58 research outputs found
A globally applicable framework for compound flood hazard modeling
Coastal river deltas are susceptible to flooding from pluvial,
fluvial, and coastal flood drivers. Compound floods, which result from the
co-occurrence of two or more of these drivers, typically exacerbate impacts
compared to floods from a single driver. While several global flood models
have been developed, these do not account for compound flooding. Local-scale
compound flood models provide state-of-the-art analyses but are hard to
scale to other regions as these typically are based on local datasets.
Hence, there is a need for globally applicable compound flood hazard
modeling. We develop, validate, and apply a framework for compound flood
hazard modeling that accounts for interactions between all drivers. It
consists of the high-resolution 2D hydrodynamic Super-Fast INundation of CoastS (SFINCS) model, which is
automatically set up from global datasets and coupled with a global
hydrodynamic river routing model and a global surge and tide model. To test
the framework, we simulate two historical compound flood events, Tropical
Cyclone Idai and Tropical Cyclone Eloise in the Sofala province of Mozambique, and compare
the simulated flood extents to satellite-derived extents on multiple days
for both events. Compared to the global CaMa-Flood model, the
globally applicable model generally performs better in terms of the critical
success index (â0.01â0.09) and hit rate (0.11â0.22) but worse in
terms of the false-alarm ratio (0.04â0.14). Furthermore, the simulated flood
depth maps are more realistic due to better floodplain connectivity and
provide a more comprehensive picture as direct coastal flooding and pluvial flooding
are simulated. Using the new framework, we determine the dominant flood
drivers and transition zones between flood drivers. These vary significantly
between both events because of differences in the magnitude of and time lag
between the flood drivers. We argue that a wide range of plausible events
should be investigated to obtain a robust understanding of compound flood
interactions, which is important to understand for flood adaptation,
preparedness, and response. As the model setup and coupling is automated,
reproducible, and globally applicable, the presented framework is a
promising step forward towards large-scale compound flood hazard modeling.</p
Measuring compound flood potential from river discharge and storm surge extremes at the global scale
The interaction between physical drivers from oceanographic, hydrological, and meteorological processes in coastal areas can result in compound flooding. Compound flood events, like Cyclone Idai and Hurricane Harvey, have revealed the devastating consequences of the co-occurrence of coastal and river floods. A number of studies have recently investigated the likelihood of compound flooding at the continental scale based on simulated variables of flood drivers, such as storm surge, precipitation, and river discharges. At the global scale, this has only been performed based on observations, thereby excluding a large extent of the global coastline. The purpose of this study is to fill this gap and identify regions with a high compound flooding potential from river discharge and storm surge extremes in river mouths globally. To do so, we use daily time series of river discharge and storm surge from state-of-the-art global models driven with consistent meteorological forcing from reanalysis datasets. We measure the compound flood potential by analysing both variables with respect to their timing, joint statistical dependence, and joint return period. Our analysis indicates many regions that deviate from statistical independence and could not be identified in previous global studies based on observations alone, such as Madagascar, northern Morocco, Vietnam, and Taiwan. We report possible causal mechanisms for the observed spatial patterns based on existing literature. Finally, we provide preliminary insights on the implications of the bivariate dependence behaviour on the flood hazard characterisation using Madagascar as a case study. Our global and local analyses show that the dependence structure between flood drivers can be complex and can significantly impact the joint probability of discharge and storm surge extremes. These emphasise the need to refine global flood risk assessments and emergency planning to account for these potential interactions
Zinc intake, status and indices of cognitive function in adults and children: a systematic review and meta-analysis
In developing countries, deficiencies of micronutrients are thought to have a major impact on child development; however, a consensus on the specific relationship between dietary zinc intake and cognitive function remains elusive. The aim of this systematic review was to examine the relationship between zinc intake, status and indices of cognitive function in children and adults. A systematic literature search was conducted using EMBASE, MEDLINE and Cochrane Library databases from inception to March 2014. Included studies were those that supplied zinc as supplements or measured dietary zinc intake. A meta-analysis of the extracted data was performed where sufficient data were available. Of all of the potentially relevant papers, 18 studies met the inclusion criteria, 12 of which were randomised controlled trials (RCTs; 11 in children and 1 in adults) and 6 were observational studies (2 in children and 4 in adults). Nine of the 18 studies reported a positive association between zinc intake or status with one or more measure of cognitive function. Meta-analysis of data from the adultâs studies was not possible because of limited number of studies. A meta-analysis of data from the six RCTs conducted in children revealed that there was no significant overall effect of zinc intake on any indices of cognitive function: intelligence, standard mean difference of <0.001 (95% confidence interval (CI) â0.12, 0.13) P=0.95; executive function, standard mean difference of 0.08 (95% CI, â0.06, 022) P=0.26; and motor skills standard mean difference of 0.11 (95% CI â0.17, 0.39) P=0.43. Heterogeneity in the study designs was a major limitation, hence only a small number (n=6) of studies could be included in the meta-analyses. Meta-analysis failed to show a significant effect of zinc supplementation on cognitive functioning in children though, taken as a whole, there were some small indicators of improvement on aspects of executive function and motor development following supplementation but high-quality RCTs are necessary to investigate this further
Crowdsourcing Methods for Data Collection in Geophysics: State of the Art, Issues, and Future Directions
Data are essential in all areas of geophysics. They are used to better understand and manage systems, either directly or via models. Given the complexity and spatiotemporal variability of geophysical systems (e.g., precipitation), a lack of sufficient data is a perennial problem, which is exacerbated by various drivers, such as climate change and urbanization. In recent years, crowdsourcing has become increasingly prominent as a means of supplementing data obtained from more traditional sources, particularly due to its relatively low implementation cost and ability to increase the spatial and/or temporal resolution of data significantly. Given the proliferation of different crowdsourcing methods in geophysics and the promise they have shown, it is timely to assess the stateâofâtheâart in this field, to identify potential issues and map out a way forward. In this paper, crowdsourcingâbased data acquisition methods that have been used in seven domains of geophysics, including weather, precipitation, air pollution, geography, ecology, surface water and natural hazard management are discussed based on a review of 162 papers. In addition, a novel framework for categorizing these methods is introduced and applied to the methods used in the seven domains of geophysics considered in this review. This paper also features a review of 93 papers dealing with issues that are common to data acquisition methods in different domains of geophysics, including the management of crowdsourcing projects, data quality, data processing and data privacy. In each of these areas, the current status is discussed and challenges and future directions are outlined
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