Ioannis Tsoukalas

Ioannis Tsoukalas
National Technical University of Athens | NTUA · Department of Water Resources and Environmental Engineering

Doctor of Engineering

About

55
Publications
17,273
Reads
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528
Citations
Introduction
Dr. Tsoukalas research interests concern the development of hydroinformatic methods and statistical/stochastic tools for the management and optimization of water-systems under uncertainty with an emphasis on large multi-reservoir and urban water systems. More specifically, his work is focused on the development of a) statistical/stochastic methods and models for the analysis, modelling, forecasting, and (multi-scale) simulation (and disaggregation) of stochastic processes (e.g., hydrometeorological), and b) surrogate-based optimization algorithms, (inspired from the recent developments in machine learning) with a focus on multi-objective problems. His ambition is contributing in, and improving decision making under uncertainty, risk analysis, as well as uncertainty quantification.
Additional affiliations
December 2018 - March 2021
National Technical University of Athens
Position
  • Senior Researcher
September 2012 - December 2018
National Technical University of Athens
Position
  • Researcher
Education
June 2014 - December 2018
National Technical University of Athens
Field of study
  • Civil Engineering
September 2010 - March 2012
National Technical University of Athens
Field of study
  • Water resources science and technology
September 2004 - March 2010
Aristotle University of Thessaloniki
Field of study
  • Civil Engineering

Publications

Publications (55)
Article
Full-text available
Stochastic models in hydrology traditionally aim at reproducing the empirically-derived statistical characteristics of the observed data rather than any specific distribution model that attempts to describe the usually non-normal, statistical behavior of the associated processes. SPARTA (Stochastic Periodic AutoRegressive To Anything) offers an alt...
Article
Full-text available
Hydrometeorological processes are typically characterized by temporal dependence, short- or long-range (e.g., Hurst behavior), as well as by non-Gaussian distributions (especially at fine time scales). The generation of long synthetic time series that resembles the marginal and joint properties of the observed ones is a prerequisite in many uncerta...
Article
Full-text available
The generation of hydrometeorological time series that exhibit a given probabilistic and stochastic behavior across multiple temporal levels, traditionally expressed in terms of specific statistical characteristics of the observed data, is a crucial task for risk-based water resources studies, and simultaneously a puzzle for the community of stocha...
Article
Full-text available
Stochastic simulation has a prominent position in a variety of scientific domains including those of environmental and water resources sciences. This is due to the numerous applications that can benefit from it, such as risk-related studies. In such domains, stochastic models are typically used to generate synthetic weather data with the desired pr...
Article
Focal point of this work is the estimation of the distribution of maxima without the use of classic extreme value theory and asymptotic properties, which may not be ideal for hydrological processes. The problem is revisited from the perspective of non-asymptotic conditions, and regards the so-called exact distribution of block-maxima of finite-size...
Article
Full-text available
As the share of renewable energy resources rapidly increases in the electricity mix, the recognition, representation, quantification, and eventually interpretation of their uncertainties become important. In this vein, we propose a generic stochastic simulation-optimization framework tailored to renewable energy systems (RES), able to address multi...
Presentation
Full-text available
The energy autonomy of small non-interconnected islands in the Mediterranean, taking advantage of their high renewable energy potential, has been a long-standing objective of local communities and stakeholders. This is also in line with the recently implemented European Green Deal, which has set the goal of increasing the renewable energy penetrati...
Article
Full-text available
We propose a novel probabilistic approach to flood hazard assessment, aiming to address the major shortcomings of everyday deterministic engineering practices in a computationally efficient manner. In this context, the principal sources of uncertainty are defined across the overall modeling procedure, namely, the statistical uncertainty of inferrin...
Article
Full-text available
Motivated by the challenges induced by the so-called Target Model and the associated changes to the current structure of the energy market, we revisit the problem of day-ahead prediction of power production from Small Hydropower Plants (SHPPs) without storage capacity. Using as an example a typical run-of-river SHPP in Western Greece, we test alter...
Article
Full-text available
Optimizing the design and operation of an Urban Water System (UWS) faces significant challenges over its lifespan to account for the uncertainties of important stressors that arise from population growth rates, climate change factors, or shifting demand patterns. The analysis of a UWS’s performance across interdependent subsystems benefits from a m...
Article
Full-text available
Establishing cooperation in transboundary rivers is challenging especially with the weak or non-existent river basin institutions. A nexus-based approach is developed to explore cooperation opportunities in transboundary river basins while considering system operation and coordination under uncertain hydrologic river regimes. The proposed approach...
Article
As the share of renewable energy resources rapidly increases in the electricity mix, the recognition, representation, quantification, and eventually interpretation of their uncertainties become important. Consequently, we propose a stochastic simulation-optimization framework tailored to renewable energy systems (RES), that is able to address multi...
Article
Full-text available
The challenging task of generating a synthetic time series at finer temporal scales than the observed data, embeds the reconstruction of a number of essential statistical quantities at the desirable (i.e., lower) scale of interest. This paper introduces a parsimonious and general framework for the downscaling of statistical quantities based solely...
Article
The limited availability of hydrometric data makes the design, management, and real-time operation of water systems a difficult task. Here, we propose a generic stochastic framework for the so-called inverse problem of hydroelectricity, using energy production data from small hydropower plants (SHPPs) to retrieve the upstream inflows. In this conte...
Article
Full-text available
Fluvial floods are one of the primary natural hazards to our society, and the associated flood risk should always be evaluated for present and future conditions. The European Union’s (EU) Floods Directive highlights the importance of flood mapping as a key stage for detecting vulnerable areas, assessing floods’ impacts, and identifying damages and...
Conference Paper
Full-text available
Hydrological calibrations with historical data are often deemed insufficient for deducing safe estimations about a model structure that imitates, as closely as possible, the anticipated catchment behaviour. Ιn order to address this issue, we investigate a promising strategy, using as drivers synthetic time series, which preserve the probabilistic p...
Conference Paper
Full-text available
Small hydropower plants (SHPPs) are subject to multiple uncertainties and complexities, despite their limited scale. These uncertainties are often ignored in the typical engineering practice, which results in risky design. As this type of renewable energy rapidly penetrates the electricity mix, the impacts of their uncertainties, exogenous and endo...
Conference Paper
Full-text available
The highly-competitive electricity market over EU and the challenges induced by the so-called “Target Model”, introduce significant uncertainties to day-ahead trades involving renewable energy, since most of these sources are driven by non-controllable weather processes (wind, solar, hydro). Here, we explore the case of small hydropower plants that...
Conference Paper
Full-text available
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, un...
Conference Paper
Full-text available
Our modern urban environment relies on critical infrastructures that serve vital societal functions, such as water supply and sanitation, which are exposed to various threats of both physical and cyber nature. Despite the progress in protection and increased vigilance, long-established practices within the water utilities may rely on precarious met...
Article
Although storage-reliability-yield (SRY) relationships have been widely used in the design and planning of water supply reservoirs, their application in hydroelectricity is practically missing. Here we revisit the SRY analysis and seek for its generic configuration for hydroelectric reservoirs, following a stochastic simulation approach. After defi...
Article
Achieving a water, food, and energy (WFE) nexus balance through policy interventions is challenging in a transboundary river basin because of the dynamic nature and intersectoral complexity that may cross borders. The Nile basin is shared by a number of riparian countries and is currently experiencing rapid population and economic growth. This has...
Article
Achieving a water, food, and energy (WFE) nexus balance through policy interventions is challenging in a transboundary river basin because of the dynamic nature and intersectoral complexity that may cross borders. The Nile basin is shared by a number of riparian countries and is currently experiencing rapid population and economic growth. This has...
Conference Paper
Full-text available
Due to their negligible storage capacity, small hydroelectric plants cannot offer regulation of flows, thus making the prediction of energy production a very difficult task, even for small time horizons. Further uncertainties arise due to the limited hydrological information, in terms of upstream inflow data, since usually the sole available measur...
Conference Paper
Full-text available
As made for most of renewable energy sources, wind energy is driven by highly uncertain and thus unpredictable meteorological processes. In the context of wind power scheduling and control, reliable wind predictions across scales is a challenging problem. However, since the generation of wind energy is, in fact, a nonlinear transformation of wind v...
Article
Full-text available
Uncertainty-aware design and management of urban water systems lies on the generation of synthetic series that precisely reproduce the distributional and dependence properties of residential water demand process (i.e., significant deviation from Gaussianity, intermittent behaviour, high spatial and temporal variability and a variety of dependence s...
Poster
Full-text available
For more than two decades, the use of artificial neural networks (ANNs) in hydrology has become an effective and efficient alternative against traditional modeling approaches, i.e. physically-based or conceptual. These can take ad-vantage of any type of available information to predict the hydrological response of complex systems, with missing data...
Poster
Full-text available
Integrated modeling of hybrid water-energy systems, comprising conventional and renewable energy sources, pumped-storage facilities and other infrastructures, which aim to serve combined water and energy uses, is a highly challenging problem. On the one hand, such systems are subject to significant uncertainties that span over all associated input...
Poster
Full-text available
Design and management of water resource systems are arguably challenging tasks, as they are mainly driven by hydrological processes that are dominated by “structured” randomness. In this vein, the stochastic simulation of the input processes is regarded an essential component for such studies. Typically, the objective of stochastic models is the ge...
Thesis
Full-text available
Hydrometeorological inputs are a key ingredient and simultaneously one of the main sources of uncertainty of every hydrological study. This type of uncertainty is referred to as hydrometeorological uncertainty and is of utmost importance in risk-based engineering works, due the high variability and randomness that is naturally embedded in physical...
Article
Full-text available
Since the prime days of stochastic hydrology back in 1960s, autoregressive (AR) and moving average (MA) models (as well as their extensions) have been widely used to simulate hydrometeorological processes. Initially, AR(1) or Markovian models with Gaussian noise prevailed due to their conceptual and mathematical simplicity. However, the ubiquitous...
Article
Full-text available
An operational framework for flood risk assessment in ungauged urban areas is developed within the implementation of the EU Floods Directive in Greece, and demonstrated for Volos metropolitan area, central Greece, which is frequently affected by intense storms causing fluvial flash floods. A scenario-based approach is applied, accounting for uncert...
Poster
Full-text available
In contrast to great advances on stochastic simulation techniques in hydrology and their importance on water management and uncertainty assessment studies, operational software packages for generating synthetic data are limited and hardly accessible. This limits their adoption to a narrow audience, excluding the vast majority of researchers and pra...
Article
Full-text available
Pressures on water resources, which have increased significantly nowadays mainly due to rapid urbanization, population growth and climate change impacts, necessitate the development of innovative wastewater treatment and reuse technologies. In this context, a mid-scale decentralized technology concerning wastewater reuse is that of sewer mining. It...
Article
Full-text available
We present and validate a global parametric model of potential evapotranspiration (PET) with two parameters that are estimated through calibration, using as explanatory variables temperature and extraterrestrial radiation. The model is tested over the globe, taking advantage of the Food and Agriculture Organization (FAO CLIMWAT) database that provi...
Article
Rapid urbanization affecting demand patterns, coupled with potential water shortages due to supply side impacts of climatic changes, has led to the emergence of new technologies for water and wastewater reuse. Sewer mining (SM) is a novel decentralized option that could potentially provide non-potable water for urban uses, including for example the...
Conference Paper
Full-text available
Stochastic simulation of hydrological processes has a key role in water resources planning and management due to its ability to incorporate hydrological uncertainty within decision-making. Due to seasonality, the statistical characteristics of such processes are considered periodic functions, thus implying the use of cyclo-stationary stochastic mod...
Article
Water scarcity, either due to increased urbanisation or climatic variability, has motivated societies to reduce pressure on water resources mainly by reducing water demand. However, this practice alone is not sufficient to guarantee the quality of life that high quality water services underpin, especially within a context of increased urbanisation....
Article
To reduce the impact of urban effluents on the environment, strict regulatory requirements have been set up for the disposal of wastewater, in most parts of the western world, requiring treatment before disposal. At the same time, the urban environment requires water inflows to satisfy a range of urban water demands, and the corresponding water abs...
Article
Full-text available
Hydrosystem management is a demanding and challenging task due to the complexity of the system dynamics, the number of decision variables and the hydrological uncertainty. In order to overcome those issues the parsimonious parameterization-simulation-optimization (PSO) framework is employed coupled with stochastically generated hydrological time-se...
Article
Full-text available
Operation of large-scale hydropower reservoirs is a complex problem that involves conflicting objectives, such as hydropower generation and water supply. Deriving optimal operational rules is a challenging task due to the non-linearity of the system dynamics and the uncertainty of future inflows and water demands. A common approach to derive optima...
Conference Paper
Development of uncertainty-aware operational rules for multi-reservoir systems is a demanding and challenging task due to the complexity of the system dynamics, the number of decision variables and the hydrological uncertainty. In order to overcome this issue the parsimonious parameterization-simulation-optimization (PSO) framework is employed coup...
Conference Paper
Full-text available
Climatic variations and resulting future uncertainties, increasing anthropogenic pressures, changes in political boundaries, ineffective or dysfunctional governance of natural resources and environmental degradation are some of the most fundamental challenges with which worldwide initiatives fostering the "think globally, act locally" concept are c...
Conference Paper
Full-text available
Modelling of large-scale hybrid renewable energy systems (HRES) is a challenging task, for which several open computational issues exist. HRES comprise typical components of hydrosystems (reservoirs, boreholes, conveyance networks, hydropower stations, pumps, water demand nodes, etc.), which are dynamically linked with renewables (e.g., wind turbin...
Conference Paper
Full-text available
Many hydrological applications require the use of long rainfall data across a wide range of fine time scales. To meet this necessity, stochastic approaches are usually employed for the generation of large number of rainfall events, following a Monte Carlo approach. In this framework, Bartlett-Lewis model (BL) is a key representative from the family...
Conference Paper
Full-text available
We present a multi-criteria simulation-optimization framework for the optimal design and setting of flood protection structures along river banks. The methodology is tested in the lower course of the Arachthos River (Epirus, Greece), downstream of the hydroelectric dam of Pournari. The entire study area is very sensitive, particularly because the r...
Conference Paper
Full-text available
In water resources optimization problems, the calculation of the objective function usually presumes to first run a simulation model and then evaluate its outputs. In several cases, however, long simulation times may pose significant barriers to the optimization procedure. Often, to obtain a solution within a reasonable time, the user has to substa...
Article
Abstract Developing long term operation rules for multi-reservoir systems is complicated due to the number of decision variables, the non-linearity of system dynamics and the hydrological uncertainty. This uncertainty can be addressed by coupling simulation models with multi-objective optimisation algorithms driven by stochastically generated hydro...
Conference Paper
The optimum management of multi-reservoir systems becomes increasingly complex when conflicting uses of water exist, i.e. water supply, irrigation, hydropower generation, etc. This is especially the case in the Nestos basin, a trans-boundary basin extending between Bulgaria and Greece. The transboundary nature of the catchment makes the management...

Questions

Question (1)
Question
Dear all, 
I would like to couple MIKE-URBAN with MATLAB in a way that i can control MIKE-URBAN from MATLAB. I know that i common way is to use COM-API interface, but i am not sure if MIKE-URBAN has that capability.
Any thoughts or advice would be useful.
Thanks

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Projects

Projects (3)
Project
The aim of this Special Issue is to provide a collection of innovative contributions related to (please read more in https://www.mdpi.com/journal/water/special_issues/stochastic_modelling): 1) Modelling and simulation of hydrometeorological processes across multiple statiotemporal scales. 2) Statistical/stochastic methods and frameworks for hydrometeorological extremes. 3) Hydrodynamic uncertainty in flood risk management. 4) Stochastic similarities among hydrometeorological processes. 5) Novel temporal or spatial downscaling approaches based on a stochastic framework. 6) The use of stochastics within hydrological and water resources engineering applications. 7) Bridging the gap between research and real-world engineering through open-source software implementations. Dr. Demetris Koutsoyiannis Dr. Panayiotis Dimitriadis Dr. Ioannis Tsoukalas Guest Editors
Project
Analysis of geophysical data is (explicitly or implicitly) based on stochastics, i.e. the mathematics of random variables and stochastic processes. These are abstract mathematical objects, whose properties distinguish them from typical variables that take on numerical values. It is important to understand these properties before making calculations with data, otherwise the results may be meaningless (not even wrong). [This project is 100% unfunded]