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Abstract
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The evolution of mankind during the last 2 centuries has generated an ever growing thrive for increased production, for the need to create novel means to generate energy and for society to change into a more consumerism-oriented version. All of these aforementioned arguments induce repeated and frequently irreversible repercussions on nature, and through constant alterations of the environment, significant global climate changes have been observed especially in the most recent times. During the last half of the century, all of these climatic changes have induced, as direct effects, the exponential rise in the number of natural disasters, and this increase is also emphasized by the ever-growing intensification of these phenomena, with devastating effects [1]. Out of all these extreme natural phenomena, floods are statistically considered some of the most damage-inducing, with an ever-more frequent recurrence time period, and can originate from fluvial sources, from extreme torrential rainfall, from coastal floods, or even due to underground causes. On a global scale, out of the entirety of registered events that took place since 1900, floods account for 25% of the events that occurred since 1900, 38% of the events registered since 1960, and 45% for events that took place since 2000 [2]. The population affected by this type of risk has dramatically decreased since the 1960′s, but the economic damages from floods, as a shared portion of the GDP at a global level, has risen from 0.02% (during the timespan between 1960-1969), up to 0.05% (between 2010-2019) [3]. The economic implications (costs of infrastructure, insurances, and even social-related issues) induced on the local communities are expected to increase even more in the following years, due to the expansion of the urban built-up areas, economic growth, and especially climate change [4,5].
The fact that natural phenomena, such as floods, induce tremendous amounts of damage, both from an economic and social perspective, has determined scientists to address this issue, and to search for potential solutions to identify areas, exposed to flood risk. In order to help mitigate this, multiple mathematical modelling algorithms were developed, with a variety of functions, such as calculating flow rate values, estimating possible recurring flow rates, mapping of flood risk, generating scenarios related to flood extent layers, warning and delay times for flash floods etc. [6,7]. Most of the aforementioned were mainly developed during the last 5 decades, justified by the increase in computational capabilities and in interest towards mitigating the negative impact of future events [2,3]. The main, general purpose they serve, is to describe the manner in which a drainage basin responds to sudden changes in flow rates, the increased values in torrential rainfall and estimate as precisely, as possible, the runoff, or even the groundwater related parameters, if required. Another aspect flood models address is the probability extent of floods along the main channel and floodplain for the main, collector river.
In order to mathematically model a flood event or simulation, significant temporal resources and labor have to be dedicated towards generating and validating the final results, therefore raising numerous technical challenges, associated to the complete characterization and cartographic representation of several physical and hydrodynamic parameters, such as: the relationship between rainfall and runoff, the heterogenic distribution of precipitation, the morphometric and pedological aspects in the study area etc. The more these parameters are better calibrated, the significantly better the final results related to the hydrological risk are, in accordance with the in-field situation [8,9]. Recent progress in the modern techniques, based on long, representative datasets are related to the increased availability of these kinds of methods, in comparison to the classic hydrodynamic analysis methodologies, which aid in the real-time forecasting of flood events. Novel detection systems (such as remote sensing techniques), in relation to modern data acquisition means, and backed by experimental techniques, provide new opportunities for calibration, validation, testing and improving the flood models [10,11,12].
The heterogenic manner through which the issue of flood risk is addressed, at the scientific, quantifiable level has determined us to compile a Special Issue which would promote publications that address flood analysis and apply some of the most novel inundation prediction models, as well as various hydrological risk simulations related to floods, that will enhance the current state of knowledge in the field as well as lead toward a better understanding of flood risk modeling. Furthermore, the current Special Issue will address the temporal aspect of flood propagation, including alert times, warning systems, flood time distribution cartographic material, and the numerous parameters involved in flood risk modeling.
Language: en |