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Prof. Demetris Koutsoyiannis
National Technical University of Athens

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0 Climatology
0 Hydrology
0 Water Resource Engineering
0 Water Resource Management
0 hydrologic cycle

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Short Biography

Demetris Koutsoyiannis is professor of Hydrology and Analysis of Hydrosystems in the National Technical University of Athens. He has served as Dean of the School of Civil Engineering, Head of the Department of Water Resources and Environmental Engineering, and Head of the Laboratory of Hydrology and Water Resources Development. He was Editor of Hydrological Sciences Journal for 12 years (2006-18), and member of the editorial boards of Hydrology and Earth System Sciences, Journal of Hydrology and Water Resources Research. He has been awarded the International Hydrology Prize– Dooge medal (2014) by International Association of Hydrological Sciences (IAHS), UNESCO and World Meteorological Organization (WMO), and the Henry Darcy Medal (2009) by European Geosciences Union (EGU). His distinctions include the Lorenz Lecture of the American Geophysical Union (AGU) (San Francisco, USA, 2014) and the Union Plenary Lecture of the International Union of Geodesy and Geophysics (IUGG) (Melbourne, Australia, 2011). He has served as professor of Hydraulics at the Hellenic Army’s Postgraduate School of Technical Education of Officers Engineers (Athens, 2007-10). He has been visiting academic/professor at the Imperial College (London, 1999-2000), Hydrologic Research Center (San Diego, 2005), Georgia Institute of Technology (Atlanta, 2005-06), University of Bologna (2006 & 2019) and Sapienza University of Rome (2008 & 2019).

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Journal article
Published: 11 August 2021 in Sustainability
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Water, energy, land, and food are vital elements with multiple interactions. In this context, the concept of a water–energy–food (WEF) nexus was manifested as a natural resource management approach, aiming at promoting sustainable development at the international, national, or local level and eliminating the negative effects that result from the use of each of the four resources against the other three. At the same time, the transition to green energy through the application of renewable energy technologies is changing and perplexing the relationships between the constituent elements of the nexus, introducing new conflicts, particularly related to land use for energy production vs. food. Specifically, one of the most widespread “green” technologies is photovoltaic (PV) solar energy, now being the third foremost renewable energy source in terms of global installed capacity. However, the growing development of PV systems results in ever expanding occupation of agricultural lands, which are most advantageous for siting PV parks. Using as study area the Thessaly Plain, the largest agricultural area in Greece, we investigate the relationship between photovoltaic power plant development and food production in an attempt to reveal both their conflicts and their synergies.

ACS Style

G.-Fivos Sargentis; Paraskevi Siamparina; Georgia-Konstantina Sakki; Andreas Efstratiadis; Michalis Chiotinis; Demetris Koutsoyiannis. Agricultural Land or Photovoltaic Parks? The Water–Energy–Food Nexus and Land Development Perspectives in the Thessaly Plain, Greece. Sustainability 2021, 13, 8935 .

AMA Style

G.-Fivos Sargentis, Paraskevi Siamparina, Georgia-Konstantina Sakki, Andreas Efstratiadis, Michalis Chiotinis, Demetris Koutsoyiannis. Agricultural Land or Photovoltaic Parks? The Water–Energy–Food Nexus and Land Development Perspectives in the Thessaly Plain, Greece. Sustainability. 2021; 13 (16):8935.

Chicago/Turabian Style

G.-Fivos Sargentis; Paraskevi Siamparina; Georgia-Konstantina Sakki; Andreas Efstratiadis; Michalis Chiotinis; Demetris Koutsoyiannis. 2021. "Agricultural Land or Photovoltaic Parks? The Water–Energy–Food Nexus and Land Development Perspectives in the Thessaly Plain, Greece." Sustainability 13, no. 16: 8935.

Oxencycl entry
Published: 28 June 2021 in Oxford Research Encyclopedia of Environmental Science
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Humanity has been modifying the natural water cycle by building large-scale water infrastructure for millennia. For most of that time, the principles of hydraulics and control theory were only imperfectly known. Moreover, the feedback from the artificial system to the natural system was not taken into account, either because it was too small to notice or took too long to appear. In the 21st century, humanity is all too aware of the effects of our adaptation of the environment to our needs on the planetary system as a whole. It is necessary to see the environment, both natural and hman-made as one integrated system. Moreover, due to the legacy of the past, the behaviour of the man-madeparts of this system needs to be adapted in a way that leads to a sustainable ecosystem. The water cycle plays a central role in that ecosystem. It is therefore essential that the behaviour of existing and planned water infrastructure fits into the natural system and contributes to its well-being. At the same time, it must serve the purpose for which it was constructed. As there are no natural feedbacks to govern its behaviour, it will be necessary to create such feedbacks, possibly in the form of real-time control systems. To do so, it would be beneficial if all persons involved in the decision process that establishes the desired system behaviour understand the basics of control systems in general and their application to different water systems in particular. This article contains a discussion of the prerequisites for and early development of automatic control of water systems, an introduction to the basics of control theory with examples, a short description of optimal control theory in general, a discussion of model predictive control in water resource management, an overview of key aspects of automatic control in water resource management, and different types of applications. Finally, some challenges faced by practitioners are mentioned.

ACS Style

Ronald van Nooijen; Demetris Koutsoyiannis; Alla Kolechkina. Optimal and Real-Time Control of Water Infrastructures. Oxford Research Encyclopedia of Environmental Science 2021, 1 .

AMA Style

Ronald van Nooijen, Demetris Koutsoyiannis, Alla Kolechkina. Optimal and Real-Time Control of Water Infrastructures. Oxford Research Encyclopedia of Environmental Science. 2021; ():1.

Chicago/Turabian Style

Ronald van Nooijen; Demetris Koutsoyiannis; Alla Kolechkina. 2021. "Optimal and Real-Time Control of Water Infrastructures." Oxford Research Encyclopedia of Environmental Science , no. : 1.

Chapter
Published: 13 June 2021 in Handbook of Water Resources Management: Discourses, Concepts and Examples
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The fundamental concepts in the field of water-energy systems and their historical evolution with emphasis on recent developments are reviewed. Initially, a brief history of the relation of water and energy is presented, and the concept of the water-energy nexus in the 21th century is introduced. The investigation of the relationship between water and energy shows that this relationship comprises both conflicting and synergistic elements. Hydropower is identified as the major industry of the sector and its role in addressing modern energy challenges by means of integrated water-energy management is highlighted. Thus, the modelling steps of designing and operating a hydropower system are reviewed, followed by an analysis of theory and physics behind energy hydraulics. The key concept of uncertainty, which characterises all types of renewable energy, is also presented in the context of the design and management of water-energy systems. Subsequently, environmental considerations and impacts of using water for energy generation are discussed, followed by a summary of the developments in the emerging field of maritime energy. Finally, present challenges and possible future directions are presented.

ACS Style

Nikos Mamassis; Andreas Efstratiadis; Panayiotis Dimitriadis; Theano Iliopoulou; Romanos Ioannidis; Demetris Koutsoyiannis. Water and Energy. Handbook of Water Resources Management: Discourses, Concepts and Examples 2021, 619 -657.

AMA Style

Nikos Mamassis, Andreas Efstratiadis, Panayiotis Dimitriadis, Theano Iliopoulou, Romanos Ioannidis, Demetris Koutsoyiannis. Water and Energy. Handbook of Water Resources Management: Discourses, Concepts and Examples. 2021; ():619-657.

Chicago/Turabian Style

Nikos Mamassis; Andreas Efstratiadis; Panayiotis Dimitriadis; Theano Iliopoulou; Romanos Ioannidis; Demetris Koutsoyiannis. 2021. "Water and Energy." Handbook of Water Resources Management: Discourses, Concepts and Examples , no. : 619-657.

Preprint
Published: 26 May 2021
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We outline and test a new methodology for genuine simulation of stochastic processes with any dependence and any marginal distribution. We reproduce time dependence with a generalized, time symmetric or asymmetric, moving-average scheme. This implements linear filtering of non-Gaussian white noise, with the weights of the filter determined by analytical equations in terms of the autocovariance of the process. We approximate the marginal distribution of the process, irrespective of its type, using a number of its cumulants, which in turn determine the cumulants of white noise in a manner that can readily support the generation of random numbers from that approximation, so that it be applicable for stochastic simulation. The simulation method is genuine as it uses the process of interest directly without any transformation (e.g. normalization). We illustrate the method in a number of synthetic and real-world applications with either persistence or antipersistence, and with non-Gaussian marginal distributions that are bounded, thus making the problem more demanding. These include distributions bounded from both sides, such as uniform, and bounded form below, such as exponential and Pareto, possibly having a discontinuity at the origin (intermittence). All examples studied show the satisfactory performance of the method.

ACS Style

Demetris Koutsoyiannis; Panayiotis Dimitriadis. Towards Generic Simulation for Demanding Stochastic Processes. 2021, 1 .

AMA Style

Demetris Koutsoyiannis, Panayiotis Dimitriadis. Towards Generic Simulation for Demanding Stochastic Processes. . 2021; ():1.

Chicago/Turabian Style

Demetris Koutsoyiannis; Panayiotis Dimitriadis. 2021. "Towards Generic Simulation for Demanding Stochastic Processes." , no. : 1.

Journal article
Published: 10 May 2021 in Hydrology and Earth System Sciences
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Whilst hydrology is a Greek term, it was not in use in the Classical literature, but much later, during the Renaissance, in its Latin form, hydrologia. On the other hand, Greek natural philosophers (or, in modern vocabulary, scientists) created robust knowledge in related scientific areas, to which they gave names such as meteorology, climate and hydraulics. These terms are now in common use internationally. Greek natural philosophers laid the foundation for hydrological concepts and the hydrological cycle in its entirety. Knowledge development was brought about by searches for technological solutions to practical problems as well as by scientific curiosity. While initial explanations belong to the sphere of mythology, the rise of philosophy was accompanied by the quest for scientific descriptions of the phenomena. It appears that the first geophysical problem formulated in scientific terms was the explanation of the flood regime of the Nile, then regarded as a paradox because of the spectacular difference from the river flow regime in Greece, i.e. the fact that the Nile flooding occurs in summer when in most of the Mediterranean the rainfall is very low. While the early attempts were unsuccessful, Aristotle was able to formulate a correct hypothesis, which he tested through what appears to be the first scientific expedition in history, in the transition from the Classical to Hellenistic periods. The Hellenistic period brought advances in all scientific fields including hydrology, an example of which is the definition and measurement of flow discharge by Heron of Alexandria. These confirm the fact that the hydrological cycle was well understood in Ancient Greece, yet it poses the question why correct explanations were not accepted and, instead, why ancient and modern mythical views were preferred up to the 18th century.

ACS Style

Demetris Koutsoyiannis; Nikos Mamassis. From mythology to science: the development of scientific hydrological concepts in Greek antiquity and its relevance to modern hydrology. Hydrology and Earth System Sciences 2021, 25, 2419 -2444.

AMA Style

Demetris Koutsoyiannis, Nikos Mamassis. From mythology to science: the development of scientific hydrological concepts in Greek antiquity and its relevance to modern hydrology. Hydrology and Earth System Sciences. 2021; 25 (5):2419-2444.

Chicago/Turabian Style

Demetris Koutsoyiannis; Nikos Mamassis. 2021. "From mythology to science: the development of scientific hydrological concepts in Greek antiquity and its relevance to modern hydrology." Hydrology and Earth System Sciences 25, no. 5: 2419-2444.

Journal article
Published: 08 May 2021 in Applied Energy
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Lacking coastal and offshore wind speed time series of sufficient length, reanalysis data and wind speed models serve as the primary sources of valuable information for wind power management. In this study, long-length observational records and modelled data from Uncertainties in Ensembles of Regional Re-Analyses system are collected, analyzed and modelled. The first stage refers to the statistical analysis of the time series marginal structure in terms of the fitting accuracy, the distributions’ tails behavior, extremes response and the power output errors, using Weibull distribution and three parameter Weibull-related distributions (Burr Type III and XII, Generalized Gamma). In the second stage, the co-located samples in time and space are compared in order to investigate the reanalysis data performance. In the last stage, the stochastic generation mathematical framework is applied based on a Generalized Hurst-Kolmogorov process embedded in a Symmetric-Moving-Average scheme, which is used for the simulation of a wind process while preserving explicitly the marginal moments, wind’s intermittency and long-term persistence. Results indicate that Burr and Generalized Gamma distribution could be successfully used for wind resource assessment, although, the latter emerged enhanced performance in most of the statistical tests. Moreover, the credibility of the reanalysis data is questionable due to increased bias and root mean squared errors, however, high-order statistics along with the long-term persistence are thoroughly preserved. Eventually, the simplicity and the flexibility of the stochastic generation scheme to reproduce the seasonal and diurnal wind characteristics by preserving the long-term dependence structure are highlighted.

ACS Style

Loukas Katikas; Panayiotis Dimitriadis; Demetris Koutsoyiannis; Themistoklis Kontos; Phaedon Kyriakidis. A stochastic simulation scheme for the long-term persistence, heavy-tailed and double periodic behavior of observational and reanalysis wind time-series. Applied Energy 2021, 295, 116873 .

AMA Style

Loukas Katikas, Panayiotis Dimitriadis, Demetris Koutsoyiannis, Themistoklis Kontos, Phaedon Kyriakidis. A stochastic simulation scheme for the long-term persistence, heavy-tailed and double periodic behavior of observational and reanalysis wind time-series. Applied Energy. 2021; 295 ():116873.

Chicago/Turabian Style

Loukas Katikas; Panayiotis Dimitriadis; Demetris Koutsoyiannis; Themistoklis Kontos; Phaedon Kyriakidis. 2021. "A stochastic simulation scheme for the long-term persistence, heavy-tailed and double periodic behavior of observational and reanalysis wind time-series." Applied Energy 295, no. : 116873.

Original paper
Published: 12 April 2021 in Stochastic Environmental Research and Risk Assessment
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Near-surface air temperature is one of the most widely studied hydroclimatic variables, as both its regular and extremal behaviors are of paramount importance to human life. Following the global warming observed in the past decades and the advent of the anthropogenic climate change debate, interest in temperature’s variability and extremes has been rising. It has since become clear that it is imperative not only to identify the exact shape of the temperature’s distribution tails, but also to understand their temporal evolution. Here, we investigate the stochastic behavior of near-surface air temperature using the newly developed estimation tool of Knowable (K-)moments. K-moments, because of their property to substitute higher-order deviations from the mean with the distribution function, enable reliable estimation and an effective alternative to order statistics and, particularly for the outliers-prone distribution tails. We compile a large set of daily timeseries (30–200 years) of average, maximum and minimum air temperature, which we standardize with respect to the monthly variability of each record. Our focus is placed on the maximum and minimum temperatures, because they are more reliably measured than the average, yet very rarely analyzed in the literature. We examine segments of each timeseries using consecutive rolling 30-year periods, from which we extract extreme values corresponding to specific return period levels. Results suggest that the average and minimum temperature tend to increase, while overall the maximum temperature is slightly decreasing. Furthermore, we model the temperature timeseries as a filtered Hurst-Kolmogorov process and use Monte Carlo simulation to produce synthetic records with similar stochastic properties through the explicit Symmetric Moving Average scheme. We subsequently evaluate how the patterns observed in the longest records can be reproduced by the synthetic series.

ACS Style

Konstantinos-Georgios Glynis; Theano Iliopoulou; Panayiotis Dimitriadis; Demetris Koutsoyiannis. Stochastic investigation of daily air temperature extremes from a global ground station network. Stochastic Environmental Research and Risk Assessment 2021, 1 -19.

AMA Style

Konstantinos-Georgios Glynis, Theano Iliopoulou, Panayiotis Dimitriadis, Demetris Koutsoyiannis. Stochastic investigation of daily air temperature extremes from a global ground station network. Stochastic Environmental Research and Risk Assessment. 2021; ():1-19.

Chicago/Turabian Style

Konstantinos-Georgios Glynis; Theano Iliopoulou; Panayiotis Dimitriadis; Demetris Koutsoyiannis. 2021. "Stochastic investigation of daily air temperature extremes from a global ground station network." Stochastic Environmental Research and Risk Assessment , no. : 1-19.

Review
Published: 11 April 2021 in Sustainability
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Since prehistoric times, water conflicts have occurred as a result of a wide range of tensions and/or violence, which have rarely taken the form of traditional warfare waged over water resources alone. Instead, water has historically been a (re)source of tension and a factor in conflicts that start for other reasons. In some cases, water was used directly as a weapon through its ability to cause damage through deprivation or erosion or water resources of enemy populations and their armies. However, water conflicts, both past and present, arise for several reasons; including territorial disputes, fight for resources, and strategic advantage. The main reasons of water conflicts are usually delimitation of boundaries, waterlogging (e.g., dams and lakes), diversion of rivers flow, running water, food, and political distresses. In recent decades, the number of human casualties caused by water conflicts is more than that of natural disasters, indicating the importance of emerging trends on water wars in the world. This paper presents arguments, fights, discourses, and conflicts around water from ancient times to the present. This diachronic survey attempts to provide water governance alternatives for the current and future.

ACS Style

Andreas Angelakis; Mohammad Valipour; Abdelkader Ahmed; Vasileios Tzanakakis; Nikolaos Paranychianakis; Jens Krasilnikoff; Renato Drusiani; Larry Mays; Fatma El Gohary; Demetris Koutsoyiannis; Saifullah Khan; Luigi Giacco. Water Conflicts: From Ancient to Modern Times and in the Future. Sustainability 2021, 13, 4237 .

AMA Style

Andreas Angelakis, Mohammad Valipour, Abdelkader Ahmed, Vasileios Tzanakakis, Nikolaos Paranychianakis, Jens Krasilnikoff, Renato Drusiani, Larry Mays, Fatma El Gohary, Demetris Koutsoyiannis, Saifullah Khan, Luigi Giacco. Water Conflicts: From Ancient to Modern Times and in the Future. Sustainability. 2021; 13 (8):4237.

Chicago/Turabian Style

Andreas Angelakis; Mohammad Valipour; Abdelkader Ahmed; Vasileios Tzanakakis; Nikolaos Paranychianakis; Jens Krasilnikoff; Renato Drusiani; Larry Mays; Fatma El Gohary; Demetris Koutsoyiannis; Saifullah Khan; Luigi Giacco. 2021. "Water Conflicts: From Ancient to Modern Times and in the Future." Sustainability 13, no. 8: 4237.

Journal article
Published: 07 April 2021 in Hydrology
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We investigate the impact of time’s arrow on the hourly streamflow process. Although time asymmetry, i.e., temporal irreversibility, has been previously implemented in stochastics, it has only recently attracted attention in the hydrological literature. Relevant studies have shown that the time asymmetry of the streamflow process is manifested at scales up to several days and vanishes at larger scales. The latter highlights the need to reproduce it in flood simulations of fine-scale resolution. To this aim, we develop an enhancement of a recently proposed simulation algorithm for irreversible processes, based on an asymmetric moving average (AMA) scheme that allows for the explicit preservation of time asymmetry at two or more time-scales. The method is successfully applied to a large hourly streamflow time series from the United States Geological Survey (USGS) database, with time asymmetry prominent at time scales up to four days.

ACS Style

Stelios Vavoulogiannis; Theano Iliopoulou; Panayiotis Dimitriadis; Demetris Koutsoyiannis. Multiscale Temporal Irreversibility of Streamflow and Its Stochastic Modelling. Hydrology 2021, 8, 63 .

AMA Style

Stelios Vavoulogiannis, Theano Iliopoulou, Panayiotis Dimitriadis, Demetris Koutsoyiannis. Multiscale Temporal Irreversibility of Streamflow and Its Stochastic Modelling. Hydrology. 2021; 8 (2):63.

Chicago/Turabian Style

Stelios Vavoulogiannis; Theano Iliopoulou; Panayiotis Dimitriadis; Demetris Koutsoyiannis. 2021. "Multiscale Temporal Irreversibility of Streamflow and Its Stochastic Modelling." Hydrology 8, no. 2: 63.

Journal article
Published: 31 March 2021 in Hydrology
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To seek stochastic analogies in key processes related to the hydrological cycle, an extended collection of several billions of data values from hundred thousands of worldwide stations is used in this work. The examined processes are the near-surface hourly temperature, dew point, relative humidity, sea level pressure, and atmospheric wind speed, as well as the hourly/daily streamflow and precipitation. Through the use of robust stochastic metrics such as the K-moments and a second-order climacogram (i.e., variance of the averaged process vs. scale), it is found that several stochastic similarities exist in both the marginal structure, in terms of the first four moments, and in the second-order dependence structure. Stochastic similarities are also detected among the examined processes, forming a specific hierarchy among their marginal and dependence structures, similar to the one in the hydrological cycle. Finally, similarities are also traced to the isotropic and nearly Gaussian turbulence, as analyzed through extensive lab recordings of grid turbulence and of turbulent buoyant jet along the axis, which resembles the turbulent shear and buoyant regime that dominates and drives the hydrological-cycle processes in the boundary layer. The results are found to be consistent with other studies in literature such as solar radiation, ocean waves, and evaporation, and they can be also justified by the principle of maximum entropy. Therefore, they allow for the development of a universal stochastic view of the hydrological-cycle under the Hurst–Kolmogorov dynamics, with marginal structures extending from nearly Gaussian to Pareto-type tail behavior, and with dependence structures exhibiting roughness (fractal) behavior at small scales, long-term persistence at large scales, and a transient behavior at intermediate scales.

ACS Style

Panayiotis Dimitriadis; Demetris Koutsoyiannis; Theano Iliopoulou; Panos Papanicolaou. A Global-Scale Investigation of Stochastic Similarities in Marginal Distribution and Dependence Structure of Key Hydrological-Cycle Processes. Hydrology 2021, 8, 59 .

AMA Style

Panayiotis Dimitriadis, Demetris Koutsoyiannis, Theano Iliopoulou, Panos Papanicolaou. A Global-Scale Investigation of Stochastic Similarities in Marginal Distribution and Dependence Structure of Key Hydrological-Cycle Processes. Hydrology. 2021; 8 (2):59.

Chicago/Turabian Style

Panayiotis Dimitriadis; Demetris Koutsoyiannis; Theano Iliopoulou; Panos Papanicolaou. 2021. "A Global-Scale Investigation of Stochastic Similarities in Marginal Distribution and Dependence Structure of Key Hydrological-Cycle Processes." Hydrology 8, no. 2: 59.

Journal article
Published: 30 March 2021 in World
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In human societies, we observe a wide range of types of stratification, i.e., in terms of financial class, political power, level of education, sanctity, and military force. In financial, political, and social sciences, stratification is one of the most important issues and tools as the Lorenz Curve and the Gini Coefficient have been developed to describe some of its aspects. Stratification is greatly dependent on the access of people to wealth. By “wealth”, we mean the quantified prosperity which increases the life expectancy of people. Prosperity is also connected to the water-food-energy nexus which is necessary for human survival. Analyzing proxies of the water-food-energy nexus, we suggest that the best proxy for prosperity is energy, which is closely related to Gross Domestic Product (GDP) per capita and life expectancy. In order to describe the dynamics of social stratification, we formulate an entropic view of wealth in human societies. An entropic approach to income distribution, approximated as available energy in prehistoric societies, till present-day economies, shows that stratification can be viewed as a stochastic process subject to the principle of maximum entropy and occurring when limits to the wealth of society are set, either by the political and economic system and/or by the limits of available technology.

ACS Style

G.-Fivos Sargentis; Theano Iliopoulou; Panayiotis Dimitriadis; Nikolaos Mamassis; Demetris Koutsoyiannis. Stratification: An Entropic View of Society’s Structure. World 2021, 2, 153 -174.

AMA Style

G.-Fivos Sargentis, Theano Iliopoulou, Panayiotis Dimitriadis, Nikolaos Mamassis, Demetris Koutsoyiannis. Stratification: An Entropic View of Society’s Structure. World. 2021; 2 (2):153-174.

Chicago/Turabian Style

G.-Fivos Sargentis; Theano Iliopoulou; Panayiotis Dimitriadis; Nikolaos Mamassis; Demetris Koutsoyiannis. 2021. "Stratification: An Entropic View of Society’s Structure." World 2, no. 2: 153-174.

Chapter
Published: 26 March 2021 in Data Analytics for Cultural Heritage
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Throughout human history, the quantification of aesthetics has intrigued philosophers, artists, and mathematicians alike. In this chapter, a methodology based on stochastic mathematics is applied for the quantification of aesthetic attributes of paintings and landscapes. The paintings analyzed include Da Vinci, Pablo Picasso, and various other celebrated paintings from 1250 AD to modern times. In regard to landscapes, the analysis focuses on the aesthetic transformations imposed to landscapes from wind energy projects. The methodology used is called stochastic 2D-C analysis and is based on a stochastic computational tool that analyzes brightness fluctuation in images. The 2D-C tool is used to measure the degree of variability and in particular the change in variability vs. scale. The application of the tool provides (a) input on the qualitative efficiency of mainstream methods used in landscape-impact analysis, (b) insights into the expression forms of the examined artists and historical periods, and finally (c) evidence that can be used in the search of the originality of an artwork of disputed authorship.

ACS Style

G.-Fivos Sargentis; Romanos Ioannidis; Michalis Chiotinis; Panayiotis G. Dimitriadis; Demetris Koutsoyiannis. Aesthetical Issues with Stochastic Evaluation. Data Analytics for Cultural Heritage 2021, 173 -193.

AMA Style

G.-Fivos Sargentis, Romanos Ioannidis, Michalis Chiotinis, Panayiotis G. Dimitriadis, Demetris Koutsoyiannis. Aesthetical Issues with Stochastic Evaluation. Data Analytics for Cultural Heritage. 2021; ():173-193.

Chicago/Turabian Style

G.-Fivos Sargentis; Romanos Ioannidis; Michalis Chiotinis; Panayiotis G. Dimitriadis; Demetris Koutsoyiannis. 2021. "Aesthetical Issues with Stochastic Evaluation." Data Analytics for Cultural Heritage , no. : 173-193.

Journal article
Published: 19 March 2021 in Water
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We revisit the notion of climate, along with its historical evolution, tracing the origin of the modern concerns about climate. The notion (and the scientific term) of climate was established during the Greek antiquity in a geographical context and it acquired its statistical content (average weather) in modern times after meteorological measurements had become common. Yet the modern definitions of climate are seriously affected by the wrong perception of the previous two centuries that climate should regularly be constant, unless an external agent acts upon it. Therefore, we attempt to give a more rigorous definition of climate, consistent with the modern body of stochastics. We illustrate the definition by real-world data, which also exemplify the large climatic variability. Given this variability, the term “climate change” turns out to be scientifically unjustified. Specifically, it is a pleonasm as climate, like weather, has been ever-changing. Indeed, a historical investigation reveals that the aim in using that term is not scientific but political. Within the political aims, water issues have been greatly promoted by projecting future catastrophes while reversing true roles and causality directions. For this reason, we provide arguments that water is the main element that drives climate, and not the opposite.

ACS Style

Demetris Koutsoyiannis. Rethinking Climate, Climate Change, and Their Relationship with Water. Water 2021, 13, 849 .

AMA Style

Demetris Koutsoyiannis. Rethinking Climate, Climate Change, and Their Relationship with Water. Water. 2021; 13 (6):849.

Chicago/Turabian Style

Demetris Koutsoyiannis. 2021. "Rethinking Climate, Climate Change, and Their Relationship with Water." Water 13, no. 6: 849.

Preprint content
Published: 04 March 2021
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Changes in the land cover occur all the time at the surface of the Earth both naturally and anthropogenically. In the last decades, certain types of land cover change, including urbanization, have been correlated to local temperature increase, but the general dynamics of this relationship are still not well understood. This work examines whether land cover is a parameter affecting temperature increase by employing global datasets of land cover change, i.e. the Historical Land-Cover Change Global Dataset, and daily temperature from the NOAA database. We thoroughly investigate the temperature variability and its possible correlation to the different types of land-cover changes. A comparison is specifically made between the rate of temperature increase measured in urban areas, and the same rate measured in nearby non-urban areas.

ACS Style

Aristoklis Lagos; Stavroula Sigourou; Panayiotis Dimitriadis; Theano Iliopoulou; Demetris Koutsoyiannis. Land Cover Change: Does it affect temperature variability? 2021, 1 .

AMA Style

Aristoklis Lagos, Stavroula Sigourou, Panayiotis Dimitriadis, Theano Iliopoulou, Demetris Koutsoyiannis. Land Cover Change: Does it affect temperature variability? . 2021; ():1.

Chicago/Turabian Style

Aristoklis Lagos; Stavroula Sigourou; Panayiotis Dimitriadis; Theano Iliopoulou; Demetris Koutsoyiannis. 2021. "Land Cover Change: Does it affect temperature variability?" , no. : 1.

Preprint content
Published: 04 March 2021
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During the last decades, scientific research in the field of flood risk management has provided new insights and strong computational tools towards the deeper understanding of the fundamental probabilistic and stochastic behaviour that characterizes such natural hazards. Flood hazards are controlled by hydrometeorological processes and their inherent uncertainties. Historically, a high percentage of flood disasters worldwide are inaccurately or ineffectively reported regarding the aggregated number of the affected people, economic losses and generated flood insurance claims. In this respect, the recently published National Flood Insurance Program (NFIP) data by the Federal Emergency Management Agency (FEMA), including more than two million claims records dating back to 1978 and more than 47 million policy records for transactions, may provide new insights into flood impacts. The aim of this research is to process the actual insurance data derived from this database, in order to detect the underlying patterns and investigate its stochastic structure, paving the way for the development of more accurate flood risk assessment and modelling strategies.

ACS Style

Konstantinos Papoulakos; Theano Iliopoulou; Panayiotis Dimitriadis; Dimosthenis Tsaknias; Demetris Koutsoyiannis. Investigating the stochastic structure of the recently published Redacted Claims data set by the FEMA National Flood Insurance Program. 2021, 1 .

AMA Style

Konstantinos Papoulakos, Theano Iliopoulou, Panayiotis Dimitriadis, Dimosthenis Tsaknias, Demetris Koutsoyiannis. Investigating the stochastic structure of the recently published Redacted Claims data set by the FEMA National Flood Insurance Program. . 2021; ():1.

Chicago/Turabian Style

Konstantinos Papoulakos; Theano Iliopoulou; Panayiotis Dimitriadis; Dimosthenis Tsaknias; Demetris Koutsoyiannis. 2021. "Investigating the stochastic structure of the recently published Redacted Claims data set by the FEMA National Flood Insurance Program." , no. : 1.

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Published: 04 March 2021
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The storage-reliability-yield (SRY) relationship is a well-established tool for preliminary design of reservoirs fulfilling consumptive water uses, yet rarely employed within hydropower planning studies. Here, we discuss the theoretical basis for representing the trade-offs between reservoir size and expected revenues from hydropower production, under uncertain inflows, by taking advantage of the stochastic simulation-optimization approach. We also demonstrate that under some assumptions, the complex and site-specific problem, mainly induced by the nonlinearity of storage-head-energy conversion, can be significantly simplified and generalized as well. The methodology is tested across varying runoff regimes and under a wide range of potential reservoir geometries, expressed in terms of a generic shape parameter of the head-storage relationship. Based on the outcomes of these analyses we derive empirical expressions that link reliable energy with summary inflow statistics, reservoir capacity and geometry.

ACS Style

Andreas Efstratiadis; Ioannis Tsoukalas; Demetris Koutsoyiannis. Revisiting the storage-reliability-yield concept in hydroelectricity. 2021, 1 .

AMA Style

Andreas Efstratiadis, Ioannis Tsoukalas, Demetris Koutsoyiannis. Revisiting the storage-reliability-yield concept in hydroelectricity. . 2021; ():1.

Chicago/Turabian Style

Andreas Efstratiadis; Ioannis Tsoukalas; Demetris Koutsoyiannis. 2021. "Revisiting the storage-reliability-yield concept in hydroelectricity." , no. : 1.

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Published: 03 March 2021
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Since the pre-industrial era at the end of the 18th century, the atmospheric carbon dioxide concentration (CO2) has increased by 47.46% from the level of 280 ppmv (parts per million volume) to 412.89 ppmv (Mauna Loa – NOAA Station, November 2020). These increased concentrations caused by natural & anthropogenic activities, interact with the aquatic environment which acts as a safety valve. Nevertheless, the absorbed CO2 amounts undergo chemical transformations, resulting in increasing ionized concentrations that can significantly reduce the water’s pH, a process described as ocean acidification. Here, we use the HOT (Hawaii-Ocean-Time series) to perform time series analysis for temperature, carbon dioxide partial pressure and pH. More specifically, we analyze their temporal changes in month and annual time lag. Then, we proceed in comparisons with relevant studies on atmospheric data to evaluate the produced results. Finally, we make an effort to disentangle the results with simplified assumptions connected with the observed impact of ocean acidification on the aquatic ecosystems.

ACS Style

Georgios Vagenas; Theano Iliopoulou; Panayiotis Dimitriadis; Demetris Koutsoyiannis. Stochastic analysis of time-series related to ocean acidification. 2021, 1 .

AMA Style

Georgios Vagenas, Theano Iliopoulou, Panayiotis Dimitriadis, Demetris Koutsoyiannis. Stochastic analysis of time-series related to ocean acidification. . 2021; ():1.

Chicago/Turabian Style

Georgios Vagenas; Theano Iliopoulou; Panayiotis Dimitriadis; Demetris Koutsoyiannis. 2021. "Stochastic analysis of time-series related to ocean acidification." , no. : 1.

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Published: 03 March 2021
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We revisit the notion of climate, along with its historical evolution, tracing the origin of the modern concerns about climate. The notion (and the scientific term) of climate has been established during the Greek antiquity in a geographical context and it acquired its statistical content (average weather) in modern times, after meteorological measurements had become common. Yet the modern definitions of climate are seriously affected by the wrong perception of the previous two centuries that climate should regularly be constant, unless an external agent acted. Therefore, we attempt to give a more rigorous definition of climate, consistent with the modern body of stochastics. We illustrate the definition by real-world data, which also exemplify the large climatic variability. Given this variability, the term “climate change” turns out to be scientifically unjustified. Specifically, it is a pleonasm as climate, like weather, has been ever changing. Indeed, a historical investigation reveals that the aim in using that term is not scientific but political. Within the political aims, water issues have been greatly promoted by projecting future catastrophes while reversing the true roles and causality directions. For this reason, we provide arguments that water is the main element that drives climate and not the opposite.

ACS Style

Demetris Koutsoyiannis. Rethinking Climate, Climate Change, and Their Relationship With Water. 2021, 1 .

AMA Style

Demetris Koutsoyiannis. Rethinking Climate, Climate Change, and Their Relationship With Water. . 2021; ():1.

Chicago/Turabian Style

Demetris Koutsoyiannis. 2021. "Rethinking Climate, Climate Change, and Their Relationship With Water." , no. : 1.

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Published: 03 March 2021
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In the last few years, the island of Crete (Greece - Eastern Mediterranean) has been affected by extreme events. In recent decades, hydrometeorological processes in the island of Crete are monitored by an extensive network of meteorological stations. Here we stochastically analyze the spatial stochastic structure of precipitation in the island by employing sophisticated statistical tools, as well as by analyzing a large database of daily precipitation records. We investigate fifty-eight rainfall stations scattered in the four prefectures of Crete, for the years 1974-2020. Descriptive statistical analysis of precipitation examines several temporal properties in the data, while correlation analysis of precipitation variability provides relations between stations and regions for spatial patterns identification. This work also investigates the precipitation variability by employing statistical tools such as the autocorrelation, autoregressive (seasonal) analysis, probability distribution function fitting, and climacogram calculation, i.e. variance of the averaged process vs. spatial and temporal scales, to identify statistical properties, temporal dependencies, potential similarities in the dependence structure and marginal probability distribution.

ACS Style

Olianna Akoumianaki; Theano Iliopoulou; Panayiotis Dimitriadis; Emmanouil Varouchakis; Demetris Koutsoyiannis. Stochastic analysis of the spatial stochastic structure of precipitation in the island of Crete, Greece. 2021, 1 .

AMA Style

Olianna Akoumianaki, Theano Iliopoulou, Panayiotis Dimitriadis, Emmanouil Varouchakis, Demetris Koutsoyiannis. Stochastic analysis of the spatial stochastic structure of precipitation in the island of Crete, Greece. . 2021; ():1.

Chicago/Turabian Style

Olianna Akoumianaki; Theano Iliopoulou; Panayiotis Dimitriadis; Emmanouil Varouchakis; Demetris Koutsoyiannis. 2021. "Stochastic analysis of the spatial stochastic structure of precipitation in the island of Crete, Greece." , no. : 1.

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Published: 03 March 2021
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Curves of rainfall intensity at various scales and for various return periods, else known as ombrian (or IDF) curves, are central design tools in hydrology and engineering. Construction of such curves often relies heavily on empirical or semi-empirical approaches, which hinder their applicability over large scales, and preclude simulation. Recent work by Koutsoyiannis (2020) has advanced these curves to theoretically-consistent stochastic models of rainfall intensity (ombrian models) extending their applicability to the full range of available scales, e.g. from minutes to decades. We present an open-source python toolbox implementing these advances in a straightforward and user-friendly manner and prove its applicability. The toolbox also employs advanced statistical fitting methods for extremes (K-moments), accounts for bias induced by temporal dependence, and allows optional blending of daily-scale data to reduce uncertainty of sub-daily records. The end result is the parameterization of the ombrian model and the graphical representation of rainfall intensity for any range of scales (supported by the data) and return periods.

Reference: Koutsoyiannis, D. 2020. ‘Rainfall extremes and Ombrian modelling’ in Stochastics of Hydroclimatic Extremes - A Cool Look at Risk (ed 0), National Technical University of Athens, Athens, pp 243-273, http://www.itia.ntua.gr/en/docinfo/2000/.

ACS Style

Theano Iliopoulou; Demetris Koutsoyiannis. PythOm: A python toolbox implementing recent advances in rainfall intensity (ombrian) curves. 2021, 1 .

AMA Style

Theano Iliopoulou, Demetris Koutsoyiannis. PythOm: A python toolbox implementing recent advances in rainfall intensity (ombrian) curves. . 2021; ():1.

Chicago/Turabian Style

Theano Iliopoulou; Demetris Koutsoyiannis. 2021. "PythOm: A python toolbox implementing recent advances in rainfall intensity (ombrian) curves." , no. : 1.