, commercial stations of untreated water for domestic uses, private wells of residences for households, and private wells for agricultural uses—were found to be in the 16–380 mg/L range. Drinking water from all commercial treated water stations has lower nitrate levels, based on the WHO standard of 50 mg/L. In contrast, almost 33% of commercial stations with untreated water (used only for domestic purposes) in the studied areas had higher nitrate levels that were unsuitable for drinking. Approximately half of the private wells of residences and wells for agricultural uses had very high nitrate levels. They can be considered unsuitable for drinking due to excessive levels of nitrates but can be used for domestic and agricultural purposes. Thus, adopting specific strategies to reduce nitrate levels in public wells in the studied areas is crucial. The data obtained in the present study are essential for equipping decision-makers with valuable insights, allowing them to enact appropriate measures, as needed, and uphold community health in the studied regions.

AbstractThis study addresses a crucial gap in our understanding of flooding in the predominantly agricultural Qaa’Jahran watershed in Yemen, where urbanization, though currently limited in extent, is rapidly expanding. We aim to discern the effects of earth fissures on flood dynamics, particularly focusing on their present significance. It is noteworthy that, in the long run, these fissures are anticipated to accumulate soil and sediment, potentially heightening the risk of future flooding. To achieve this, we developed a comprehensive floodplain delineation model, incorporating field observations and rainfall data from the Integrated Multi-satellitE Retrievals for GPM (IMERG) algorithm. Additionally, advanced hydrologic and hydraulic models were integrated to accurately simulate runoff hydrographs and create flood inundation maps. Our findings underscore the considerable influence of earth fissures, effectively mitigating runoff volume, peak discharge, flood depths and inundated areas during storm events. It is imperative to emphasize that specific areas remain persistently vulnerable, with water levels surpassing one meter during historical floods. This reinforces the ongoing risk of flooding in targeted zones and emphasizes the necessity of implementing tailored flood management strategies. In conclusion, this study makes a significant contribution to the field, providing a comprehensive analysis of the intricate factors influencing flooding in the Qaa’Jahran watershed. The integration of flood inundation mapping, advanced hydrologic modelling and meticulous consideration of earth fissures offers a distinctive perspective on flood dynamics in a rapidly evolving and urbanizing environment. Furthermore, it highlights the critical implications for effective flood risk management and urban planning, not only in the Qaa’Jahran watershed but also in similar urbanizing regions worldwide.

Abstract Makkah region is one of the most flash flood-prone areas of Saudi Arabia due to terrain characteristics and the synoptic-scale weather conditions that intensify through interaction with the local topography causing high convective short-lived rainfall events, although these conditions are quite infrequent. Most of these events last for less than two hours. This study aims to assess the performance of five satellite precipitation products over a 1725 km2 sparsely gauged, arid basin. A fully distributed, physically based hydrologic model was forced by the five satellite precipitation products, and the evaluation included the hydrographs and runoff maps predicted by the model. Moreover, the propagation of the satellite rainfall errors into runoff predictions was quantified. Large variations and significant biases were found in satellites precipitation estimates compared to the available ground rainfall measurements. The Early IMERG product showed the best agreement with the reported total rainfall accumulations followed by Late IMERG while the other products significantly underestimated precipitation accumulations. Comparison with estimated runoff peaks showed that the Early IMERG product has the lowest errors in runoff peaks. Therefore, the hydrographs produced by the Early IMERG product were used as a reference to quantify the propagation of satellite precipitation errors into runoff predictions over the Makkah watershed. The results clearly indicated that both systematic and random rainfall errors were significantly amplified in runoff predictions.

Global Digital Elevation Models (GDEMs) have been increasingly used to assess the risk of flooding worldwide. However, their effectiveness and the performance of flood risk models in areas with complex terrain, such as Jeddah, Saudi Arabia, have not been comprehensively studied. This study aims to compare the performance of five distinct Global Digital Elevation Models (GDEMs) − 30-m SRTM, 30-m ASTER, 90-m MERIT, 10 m Sentinel-1 DEM, and 12.5 m ALOSPALSAR - in estimating the inundation extent and depth of the Jeddah watershed, including three dams. Both hydrological and hydraulic modeling approaches were utilized to achieve this objective. The study findings revealed that all Global Digital Elevation Models (GDEMs) produced similar watershed boundaries in the mountain area (Wadi Qaws), except for ALOS-PALSAR, which generated a different watershed boundary from previous reports and studies. However, all GDEMs failed to accurately delineate the drainage area of one of the dams, except for SRTM and ALOS-PALSAR. Moreover, ASTER and SRTM products provided the closest estimates to ground observations, producing peak discharges of 114.1 m3/s and 110 m3/s, respectively. For the entire watershed, encompassing mountain, urban, and coastal areas, GDEMs demonstrated significant differences in the watershed boundary, streams, outlet location, and peak discharge at the watershed outlet. In addition, each GDEM's flood inundation map was significantly distinct. Overall, the results suggest that SRTM outperformed all other GDEMs in the mountain area.

Abstract Background Apps have been shown to be an effective tool in changing patients’ behaviours in orthodontics and can be used to improve their compliance with treatment. The Behaviour Change Techniques (BCTs) and quality (using MARS) within these apps have previously not been published. Objectives 1. To evaluate the quality of these apps aiming to change behaviour. 2. To assess BCTs used in patient focused orthodontic apps. Methods The UK Google Play and Apple App Stores were searched to identify all orthodontic apps and 305 apps were identified. All 305 apps were assessed for the presence of BCTs using an accepted taxonomy of BCTs (Behaviour Change Wheel (BCW)), widely utilised in healthcare. Of those containing BCTs, the quality was assessed using the Mobile App Rating Scale (MARS), a validated and multi-dimensional tool which rates apps according to 19 objective criteria. Data collection was carried out by two calibrated, independent assessors and repeated after 6 weeks for 25% of the apps by both assessors. Results BCTs were found in 31 apps, although only 18 of them were analysed for quality and 13 apps were excluded. Six different BCTs were identified: these were most commonly ‘prompts/cues’, and ‘information about health consequences’. All apps were shown to be of moderate quality (range 3.1–3.7/5). Inter-rater and intra-rater reliability for BCT and quality assessment were excellent. Conclusions The current availability of orthodontic apps of sufficient quality to recommend to patients is very limited. There is therefore a need for high-quality orthodontic apps with appropriate BCTs to be created, which may be utilised to improve patients’ compliance with treatment.

The purpose of this study is to understand flooding in a 1,725-km2 arid catchment in Makkah Province, Saudi Arabia, with very limited ground observations. This mountainous catchment includes densely urbanized areas built on lowlands and in the ephemeral streams of flood zones, which makes them vulnerable to flooding. A physically based, fully distributed hydrologic model was produced by three Integrated Multi-satellite Retrievals for Global Precipitation Measurement Mission (IMERG) high-resolution satellite rainfall products, together with a limited number of ground observations to simulate recent flood events. The hydrologic model was calibrated and validated using two events that occurred in 2010 and 2018, respectively. Details of the flooding in the urbanized areas were examined through simulation of a third event. Significant differences were noticed when the three IMERG rainfall products (Early, Late, and Final) were compared in terms of the spatial patterns and total half-hour accumulation for the three events. Accordingly, a method was developed to remove the biases of IMERG rainfall estimates using ground observations. The Early product was the closest to ground observations, producing peak discharges of 428 m3/s and 663.6 m3/s for calibration and validation storm events, respectively, and resulted in better estimates of the observed peak discharge even before adjustment. The Final run product significantly underestimated rainfall, as peak discharges of 204 m3/s and 123 m3/s for calibration and validation storm events, respectively, resulted in an amplified underestimation of the runoff.

This study was conducted to investigate the spatiotemporal changes of land use/land cover (LULC) along the eastern coast of the United Arab Emirates (UAE) over a 20-year period using an integration of remote sensing and Geographic Information Systems techniques. The impact of land use change on flooding potential was also investigated through hydrologic model simulations. Landsat images of the years 1996, 2006 and 2016 were processed and analyzed. Change detection was carried out to assess changes in the built-up areas. Furthermore, the impact of urbanization on flooding was assessed using a hydrologic model in two major watersheds of Fujairah Emirate. It was observed that for the period 1996–2006 the vegetation and the built-up areas had increased at a rate of 11.23% and 24.56%, respectively. For the period 2006–2016, this expansion more than doubled in terms of the vegetation class (27.51%) and slightly increased for the built-up class (28.98%). The change detection analysis revealed that urbanization has mostly occurred along the coastal boundary. Hydrologic model simulations quantified the role of urbanization in increasing the flooding potential. The increase depends on watershed characteristics and the rate of change in urbanization and the magnitude of the rainfall event.

The aim of this study is to build a flood simulation model for the city of Hafr Al-Batin catchment area. The model consists of a hydrologic model, a hydraulic model and pre- and post-processing tools. A geographic information system-based modelling interface was used to pre-process the terrain and rainfall data and generate input files for hydrologic and hydraulic models. Soil map data, land cover map, land use map and digital elevation model was used to delineate the physical watershed's characteristics. The runoff estimation was based on the widely known Soil Conservation Service curve number approach. The hydrologic/hydraulic model simulations simulated the runoff hydrograph corresponding to different design storms and helped to delineate the resulting flood inundation maps. The results indicate good agreement between the delineated inundation map and the hazard map developed by the municipality. They also show that the location of the city complicates the runoff response for small storms creating two distinct peaks. The results of this study can be utilized for planning purposes and in the design of flood control structures as the study has estimated the runoff corresponding to different design storms and used hydraulics and geospatial data in delineating the flood zones.

Conventionally, in situ rainfall data are used to develop Intensity Duration Frequency (IDF) curves, which are one of the most effective tools for modeling the probability of the occurrence of extreme storm events at different timescales. The rapid recent technological advancements in precipitation sensing, and the finer spatio-temporal resolution of data have made the application of remotely sensed precipitation products more dominant in the field of hydrology. Some recent studies have discussed the potential of remote sensing products for developing IDF curves. This study employs a 19-year NEXRAD Stage-IV high-resolution radar data (2002–2020) to develop IDF curves over the entire state of Texas at a fine spatial resolution. The Annual Maximum Series (AMS) were fitted to four widely used theoretical Extreme Value statistical distributions. Gumble distribution, a unique scenario of the Generalized Extreme Values (GEV) family, was found to be the best model for more than 70% of the state’s area for all storm durations. Validation of the developed IDFs against the operational Atlas 14 IDF values shows a ±27% difference in over 95% of the state for all storm durations. The median of the difference stays between −10% and +10% for all storm durations and for all return periods in the range of (2–100) years. The mean difference ranges from −5% for the 100-year return period to 8% for the 10-year return period for the 24-h storm. Generally, the western and northern regions of the state show an overestimation, while the southern and southcentral regions show an underestimation of the published values.

The catastrophic implication of harmful algal bloom (HAB) events in the Arabian Gulf is a strong indication that the study of the spatiotemporal distribution of chlorophyll-a and its relationship with other variables is critical. This study analyzes the relationship between chlorophyll-a (Chl-a) and sea surface temperature (SST) and their trends in the Arabian Gulf and the Gulf of Oman along the United Arab Emirates coast. Additionally, the relationship between bathymetry and Chl-a and SST was examined. The MODIS Aqua product with a resolution of 1 × 1 km2 was employed for both chlorophyll-a and SST covering a timeframe from 2003 to 2019. The highest concentration of chlorophyll-a was seen in the Strait of Hormuz with an average of 2.8 mg m−3, which is 1.1 mg m−3 higher than the average for the entire study area. Three-quarters of the study area showed a significant correlation between the Chl-a and SST. The shallow (deep) areas showed a strong positive (negative) correlation between the Chl-a and SST. The results indicate the presence of trends for both variables across most of the study area. SST significantly increased in more than two-thirds of the study area in the summer with no significant trends detected in the winter.

Tropical Storm Imelda struck the southeast coastal regions of Texas from 17–19 September, 2019, and delivered precipitation above 500 mm over about 6000 km2. The performance of the three IMERG (Early-, Late-, and Final-run) GPM satellite-based precipitation products was evaluated against Stage-IV radar precipitation estimates. Basic and probabilistic statistical metrics, such as CC, RSME, RBIAS, POD, FAR, CSI, and PSS were employed to assess the performance of the IMERG products. The products captured the event adequately, with a fairly high POD value of 0.9. The best product (Early-run) showed an average correlation coefficient of 0.60. The algorithm used to produce the Final-run improved the quality of the data by removing systematic errors that occurred in the near-real-time products. Less than 5 mm RMSE error was experienced in over three-quarters (ranging from 73% to 76%) of the area by all three IMERG products in estimating the Tropical Storm Imelda. The Early-run product showed a much better RBIAS relatively to the Final-run product. The overall performance was poor, as areas with an acceptable range of RBIAS (i.e., between −10% and 10%) in all the three IMERG products were only 16% to 17% of the total area. Overall, the Early-run product was found to be better than Late- and Final-run.

In studies on the health impacts of air pollution, regression analysis continues to advance far beyond classical linear regression, which many scientists may have become familiar with in an introductory statistics course. With each new level of complexity, regression analysis may become less transparent, even to the analyst working with the data. This may be especially true in count data regression models, where the response variable (typically given the symbol y) is count data (i.e., takes on values of 0, 1, 2, …). In such models, the normal distribution (the familiar bell-shaped curve) for the residuals (i.e., the differences between the observed values and the values predicted by the regression model) no longer applies. Unless care is taken to correctly specify just how those residuals are distributed, the tendency to accept untrue hypotheses may be greatly increased. The aim of this paper is to present a simple histogram of predicted and observed count values (POCH), which, while rarely found in the environmental literature but presented in authoritative statistical texts, can dramatically reduce the risk of accepting untrue hypotheses. POCH can also increase the transparency of count data regression models to analysts themselves and to the scientific community in general.

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Continuous monitoring of stream water quality is needed as it has significant impacts on human and ecological health and well-being. Estimating water quality between sampling dates requires model simulation based on the available geospatial and water quality data for a given watershed. Models such as the Soil and Water Assessment Tool (SWAT) can be used to estimate the missing water quality data. In this study, SWAT was used to estimate water quality at a monitoring station near the outlet of the San Antonio River. Precipitation data from both rain gauges and weather radar were used to force the SWAT simulations. Virtual rain gauges which were based on weather radar data were created in the approximate centres of the 163 sub-watersheds of the San Antonio River Basin for SWAT simulations. This method was first tested in a smaller watershed in the middle of the Guadalupe River Basin resulting in increased model efficiency in simulating surface run-off. The method was then applied to the San Antonio River watershed and yielded good simulations for surface run-off (R2 = 0.7), nitrate (R2 = 0.6) and phosphate (R2 = 0.5) at the watershed outlet (Goliad, TX – USGS (United States Geological Survey) gauge) as compared to observed data. The study showed that the proper use of weather radar precipitation in SWAT model simulations improves the estimation of missing water quality data.

Riyadh, the capital of the Kingdom of Saudi Arabia, has experienced unusual levels of urbanization in the past few decades, making it one of the fastest growing cities in the world. This paper examines flood hazards in the rapidly urbanizing catchment of Al-Aysen in Riyadh. Remote sensing and geographic information system techniques were employed to obtain and prepare input data for hydrologic and hydraulic models, with the former based on the very popular curve number approach. Due to the limited nature of the rainfall data, observations from two rain gauges in the vicinity of the catchment were used to estimate design storms. The hydrologic model was run in a semi-distributed mode by dividing the catchment into many sub-catchments. The impact of urbanization on run-off volume and peak discharge resulting from different storms was investigated, with various urbanization scenarios simulated. Flood hazard zones and affected streets were also identified through hydrologic/hydraulic model simulation. The mismatch between administrative and catchment boundaries can create problems in flood risk management for similar cities since hydrologic processes and flood hazards are based on the hydrologic connectivity. Since flooding events impact the road network and create driving hazards, governmental decision-makers must take the necessary precautions to protect drivers in these situations.

This study uses fatal crash data and geospatial analysis to examine the temporal and spatial distribution of rain-related fatal crashes in Texas from 1982 to 2011. The data were obtained from the Fatality Analysis Reporting System maintained by the National Highway Traffic Safety Administration. The Getis–Ord Gi*(di) statistic was used to identify spatial clustering patterns of rain-related fatal crashes and their correlation with rainfall and compare them to spatial patterns of other crashes. The spatial statistical analysis reveals spatial patterns for rain-related crashes that are clustered in different areas at different levels of confidence. The temporal variability of raw and normalized fatal crashes and rain-related crashes was also investigated at the state level. Although the population of Texas increased by more than 67% over the study period, with a corresponding increase in the number of vehicles, the fatal crashes and rain-related crashes in Texas did not increase but decreased instead. Results suggest that rain is a contributor to crashes in few counties but at less than 95% confidence in some of the wetter counties. These counties should be the focus of further research and detailed analysis to identify underlying crash contributing factors such that safety countermeasures can be developed.

The present work includes studying the kinetics of the adsorptionof two sugars (maltose and glucose)on activated carbon (GAC) and comparison between them. These sugars are used as draw solution in the forward osmosis process in MOD-SET system(manipulated osmosis desalination system, MOD combined with solute exchange technique, SET). In this work, batch experiment in a stirred tank was carried out to study kinetics adsorption. The experiment was carried out using HPLC to determine the concentrations of sucrose and maltosebefore and after adsorption. The kinetic models used are pseudo-first order, pseudo-second order, intraparticle diffusion and mass transfer model. The findings indicates that sucrose and maltose sorption onto GAC are both well represented by the pseudo second order model.

Satellite-based precipitation products are becoming available at very high temporal and spatial resolutions, which has accelerated their use in various hydro-meteorological and hydro-climatological applications. Because the quantitative accuracy of such products is affected by numerous factors related to atmospheric and terrain properties, validating them over different regions and environments is needed. This study investigated the performance of two high-resolution global satellite-based precipitation products: the climate prediction center MORPHing technique (CMORPH) and the latest version of the Integrated Multi-SatellitE Retrievals for the Global Precipitation Mission (GPM) algorithm (IMERG), V06, over the United Arab Emirates from 2010 through 2018. The estimates of the products and that of 71 in situ rain gauges distributed across the country were compared by employing several common quantitative, categorical, and graphical statistical measures at daily, event-duration, and annual temporal scales, and at the station and study area spatial scales. Both products perform quite well in rainfall detection (above 70%), but report rainfall not observed by the rain gauges at an alarming rate (more than 30%), especially for light rain (lower quartile). However, for moderate and intense (upper quartiles) rainfall rates, performance is much better. Because both products are highly correlated with rain gauge observations (mostly above 0.7), the satellite rainfall estimates can probably be significantly improved by removing the bias. Overall, the CMORPH and IMERG estimates demonstrate great potential for filling spatial gaps in rainfall observations, in addition to improving the temporal resolution. However, further improvement is required, regarding the overestimation and underestimation of small and large rainfall amounts, respectively.

Cardiac catheterization is a common word for a set of procedures that are implemented using this method, such as coronary angiography and left ventricle angiography. Coronary angiography is that invasive procedure which assumed as the golden standard for the diagnosis, estimation, and curing of heart diseases. There is a shortage of research of undergraduate students. The purpose of this descriptive cross-sectional study has been conducted to assess nurses’ knowledge regarding cardiac catheterization and associated factors at General Hospital in Rania city. Data were collected from a stability sample of 60 nurses using demographic form instead of the section with the conductive questionnaire of Knowledge regarding cardiac catheterization . The majority of study participants were female (81.7%) Therefore, 70% of nurses were married. About 43.3% of study participants were Academic nurse while (40%) of them were Institute nurse, however level of knowledge form institute graduated nurses has a highest level and the majority of participants were not trained (95%). Results acquired have shown that there is no sufficient knowledge of nurses regarding cardiac catheterization, among all levels of nurses and there is a significant relationship between most socio-demographic data in true question but there are opposite result for false questions. We therefore recommend the training course by ministry of health for nurses to improve the knowledge and health awareness regarding cardiac catheterization.

This paper presents a study on the potential of osmotic energy for power production. The study includes both pilot plant testing and theoretical modelling as well as cost estimation. A projected cost of £30/MWh of clean electricity could be achieved by using a Hydro-Osmotic Power (HOP) plant if a suitable membrane is used and the osmotic potential difference between the two solutions is greater than 25 bar; a condition that can be readily found in many sites around the world. Results have shown that the membrane system accounts for 50%–80% of the HOP plant cost depending on the salinity difference level. Thus, further development in membrane technology and identifying suitable membranes would have a significant impact on the feasibility of the process and the route to market. As the membrane permeability determines the HOP process feasibility, this paper also describes the effect of the interaction between the fluid and the membrane on the system permeability. It has been shown that both the fluid physical properties as well as the membrane micro-structural parameters need to be considered if further development of the HOP process is to be achieved.

HydroViz is a Web-based, student-centered, educational tool designed to support active learning in the field of Engineering Hydrology. The design of HydroViz is guided by a learning model that is based on learning with data and simulations, using real-world natural hydrologic systems to convey theoretical concepts, and using Web-based technologies for dissemination of the hydrologic education developments. This model, while being used in a hydrologic education context, can be adapted in other engineering educational settings. HydroViz leverages the free Google Earth resources to enable presentation of geospatial data layers and embed them in web pages that have the same look and feel of Google Earth. These design features significantly facilitate the dissemination and adoption of HydroViz by any interested educational institutions regardless of their access to data or computer models. To facilitate classroom usage, HydroViz is populated with a set of course modules that can be used incrementally within different stages of an engineering hydrology curriculum. A pilot evaluation study was conducted to determine the effectiveness of the HydroViz tool in delivering its educational content, to examine the buy-in of the program by faculty and students, and to identify specific project components that need to be further pursued and improved. A total of 182 students from seven freshmen and senior-level undergraduate classes in three universities participated in the study. HydroViz was effective in facilitating students' learning and understanding of hydrologic concepts and increasing related skills. Students had positive perceptions of various features of HydroViz and they believe that HydroViz fits well in the curriculum. In general, HydroViz tend to be more effective with students in senior-level classes than students in freshmen classes. Lessons gained from this pilot study provide guidance for future adaptation and expansion studies to scale-up the application and utility of HydroViz and other similar systems into various hydrology and water-resource engineering curriculum settings. The paper presents a set of design principles that contribute to the development of other active hydrology educational systems.

Florence made landfall on the southeastern coast of North Carolina (NC) generating torrential rainfall and severe flooding that led to 53 fatalities in three states (NC, SC, and VA) and $16⁻$40 billion in damage. Seventy-seven percent (77%) of the fatalities occurred in the rural flood plains of NC with Duplin county reporting a high of eight deaths. Approximately 50% of the total number of hurricane-related fatalities across the three states were vehicle-related. The predominant demographic at risk were males over the age of 50 years. The type of property damage was in line with other major hurricanes and predominantly affected residential structures (93% of the total number of damaged buildings). Florence is among the top 10 costliest hurricanes in U.S. history with approximately 50% of the damage projected as uninsured losses due to residential flooding. The cumulative 5-day rainfall resulted in major flooding along the Cape Fear, Lumberton, and Neuse rivers where many industrial waste sites (hog manure lagoons and coal ash pits) are located. Several of these waste sites located in the flood plain were breached and have likely cross-contaminated the waterways and water treatment operations. The observed extent of the flooding, environmental contamination, and impact to public health caused by Florence will add to the long-term disaster related mortality and morbidity rates and suggests an expansion of the 100-yr flood hazard zone to communicate the expanded risk to the public.

Property damages caused by hydrometeorological disasters in Texas during the period 1960–2016 totaled $54.2 billion with hurricanes, tropical storms, and hail accounting for 56%, followed by flooding and severe thunderstorms responsible for 24% of the total damages. The current study provides normalized trends to support the assertion that the increase in property damage is a combined contribution of stronger disasters as predicted by climate change models and increases in urban development in risk prone regions such as the Texas Gulf Coast. A comparison of the temporal distribution of damages normalized by population and GDP resulted in a less statistically significant increasing trend per capita. Seasonal distribution highlights spring as the costliest season (March, April and May) while the hurricane season (June through November) is well aligned with the months of highest property damage. Normalization of property damage by GDP during 2001–2016 showed Dallas as the only metropolitan statistical area (MSA) with a significant increasing trend of the 25 MSAs in Texas. Spatial analysis of property damage per capita highlighted the regions that are at greater risk during and after a major disaster given their limited economic resources compared to more urbanized regions. Variation in the causes of damage (wind or water) and types of damage that a “Hurricane” can produce was investigated using Hazus model simulation. A comparison of published damage estimates at time of occurrence with simulation outputs for Hurricanes Carla, 1961; Alicia, 1983; and Ike, 2008 based on 2010 building exposure highlighted the impact of economic growth, susceptibility of wood building types, and the predominant cause of damage. Carla and Ike simulation models captured less than 50% of their respective estimates reported by other sources suggesting a broad geographical zone of damage with flood damage making a significant contribution. Conversely, the model damage estimates for Alicia are 50% higher than total damage estimates that were reported at the time of occurrence suggesting a substantial increase in building exposure susceptible to wind damage in the modeled region from 1983 – 2010.

Hurricanes and other severe coastal storms have become more frequent and destructive during recent years. Hurricane Harvey, one of the most extreme events in recent history, advanced as a category IV storm and brought devastating rainfall to the Houston, TX, region during 25–29 August 2017. It inflicted damage of more than $125 billion to the state of Texas infrastructure and caused multiple fatalities in a very short period of time. Rainfall totals from Harvey during the 5-day period were among the highest ever recorded in the United States. Study of this historical devastating event can lead to better preparation and effective reduction of far-reaching consequences of similar events. Precipitation products based on satellites observations can provide valuable information needed to understand the evolution of such devastating storms. In this study, the ability of recent Integrated Multi-satellitE Retrievals for Global Precipitation Mission (GPM-IMERG) final-run product to capture the magnitudes and spatial (0.1° × 0.1°)/temporal (hourly) patterns of rainfall resulting from hurricane Harvey was evaluated. Hourly gridded rainfall estimates by ground radar (4 × 4 km) were used as a reference dataset. Basic and probabilistic statistical indices of the satellite rainfall products were examined. The results indicated that the performance of IMERG product was satisfactory in detecting the spatial variability of the storm. It reconstructed precipitation with nearly 62% accuracy, although it systematically under-represented rainfall in coastal areas and over-represented rainfall over the high-intensity regions. Moreover, while the correlation between IMERG and radar products was generally high, it decreased significantly at and around the storm core.

Accurate precipitation measurements for high magnitude rainfall events are of great importance in hydrometeorology and climatology research. The focus of the study is to assess the performance of satellite-based precipitation products against a gauge adjusted Next-Generation Radar (NEXRAD) Stage IV product during high magnitude rainfall events. The assessment was categorized across three spatial scales using watershed ranging from ~200–10,000 km2. The propagation of the errors from rainfall estimates to runoff estimates was analyzed by forcing a hydrologic-model with the satellite-based precipitation products for nine storm events from 2004 to 2015. The National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center (CPC) Morphing Technique (CMORPH) products showed high correlation to the NEXRAD estimates in all spatial domains, and had an average Nash-Sutcliffe coefficient of 0.81. The Global Precipitation Measurement (GPM) Early product was inconsistent with a very high variance of Nash-Sutcliffe coefficient in all spatial domains (from −0.46 to 0.38), however, the variance decreased as the watershed size increased. Surprisingly, Tropical Rainfall Measuring Mission (TRMM) also showed a very high variance in all the performance statics. In contrast, the un-corrected product of the TRMM showed a relatively better performance. The errors of the precipitation estimates were amplified in the simulated hydrographs. Even though the products provide evenly distributed near-global spatiotemporal estimates, they significantly underestimate strong storm events in all spatial scales.

A new O-ring flat sheet membrane module design was used to investigate the performance of Vacuum Membrane Distillation (VMD) for water desalination using two commercial polytetrafluoroethylene (PTFE) and polyvinylidene fluoride (PVDF) flat sheet hydrophobic membranes. The design of the membrane module proved its applicability for achieving a high heat transfer coefficient of the order of 103 (W/m2 K) and a high Reynolds number (Re). VMD experiments were conducted to measure the heat and mass transfer coefficients within the membrane module. The effects of the process parameters, such as the feed temperature, feed flow rate, vacuum degree, and feed concentration, on the permeate flux have been investigated. The feed temperature, feed flow rate, and vacuum degree play an important role in enhancing the performance of the VMD process; therefore, optimizing all of these parameters is the best way to achieve a high permeate flux. The PTFE membrane showed better performance than the PVDF membrane in VMD desalination. The obtained water flux is relatively high compared to that reported in the literature, reaching 43.8 and 52.6 (kg/m2 h) for PVDF and PTFE, respectively. The salt rejection of NaCl was higher than 99% for both membranes.