Robustness - Science topic

Using SmartPLS4 in data analysis. I obtained two VIFs which are > to 10 and a HTMT which is equal to 1.07.

How to justify adequately these values and which robust and relevant references can be used to persuade the reviewers?

Thank you

Is flood forecasting for the rivers of the European continent a scientific operation? Can a human mechanism be created to accurately predict floods in the European continent?

Pluvial flooding is a result of overland flow and ponding before the runoff enters any watercourse, drainage system or sewer, or cannot enter it because the network is full to capacity, usually caused by intense rainfall. River and coastal floods get the most attention since they are largest and last the longest, while pluvial floods are relatively marginalized in research. Therefore, the main goal of this research was to show risk posed by pluvial floods, their connection to current global climate change processes, present effects of flooding in European cities, as well as what we can expect in the future. Furthermore, the aims were to present and get more familiar with scientific projects, strategies, directives and measures devised both on national and international levels, that deal with urban pluvial flood issues across the European continent. Climate change projections indicate that there will be an increase in the frequency and intensity of rainfall events throughout Europe and along with ongoing urbanization, the problem of pluvial flooding will most certainly require more attention, which it is starting to receive. Some countries have already developed their strategies and initiatives and implemented both structural and non-structural measures, such as spatial planning, constructional measures, information systems, reducing land sealing through policies, building codes and standards, on-site improvement of retention, infiltration, evaporation, and rainfall water recycling with the use of green roofs, permeable or porous pavements, rain gardening or urban rainwater harvesting. At the same time, there are numerous research papers, studies, conferences and workshops devoted to the problem of pluvial flooding and its management carried out in an attempt to properly deal with this hazard. Keywords: urban areas; pluvial flooding; climate change; precipitation; scientific projects; water management; Europe. Floods are the most prevalent natural hazard in Europe. Between 1998 and 2009, Europe suffered over 213 major damaging floods (Bakker et al., 2013). Coastal and river floods receive the most attention as they are generally the floods that are largest and last the longest, while pluvial floods are relatively underrepresented in research (Nicklin et al., 2019), most likely due to the smaller scale of individual events (Dawson et al., 2008). The absolute record of annual flood loss of all types of floods in Europe was observed in August 2002, when the material damage exceeded €20 billion, in nominal value (Kundzewicz et al., 2012). However, there is an increasing problem of massive and intensifying flood damages in areas away from rivers. For example, in Great Britain two flood events in summer 2007 cost nearly €6 billion (Falkenhagen, 2010). Recent research has suggested that due to the frequent nature of pluvial floods, cumulative direct damage to property caused by those type of floods equals or may even exceed damage from river and coastal floods (Nicklin et al., 2019). Pluvial floods produce less damage but the frequency is higher and the cumulative damage over the years can be just as high as from fluvial flooding events (Acosta-Coll et al., 2018) or even higher (Szewrański et al., 2018a). For instance, of the 11 000 properties flooded in autumn of 2000 in the UK, 83% were outside coastal and fluvial floodplains, suggesting that flooding was caused by local pluvial events, sewer flooding or groundwater (Dawson et al., 2008). Pluvial flooding can be defined as flooding that results from overland flow and ponding before the runoff enters any watercourse, drainage system or sewer, or cannot enter it because the network is full to capacity and is usually caused by intense localized rainfall. This problem is enhanced in cities with insufficient or non-existent sewer systems (Acosta-Coll et al., 2018). Also, Falconer et al. (2009) state that it’s important not to confuse ‘pluvial flooding’ with ‘surface water flooding’. According to them, surface water flooding usually refers to combined flooding in urban areas during heavy rainfall. As such, it includes pluvial flooding, sewer flooding, flooding from small open-channels and overland flows from groundwater springs. Pluvial flooding is also different from ‘flash flooding’, which may also be associated with high-intensity rainfall but usually arises from a watercourse. Further in the text of this paper terms “urban pluvial flooding”, “inland pluvial flooding”, “pluvial flooding” ,“intra-urban system flooding”, “urban drainage flooding” and “surface water flooding” will be used interchangeably. Pluvial flooding only occurs when the rainfall rate exceeds the capacity of storm water drains to evacuate the water and the capacity of the ground to absorb water and this is usually associated with short-duration storms (of up to three hours) and with rainfalls that exceed 20 – 25 mm per hour; but it can also occur after rainfalls of smaller intensity, approximately 10 mm per hour, that happen over longer periods, especially if the ground surface is impermeable by being developed, saturated or frozen (Houston et al., 2011). However, pluvial floods depend not only on the amount and duration of precipitation but also on the hydrological characteristics of the basin, such as runoff magnitude, antecedent moisture condition, drainage area and soil type (Acosta-Coll et al., 2018). In addition, land use change, particularly urbanization, is also changing the proportion of precipitation which becomes runoff and also reduces the delay between precipitation and the runoff reaching a watercourse (Green et al., 2013). According to Li (2012) the urban storm water logging problems result from various causes, such as the uneven distribution of precipitation in time and space, inadequate urban water-logging emergency response systems, decreasing green areas and filling of waterbodies because of urbanization and insufficient capacity in the storm water drainage system without proper maintenance and upgrading.Other reasons for frequent inundation include outdated sewer-stormwater systems, greater areas of impervious urban fabric and larger urban population (Sušnik et al., 2014). Increasing urbanization often results in an expansion of impermeable areas, whereby the higher proportion of sealed soils result in an increased runoff volume and a decreased response time of a catchment, while further risk comes from urban areas expanding into flood risk areas (Swart et al., 2012). The main goals of this research are twofold: a) first, to show connection between current global climate change processes and urban pluvial flooding, and present effects of flooding in European cities, as well as what we can expect in the future; b) and secondly, to present strategies, directives and measures devised both on national and international levels, as well as scientific projects that deal with urban pluvial flood issues in order to contribute to better mitigation and adaptation actions in European cities. For our analysis we used the scientific literature in the last 10 to 12 years, as well as official documents from international institutions (such as UN, EU) or national governments.The occurance of pluvial or flash floods due to highintensity rainfall events is nothing new. However, it appears that the frequency with which they are happening, their impact on human lives, damage and disruption is increasing, very likely because of the climate change, and unfortunately it’s predicted to increase further (Falconer et al., 2009). As presented by IPCC Fifth Assessment Report (2014) on the world-wide impacts of climate change on rainfall extremes and urban drainage, it was ob-served that typical increases in rainfall intensity at small urban hydrology scales range from 10% to 60% from control periods in the recent past (typically 1961–1990) up to 2100 (Figure 1). These changes in extreme short-duration rainfall events may have significant impacts for urban drainage systems and pluvial flooding. The Danish Meteorological Institute (DMI) predicts that the intensity of the heavy downpours will rise by 20-50% by 2100, the most for the very rare events which will have great implication on how the rain will run off surfaces and on the burden on sewer systems and watercourses (Copenhagen Climate Adaptation Plan, 2009). Climate change is expected to increase the frequency and intensity of rainfall events throughout Europe (Sušnik et al., 2014), especially in the central and northern parts (“STAR-FLOOD”; https://www.starflood.eu/). Flood hazard may also rise during wetter and warmer winters, with increasingly more frequent rain and less frequent snow (“STAR-FLOOD”; https://www.starflood.eu/), while warmer atmosphere will hold higher amount of water vapor (Kundzewicz, 2015). There will be a marked increase in extremes in Europe, in particular, in heat waves, droughts, and heavy precipitation events, according to the Fifth IPCC Assessment Report (2014). Changes in extreme precipitation depend on the region, with high probability of increased extreme precipitation in Northern Europe (all seasons) and Continental Europe (except summer). This may result in more frequent and more intense floods of various types such as local, sudden floods (flash floods); extensive, longer-lasting pluvial and fluvial floods; coastal floods and snowmelt floods (Menne & Murray, 2013). With the expected changes, the drainage system built today probably won’t be able to meet the desired service levels in the future (Zhou et al., 2012).On the other hand, some authors state that climatechange impacts on future extreme precipitation, and consequently on pluvial flooding, is surrounded by large uncertainties. One of the uncertainties lies in the incomplete understanding of processes and components in the Earth’s system, resulting in large model uncertainties and thus large variations in projected change of future precipitation extremes between different models (Kaspersen et al., 2017). In addition, climate models provide an assessment of only anthropogenic impacts and usually don’t account for natural changes that will occur at the same time, while questions arise about the assumptions behind the climate models and how these assumptions influence the projections (Arnbjerg-Nielsen et al., 2013). However, the uncertainties associated with climate change should not be an argument for delaying investigating its possible impact on pluvial flooding or postponing adaptation actions. Instead, uncertainties should be accounted for while flexible and sustainable solutions should be sought, some of which will be presented in the following sections. Current risks from pluvial flooding and future projections Risks and adverse effects posed by pluvial flooding are numerous (Figure 2). The direct and indirect impacts of extreme weather include losses in economic terms, the damaging and destruction of private buildings and urban infrastructure, the loss of human lives and the degradation of safety and the deterioration of water quality (Szewrański et al., 2018a). In addition, flooding, especially as a result of intense precipitation, is the predominant cause of weather-related disruption to the transport sector (Pregnolato et al., 2017) and traffic delay and inconvenience (Zhou et al., 2012). Examples of indirect effects are also lost working hours and health impacts on affected residents, which can manifest if sewer water flows onto streets or if pluvial flood water stands stagnant (Sušnik et al., 2014). Furthermore, indirect impacts may occur beyond the location and time of a flood event, such as long-lasting trauma and stress (Szewrański et al., 2018b). On the other hand, average mortality for just drainage floods is low. More than half of the drainage events in the dataset causes one or zero fatalities (Jonkman & Vrijling, 2008). According to the European Environment Agency (2012) there are several factors that tend to increase the risk of pluvial flooding: • Old drainage infrastructure often does not keep pace with an on-going urbanization.Combined sewer systems in older areas (rainfall drains into sewers that are carrying sewage and both are transferred to sewage treatment) which are more vulnerable to excessive rainfall than a separate treatment.The existence of inadequate maintenance of the drainage channels to monitor debris and solid waste within such systems. • Inadequate discharge of excess water to the regional water system. Douglas et al. (2010) analyzed potential weak points of risk management of serious pluvial flooding in the case study of flooding in Heywood, Greater Manchester in 2004 and 2006. Here it was revealed that all agencies involved in flood risk management, and in particular planners, require more robust, and more localized data. This study has also highlighted that the general public are confused about who does what and who is responsible for pluvial flood risk management, and are not so well informed about how best to protect their properties. Also, many agencies underestimate the ongoing health and social effects of flooding. Modeling studies show that urbanization and increasing rainfall intensity will increase drainage overflow volumes that will result in more frequent and severe pluvial flooding (Miller & Hutchins, 2017). At present about 55% of the global population live in cities and by 2050 almost two thirds of the world’s population will live in urban environments (Sörensen et al., 2016). Over 80% of the population in Britain lives in urban areas while it’s predicted that population growth will reach 74.3 million by 2039 (Miller & Hutchins, 2017). A new study shows that the total urban area exposed to flooding in Europe has increased by 1000% over the past 150 years (Jongman, 2018). This means that urbanization with an increase of non-permeable surfaces and lack of natural drainage created additional flooding issues that did not previously exist and that never before there had been so many human assets that were in the way of floods like today. And according to Kazmierczak & Cavan (2011), the negative correlations between green space cover and the proportion of an area susceptible to flooding suggest that the increasing amount of sealed surfaces in an area aggravates the problem of flooding through increased runoff and reduced infiltration capacity. Furthermore, Guerreiro et al. (2017) developed a map of Europe which represents a percentage of city flooded for historical hourly rainfall for a 10-year return period (Figure 3). The growing urban population and degree of urbanization puts great pressure on the existing drainage systems, increasing the likelihood of them being overwhelmed (“Urban pluvial flooding and climate change: London (UK), Rafina (Greece) and Coimbra (Portugal)”; https://www.imperial.ac.uk/grantham/ research/resources-and-pollution/water-securityand-flood-risk/urban-flooding/). Systems currently designed for a 20-year return period of flooding, might flood with a mean recurrence interval of 5 years by the end of the century (“Flash floods and Urban flooding”; https://www.climatechangepost.com). On 7th August in 2002, an inch of rain fell in central London in 30 minutes during the evening “rush hour”, resulting in the closure of 5 mainline railway stations, and considerable disruption as London’s drainage infrastructure was too old and overloaded to cope with such events (Crichton, 2005). According to the UK statistics (“Facts About Floods in the UK”; https://rainbow-int-franchise.co.uk/flooding-statistics-uk/) the residents of around 2.4 million UK properties are at risk from fluvial and coastal flooding each year, while a further 2.8 million are susceptible to surface water – or pluvial – flooding. Kaspersen et al. (2017) in their research found that urban development in Odense and Vienna influences the extent of flooding considerably, while only marginally affecting the degree of flooding for Strasbourg and Nice. This suggests that, while further soil sealing in Odense and Vienna (and similar urban areas) should be considered very carefully, as it may substantially increase their exposure to pluvial flooding, urban development effect on pluvial flooding varies locally and should be considered with that in mind. The financial implications of pluvial flooding can be significant. It is estimated that in the Netherlands, between 1986 and 2009 the total damage from pluvial floods was €674 million (Sušnik et al., 2014). Nicklin et al. (2019) did the research and used a combination of 3D flood modelling and the WSS (Dutch ‘Waterschadeschatter’) flood damage estimation tool to assess direct flood damage from a 60 mm/1-h pluvial flood event in two urban areas: Belgrave (Leicester, United Kingdom) and Lombardijen (Rotterdam, the Netherlands). For Belgrave, direct damage was estimated at roughly €11 million, while for Lombardijen direct damage was €12.4 million. In England and Wales during summer of 2007 there were about 48 000 households and nearly 7300 businesses flooded (Menne & Murray, 2013) while insurance claims from the homes and businesses affected are approaching £3 billion and other costs amount to around £1 billion (Environment Agency, 2007). According to Bernet et al. (2017) in Switzerland, of all damage due to surface water floods and fluvial floods between 1999 and 2013, surface water floods are responsible for at least 45 % of the flood damage to buildings and 23 % of the associated direct tangible losses. Houston et al. (2011) estimated that almost 2 million people in urban areas in the UK face an annual 0.5 per cent probability (‘1 in 200-year’) of pluvial flooding. Most of the areas with lower percentage of city flooded are in the north and west coastal parts of Europe, while the higher percentages are predominately in continental and Mediterranean areas (Guerreiro et al., 2017). When talking about the Mediterranean region, major population and economic growth has taken place along its coast in the past century, which led to extension of urban settlements inside flood prone areas (Gaume et al., 2016). Lugeri et al. (2006) analyzed flood risk exposure in 13 European countries and found that Slovenia has the highest share of urban fabric built in flood prone areas - more than 70%. An estimated 3.8 million properties are thought to be at risk from pluvial flooding in England which represent around 10% of all properties, while in Scotland some 15 000 properties have been estimated to be at pluvial flood risk (Houston et al., 2011). The expected annual damages from urban flooding in the UK are estimated at £0.27 billion which compares to £0.6 - 2.1 billion for fluvial and coastal flooding and the estimate for the future is that this could be as much as £2 to 15 billion by 2080 compared to £1.5 – 20 billion for fluvial and coastal flooding (Dawson et al., 2008). Furthermore, Evans et al. (2008) in the Pitt Review estimated that the future risk from the intra-urban system flooding might rise by the 2080s to be of the same order as fluvial and coastal flood risk. Menne & Murray (2013) did the research on the floods in the European region and their health effects and found that in the period between 2005 and 2010, 16 countries were affected by pluvial floods: Bosnia and Herzegovina, Croatia, Czech Republic, Hungary, Malta, Poland, Republic of Moldova, Serbia, Slovenia, Spain, Sweden, Tajikistan, Republic of North Macedonia, Turkey, Ukraine, United Kingdom (England and Wales). And as mentioned in the previous part, with the projection for the continuous increase of heavy rain contribution to total precipitation (Santato et al., 2013) and with current urbanization and population growth, it is estimated that by 2050, 3.2 million people in urban areas in the UK could be at risk from pluvial flooding, which is an increase of 1.2 million (Houston et al., 2011). Figure 4, developed by European Environment Agency (2012), shows the projected change in the annual number of days with heavy rainfall in 2071–2100 against the reference period (1961–1990). Projections for regions south of the Alps show a decline in the number of days with extreme precipitation of up to five days and more. Most regions north of the Alps expect an increase, mostly of one to three days. In addition, this map shows the degree of mean soil sealing per urbanized areas of cities. Cities with high soil sealing and an increasing number of intensive rainfall events — in particular in north-western and northern Europe — face a higher risk of urban drainage flooding. Nevertheless, cities in areas with a decreasing number of such events but high soil sealing still face a flooding risk, just less often. Cities of high and low soil sealing can be found in all regions and do not cluster in a particular region with the exception of low sealing levels in cities in Finland, Norway, Slovenia and Sweden. Cyprus, Estonia, Greece and Luxembourg are countries with a high share of cities with elevated levels of soil sealing. Examples of pluvial flooding events across European continent Gaume et al. (2009) have compiled a comprehensive data record of flash floods for seven European hydrometeorological regions. This inventory was the first step towards an atlas of extreme flash floods in Europe while the objective was to document a minimum number of 30 floods in each region, especially the events considered as the most extreme or ‘‘top 30” flash floods which are homogeneously distributed over the selected period. However, this research didn’t include pluvial floods and there couldn’t be found any similar analysis that would focus on pluvial flooding events in Europe. Therefore, this section will provide a few examples of pluvial flooding occurrences that had significant economic and social impact on the communities in Europe affected by this hazard. In the summer of 2007, floods that struck much of the United Kingdom during June and July affected hundreds of thousands of people. This event was the most serious inland pluvial and fluvial flood ever recorded, with 13 deaths, about 7000 people rescued from floodwaters by the emergency services, and about 48 000 households and nearly 7300 businesses flooded (Menne & Murray, 2013), while the insurance claims from the homes and businesses flooded approached £3 billion (Environment Agency, 2007). The floods caused the loss of essential services, almost half a million people were without water or electricity supply, transport networks failed, a dam breach was narrowly averted, and emergency facilities and telecommunications were put out of action (Menne & Murray, 2013). During June, July, and August of 2007 a succession of depressions tracked over the UK, bringing heavy rainfall and triggering multiple flooding events (Stuart-Menteth, 2007). With 414 mm of rain, England and Wales haven’t seen a wetter May to July since records began in 1766 (Environment Agency, 2007). On 12th June 2007, a total of 98.3 mm of rain fell in one hour in East and South Belfast which resulted in both fluvial flash flooding and pluvial flooding which caused major disruption throughout Belfast with over 400 properties affected (Falconer, 2009). Two particularly large floods hit within just four weeks of each other. First, the northeast of England was badly affected following heavy rainfall on June 25th, which caused flooding in cities and towns such as Sheffield, Doncaster, Rotherham, Louth, and Kingston-upon-Hull (Figure 5). Some areas were hit again by further flooding after more severe rains on July 20th, which affected a much larger area of central England, including Oxford, Gloucester, Tewkesbury, Evesham, and Abingdon (Stuart-Menteth, 2007). According to the emergency services, that summer saw the greatest number of search and rescue missions in the country since the Second World War (Environment Agency, 2007).Just a couple of years before this event, at the end of July in 2002, another extreme case of storms affected much of the UK, especially West and central Scotland, and produced extreme amount of rainfall at several locations in localized intense heavy downpours generating surface water flooding and pluvial flooding affecting small urban watercourses, drainage systems and sewers (Falconer, 2009). The full storm began at approximately 10:30 am on 30 July 2002 and continued for a total of approximately 10 hours, it measured 75mm depth and had a maximum intensity of 94.5 mm/h which can be linked to a maximum return period of 100 years (Wilson & Spiers, 2003). According to the European Environment Agency (2012), on July 2nd 2011, Copenhagen in Denmark was hit by a huge thunderstorm after a substantially hot period. During a two hour period over, 150 mm of rain fell in the city centre. This became the biggest single rainfall in Copenhagen since measurements began in the mid-1800s. The city’s sewers were unable to handle all of the water and as a result many streets were flooded and sewers overflowed into houses, basements and onto streets thereby flooding the city (Figure 6). Insurance damages alone were estimated at €650–700 million. Damage to municipal infrastructure not covered by insurance, such as roads, amounted to €65 million. The Marmara region in north-western Turkey suffered from a series of floods during the period from 7th until 10th September in 2009, with 35 000 people affected, 32 human losses and more than $100 million of economic damage. The 24-hour rainfall amounts varied between 100 and 253 mm during the flooding period and additional factors such as land use changes, urbanization, poor drainage, and construction and settling in the flood-prone areas worsened consequences of the floods, especially in major urban areas of the region. Istanbul suffered most from floods where some suburban districts were submerged and the city’s highways were turned into rivers and transportation and communication infrastructures were damaged (Kömüşcü & Çelik, 2012). On the 18th September in 2007 an extreme rainfall event affected approximately one-third of Slovenia, causing the damage of €200 million and six casualties (Rusjan et al., 2009). In the town Železniki, the observed maximum daily amount of rainfall was nearly 200 mm, which was the highest recorded amount of precipitation since the beginning of the measurements in 1930 and it devastated the town of Železniki: three people lost their lives, while it was estimated that the flood caused nearly €100 million of damage (Markošek, 2008). In June of 2010 storms hit the south-east of France and the large amounts of heavy rain led to localized flash flooding and pluvial flooding which caused severe damage and loss of life in southern France, and a number of towns in the department of Var were affected, with hundreds of homes flooded (Moreau & Roumagnac, 2010). Torrential rainfall hit southern Italy and produced major flooding in parts of Sicily and Calabria on October 4th 2018. The urban area of Catania, Sicily was strongly hit where streets turned into rivers (Figure 7). Catania experienced intense rainfall with about 50 mm falling in only 20 minutes as the severe thunderstorm passed (“Major flash floods hit urban areas of Catania, Sicily”; http://www.severe-weather.eu/news/major-flash-floods-hit-urban-areas-of-catania-sicily/).In May and June of 2016, Germany was struck with recurring thunderstorms, with damage across Germany totaled €2.6 billion (Faust, 2018). Parts of Germany have come to a standstill after storms and torrential rain, especially in the south in May this year as well. One person died and daily life has been disrupted. Heavy rain and thunderstorms, mainly in southern and central Germany, have left rivers overflowing and streets flooded (Silk, 2019).Pluvial flooding risk management Adopted measures and strategies Measures and strategies that increase the specific response capacity of cities to flooding, according to Swart et al. (2012), can be classified into structural and non-structural measures or into grey, green and soft measures (Figure 8). The response capacity measures include spatial planning, constructional measures, risk acceptance, behavioral adaptation, information systems, technical flood protection and increasing natural water retention in catchment areas and reducing land sealing. Structural measures decrease the risk and they are mostly effective, but they usually involve management problems. On the other hand, nonstructural measures reduce vulnerability and when they are permanent they are reliable but can be socially costly while when they are temporary and less costly they become less reliable (Working Group F, 2010). These can be classified as passive and active where active non-structural measures are those that promote direct interaction with people, such as training, local management, early warning systems for people, public information, while passive measures involve policies, building codes and standards, and land use regulations (Acosta-Coll et al., 2018). Some of the adaptation measures involve the on-site improvement of retention, infiltration, evaporation, and rainfall water recycling with the use of green roofs, permeable or porous pavements, rain gardening, urban rainwater harvesting, or the application of water-absorbing geocomposites (Szewrański et al., 2018b). The problem of pluvial flooding is slowly starting to receive more attention, according to the interviews conducted by Mees et al. (2016) and numerous research papers (Candela & Aronica, 2016; Falconer et al., 2009; Szewrański et al., 2018a/b; Fritsch et al., 2016), conferences and workshops (Third Hydrology Forum, Oslo, 2016; Flash Floods and Pluvial Flooding Workshop, Calgari, 2010; 3rd European Conference on Flood Risk Management, Lyon, 2016) done on this topic. Through further examples of different projects, strategies and initiatives implemented in European countries separately or in mutual cooperation across the continent, various methods of urban pluvial flooding management will be observed. For instance, The EU Directive on the assessment and management of flood risks (pluvial floods included), often referred to as the Floods Directive, entered into force on 26th November 2007, which main aim is to reduce and manage the risks posed by floods to human health, the environment, cultural heritage and economic activity (Bakker et al., 2013). Floods Directive contains a three-stage approach: first, a preliminary flood risk assessment must be undertaken, then flood hazard maps and flood risk maps are to be prepared and in the final stage, member states must establish Flood Risk Management plans. Priest et al. (2016) did an analysis which indicates that the effect of the Flood Directive is highly variable among the six European countries they studied (Belgium, England, France, the Netherlands, Poland, and Sweden), but despite the shortcomings of the Flood Directive in directly affecting flood risk outcomes, it has had a positive influence in stimulating discussion and flood risk management planning in member states that were perhaps lagging behind. Or, another example, according to Land Use Consultants (2003) Sustainable Urban Drainage Systems, involves moving away from conventional piped systems and toward engineering solutions that mimic natural drainage processes and minimize adverse effects on the environment which may take the form of infiltration systems whereby water is soaked away into the ground or they may be attenuation systems, which release flows gradually to watercourses or sewers. Separate storm water and foul water systems can increase drainage capacity and reduce the likelihood of sewage mixing with pluvial flood water (Houston et al., 2011). As mentioned previously, there are different uncertainties that surround risk assessments for urban flooding, particularly connected to the climate change models and small-scale projections of extreme precipitation. Kaspersen & Kirsten (2017) proposed a way to address these uncertainties by using a very detailed integrated data and modelling approach, such as the DIAS Danish Integrated Assessment System tool they described in detail, which can help identify particularly vulnerable and valuable assets that climate change adaptation measures should protect. While the warning about extreme weather events in Germany is done nationwide by the German Meteorological Service, flood forecasting and warning is decentralized in Germany which poses the main challenge of handling of measured data coming from various providers and monitoring networks in individual formats (Osnabrugge et al., n.d.). German Water Association (DWA) set up different working groups with the aim to establish technical standards and provide affected interest groups with guidelines and practical advice which in the year 2013 during a heavy rainfall event with a return period of about 100 years has proven to significantly reduce flood risk and gain acceptance in public (Fritsch et al., 2016). As a further example, Hamburg has introduced a separate rain water drainage system in recent years and introduced financial penalties, if rain water is not locally drained by home owners (Schlünzen & Bohnenstengel, 2016). Projects related with pluvial flooding issues The following table represents various examples of different projects, strategies and initiatives implemented in European countries separately or in mutual cooperation across the continent that deal with and manage pluvial flooding. Good examples of pluvial flooding risk management could be found outside of Europe as well and perhaps studied further in the attempt to adapt good practices from across the world. For example, China is currently in the process of implementing a policy initiative called sponge cities to holistically tackle urban pluvial flooding while promoting sustainable urban development with reduced environmental impact. This initiative is well-grounded in scientific under .Conclusions Pluvial flooding, or flooding that is a result of intense localized rainfall that exceeds the capacity of a drainage system, is getting wider awareness in Europe. The estimates that cumulative damage from pluvial flooding over the years can be just as high as from fluvial flooding events or even higher is worrying and a cause for a concern. Risks posed by pluvial flooding are numerous, from economic losses, destruction of private buildings and urban infrastructure to the loss of human lives, decrease of water and health impacts. With climate change projections that there will be an increase in the frequency and intensity of rainfall events throughout Europe and with ongoing urbanization with its own effects, adaptive and sustainable solutions should be explored and pursued as soon as possible. The problem of pluvial flooding is most certainly starting to receive more attention and some countries have already developed their strategies for dealing with this hazard. As this review shows, there are already numerous researches, papers, studies, conferences and workshops dedicated to the problem of pluvial flooding and its management. Various project strategies and initiatives that deal with pluvial flooding risk management have been implemented in some of the European countries separately or in cooperation with one another. Some of the measures presented include spatial planning, constructional measures, risk acceptance, information systems, early warning systems for people, reducing land sealing through policies, building codes and standards and land use regulations, as well as adaptation measures such as the on-site improvement of retention, infiltration, evaporation, and rainfall water recycling with the use of green roofs, permeable or porous pavements, rain gardening or urban rainwater harvesting.

Acosta-Coll, M., Merelo, F., Peiro, M.M., & De la Hoz, E. (2018). Real-Time Early Warning System Design for Pluvial Flash Floods—A Review. Sensors, 18, 2255. DOI:10.3390/s18072255 Arnbjerg-Nielsen, K., Willems, P., Olsson, J., Beecham, S., Pathirana, A., Gregersen, I., Madsen, H., & Nguyen, V.-T.V. (2013). Impacts of Climate Change on Rainfall Extremes and Urban Drainage Systems. Water science and technology, 68(1), 16-28. DOI:10.2166/wst.2013.251 Ashley, R., Blanksby, J., Maguire, T. & Leahy, T. (2019). Frameworks for Adapting to Flood Risk: Experiences from the EU’s Flood Resilient City Project. Bakker, M.H.N., Green, C., Driessen, P., Hegger, D., Delvaux, B., van Rijswick, M., Suykens, C., Beyers, J.C, Deketelaere, K., van Doorn-Hoekveld, W., & Dieperink, C. (2013). Flood Risk Management in Europe: European flood regulation. STAR-FLOOD Consortium, Utrecht, The Netherlands. ISBN: 978- 94-91933-04-2 Bernet, D.B., Prasuhn, V., & Weingartner, R. (2017). Surface water floods in Switzerland: what insurance claim records tell us about the damage in space and time. Natural Hazards and Earth System Sciences, 17, 1659-1682. https://doi.org/10.5194/ nhess-17-1659-2017 Candela, A., & Aronica, G.T. (2016, September). Derivation of Rainfall Thresholds for Pluvial Flood Risk Warning in Urbanised Areas. XXXV Convegno Nazionale di Idraulica e Costruzioni Idrauliche, 14th – 16th September 2016, Bologna, Italy. https:// doi.org/10.1051/e3sconf/20160718016 Crichton, D. (2005). Flood risk & insurance in England & Wales: are there lessons to be learned from Scotland? Technical Papers 1 Benfield Greig Hazard Research Centre Dawson, R.J., Speight, L., Hall, J.W., Djordjevic, S., Savić, D., & Leandro, J. (2008). Attribution of flood risk in urban areas. Journal of Hydroinformatics, Vol. 10, No. 4, 275-288. DOI: 10.2166/hydro.2008.054 Douglas, I., Garvin, S., Lawson, N., Richards, J., Tippett, J., & White, I. (2010). Urban pluvial flooding: a qualitative case study of cause, effect and nonstructural mitigation. Journal of Flood Risk Management, 3, 112–125. DOI:10.1111/j.1753-318X.2010.01061.x Environment Agency (2007). Review of 2007 summer floods. Environment Agency, Bristol. European Environment Agency (2012). Urban adaptation to climate change in Europe. Challenges and opportunities for cities together with supportive national and European policies. EEA Report No 2/2012. Copenhagen, Denmark. Evans, E.P., Simm, J.D., Thorne, C.R., Arnell, N.W., Ashley, R.M., Hess, T.M., Lane, S.N., Morris, J., Nicholls, R.J., Penning-Rowsell, E.C., Reynard, N.S., Saul, A.J., Tapsell, S.M., Watkinson, A.R., & Wheater, H.S. (2008). An update of the Foresight Future Flooding 2004 qualitative risk analysis. Cabinet Office, London. Falconer, R. (2009, November). Pluvial Flooding and Surface Water Management. European Water Management and Implementation of the Floods Directive. 5th EWA Brussels Conference, 6th November 2009, Brussels, Belgium. Falconer, R., Cobby, D., Smyth, P., Astle, G., Dent, J., & Golding, B. (2009). Pluvial flooding: New approaches in flood warning, mapping and risk management. Journal of Flood Risk Management, 2, 198 - 208. DOI: 10.1111/j.1753-318X.2009.01034.x Falkenhagen, B. (2010, May). Flash flood and pluvial flooding from the point of view of the insurance industry. EUROPEAN COMMISSION – WFD COMMON IMPLEMENTATION STRATEGY, WG F Thematic Workshop on Implementation of the Floods Directive 2007/60/EC, “FLASH FLOODS AND PLUVIAL FLOODING”, 26th – 28th May 2010, Cagliari, Italy Faust, E. (2018). Parts of Germany under water. Available at: https://www.munichre.com/topics-online/ en/climate-change-and-natural-disasters/naturaldisasters/floods/floods-in-germany-2018.html Fritsch, K. Assmann, A., & Tyrna, B. (2016, October). Long-term experiences with pluvial flood risk management. 3rd European Conference on Flood Risk Management, E3S Web of Conferences. 7. 04017. 17th – 21st October, 2016, Lyon, France. DOI:10.1051/e3sconf/20160704017. Gaume, E., Bain, V., Bernardara, P., Newinger, O.,Barbuc, M., Bateman, A., Blaškovičová, L., Blöschl, G., Borga, M., Dumitrescu, A., Daliakopoulos, I., Garcia, J., Irimescu, A., Kohnová, S., Koutroulis, A., Marchi, L., Matreata, S., Medina, V., Preciso, E., & Viglione, A. (2009). A Collation of Data on European Flash Floods. Journal of Hydrology, 367, 70-78. DOI:10.1016/j.jhydrol.2008.12.028 Gaume, E., Borga, M., Llassat, M.C., Maouche, S., Lang, M., & Diakakis, M. (2016). Mediterranean extreme floods and flash floods.The Mediterranean Region under Climate Change. A Scientific Update, IRD Editions, 133-144, Coll. Green, C., Dieperink, C., Ek, K., Hegger, D.L.T., Pettersson, M., Priest, S., & Tapsell, S. (2013). Flood Risk Management in Europe: the flood problem and interventions (report no D1.1.1), STAR-FLOOD.

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Flood forecasting in Europe is a scientifically strong but changing field given increasing focus on pluvial flood issues. Relying on real-time monitoring (river gauges, rainfall radars, satellite data), hydrological models (simulating river responses to rainfall and snowmelt), meteorological forecasts (numerical weather prediction models from ECMWF, DWD, and Météo-France), and early warning systems like the European Flood Awareness System (EFAS), European flood forecasting systems for rivers combine meteorology, hydrology, and sophisticated computational modeling. These technologies allow authorities to plan for possible floods days in advance by providing probabilistic projections. Uncertainties in rainfall predictions—where small mistakes may greatly affect flood volume and timing—as well as complicated interactions from urbanization, soil saturation, and abrupt snowmelt make absolute precision still elusive. Especially hard to forecast is pluvial flooding, which results from short-duration, high-intensity rain exceeding drainage systems before flowing into rivers. Still, predicting accuracy is being continuously improved by advances in artificial intelligence, high-resolution modelling, and better data assimilation including satellite observations and IoT sensors. Driven by climate change-induced excessive rainfall, urbanization (which raises impermeable surfaces), and aging drainage infrastructure, pluvial flooding presents a growing danger. Europe is implementing structural and non-structural policies to reduce these risks, including green infrastructure (permeable pavements, rain gardens, green roofs), better urban planning (limiting development in flood-prone areas), real-time flash flood alerts, and regulatory frameworks like the EU Floods Directive (2007/60/EC), which requires flood risk assessments and management plans. Although no system can forecast floods with 100% precision, continuous developments in adaptive infrastructure, monitoring, and modeling are enhancing Europe's resistance to both fluvial and pluvial flood threats.

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Is flood forecasting for the rivers of the European continent a scientific operation? Can a human mechanism be created to accurately predict floods in the European continent?

Pluvial flooding is a result of overland flow and ponding before the runoff enters any watercourse, drainage system or sewer, or cannot enter it because the network is full to capacity, usually caused by intense rainfall. River and coastal floods get the most attention since they are largest and last the longest, while pluvial floods are relatively marginalized in research. Therefore, the main goal of this research was to show risk posed by pluvial floods, their connection to current global climate change processes, present effects of flooding in European cities, as well as what we can expect in the future. Furthermore, the aims were to present and get more familiar with scientific projects, strategies, directives and measures devised both on national and international levels, that deal with urban pluvial flood issues across the European continent. Climate change projections indicate that there will be an increase in the frequency and intensity of rainfall events throughout Europe and along with ongoing urbanization, the problem of pluvial flooding will most certainly require more attention, which it is starting to receive. Some countries have already developed their strategies and initiatives and implemented both structural and non-structural measures, such as spatial planning, constructional measures, information systems, reducing land sealing through policies, building codes and standards, on-site improvement of retention, infiltration, evaporation, and rainfall water recycling with the use of green roofs, permeable or porous pavements, rain gardening or urban rainwater harvesting. At the same time, there are numerous research papers, studies, conferences and workshops devoted to the problem of pluvial flooding and its management carried out in an attempt to properly deal with this hazard. Keywords: urban areas; pluvial flooding; climate change; precipitation; scientific projects; water management; Europe. Floods are the most prevalent natural hazard in Europe. Between 1998 and 2009, Europe suffered over 213 major damaging floods (Bakker et al., 2013). Coastal and river floods receive the most attention as they are generally the floods that are largest and last the longest, while pluvial floods are relatively underrepresented in research (Nicklin et al., 2019), most likely due to the smaller scale of individual events (Dawson et al., 2008). The absolute record of annual flood loss of all types of floods in Europe was observed in August 2002, when the material damage exceeded €20 billion, in nominal value (Kundzewicz et al., 2012). However, there is an increasing problem of massive and intensifying flood damages in areas away from rivers. For example, in Great Britain two flood events in summer 2007 cost nearly €6 billion (Falkenhagen, 2010). Recent research has suggested that due to the frequent nature of pluvial floods, cumulative direct damage to property caused by those type of floods equals or may even exceed damage from river and coastal floods (Nicklin et al., 2019). Pluvial floods produce less damage but the frequency is higher and the cumulative damage over the years can be just as high as from fluvial flooding events (Acosta-Coll et al., 2018) or even higher (Szewrański et al., 2018a). For instance, of the 11 000 properties flooded in autumn of 2000 in the UK, 83% were outside coastal and fluvial floodplains, suggesting that flooding was caused by local pluvial events, sewer flooding or groundwater (Dawson et al., 2008). Pluvial flooding can be defined as flooding that results from overland flow and ponding before the runoff enters any watercourse, drainage system or sewer, or cannot enter it because the network is full to capacity and is usually caused by intense localized rainfall. This problem is enhanced in cities with insufficient or non-existent sewer systems (Acosta-Coll et al., 2018). Also, Falconer et al. (2009) state that it’s important not to confuse ‘pluvial flooding’ with ‘surface water flooding’. According to them, surface water flooding usually refers to combined flooding in urban areas during heavy rainfall. As such, it includes pluvial flooding, sewer flooding, flooding from small open-channels and overland flows from groundwater springs. Pluvial flooding is also different from ‘flash flooding’, which may also be associated with high-intensity rainfall but usually arises from a watercourse. Further in the text of this paper terms “urban pluvial flooding”, “inland pluvial flooding”, “pluvial flooding” ,“intra-urban system flooding”, “urban drainage flooding” and “surface water flooding” will be used interchangeably. Pluvial flooding only occurs when the rainfall rate exceeds the capacity of storm water drains to evacuate the water and the capacity of the ground to absorb water and this is usually associated with short-duration storms (of up to three hours) and with rainfalls that exceed 20 – 25 mm per hour; but it can also occur after rainfalls of smaller intensity, approximately 10 mm per hour, that happen over longer periods, especially if the ground surface is impermeable by being developed, saturated or frozen (Houston et al., 2011). However, pluvial floods depend not only on the amount and duration of precipitation but also on the hydrological characteristics of the basin, such as runoff magnitude, antecedent moisture condition, drainage area and soil type (Acosta-Coll et al., 2018). In addition, land use change, particularly urbanization, is also changing the proportion of precipitation which becomes runoff and also reduces the delay between precipitation and the runoff reaching a watercourse (Green et al., 2013). According to Li (2012) the urban storm water logging problems result from various causes, such as the uneven distribution of precipitation in time and space, inadequate urban water-logging emergency response systems, decreasing green areas and filling of waterbodies because of urbanization and insufficient capacity in the storm water drainage system without proper maintenance and upgrading.Other reasons for frequent inundation include outdated sewer-stormwater systems, greater areas of impervious urban fabric and larger urban population (Sušnik et al., 2014). Increasing urbanization often results in an expansion of impermeable areas, whereby the higher proportion of sealed soils result in an increased runoff volume and a decreased response time of a catchment, while further risk comes from urban areas expanding into flood risk areas (Swart et al., 2012). The main goals of this research are twofold: a) first, to show connection between current global climate change processes and urban pluvial flooding, and present effects of flooding in European cities, as well as what we can expect in the future; b) and secondly, to present strategies, directives and measures devised both on national and international levels, as well as scientific projects that deal with urban pluvial flood issues in order to contribute to better mitigation and adaptation actions in European cities. For our analysis we used the scientific literature in the last 10 to 12 years, as well as official documents from international institutions (such as UN, EU) or national governments.The occurance of pluvial or flash floods due to highintensity rainfall events is nothing new. However, it appears that the frequency with which they are happening, their impact on human lives, damage and disruption is increasing, very likely because of the climate change, and unfortunately it’s predicted to increase further (Falconer et al., 2009). As presented by IPCC Fifth Assessment Report (2014) on the world-wide impacts of climate change on rainfall extremes and urban drainage, it was ob-served that typical increases in rainfall intensity at small urban hydrology scales range from 10% to 60% from control periods in the recent past (typically 1961–1990) up to 2100 (Figure 1). These changes in extreme short-duration rainfall events may have significant impacts for urban drainage systems and pluvial flooding. The Danish Meteorological Institute (DMI) predicts that the intensity of the heavy downpours will rise by 20-50% by 2100, the most for the very rare events which will have great implication on how the rain will run off surfaces and on the burden on sewer systems and watercourses (Copenhagen Climate Adaptation Plan, 2009). Climate change is expected to increase the frequency and intensity of rainfall events throughout Europe (Sušnik et al., 2014), especially in the central and northern parts (“STAR-FLOOD”; https://www.starflood.eu/). Flood hazard may also rise during wetter and warmer winters, with increasingly more frequent rain and less frequent snow (“STAR-FLOOD”; https://www.starflood.eu/), while warmer atmosphere will hold higher amount of water vapor (Kundzewicz, 2015). There will be a marked increase in extremes in Europe, in particular, in heat waves, droughts, and heavy precipitation events, according to the Fifth IPCC Assessment Report (2014). Changes in extreme precipitation depend on the region, with high probability of increased extreme precipitation in Northern Europe (all seasons) and Continental Europe (except summer). This may result in more frequent and more intense floods of various types such as local, sudden floods (flash floods); extensive, longer-lasting pluvial and fluvial floods; coastal floods and snowmelt floods (Menne & Murray, 2013). With the expected changes, the drainage system built today probably won’t be able to meet the desired service levels in the future (Zhou et al., 2012).On the other hand, some authors state that climatechange impacts on future extreme precipitation, and consequently on pluvial flooding, is surrounded by large uncertainties. One of the uncertainties lies in the incomplete understanding of processes and components in the Earth’s system, resulting in large model uncertainties and thus large variations in projected change of future precipitation extremes between different models (Kaspersen et al., 2017). In addition, climate models provide an assessment of only anthropogenic impacts and usually don’t account for natural changes that will occur at the same time, while questions arise about the assumptions behind the climate models and how these assumptions influence the projections (Arnbjerg-Nielsen et al., 2013). However, the uncertainties associated with climate change should not be an argument for delaying investigating its possible impact on pluvial flooding or postponing adaptation actions. Instead, uncertainties should be accounted for while flexible and sustainable solutions should be sought, some of which will be presented in the following sections. Current risks from pluvial flooding and future projections Risks and adverse effects posed by pluvial flooding are numerous (Figure 2). The direct and indirect impacts of extreme weather include losses in economic terms, the damaging and destruction of private buildings and urban infrastructure, the loss of human lives and the degradation of safety and the deterioration of water quality (Szewrański et al., 2018a). In addition, flooding, especially as a result of intense precipitation, is the predominant cause of weather-related disruption to the transport sector (Pregnolato et al., 2017) and traffic delay and inconvenience (Zhou et al., 2012). Examples of indirect effects are also lost working hours and health impacts on affected residents, which can manifest if sewer water flows onto streets or if pluvial flood water stands stagnant (Sušnik et al., 2014). Furthermore, indirect impacts may occur beyond the location and time of a flood event, such as long-lasting trauma and stress (Szewrański et al., 2018b). On the other hand, average mortality for just drainage floods is low. More than half of the drainage events in the dataset causes one or zero fatalities (Jonkman & Vrijling, 2008). According to the European Environment Agency (2012) there are several factors that tend to increase the risk of pluvial flooding: • Old drainage infrastructure often does not keep pace with an on-going urbanization.Combined sewer systems in older areas (rainfall drains into sewers that are carrying sewage and both are transferred to sewage treatment) which are more vulnerable to excessive rainfall than a separate treatment.The existence of inadequate maintenance of the drainage channels to monitor debris and solid waste within such systems. • Inadequate discharge of excess water to the regional water system. Douglas et al. (2010) analyzed potential weak points of risk management of serious pluvial flooding in the case study of flooding in Heywood, Greater Manchester in 2004 and 2006. Here it was revealed that all agencies involved in flood risk management, and in particular planners, require more robust, and more localized data. This study has also highlighted that the general public are confused about who does what and who is responsible for pluvial flood risk management, and are not so well informed about how best to protect their properties. Also, many agencies underestimate the ongoing health and social effects of flooding. Modeling studies show that urbanization and increasing rainfall intensity will increase drainage overflow volumes that will result in more frequent and severe pluvial flooding (Miller & Hutchins, 2017). At present about 55% of the global population live in cities and by 2050 almost two thirds of the world’s population will live in urban environments (Sörensen et al., 2016). Over 80% of the population in Britain lives in urban areas while it’s predicted that population growth will reach 74.3 million by 2039 (Miller & Hutchins, 2017). A new study shows that the total urban area exposed to flooding in Europe has increased by 1000% over the past 150 years (Jongman, 2018). This means that urbanization with an increase of non-permeable surfaces and lack of natural drainage created additional flooding issues that did not previously exist and that never before there had been so many human assets that were in the way of floods like today. And according to Kazmierczak & Cavan (2011), the negative correlations between green space cover and the proportion of an area susceptible to flooding suggest that the increasing amount of sealed surfaces in an area aggravates the problem of flooding through increased runoff and reduced infiltration capacity. Furthermore, Guerreiro et al. (2017) developed a map of Europe which represents a percentage of city flooded for historical hourly rainfall for a 10-year return period (Figure 3). The growing urban population and degree of urbanization puts great pressure on the existing drainage systems, increasing the likelihood of them being overwhelmed (“Urban pluvial flooding and climate change: London (UK), Rafina (Greece) and Coimbra (Portugal)”; https://www.imperial.ac.uk/grantham/ research/resources-and-pollution/water-securityand-flood-risk/urban-flooding/). Systems currently designed for a 20-year return period of flooding, might flood with a mean recurrence interval of 5 years by the end of the century (“Flash floods and Urban flooding”; https://www.climatechangepost.com). On 7th August in 2002, an inch of rain fell in central London in 30 minutes during the evening “rush hour”, resulting in the closure of 5 mainline railway stations, and considerable disruption as London’s drainage infrastructure was too old and overloaded to cope with such events (Crichton, 2005). According to the UK statistics (“Facts About Floods in the UK”; https://rainbow-int-franchise.co.uk/flooding-statistics-uk/) the residents of around 2.4 million UK properties are at risk from fluvial and coastal flooding each year, while a further 2.8 million are susceptible to surface water – or pluvial – flooding. Kaspersen et al. (2017) in their research found that urban development in Odense and Vienna influences the extent of flooding considerably, while only marginally affecting the degree of flooding for Strasbourg and Nice. This suggests that, while further soil sealing in Odense and Vienna (and similar urban areas) should be considered very carefully, as it may substantially increase their exposure to pluvial flooding, urban development effect on pluvial flooding varies locally and should be considered with that in mind. The financial implications of pluvial flooding can be significant. It is estimated that in the Netherlands, between 1986 and 2009 the total damage from pluvial floods was €674 million (Sušnik et al., 2014). Nicklin et al. (2019) did the research and used a combination of 3D flood modelling and the WSS (Dutch ‘Waterschadeschatter’) flood damage estimation tool to assess direct flood damage from a 60 mm/1-h pluvial flood event in two urban areas: Belgrave (Leicester, United Kingdom) and Lombardijen (Rotterdam, the Netherlands). For Belgrave, direct damage was estimated at roughly €11 million, while for Lombardijen direct damage was €12.4 million. In England and Wales during summer of 2007 there were about 48 000 households and nearly 7300 businesses flooded (Menne & Murray, 2013) while insurance claims from the homes and businesses affected are approaching £3 billion and other costs amount to around £1 billion (Environment Agency, 2007). According to Bernet et al. (2017) in Switzerland, of all damage due to surface water floods and fluvial floods between 1999 and 2013, surface water floods are responsible for at least 45 % of the flood damage to buildings and 23 % of the associated direct tangible losses. Houston et al. (2011) estimated that almost 2 million people in urban areas in the UK face an annual 0.5 per cent probability (‘1 in 200-year’) of pluvial flooding. Most of the areas with lower percentage of city flooded are in the north and west coastal parts of Europe, while the higher percentages are predominately in continental and Mediterranean areas (Guerreiro et al., 2017). When talking about the Mediterranean region, major population and economic growth has taken place along its coast in the past century, which led to extension of urban settlements inside flood prone areas (Gaume et al., 2016). Lugeri et al. (2006) analyzed flood risk exposure in 13 European countries and found that Slovenia has the highest share of urban fabric built in flood prone areas - more than 70%. An estimated 3.8 million properties are thought to be at risk from pluvial flooding in England which represent around 10% of all properties, while in Scotland some 15 000 properties have been estimated to be at pluvial flood risk (Houston et al., 2011). The expected annual damages from urban flooding in the UK are estimated at £0.27 billion which compares to £0.6 - 2.1 billion for fluvial and coastal flooding and the estimate for the future is that this could be as much as £2 to 15 billion by 2080 compared to £1.5 – 20 billion for fluvial and coastal flooding (Dawson et al., 2008). Furthermore, Evans et al. (2008) in the Pitt Review estimated that the future risk from the intra-urban system flooding might rise by the 2080s to be of the same order as fluvial and coastal flood risk. Menne & Murray (2013) did the research on the floods in the European region and their health effects and found that in the period between 2005 and 2010, 16 countries were affected by pluvial floods: Bosnia and Herzegovina, Croatia, Czech Republic, Hungary, Malta, Poland, Republic of Moldova, Serbia, Slovenia, Spain, Sweden, Tajikistan, Republic of North Macedonia, Turkey, Ukraine, United Kingdom (England and Wales). And as mentioned in the previous part, with the projection for the continuous increase of heavy rain contribution to total precipitation (Santato et al., 2013) and with current urbanization and population growth, it is estimated that by 2050, 3.2 million people in urban areas in the UK could be at risk from pluvial flooding, which is an increase of 1.2 million (Houston et al., 2011). Figure 4, developed by European Environment Agency (2012), shows the projected change in the annual number of days with heavy rainfall in 2071–2100 against the reference period (1961–1990). Projections for regions south of the Alps show a decline in the number of days with extreme precipitation of up to five days and more. Most regions north of the Alps expect an increase, mostly of one to three days. In addition, this map shows the degree of mean soil sealing per urbanized areas of cities. Cities with high soil sealing and an increasing number of intensive rainfall events — in particular in north-western and northern Europe — face a higher risk of urban drainage flooding. Nevertheless, cities in areas with a decreasing number of such events but high soil sealing still face a flooding risk, just less often. Cities of high and low soil sealing can be found in all regions and do not cluster in a particular region with the exception of low sealing levels in cities in Finland, Norway, Slovenia and Sweden. Cyprus, Estonia, Greece and Luxembourg are countries with a high share of cities with elevated levels of soil sealing. Examples of pluvial flooding events across European continent Gaume et al. (2009) have compiled a comprehensive data record of flash floods for seven European hydrometeorological regions. This inventory was the first step towards an atlas of extreme flash floods in Europe while the objective was to document a minimum number of 30 floods in each region, especially the events considered as the most extreme or ‘‘top 30” flash floods which are homogeneously distributed over the selected period. However, this research didn’t include pluvial floods and there couldn’t be found any similar analysis that would focus on pluvial flooding events in Europe. Therefore, this section will provide a few examples of pluvial flooding occurrences that had significant economic and social impact on the communities in Europe affected by this hazard. In the summer of 2007, floods that struck much of the United Kingdom during June and July affected hundreds of thousands of people. This event was the most serious inland pluvial and fluvial flood ever recorded, with 13 deaths, about 7000 people rescued from floodwaters by the emergency services, and about 48 000 households and nearly 7300 businesses flooded (Menne & Murray, 2013), while the insurance claims from the homes and businesses flooded approached £3 billion (Environment Agency, 2007). The floods caused the loss of essential services, almost half a million people were without water or electricity supply, transport networks failed, a dam breach was narrowly averted, and emergency facilities and telecommunications were put out of action (Menne & Murray, 2013). During June, July, and August of 2007 a succession of depressions tracked over the UK, bringing heavy rainfall and triggering multiple flooding events (Stuart-Menteth, 2007). With 414 mm of rain, England and Wales haven’t seen a wetter May to July since records began in 1766 (Environment Agency, 2007). On 12th June 2007, a total of 98.3 mm of rain fell in one hour in East and South Belfast which resulted in both fluvial flash flooding and pluvial flooding which caused major disruption throughout Belfast with over 400 properties affected (Falconer, 2009). Two particularly large floods hit within just four weeks of each other. First, the northeast of England was badly affected following heavy rainfall on June 25th, which caused flooding in cities and towns such as Sheffield, Doncaster, Rotherham, Louth, and Kingston-upon-Hull (Figure 5). Some areas were hit again by further flooding after more severe rains on July 20th, which affected a much larger area of central England, including Oxford, Gloucester, Tewkesbury, Evesham, and Abingdon (Stuart-Menteth, 2007). According to the emergency services, that summer saw the greatest number of search and rescue missions in the country since the Second World War (Environment Agency, 2007).Just a couple of years before this event, at the end of July in 2002, another extreme case of storms affected much of the UK, especially West and central Scotland, and produced extreme amount of rainfall at several locations in localized intense heavy downpours generating surface water flooding and pluvial flooding affecting small urban watercourses, drainage systems and sewers (Falconer, 2009). The full storm began at approximately 10:30 am on 30 July 2002 and continued for a total of approximately 10 hours, it measured 75mm depth and had a maximum intensity of 94.5 mm/h which can be linked to a maximum return period of 100 years (Wilson & Spiers, 2003). According to the European Environment Agency (2012), on July 2nd 2011, Copenhagen in Denmark was hit by a huge thunderstorm after a substantially hot period. During a two hour period over, 150 mm of rain fell in the city centre. This became the biggest single rainfall in Copenhagen since measurements began in the mid-1800s. The city’s sewers were unable to handle all of the water and as a result many streets were flooded and sewers overflowed into houses, basements and onto streets thereby flooding the city (Figure 6). Insurance damages alone were estimated at €650–700 million. Damage to municipal infrastructure not covered by insurance, such as roads, amounted to €65 million. The Marmara region in north-western Turkey suffered from a series of floods during the period from 7th until 10th September in 2009, with 35 000 people affected, 32 human losses and more than $100 million of economic damage. The 24-hour rainfall amounts varied between 100 and 253 mm during the flooding period and additional factors such as land use changes, urbanization, poor drainage, and construction and settling in the flood-prone areas worsened consequences of the floods, especially in major urban areas of the region. Istanbul suffered most from floods where some suburban districts were submerged and the city’s highways were turned into rivers and transportation and communication infrastructures were damaged (Kömüşcü & Çelik, 2012). On the 18th September in 2007 an extreme rainfall event affected approximately one-third of Slovenia, causing the damage of €200 million and six casualties (Rusjan et al., 2009). In the town Železniki, the observed maximum daily amount of rainfall was nearly 200 mm, which was the highest recorded amount of precipitation since the beginning of the measurements in 1930 and it devastated the town of Železniki: three people lost their lives, while it was estimated that the flood caused nearly €100 million of damage (Markošek, 2008). In June of 2010 storms hit the south-east of France and the large amounts of heavy rain led to localized flash flooding and pluvial flooding which caused severe damage and loss of life in southern France, and a number of towns in the department of Var were affected, with hundreds of homes flooded (Moreau & Roumagnac, 2010). Torrential rainfall hit southern Italy and produced major flooding in parts of Sicily and Calabria on October 4th 2018. The urban area of Catania, Sicily was strongly hit where streets turned into rivers (Figure 7). Catania experienced intense rainfall with about 50 mm falling in only 20 minutes as the severe thunderstorm passed (“Major flash floods hit urban areas of Catania, Sicily”; http://www.severe-weather.eu/news/major-flash-floods-hit-urban-areas-of-catania-sicily/).In May and June of 2016, Germany was struck with recurring thunderstorms, with damage across Germany totaled €2.6 billion (Faust, 2018). Parts of Germany have come to a standstill after storms and torrential rain, especially in the south in May this year as well. One person died and daily life has been disrupted. Heavy rain and thunderstorms, mainly in southern and central Germany, have left rivers overflowing and streets flooded (Silk, 2019).Pluvial flooding risk management Adopted measures and strategies Measures and strategies that increase the specific response capacity of cities to flooding, according to Swart et al. (2012), can be classified into structural and non-structural measures or into grey, green and soft measures (Figure 8). The response capacity measures include spatial planning, constructional measures, risk acceptance, behavioral adaptation, information systems, technical flood protection and increasing natural water retention in catchment areas and reducing land sealing. Structural measures decrease the risk and they are mostly effective, but they usually involve management problems. On the other hand, nonstructural measures reduce vulnerability and when they are permanent they are reliable but can be socially costly while when they are temporary and less costly they become less reliable (Working Group F, 2010). These can be classified as passive and active where active non-structural measures are those that promote direct interaction with people, such as training, local management, early warning systems for people, public information, while passive measures involve policies, building codes and standards, and land use regulations (Acosta-Coll et al., 2018). Some of the adaptation measures involve the on-site improvement of retention, infiltration, evaporation, and rainfall water recycling with the use of green roofs, permeable or porous pavements, rain gardening, urban rainwater harvesting, or the application of water-absorbing geocomposites (Szewrański et al., 2018b). The problem of pluvial flooding is slowly starting to receive more attention, according to the interviews conducted by Mees et al. (2016) and numerous research papers (Candela & Aronica, 2016; Falconer et al., 2009; Szewrański et al., 2018a/b; Fritsch et al., 2016), conferences and workshops (Third Hydrology Forum, Oslo, 2016; Flash Floods and Pluvial Flooding Workshop, Calgari, 2010; 3rd European Conference on Flood Risk Management, Lyon, 2016) done on this topic. Through further examples of different projects, strategies and initiatives implemented in European countries separately or in mutual cooperation across the continent, various methods of urban pluvial flooding management will be observed. For instance, The EU Directive on the assessment and management of flood risks (pluvial floods included), often referred to as the Floods Directive, entered into force on 26th November 2007, which main aim is to reduce and manage the risks posed by floods to human health, the environment, cultural heritage and economic activity (Bakker et al., 2013). Floods Directive contains a three-stage approach: first, a preliminary flood risk assessment must be undertaken, then flood hazard maps and flood risk maps are to be prepared and in the final stage, member states must establish Flood Risk Management plans. Priest et al. (2016) did an analysis which indicates that the effect of the Flood Directive is highly variable among the six European countries they studied (Belgium, England, France, the Netherlands, Poland, and Sweden), but despite the shortcomings of the Flood Directive in directly affecting flood risk outcomes, it has had a positive influence in stimulating discussion and flood risk management planning in member states that were perhaps lagging behind. Or, another example, according to Land Use Consultants (2003) Sustainable Urban Drainage Systems, involves moving away from conventional piped systems and toward engineering solutions that mimic natural drainage processes and minimize adverse effects on the environment which may take the form of infiltration systems whereby water is soaked away into the ground or they may be attenuation systems, which release flows gradually to watercourses or sewers. Separate storm water and foul water systems can increase drainage capacity and reduce the likelihood of sewage mixing with pluvial flood water (Houston et al., 2011). As mentioned previously, there are different uncertainties that surround risk assessments for urban flooding, particularly connected to the climate change models and small-scale projections of extreme precipitation. Kaspersen & Kirsten (2017) proposed a way to address these uncertainties by using a very detailed integrated data and modelling approach, such as the DIAS Danish Integrated Assessment System tool they described in detail, which can help identify particularly vulnerable and valuable assets that climate change adaptation measures should protect. While the warning about extreme weather events in Germany is done nationwide by the German Meteorological Service, flood forecasting and warning is decentralized in Germany which poses the main challenge of handling of measured data coming from various providers and monitoring networks in individual formats (Osnabrugge et al., n.d.). German Water Association (DWA) set up different working groups with the aim to establish technical standards and provide affected interest groups with guidelines and practical advice which in the year 2013 during a heavy rainfall event with a return period of about 100 years has proven to significantly reduce flood risk and gain acceptance in public (Fritsch et al., 2016). As a further example, Hamburg has introduced a separate rain water drainage system in recent years and introduced financial penalties, if rain water is not locally drained by home owners (Schlünzen & Bohnenstengel, 2016). Projects related with pluvial flooding issues The following table represents various examples of different projects, strategies and initiatives implemented in European countries separately or in mutual cooperation across the continent that deal with and manage pluvial flooding. Good examples of pluvial flooding risk management could be found outside of Europe as well and perhaps studied further in the attempt to adapt good practices from across the world. For example, China is currently in the process of implementing a policy initiative called sponge cities to holistically tackle urban pluvial flooding while promoting sustainable urban development with reduced environmental impact. This initiative is well-grounded in scientific under .Conclusions Pluvial flooding, or flooding that is a result of intense localized rainfall that exceeds the capacity of a drainage system, is getting wider awareness in Europe. The estimates that cumulative damage from pluvial flooding over the years can be just as high as from fluvial flooding events or even higher is worrying and a cause for a concern. Risks posed by pluvial flooding are numerous, from economic losses, destruction of private buildings and urban infrastructure to the loss of human lives, decrease of water and health impacts. With climate change projections that there will be an increase in the frequency and intensity of rainfall events throughout Europe and with ongoing urbanization with its own effects, adaptive and sustainable solutions should be explored and pursued as soon as possible. The problem of pluvial flooding is most certainly starting to receive more attention and some countries have already developed their strategies for dealing with this hazard. As this review shows, there are already numerous researches, papers, studies, conferences and workshops dedicated to the problem of pluvial flooding and its management. Various project strategies and initiatives that deal with pluvial flooding risk management have been implemented in some of the European countries separately or in cooperation with one another. Some of the measures presented include spatial planning, constructional measures, risk acceptance, information systems, early warning systems for people, reducing land sealing through policies, building codes and standards and land use regulations, as well as adaptation measures such as the on-site improvement of retention, infiltration, evaporation, and rainfall water recycling with the use of green roofs, permeable or porous pavements, rain gardening or urban rainwater harvesting.

Acosta-Coll, M., Merelo, F., Peiro, M.M., & De la Hoz, E. (2018). Real-Time Early Warning System Design for Pluvial Flash Floods—A Review. Sensors, 18, 2255. DOI:10.3390/s18072255 Arnbjerg-Nielsen, K., Willems, P., Olsson, J., Beecham, S., Pathirana, A., Gregersen, I., Madsen, H., & Nguyen, V.-T.V. (2013). Impacts of Climate Change on Rainfall Extremes and Urban Drainage Systems. Water science and technology, 68(1), 16-28. DOI:10.2166/wst.2013.251 Ashley, R., Blanksby, J., Maguire, T. & Leahy, T. (2019). Frameworks for Adapting to Flood Risk: Experiences from the EU’s Flood Resilient City Project. Bakker, M.H.N., Green, C., Driessen, P., Hegger, D., Delvaux, B., van Rijswick, M., Suykens, C., Beyers, J.C, Deketelaere, K., van Doorn-Hoekveld, W., & Dieperink, C. (2013). Flood Risk Management in Europe: European flood regulation. STAR-FLOOD Consortium, Utrecht, The Netherlands. ISBN: 978- 94-91933-04-2 Bernet, D.B., Prasuhn, V., & Weingartner, R. (2017). Surface water floods in Switzerland: what insurance claim records tell us about the damage in space and time. Natural Hazards and Earth System Sciences, 17, 1659-1682. https://doi.org/10.5194/ nhess-17-1659-2017 Candela, A., & Aronica, G.T. (2016, September). Derivation of Rainfall Thresholds for Pluvial Flood Risk Warning in Urbanised Areas. XXXV Convegno Nazionale di Idraulica e Costruzioni Idrauliche, 14th – 16th September 2016, Bologna, Italy. https:// doi.org/10.1051/e3sconf/20160718016 Crichton, D. (2005). Flood risk & insurance in England & Wales: are there lessons to be learned from Scotland? Technical Papers 1 Benfield Greig Hazard Research Centre Dawson, R.J., Speight, L., Hall, J.W., Djordjevic, S., Savić, D., & Leandro, J. (2008). Attribution of flood risk in urban areas. Journal of Hydroinformatics, Vol. 10, No. 4, 275-288. DOI: 10.2166/hydro.2008.054 Douglas, I., Garvin, S., Lawson, N., Richards, J., Tippett, J., & White, I. (2010). Urban pluvial flooding: a qualitative case study of cause, effect and nonstructural mitigation. Journal of Flood Risk Management, 3, 112–125. DOI:10.1111/j.1753-318X.2010.01061.x Environment Agency (2007). Review of 2007 summer floods. Environment Agency, Bristol. European Environment Agency (2012). Urban adaptation to climate change in Europe. Challenges and opportunities for cities together with supportive national and European policies. EEA Report No 2/2012. Copenhagen, Denmark. Evans, E.P., Simm, J.D., Thorne, C.R., Arnell, N.W., Ashley, R.M., Hess, T.M., Lane, S.N., Morris, J., Nicholls, R.J., Penning-Rowsell, E.C., Reynard, N.S., Saul, A.J., Tapsell, S.M., Watkinson, A.R., & Wheater, H.S. (2008). An update of the Foresight Future Flooding 2004 qualitative risk analysis. Cabinet Office, London. Falconer, R. (2009, November). Pluvial Flooding and Surface Water Management. European Water Management and Implementation of the Floods Directive. 5th EWA Brussels Conference, 6th November 2009, Brussels, Belgium. Falconer, R., Cobby, D., Smyth, P., Astle, G., Dent, J., & Golding, B. (2009). Pluvial flooding: New approaches in flood warning, mapping and risk management. Journal of Flood Risk Management, 2, 198 - 208. DOI: 10.1111/j.1753-318X.2009.01034.x Falkenhagen, B. (2010, May). Flash flood and pluvial flooding from the point of view of the insurance industry. EUROPEAN COMMISSION – WFD COMMON IMPLEMENTATION STRATEGY, WG F Thematic Workshop on Implementation of the Floods Directive 2007/60/EC, “FLASH FLOODS AND PLUVIAL FLOODING”, 26th – 28th May 2010, Cagliari, Italy Faust, E. (2018). Parts of Germany under water. Available at: https://www.munichre.com/topics-online/ en/climate-change-and-natural-disasters/naturaldisasters/floods/floods-in-germany-2018.html Fritsch, K. Assmann, A., & Tyrna, B. (2016, October). Long-term experiences with pluvial flood risk management. 3rd European Conference on Flood Risk Management, E3S Web of Conferences. 7. 04017. 17th – 21st October, 2016, Lyon, France. DOI:10.1051/e3sconf/20160704017. Gaume, E., Bain, V., Bernardara, P., Newinger, O.,Barbuc, M., Bateman, A., Blaškovičová, L., Blöschl, G., Borga, M., Dumitrescu, A., Daliakopoulos, I., Garcia, J., Irimescu, A., Kohnová, S., Koutroulis, A., Marchi, L., Matreata, S., Medina, V., Preciso, E., & Viglione, A. (2009). A Collation of Data on European Flash Floods. Journal of Hydrology, 367, 70-78. DOI:10.1016/j.jhydrol.2008.12.028 Gaume, E., Borga, M., Llassat, M.C., Maouche, S., Lang, M., & Diakakis, M. (2016). Mediterranean extreme floods and flash floods.The Mediterranean Region under Climate Change. A Scientific Update, IRD Editions, 133-144, Coll. Green, C., Dieperink, C., Ek, K., Hegger, D.L.T., Pettersson, M., Priest, S., & Tapsell, S. (2013). Flood Risk Management in Europe: the flood problem and interventions (report no D1.1.1), STAR-FLOOD.

The h-index and i10-index provided by Google Scholar are generally more robust and dynamic compared to those on ResearchGate, which can be less transparent and less frequently updated. Given this, why are we relying on the ResearchGate h-index?

Using SmartPLS4 in data analysis. I obtained two VIFs which are > to 10 and a HTMT which is equal to 1.07.

How to justify adequately these values and which robust and relevant references can be used to persuade the reviewers?

Thanks

I am exploring sensor fusion strategies to combine data from gas sensors and anemometers for robotic navigation. The objective is to integrate these inputs in a manner that addresses their different response rates and noise characteristics, ultimately enhancing navigation robustness across varied settings. I’m specifically seeking general guidance on efficient fusion techniques, managing synchronization challenges, and handling signal discrepancies—all while keeping the approach abstract to avoid divulging project-specific details. Any insights or references to relevant literature would be greatly appreciated.

Hi,

I'm having problems with silique filling in my WT plants. I'm getting robust inflorescences with thick shoots, but almost no seeds are being produced.

Has anyone had this problem before and can offer any advice?

Thank you!

DOLS is a parametric and FMOLS is a non-parametric approach. However, there are numbers of studies where they have done both the tests for the same dataset as robustness check.

My question is how can both the parametric and non-parametric tests can be applied on the same dataset?

regression models in the social sciences exact or no?

Unfortunately, I do not have a robust system for performing molecular dynamics using Gromacs software. Please help me in this regard.

Hi everyone, I am seeking guidance on constructing an age-depth model for sedimentary deposits of Miocene age using foraminifera (Planktic and Benthic). While I am familiar with the Bayesian age modelling program Bacon, commonly employed for Holocene and recent sediments, I am uncertain of its applicability to the Miocene epoch. Could you please advise on whether Bacon is a suitable tool for this purpose? If not, I would be grateful for suggestions on alternative methodologies for age-depth modelling in Miocene sediments. Thank you.

I performed a 3-replicate qPCR experiment and calculated the fold change using 2^(-ΔΔCt).

To combine the results of the replicates into one graph, I normalised the fold change by dividing the reference condition's fold change by itself (resulting in 1) and then dividing all other conditions by the reference.

I used the geometric mean to calculate the average fold change across the replicates, as I believe the arithmetic mean might be inaccurate in this case.

Is this approach correct for analysing my data? Or is there another more robust method you would recommend for this type of analysis?

Thank you!

In today’s rapidly evolving threat landscape, cyber risks are characterized by four critical dimensions: Velocity, Volume, Variety, and Visibility. These “4 Vs” present unique challenges, requiring organizations to adopt continuous assessment strategies that go beyond traditional, static risk evaluations.

This discussion seeks to explore how organizations can effectively implement continuous cyber risk assessment methodologies to address the dynamic nature of cyber risks while ensuring alignment with strategic business objectives.

- What strategies and frameworks have proven effective in managing the 4 Vs of cyber risks?

- How can organizations enhance real-time risk visibility, prioritization and adaptability?

- What role do people, processes, and technology play in creating a robust approach to continuous cyber risk assessment?

- We invite researchers, practitioners, and cybersecurity enthusiasts to share insights, case studies, and innovative approaches to this pressing topic. Let’s collectively explore how continuous assessment can enable organizations to stay resilient in the face of ever-changing cyber threats.

When conducting empirical research on "the dynamic relationship between economic growth and greenhouse gas emissions for oil-exporting countries". From your point of view, what is the most suitable sample of countries for generating robust and policy-relevant findings?

Dear all, the relation between the discrete measurement noise matrix, Rk, and the continuous measurement noise matrix,R(t), of the Kalman filter is given in the book (Optimal and Robust Estimation With an Introduction to Stochastic Control Theory, 2008, page 87) as Rk=R(t)/T, where T is the sampling time. In this equation there is unbalance in the units because the units of Rk are R(t) /unit time. Could anyone help to explain how this comes because the units of Rk should be the same as R(t).

Hi everyone, I am currently working on building an econometric model to predict cost overruns in construction projects in Quebec. This model will identify various economic variables (inflation, exchange rates, labor costs, etc.) and use historical data tested over different time periods to evaluate the model’s robustness and accuracy.

Given the complexity of this topic, I am seeking advice and suggestions from the community. Here are some questions I have:

Any advice or guidance would be greatly appreciated. Thank you in advance for your time and assistance 😊.

I am developing a modular educational robotics kit and looking for more robust and practical alternatives to traditional jumpers. The goal is to ensure secure and durable electrical connections while facilitating frequent assembly and disassembly by students. Would magnetic connectors, quick-release terminals, or other solutions be viable for this context?

The same drivers that have heralded the rise of quantum open architecture will enable it to accelerate the advent of utility-scale quantum computing in the future. As technology progresses, the complexity and development cost of each quantum computing component grows exponentially. This provides a strong incentive for companies to down-scope and specialise vertically. Even companies that currently develop most of the quantum computing stack in-house will transition to QOA.

New Capabilities Will Expand the Scope of Quantum Open Architecture Quantum Computing

Next-generation components and systems play a pivotal role in advancing utility-scale quantum computing. Scalable quantum processors, like those developed by QuantWare, are essential for building larger, more powerful quantum systems. These processors are designed to integrate seamlessly with up-stack technologies (advanced control hardware and cryogenic systems) and down-stack (novel qubit types and application-specific designs), creating the foundation for robust quantum computing platforms.

source: Quantum Computing Horizons: The Future of Quantum Open Architecture

Sub-Research Questions

1. What are the socio-economic impacts of poor data quality on financial forecasting in developing economies?

• This question aims to explore how data quality issues specifically affect financial forecasting in developing economies, where data infrastructure may be less robust. It addresses the broader socio-economic implications, such as the impact on economic growth, investment decisions, and financial stability.

2. How can emerging technologies, such as artificial intelligence and blockchain, be leveraged to improve data quality in financial forecasting?

• This question focuses on the potential of emerging technologies to enhance data quality. It explores how AI and blockchain can be used to ensure data accuracy, integrity, and reliability in financial forecasting.

Themes ought to include:

guaranteeing accurate portrayal of participants' opinions.

both externally divergent (different from other themes) and internally consistent (coherence within the theme).

evaluated iteratively, incorporating triangulation or peer debriefing to increase dependability.

Human rights violations occur when actions by state or non-state actors infringe upon the basic rights and freedoms to which all humans are entitled, as outlined in international agreements like the Universal Declaration of Human Rights (UDHR) and various other treaties. These rights encompass civil, political, economic, social, and cultural dimensions, which are essential for dignity, freedom, and equality. Violations can take many forms, including, but not limited to:

1. Civil and Political Rights Violations

2. Economic, Social, and Cultural Rights Violations

3. Genocide, War Crimes, and Crimes Against Humanity

4. Environmental Degradation and Climate-Related Violations

5. Gender-Based Violence and Discrimination

Mechanisms for Addressing Human Rights Violations

International and regional bodies, such as the United Nations, the International Criminal Court (ICC), and human rights organizations, work to document, report, and advocate against human rights violations. Victims and civil society groups often rely on these organizations to seek accountability, raise awareness, and push for legislative or policy reforms. However, persistent challenges remain, especially in areas where governments or powerful groups are implicated in rights abuses.

Ending human rights violations requires robust legal frameworks, political will, international cooperation, and a strong civil society that advocates for justice, accountability, and systemic reforms that protect individuals and uphold fundamental human rights.

Hi. I construct a multidimensional data quality indicators for a low-cost wireless sensors network. Currently, it is tested using synthetic data that reproduce data quality issues such as accuracy, timeliness, completeness and reliability. Is there any testing methods using real world datasets that can test the robustness of the indicators?

Hello,

Is ML robust to non-normal distribution data or does it assume normality in Mplus?

Best,

What sample size considerations are critical for achieving robust results in SEM, especially when using complex models with multiple latent variables?

Physics is the subject of non multiple explanations i.e one and robust, it drives part of 8ts prestige from this.

However, as gravity is at the same time explained as curvature of spacetime and an effect of the presence of mass, this principle has an exception.

What are the implications? I.e can science in the future be multi-explanation disci9line, provided that these explanations are simple, precise and minimum number of phenomena unificational!?

Modifying the original Feistel structure will it be feasible to design a lightweight and robust encryption algorithm. Somehow changing the structure's original flow and adding some mathematical functions there. I welcome everyone's view.

Hi everyone,

I am quite confused about the efficiency of ATE estimators. For example, AIPW (doubly robust) is more efficient than IPW if outcome regression is correctly specified.

But many papers (Bounded, efficient and doubly robust estimation with inverse weighting) also said IPW can achieve the semiparametric efficiency bound. Since bound is the lowest, does it mean IPW and AIPW have the same asymptotical variance?

Thanks for your help in advance!

Best,

Jun

Can someone suggest a robust and reliable PCR protocol for sex determination from mouse genomic DNA?

Long story short:

I use a long unbalanced panel data set.

All tests indicate that 'fixed effects' is more appropriate than 'random effects' or 'pooled OLS'.

No serial correlation.

BUT, heteroskedasticity is present, even with robust White standard errors.

Can someone suggest a way to either 'remove' or just 'deal' with heteroskedasticity in panel data model?

The components as well as the type of data needed to design an electronic load controller for a 300kVA alternator(robust) for a mini hydro(150kVA).

I have identified many solutions. I need suggestion from somebody with application experience of this topic to identify the most reliable and robust procedure.

Why does information theory explain aging, evolution vs creationism, critical rationalism, computer programming and much more?

Perhaps information has a very open definition thus, is very robust.

Help Needed! Impact of Sustainable Materials on Project Management Hi everyone, I'm working on my thesis titled: "Impact of Sustainable Materials on Project Management in the Construction Industry". I'm reaching out to construction professionals, project managers, green building experts, professors, lecturers, and students for your valuable insights! In this research, I'm exploring how the use of sustainable materials is influencing project management practices within the construction industry. Understanding these impacts will be crucial for promoting more sustainable building practices in the future. To contribute to my research, I've created a short survey that takes less than 10 minutes to complete. Your participation would be greatly appreciated! https://lnkd.in/d4Hj9aYr Who can participate? Construction professionals (architects, engineers, project managers) Green building experts and sustainability consultants Professors, lecturers, and students in construction management or related fields What are the benefits of participating? Your insights will contribute to valuable research on sustainable construction practices. You'll help to shape the future of project management in the construction industry. You'll receive a summary of the research findings once completed (optional). Sharing is caring! Please share this post with your network of construction professionals and anyone interested in sustainable building practices. The more responses I receive, the more robust the research will be.

Dear Community,

I would like to develop and validate a qualitative NMR method for the analysis of a specific category of chemicals, and my question is the following: What are the criteria that I must assess?

I found a publication that states that the Limit of detection (LOD), the specificity and selectivity (NMR is inherently specific though), and Robustness must be investigated for a qualitative NMR method. But then what would be the experimental protocol to assess those criteria? For example: is there a need to perform the same experiment multiple times (on the same sample) and calculate the standard deviation for the estimation of the LOD, or just one experiment would be enough?

I would be more than grateful if someone experimented with NMR method development could provide more details on the subject.

Thank you.

Reversed flow on 28 faces of pressure-outlet 7.

Stabilizing mp-x-momentum to enhance linear solver robustness.

Stabilizing mp-x-momentum using GMRES to enhance linear solver robustness.

Stabilizing mp-y-momentum to enhance linear solver robustness.

Stabilizing mp-y-momentum using GMRES to enhance linear solver robustness.

Stabilizing k to enhance linear solver robustness.

Stabilizing k using GMRES to enhance linear solver robustness.

Divergence detected in AMG solver: k Stabilizing epsilon to enhance linear solver robustness.

Stabilizing epsilon using GMRES to enhance linear solver robustness.

Divergence detected in AMG solver: epsilon Stabilizing flue-gas-species-0 to enhance linear solver robustness.

Stabilizing flue-gas-species-1 to enhance linear solver robustness.

Stabilizing temperature to enhance linear solver robustness.

Stabilizing temperature using GMRES to enhance linear solver robustness.

Stabilizing vof-1 to enhance linear solver robustness.

absolute pressure limited to 5.000000e+10 in 2708 cells on zone 4

turbulent viscosity limited to viscosity ratio of 1.000000e+05 in 7089 cells

Divergence detected in AMG solver: k

Divergence detected in AMG solver: epsilon

Divergence detected in AMG solver: k

Divergence detected in AMG solver: epsilon

Divergence detected in AMG solver: k

Divergence detected in AMG solver: epsilon

Divergence detected in AMG solver: k

Divergence detected in AMG solver: epsilon

Divergence detected in AMG solver: k

Divergence detected in AMG solver: epsilon

Divergence detected in AMG solver: k

Divergence detected in AMG solver: epsilon

Divergence detected in AMG solver: k

Divergence detected in AMG solver: epsilon

Divergence detected in AMG solver: k

Divergence detected in AMG solver: epsilon

Divergence detected in AMG solver: k

Divergence detected in AMG solver: epsilon

Divergence detected in AMG solver: k

Divergence detected in AMG solver: epsilon

Divergence detected in AMG solver: k

Divergence detected in AMG solver: epsilon

Error at host: floating point exception

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Compute processes interrupted. Processing can be resumed.

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a) Design a scalable and robust network architecture that can handle the increasing data traffic and support various communication technologies.

b) Recommend suitable transmission technologies, such as fiber optics, microwave of satellite, based on factors like bandwidth requirements, distance coverage and reliability.

c) Incorporate robust security measures to protect the network against cyber threats and ensure high reliability through redundancy and backup systems.

Hello all,

I'm starting a project where we want to automate the video analysis of people working in different environments to produce ergonomic measures like hip flexion, shoulder extension, etc. We already tested some AI-based libraries like OpenPose, MMPose, Mediapipe, etc.

One of the project's objective was to estimate the precision and robustness of these vision solutions compared to some ground truth obtained by physical MoCap systems like the Movella system, previously known as XSens.

The problem is that the price of the Movella system, 8,500USD for hardware and 13,500USD/year for software, is way too high for our limited expected usage (maybe 1 month?). Do you know of some other MoCap systems that might be appropriate for this usage?

Note: We don't need a system so robust as to resist a fight scene motion capture.

1)

2)

Hello,

I have a question regarding the interpretation of the results from an experiment I conducted. Each participant answered 4 questions measuring motivation, satisfaction, help, and collaboration (my dependent variables) in 7 different scenarios (my independent variables). To analyze my results, I used three methods: a Wilcoxon signed rank test, a regression with standard errors clustered at the individual level - CRSE (to control for individual heterogeneity), and an ordinal regression (using GENLIN ) to account for the ordinal nature of the dependent variable.

The aim of this analysis was to verify if the significant results obtained with the Wilcoxon test were consistent across the other two methods. I conclude that significant results found with the Wilcoxon test, if they are also significant in the other two regressions, are robust.

Conversely, if an effect is significant in the Wilcoxon test and in the regression with CRSE ( standard errors cluster at the individual level), but not in the ordinal regression (GENLIN ordinal), I consider that this is not a robust effect, indicating that the result is not consistent across the three tests, this indicates that there is an indication of the effect, but that this indication is weak.

For the majority of my results, they are robust, but I have some scenarios where significant effects on certain dependent variables are no longer significant in the ordinal regression, but are in the Wilcoxon test and the regression with clustered standard errors. I am wondering why this happens and how to explain it.

I am working with SPSS version 27. Could you help me better understand these results and their interpretation?

Thank you in advance for your help.

Molecular dynamics simulation web servers

How does the application of generative adversarial networks (GANs) for data augmentation impact the robustness and accuracy of image classification models?

Hello.

I'm currently working on a control system for a doubly fed induction generator (DFIG) as part of my thesis project. Traditionally, fuzzy logic controllers (FLCs) use the error (e) and the derivative of error (\frac{de}{dt}) as inputs. However, in my implementation, I decided to use the integral of the error (\frac{1){s}) instead of the derivative after reading that it's possible in a certain textbook. Surprisingly, this approach has yielded very good results in my simulations. Despite the positive outcomes, my thesis supervisor mentioned that they had never encountered the integral of the error being used as an input in FLCs before. To ensure the robustness and academic validity of my approach, I need to back it up with some literature or resources that discuss this methodology.

Has anyone here used the integral of error in their fuzzy logic controllers, or come across any papers or textbooks that mention this practice? Any guidance, references, or suggestions would be immensely helpful.

Thanks in advance for your help!

What is robust load balancing in high-performance distributed computing systems? And what solutions do you suggest for it?

Hello,

I am using movestay command for ESR model analysis, but I get an error message.

Can anyone help me please?

movestay (ln_wage = $x), select(union= $x msp) vce (robust)

The error message is:

Fitting initial values .....initial vector: copy option requires either a matrix or a list of numbers

r(198);

Thanks in advance for your kindness

Hello everyone

1. Please suggest a robust free software to analysis the XRD results to obtain the corresponding 3d structure of a protein.

2. Is the xrd diffractogram with only a single peak better than a diffractogram with multiple peaks or vice versa? And what are the reasons?

3. What does raw.file show after xrd analysis?

Thanks to all

I am working on Battery Pack Thermal Analysis for an Electric Vehicle. Whenever I get to the point of pressing "Run Calculation", the solver displays 1 iteration only then displays some info and "Floating Point Exception". Here are the messages displayed in the console:

iter energy uds-0 uds-1 time/iter

1 1.6096e-07 7.8111e-07 7.7842e-07 0:00:40 10

Stabilizing temperature to enhance linear solver robustness.

Stabilizing temperature using GMRES to enhance linear solver robustness.

Divergence detected in AMG solver: temperature Stabilizing uds-0 to enhance linear solver robustness.

Stabilizing uds-0 using GMRES to enhance linear solver robustness.

Divergence detected in AMG solver: uds-0 Stabilizing uds-1 to enhance linear solver robustness.

Stabilizing uds-1 using GMRES to enhance linear solver robustness.

Divergence detected in AMG solver: uds-1

Divergence detected in AMG solver: temperature

Divergence detected in AMG solver: uds-0

Divergence detected in AMG solver: uds-1

Divergence detected in AMG solver: temperature

Divergence detected in AMG solver: uds-0

Divergence detected in AMG solver: uds-1

Divergence detected in AMG solver: temperature

Divergence detected in AMG solver: uds-0

Divergence detected in AMG solver: uds-1

Divergence detected in AMG solver: temperature

Divergence detected in AMG solver: uds-0

Divergence detected in AMG solver: uds-1

Divergence detected in AMG solver: temperature

Divergence detected in AMG solver: uds-0

Divergence detected in AMG solver: uds-1

Error at host: floating point exception

===============Message from the Cortex Process================================

Compute processes interrupted. Processing can be resumed.

==============================================================================

Error at Node 3: floating point exception

Error at Node 2: floating point exception

Error at Node 5: floating point exception

Error at Node 4: floating point exception

Error at Node 1: floating point exception

Error at Node 0: floating point exception

Error: floating point exception

Error Object: #f

I am new to Ansys Fluent, so I will be glad if anyone helps me throughout this problem. Thanks in advance!

I am searching for and trying to develop an interesting project topic for my MSc. thesis that relates to data acquisition, sensors, or anyone relating to robust or predictive control.

What is the best technique to employ as a robustness check with wavelet coherence to investigate the impact of uncertainty on the stock market ( weekly data)?

I need to construct a robust phylogeny based on the core genome of the strains. I have around 61 genomes of the strains. I want to know which bioinformatics tool is needed ?

Dear researchers,

Is it possible to consider Cost-Benefit Analysis (CBA) as a suitable form of robustness check in econometric analysis, taking into account its effectiveness in assessing the resilience and reliability of the findings?

There are lots of methods to check the robustness in a regression, like changing the key variables, using another econometric methods, etc. However, is it possible to use the results calculated by CBA to prove the results induced by econometric analysis? The results of CBA could be some additional evidence to defend the conclusion of econometrics.

. xtabond2 IndicedeTheil PIBparhabitantUSconstants InflationdéflateurduPIBa ITC Créditintérieurfourniausecte, gmm( IndicedeThei

> l, lag(2 4)collapse) iv( PIBparhabitantUSconstants InflationdéflateurduPIBa ITC Créditintérieurfourniausecte) twostep small n

> odiffsargan

Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm.

Dynamic panel-data estimation, two-step system GMM

------------------------------------------------------------------------------

Group variable: codepays Number of obs = 171

Time variable : Année Number of groups = 10

Number of instruments = 9 Obs per group: min = 12

F(4, 9) = 559.85 avg = 17.10

Prob > F = 0.000 max = 20

----------------------------------------------------------------------------------------------

IndicedeTheil | Coef. Std. Err. t P>|t| [95% Conf. Interval]

-----------------------------+----------------------------------------------------------------

PIBparhabitantUSconstants | .0000781 .0000141 5.53 0.000 .0000461 .00011

InflationdéflateurduPIBa | -.0137815 .0021388 -6.44 0.000 -.0186197 -.0089432

ITC | .0045328 .0029732 1.52 0.162 -.002193 .0112587

Créditintérieurfourniausecte | -.0241084 .0106227 -2.27 0.049 -.0481386 -.0000781

_cons | 3.522798 .8558666 4.12 0.003 1.586694 5.458903

----------------------------------------------------------------------------------------------

Warning: Uncorrected two-step standard errors are unreliable.

Instruments for first differences equation

Standard

D.(PIBparhabitantUSconstants InflationdéflateurduPIBa ITC

Créditintérieurfourniausecte)

GMM-type (missing=0, separate instruments for each period unless collapsed)

L(2/4).IndicedeTheil collapsed

Instruments for levels equation

Standard

PIBparhabitantUSconstants InflationdéflateurduPIBa ITC

Créditintérieurfourniausecte

_cons

GMM-type (missing=0, separate instruments for each period unless collapsed)

DL.IndicedeTheil collapsed

------------------------------------------------------------------------------

Arellano-Bond test for AR(1) in first differences: z = -0.35 Pr > z = 0.724

Arellano-Bond test for AR(2) in first differences: z = -0.68 Pr > z = 0.498

------------------------------------------------------------------------------

Sargan test of overid. restrictions: chi2(4) = 141.46 Prob > chi2 = 0.000

(Not robust, but not weakened by many instruments.)

Hansen test of overid. restrictions: chi2(4) = 5.04 Prob > chi2 = 0.283

(Robust, but weakened by many instruments.)

I perfomed 2SLS ,

In the robust version i found the endogeneity , but did not found in non robust version.

The results in robust version is validy? need your help.

Non Robust options

Could you recommend the most effective Python libraries for Machine Learning, such as TensorFlow, scikit-learn, and PyTorch, which empower developers with efficient tools for building robust models?

I have calculated a robust 2x3 mixed anova in R (with the package WRS2).

Now I wanted to calculate the effect sizes. However, I can't find anywhere how to calculate them for the robust anova. Does anyone know a function in R with which this is possible?

Hi everyone,

I have an dependent ordinal variable (five point Likert item) and a nominal grouping variable with five categories and want to test for differences in the responses on the dependent variables between the categories.

For that purpose I considered applying a Kruskal-Wallis with subsequent Dunn's tests.

The problem is that by inspecting of the boxplots the distributions of the responses differ quite a much between groups.

How robust is KW to the violation of the sameness of distribution shape assumption?

What are possible alternatives to the KW in this case?

Does the issue of multicollinearity affect the reliability, interpretation, and robustness of a mediation analysis?

I want to use these methods in SPSS or MATLAB software, but I don't know how to do it, can anyone help me?

If you know a video or site, please send it to me.

If you know any other software that can do these methods easily, please tell me.

Adversarial attacks exploit vulnerabilities in AI models, leading to incorrect predictions. Developing robust defense mechanisms is essential to safeguard AI systems from such threats.

AI-generated fake content, including "deepfake" videos, poses significant challenges to trust, media integrity, and the spread of misinformation, necessitating robust detection and verification mechanisms.

I am working to increase the dynamic range of a sandwich ELISA and the robustness. I have worked on the capture antibody concentration, primary and secondary antibodies concentration, the plastic, the blocking, coating and washing buffers. The robustness is now OK by changing the buffers but the dynamic range stay still very low. Have you got any ideas?

Dears,

I am running a var (1) model. My optimal lag selection criteria are giving me different optimal lags: AIC is giving me 4 lags as most of the other tests are. SBIC, however, is giving me an optimal lag of 1. I tried all the options, and seems my model is not significant when i increase my lags as shown by AIC and other tests. if I use SBIC, my model is significant and results look reasonable. However, my VAR (1) is serially auto correlated and probably suffering from heteroskedasticity. Could you please any help on how test for heterskedasticity for VAR system? Is it possible to run HAC Var model and make the errors robust both for heteroskedasticity and serial auto correlation? I am using STATA.

Thanks!

Hello, I conducted 2-Stage System GMM in the STATA program. However, I couldn't find a code to adjust the number of instrumental variables. If there exists such a code, could you share it, please? Where should I add this code in my main code line?

Thanks in advance..

My main code line

xtabond2 X1 L.X1 X2 lnX3 lnX9 lnX15 lnX16, gmm(L.X1, collapse) twostep robust nomata iv(L.X2 L.X3 L.lnX9 L.lnX15 L.lnX16)

Most empirical papers use a single econometric method to demonstrate a relationship between two variables. For robustness, is not it safer to use a variety of methods to conclude (cointegration IV models with thresholds, wavelet)?

We are studying on dynamic teams. We have developed an O2O platform for soccer activity organizing and team management. Teams in the platform are dynamic and boundary-blurring.

We are writing research articles based on our developed platform. While we have a question about robustness testing, that is, we don't know if it is okay to use another period's dataset of the platform to do robustness testing. Is there any research article doing robustness testing in the same way?

Here are my Matlab files for the paper we recently published in IET Control Theory and Applications. The paper is about designing robust controllers for networked systems. It is hoped that these codes will help students to understand how a robust approach would be coded.

Code Matlab a Robust Controller +LMI+Multi-agent systems

Yalmip Toolbox must be added to Matlab.

How to Install a MATLAB toolbox?

After that, you can run the attached codes.

Hi,

I am looking for an equipment that primarily is designed for separation of heterogenous composite system and it must be that robust to tackle asphalt mixture. The equipment can be associated to any lab regardless of its applications to pavement industry.

Note: I am looking for one other than the centrifuge extractor as its not addressing the purpose.

Best,

Gohar

I'm trying to specify a model with government expenditures and economic growth. My VECM passes all the robustness checks, when variables are included without transformations, but the coefficients are abnormally high, because I'm including GDP per capita data in absilolute values and expenditures data in percentages. If I take all variables in log transformations, then the coefficients make sense, however, the model has serial correlation and heteroskedasticity problems (only in logs). Can I proceed with the VECM model without log transformations?

Access to healthcare is of paramount importance to public health and well-being. Governments have a responsibility to ensure that their citizens have access to quality healthcare in order to maintain a thriving society. Robust public health systems are essential for providing equitable, affordable, and effective healthcare for all. Quality healthcare services must be available to all segments of the population, regardless of income, race, or geography.

I need any help to make me clear on this topic.

I am working on grafting two nanoparticles of various sizes, i.e., one is 10-20nm, while the other is around 100nm. Can anyone please tell me a simple, robust, and efficient grafting technique to decorate smaller nanoparticles on top of the larger nanoparticle?