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 (−0.01–0.09) and hit rate (0.11–0.22) but worse in terms of the false-alarm ratio (0.04–0.14). 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

Long-term sea-level rise necessitates a commitment to adaptation: a first order assessment

Without adaptation, sea-level rise (SLR) will put more people at risk of flooding. This requires a timely and adequate commitment to adaptation. In this paper, we show how adaptation needs to unfold over time to manage climate-induced SLR. We use a novel scenario-neutral approach, applied globally and subsequently combined with SLR and population scenarios, to assess when, where, and how fast to adapt up to 2150. As rates of SLR accelerate, adaptation needs to occur at an increasing pace or at a larger scale. While it is certain that adaptation will be necessary, it is uncertain when and how fast. After only ~0.15m SLR relative to 2020, 1 million people need to adapt to permanent submergence and the amount of people at risk of a 100-year flood increases with 21% to 83 million people. This would occur in the next 30 (20-45) years for RCP4.5 and within 25 (18-36) years under RCP8.5, assuming no change in protection or population. The uncertainty in timing increases with higher SLR, albeit for some impacts it can still a matter of time. Population at risk of a 100-year flood doubles after 0.75m SLR which could occur by ~2080 (2068-2088), 2100 (2085-2130), or 2150 (2115-beyond 2150) under a high-end, RCP8.5, or RCP4.5 scenario respectively. The rate, at which the risk increases, differs strongly per country. In some countries an additional 1-5 million people of the present population will be at risk of a 100-year flood within the next two decades, while others have more time to adapt but will see rapid growth of risk past 2100. Combining SLR impacts with projected population change further increases the number of people at risk of a 100-year flood by ~13% between 2040-2060 (under both RCP8.5-SSP5 or RCP4.5-SSP2). This can be managed through protecting, floodproofing or limiting developments in high-risk areas. A commitment to adaptation is inevitable to maintain risk at present levels. With increasing warnings of the potential for accelerated SLR due to rapid ice sheet melt, adaptation may need to happen faster and sooner than previously anticipated which can have consequences for how to adapt. Failure to acknowledge the potential and long-term (including beyond 2100) adaptation commitment in development and adaptation planning may lead to a commitment gap and subsequently expensive retrofitting of infrastructure, creation of stranded assets, and less time to adapt at greater cost. In contrast, considering the long-term adaptation commitment can support timely adaptation and alignment with other societal goals

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

Twitter Flood Mapping Scripts: First Release

The increasing number and severity of floods, driven by phenomena such as urbanization, deforestation, subsidence and climate change, create a growing need for accurate and timely flood maps. In this paper we present and evaluate a method to create deterministic and probabilistic flood maps from Twitter messages that mention locations of flooding. A deterministic flood map created for the December 2015 flood in the city of York (UK) showed good performance (F(2) =  0.69; a statistic ranging from 0 to 1, with 1 expressing a perfect fit with validation data). The probabilistic flood maps we created showed that, in the York case study, the uncertainty in flood extent was mainly induced by errors in the precise locations of flood observations as derived from Twitter data. Errors in the terrain elevation data or in the parameters of the applied algorithm contributed less to flood extent uncertainty. Although these maps tended to overestimate the actual probability of flooding, they gave a reasonable representation of flood extent uncertainty in the area. This study illustrates that inherently uncertain data from social media can be used to derive information about flooding

Impacts of metal mining on river systems: a global assessment

This is the author accepted manuscript. The final version is available from the American Association for the Advancement of Science via the DOI in this record Data and materials availability: The Water and Planetary Health Analytics (WAPHA) global metal mines database is divided into four components. Publicly available data on (i) active and (ii) inactive metal mines are available from the US Geological Survey Mineral Resources Data System [https://mrdata.usgs.gov/mrds/ (31)], the BritPits database of the British Geological Survey [https://www.bgs.ac.uk/datasets/britpits/ (32)], and the S&P Global Market Intelligence database [https://www.spglobal.com/marketintelligence/en/campaigns/metals-mining (33)]. In addition, data for ~100,000 additional active and inactive mines obtained from academic and gray literature are stored in the WAPHA database [https://doi.org/10.5061/dryad.j3tx95xmg (29)]. Publicly available data relating to (iii) TSFs and (iv) TDFs are available from ICOLD/UNEP [https://books.google.co.uk/books?id=8W0hAQAAIAAJ (34)], the World Information Service on Energy [https://wise-uranium.org/mdaf.html (35)], the World Mine Tailings Failures and Global Tailings Portal databases [https://tailing.grida.no/ (36)]. Additional TSF/TDF data obtained from academic and gray literature are stored in the WAPHA database [https://doi.org/10.5061/dryad.j3tx95xmg (29)]. Modeling was implemented procedurally in MATLAB v9.9.0 (R2020b) (37) with the open source TopoToolbox MATLAB program for the analysis of digital elevation models (https://topotoolbox.wordpress.com). The modeling workflow is presented in fig. S8 with example code available in the WAPHA database [https://doi.org/10.5061/dryad.j3tx95xmg (29)]An estimated 23 million people live on floodplains affected by potentially dangerous concentrations of toxic waste derived from past and present metal mining activity. We analyzed the global dimensions of this hazard, particularly in regard to lead, zinc, copper, and arsenic, using a georeferenced global database detailing all known metal mining sites and intact and failed tailings storage facilities. We then used process-based and empirically tested modeling to produce a global assessment of metal mining contamination in river systems and the numbers of human populations and livestock exposed. Worldwide, metal mines affect 479,200 kilometers of river channels and 164,000 square kilometers of floodplains. The number of people exposed to contamination sourced from long-term discharge of mining waste into rivers is almost 50 times greater than the number directly affected by tailings dam failures.University of Lincol

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 adult’s 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) –0.12, 0.13) P=0.95; executive function, standard mean difference of 0.08 (95% CI, –0.06, 022) P=0.26; and motor skills standard mean difference of 0.11 (95% CI –0.17, 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