Aristotelis Tegos

Civil Engineer, MSc., Dr. Engineer
tegosaris@yahoo.gr

Participation in research projects

Participation as Researcher

  1. Maintenance, upgrading and extension of the Decision Support System for the management of the Athens water resource system
  2. Flood risk estimation and forecast using hydrological models and probabilistic methods
  3. Investigation of management scenarios for the Smokovo reservoir

Participation in engineering studies

  1. Specific Technical Study for the Ecological Flow from the Dam of Stratos

Published work

Publications in scientific journals

  1. A. Tegos, S. Stefanidis, J. Cody, and D. Koutsoyiannis, On the sensitivity of standardized-precipitation-evapotranspiration and aridity indexes using alternative potential evapotranspiration models, Hydrology, 10 (3), 64, doi:10.3390/hydrology10030064, 2023.
  2. A. Tegos, N. Malamos, and D. Koutsoyiannis, RASPOTION - A new global PET dataset by means of remote monthly temperature data and parametric modelling, Hydrology, 9 (2), 32, doi:10.3390/hydrology9020032, 2022.
  3. P. Dimitriadis, A. Tegos, and D. Koutsoyiannis, Stochastic analysis of hourly to monthly potential evapotranspiration with a focus on the long-range dependence and application with reanalysis and ground-station data, Hydrology, 8 (4), 177, doi:10.3390/hydrology8040177, 2021.
  4. A. Koskinas, and A. Tegos, StEMORS: A stochastic eco-hydrological model for optimal reservoir sizing, Open Water Journal, 6 (1), 1, 2020.
  5. A. Koskinas, A. Tegos, P. Tsira, P. Dimitriadis, T. Iliopoulou, P. Papanicolaou, D. Koutsoyiannis, and Τ. Williamson, Insights into the Oroville Dam 2017 spillway incident, Geosciences, 9 (37), doi:10.3390/geosciences9010037, 2019.
  6. A. Tegos, W. Schlüter, N. Gibbons, Y. Katselis, and A. Efstratiadis, Assessment of environmental flows from complexity to parsimony - Lessons from Lesotho, Water, 10 (10), 1293, doi:10.3390/w10101293, 2018.
  7. N. Malamos, I. L. Tsirogiannis, A. Tegos, A. Efstratiadis, and D. Koutsoyiannis, Spatial interpolation of potential evapotranspiration for precision irrigation purposes, European Water, 59, 303–309, 2017.
  8. A. Tegos, N. Malamos, A. Efstratiadis, I. Tsoukalas, A. Karanasios, and D. Koutsoyiannis, Parametric modelling of potential evapotranspiration: a global survey, Water, 9 (10), 795, doi:10.3390/w9100795, 2017.
  9. A. Tegos, H. Tyralis, D. Koutsoyiannis, and K. H. Hamed, An R function for the estimation of trend signifcance under the scaling hypothesis- application in PET parametric annual time series, Open Water Journal, 4 (1), 66–71, 6, 2017.
  10. H. Tyralis, A. Tegos, A. Delichatsiou, N. Mamassis, and D. Koutsoyiannis, A perpetually interrupted interbasin water transfer as a modern Greek drama: Assessing the Acheloos to Pinios interbasin water transfer in the context of integrated water resources management, Open Water Journal, 4 (1), 113–128, 12, 2017.
  11. P. Dimitriadis, A. Tegos, A. Oikonomou, V. Pagana, A. Koukouvinos, N. Mamassis, D. Koutsoyiannis, and A. Efstratiadis, Comparative evaluation of 1D and quasi-2D hydraulic models based on benchmark and real-world applications for uncertainty assessment in flood mapping, Journal of Hydrology, 534, 478–492, doi:10.1016/j.jhydrol.2016.01.020, 2016.
  12. A. Tegos, A. Efstratiadis, N. Malamos, N. Mamassis, and D. Koutsoyiannis, Evaluation of a parametric approach for estimating potential evapotranspiration across different climates, Agriculture and Agricultural Science Procedia, 4, 2–9, doi:10.1016/j.aaspro.2015.03.002, 2015.
  13. A. Tegos, N. Malamos, and D. Koutsoyiannis, A parsimonious regional parametric evapotranspiration model based on a simplification of the Penman-Monteith formula, Journal of Hydrology, 524, 708–717, doi:10.1016/j.jhydrol.2015.03.024, 2015.
  14. A. Efstratiadis, A. Tegos, A. Varveris, and D. Koutsoyiannis, Assessment of environmental flows under limited data availability – Case study of the Acheloos River, Greece, Hydrological Sciences Journal, 59 (3-4), 731–750, doi:10.1080/02626667.2013.804625, 2014.
  15. D. Koutsoyiannis, N. Mamassis, and A. Tegos, Logical and illogical exegeses of hydrometeorological phenomena in ancient Greece, Water Science and Technology: Water Supply, 7 (1), 13–22, 2007.

Book chapters and fully evaluated conference publications

  1. P. Dimitriadis, A. Tegos, A. Petsiou, V. Pagana, I. Apostolopoulos, E. Vassilopoulos, M. Gini, A. D. Koussis, N. Mamassis, D. Koutsoyiannis, and P. Papanicolaou, Flood Directive implementation in Greece: Experiences and future improvements, 10th World Congress on Water Resources and Environment "Panta Rhei", Athens, European Water Resources Association, 2017.
  2. N. Malamos, I. L. Tsirogiannis, A. Tegos, A. Efstratiadis, and D. Koutsoyiannis, Spatial interpolation of potential evapotranspiration for precision irrigation purposes, 10th World Congress on Water Resources and Environment "Panta Rhei", Athens, European Water Resources Association, 2017.
  3. A. Tegos, A. Efstratiadis, and D. Koutsoyiannis, A parametric model for potential evapotranspiration estimation based on a simplified formulation of the Penman-Monteith equation, Evapotranspiration - An Overview, edited by S. Alexandris, 143–165, doi:10.5772/52927, InTech, 2013.
  4. D. Koutsoyiannis, N. Mamassis, and A. Tegos, Logical and illogical exegeses of hydrometeorological phenomena in ancient Greece, Proceedings of the 1st IWA International Symposium on Water and Wastewater Technologies in Ancient Civilizations, edited by A. N. Angelakis and D. Koutsoyiannis, Iraklio, 135–143, doi:10.13140/RG.2.1.4188.4408, International Water Association, 2006.

Conference publications and presentations with evaluation of abstract

  1. A. Tegos, P. Dimitriadis, and D. Koutsoyiannis, Stochastic investigation of the correlation structure and probability distribution of the global potential evapotranspiration, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-17849-3, European Geosciences Union, 2018.
  2. N. Malamos, A. Tegos, I. L. Tsirogiannis, A. Christofides, and D. Koutsoyiannis, Implementation of a regional parametric model for potential evapotranspiration assessment, IrriMed 2015 – Modern technologies, strategies and tools for sustainable irrigation management and governance in Mediterranean agriculture, Bari, doi:10.13140/RG.2.1.3992.0725, 2015.
  3. A. Koukouvinos, D. Nikolopoulos, A. Efstratiadis, A. Tegos, E. Rozos, S.M. Papalexiou, P. Dimitriadis, Y. Markonis, P. Kossieris, H. Tyralis, G. Karakatsanis, K. Tzouka, A. Christofides, G. Karavokiros, A. Siskos, N. Mamassis, and D. Koutsoyiannis, Integrated water and renewable energy management: the Acheloos-Peneios region case study, European Geosciences Union General Assembly 2015, Geophysical Research Abstracts, Vol. 17, Vienna, EGU2015-4912, doi:10.13140/RG.2.2.17726.69440, European Geosciences Union, 2015.
  4. A. Tegos, A. Efstratiadis, N. Malamos, N. Mamassis, and D. Koutsoyiannis, Evaluation of a parametric approach for estimating potential evapotranspiration across different climates, IRLA2014 – The Effects of Irrigation and Drainage on Rural and Urban Landscapes, Patras, doi:10.13140/RG.2.2.14004.24966, 2014.
  5. N. Bountas, N. Boboti, E. Feloni, L. Zeikos, Y. Markonis, A. Tegos, N. Mamassis, and D. Koutsoyiannis, Temperature variability over Greece: Links between space and time, Facets of Uncertainty: 5th EGU Leonardo Conference – Hydrofractals 2013 – STAHY 2013, Kos Island, Greece, doi:10.13140/RG.2.2.17739.80164, European Geosciences Union, International Association of Hydrological Sciences, International Union of Geodesy and Geophysics, 2013.
  6. A. Efstratiadis, A. Koukouvinos, P. Dimitriadis, A. Tegos, N. Mamassis, and D. Koutsoyiannis, A stochastic simulation framework for flood engineering, Facets of Uncertainty: 5th EGU Leonardo Conference – Hydrofractals 2013 – STAHY 2013, Kos Island, Greece, doi:10.13140/RG.2.2.16848.51201, European Geosciences Union, International Association of Hydrological Sciences, International Union of Geodesy and Geophysics, 2013.
  7. V. Pagana, A. Tegos, P. Dimitriadis, A. Koukouvinos, P. Panagopoulos, and N. Mamassis, Alternative methods in floodplain hydraulic simulation - Experiences and perspectives, European Geosciences Union General Assembly 2013, Geophysical Research Abstracts, Vol. 15, Vienna, EGU2013-10283-2, European Geosciences Union, 2013.
  8. A. Oikonomou, P. Dimitriadis, A. Koukouvinos, A. Tegos, V. Pagana, P. Panagopoulos, N. Mamassis, and D. Koutsoyiannis, Floodplain mapping via 1D and quasi-2D numerical models in the valley of Thessaly, Greece, European Geosciences Union General Assembly 2013, Geophysical Research Abstracts, Vol. 15, Vienna, EGU2013-10366, doi:10.13140/RG.2.2.25165.03040, European Geosciences Union, 2013.
  9. A. Varveris, P. Panagopoulos, K. Triantafillou, A. Tegos, A. Efstratiadis, N. Mamassis, and D. Koutsoyiannis, Assessment of environmental flows of Acheloos Delta, European Geosciences Union General Assembly 2010, Geophysical Research Abstracts, Vol. 12, Vienna, 12046, doi:10.13140/RG.2.2.14849.66404, European Geosciences Union, 2010.
  10. A. Tegos, N. Mamassis, and D. Koutsoyiannis, Estimation of potential evapotranspiration with minimal data dependence, European Geosciences Union General Assembly 2009, Geophysical Research Abstracts, Vol. 11, Vienna, 1937, doi:10.13140/RG.2.2.27222.86089, European Geosciences Union, 2009.
  11. A. Efstratiadis, A. Tegos, I. Nalbantis, E. Rozos, A. Koukouvinos, N. Mamassis, S.M. Papalexiou, and D. Koutsoyiannis, Hydrogeios, an integrated model for simulating complex hydrographic networks - A case study to West Thessaly region, 7th Plinius Conference on Mediterranean Storms, Rethymnon, Crete, doi:10.13140/RG.2.2.25781.06881, European Geosciences Union, 2005.

Presentations and publications in workshops

  1. A. Tegos, A. Efstratiadis, A. Varveris, N. Mamassis, A. Koukouvinos, and D. Koutsoyiannis, Assesment and implementation of ecological flow constraints in large hydroelectric works: The case of Acheloos, Ecological flow of rivers and the importance of their true assesment, 2014.
  2. D. Koutsoyiannis, N. Mamassis, and A. Tegos, Hydrometeorological issues in ancient Greek science and philosophy, The Eco-nomy of Water, edited by E Efthymiopoulos and M. Modinos, Hydra island, doi:10.13140/RG.2.2.25574.63040, Hellenica Grammata, 2009.

Various publications

  1. A. Tegos, Acheloos, 2009.
  2. A. Tegos, Acheloos: Does the water belong only to fish?, March 2009.

Academic works

  1. A. Tegos, State-of-the-art approach for potential evapotranspiration assessment, PhD thesis, 123 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, Athens, November 2019.
  2. A. Tegos, Simplification of evapotranspiration estimation in Greece, Postgraduate Thesis, Department of Water Resources and Environmental Engineering – National Technical University of Athens, Athens, 2007.
  3. A. Tegos, Combined simultation of hydrological-hydrogeological processes and operation of Western Thessaly hydrosystem, Diploma thesis, 132 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, September 2005.

Research reports

  1. A. Koukouvinos, A. Efstratiadis, D. Nikolopoulos, H. Tyralis, A. Tegos, N. Mamassis, and D. Koutsoyiannis, Case study in the Acheloos-Thessaly system, Combined REnewable Systems for Sustainable ENergy DevelOpment (CRESSENDO), 98 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, October 2015.
  2. N. Mamassis, R. Mavrodimou, A. Efstratiadis, M. Heidarlis, A. Tegos, A. Koukouvinos, P. Lazaridou, M. Magaliou, and D. Koutsoyiannis, Investigation of alternative organisations and operations of a Water Management Body for the Smokovo projects, Investigation of management scenarios for the Smokovo reservoir, Report 2, 73 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, March 2007.
  3. A. Efstratiadis, A. Tegos, G. Karavokiros, I. Kyriazopoulou, and I. Vazimas, Master Plan for water resources management for the area of Karditsa, Integrated Management of Hydrosystems in Conjunction with an Advanced Information System (ODYSSEUS), Report 16, 132 pages, NAMA, Athens, December 2006.
  4. A. Efstratiadis, A. Koukouvinos, E. Rozos, A. Tegos, and I. Nalbantis, Theoretical documentation of model for simulating hydrological-hydrogeological processes of river basin "Hydrogeios", Integrated Management of Hydrosystems in Conjunction with an Advanced Information System (ODYSSEUS), Contractor: NAMA, Report 4a, 103 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, December 2006.

Details on research projects

Participation as Researcher

  1. Maintenance, upgrading and extension of the Decision Support System for the management of the Athens water resource system

    Duration: October 2008–November 2011

    Budget: €72 000

    Project director: N. Mamassis

    Principal investigator: D. Koutsoyiannis

    This research project includes the maintenance, upgrading and extension of the Decision Support System that developed by NTUA for EYDAP in the framework of the research project “Updating of the supervision and management of the water resources’ system for the water supply of the Athens’ metropolitan area”. The project is consisted of the following parts: (a) Upgrading of the Data Base, (b)Upgrading and extension of hydrometeorological network, (c) upgrading of the hydrometeorological data process software, (d) upgrading and extension of the Hydronomeas software, (e) hydrological data analysis and (f) support to the preparation of the annual master plans

  1. Flood risk estimation and forecast using hydrological models and probabilistic methods

    Duration: February 2007–August 2008

    Budget: €15 000

    Commissioned by: National Technical University of Athens

    Contractor: Department of Water Resources and Environmental Engineering

    Collaborators: Hydrologic Research Center

    Project director: D. Koutsoyiannis

    Principal investigator: S.M. Papalexiou

    Programme: Πρόγραμμα Βασικής Έρευνας ΕΜΠ "Κωνσταντίνος Καραθεοδωρή"

    The objective of this project is the development of an integrated framework for the estimation and forecast of flood risk using stochastic, hydrological and hydraulics methods. The study area is the Boeticos Kephisos river basin. The project includes analysis of severe storm episodes in the basin, the understanding of mechanisms of flood generation in this karstic basin and the estimation of flood risk in characteristic sites of the hydrosystem.

  1. Investigation of management scenarios for the Smokovo reservoir

    Duration: November 2005–December 2006

    Budget: €60 000

    Commissioned by: Special Directorate for the Management of Corporate Programs of Thessaly

    Contractor: Department of Water Resources, Hydraulic and Maritime Engineering

    Project director: D. Koutsoyiannis

    Principal investigator: N. Mamassis

    Programme: Επιχειρησιακά Σχέδια Διαχείρισης Δικτύων Σμοκόβου

Details on engineering studies

  1. Specific Technical Study for the Ecological Flow from the Dam of Stratos

    Duration: January 2009–June 2009

    Commissioned by: Public Power Corporation

    Contractor: ECOS Consultants S.A.

Published work in detail

Publications in scientific journals

  1. A. Tegos, S. Stefanidis, J. Cody, and D. Koutsoyiannis, On the sensitivity of standardized-precipitation-evapotranspiration and aridity indexes using alternative potential evapotranspiration models, Hydrology, 10 (3), 64, doi:10.3390/hydrology10030064, 2023.

    This paper examines the impacts of three different potential evapotranspiration (PET) models on drought severity and frequencies indicated by the standardized precipitation index (SPEI). The standardized precipitation-evapotranspiration index is a recent approach to operational monitoring and analysis of drought severity. The standardized precipitation-evapotranspiration index combines precipitation and temperature data, quantifying the severity of a drought as the difference in a timestep as the difference between precipitation and PET. The standardized precipitation-evapotranspiration index thus represents the hydrological processes that drive drought events more realistically than the standardized precipitation index at the expense of additional computational complexity and increased data demands. The additional computational complexity is principally due to the need to estimate PET within each time step. The standardized precipitation-evapotranspiration index was originally defined using the Thornthwaite PET model. However, numerous researchers have demonstrated the standardized precipitation-evapotranspiration index is sensitive to the PET model adopted. PET models requiring sparse meteorological inputs, such as the Thornthwaite model, have particular utility for drought monitoring in data scarce environments. The aridity index (AI) investigates the spatiotemporal changes in the hydroclimatic system. It is defined as the ratio between potential evapotranspiration and precipitation. It is used to characterize wet (humid) and dry (arid) regions. In this study, a sensitivity analysis for the standardized precipitation-evapotranspiration and aridity indexes was carried out using three different PET models; namely, the Penman–Monteith model, a temperature-based parametric model and the Thornthwaite model. The analysis was undertaken in six gauge stations in California region where long-term drought events have occurred. Having used the Penman–Monteith model as the PET model for estimating the standardized precipitation-evapotranspiration index, our findings highlight the presence of uncertainty in defining the severity of drought, especially for large timescales (12 months to 48 months), and that the PET parametric model is a preferable model to the Thornthwaite model for both the standardized precipitation-evapotranspiration index and the aridity indexes. The latter outcome is worth further consideration for when climatic studies are under development in data scarce areas where full required meteorological variables for Penman–Monteith assessment are not available.

    Full text: http://www.itia.ntua.gr/en/getfile/2276/1/documents/hydrology-10-00064-v2.pdf (2598 KB)

  1. A. Tegos, N. Malamos, and D. Koutsoyiannis, RASPOTION - A new global PET dataset by means of remote monthly temperature data and parametric modelling, Hydrology, 9 (2), 32, doi:10.3390/hydrology9020032, 2022.

    Regional estimations of Potential Evapotranspiration (PET) are of key interest for a number of geosciences, particularly those that are water-related (hydrology, agrometeorology). Therefore, several models have been developed for the consistent quantification of different time scales (hourly, daily, monthly, annual). During the last few decades, remote sensing techniques have continued to grow rapidly with the simultaneous development of new local and regional evapotranspiration datasets. Here, we develop a novel set T maps over the globe, namely RASPOTION, for the period 2003 to 2016, by integrating: (a) mean climatic data at 4088 stations, extracted by the FAO-CLIMWAT database; (b) mean monthly PET estimates by the Penman–Monteith method, at the aforementioned locations; (c) mean monthly PET estimates by a recently proposed parametric model, calibrated against local Penman–Monteith data; (d) spatially interpolated parameters of the Parametric PET model over the globe, using the Inverse Distance Weighting technique; and (e) remote sensing mean monthly air temperature data. The RASPOTION dataset was validated with in situ samples (USA, Germany, Spain, Ireland, Greece, Australia, China) and by using a spatial Penman–Monteith estimates in England. The results in both cases are satisfactory. The main objective is to demonstrate the practical usefulness of these PET map products across different research disciplines and spatiotemporal scales, towards assisting decision making for both short- and long-term hydro-climatic policy actions.

    Remarks:

    The data accompanying the paper are open and available for free: https://ntuagr-my.sharepoint.com/:f:/g/personal/dkoutsog_ntua_gr/EvSuyFR7zl1Jiax1YKbPhW0BT9-swkLHdw-LuhGE4gd5Cg?e=OtYQMn

    Full text: http://www.itia.ntua.gr/en/getfile/2167/1/documents/hydrology-09-00032-v2.pdf (4154 KB)

  1. P. Dimitriadis, A. Tegos, and D. Koutsoyiannis, Stochastic analysis of hourly to monthly potential evapotranspiration with a focus on the long-range dependence and application with reanalysis and ground-station data, Hydrology, 8 (4), 177, doi:10.3390/hydrology8040177, 2021.

    The stochastic structures of potential evaporation and evapotranspiration (PEV and PET or ETo) are analyzed using the ERA5 hourly reanalysis data and the Penman–Monteith model applied to the well-known CIMIS network. The latter includes high-quality ground meteorological samples with long lengths and simultaneous measurements of monthly incoming shortwave radiation, temperature, relative humidity, and wind speed. It is found that both the PEV and PET processes exhibit a moderate long-range dependence structure with a Hurst parameter of 0.64 and 0.69, respectively. Additionally, it is noted that their marginal structures are found to be light-tailed when estimated through the Pareto–Burr–Feller distribution function. Both results are consistent with the global-scale hydrological-cycle path, determined by all the above variables and rainfall, in terms of the marginal and dependence structures. Finally, it is discussed how the existence of, even moderate, long-range dependence can increase the variability and uncertainty of both processes and, thus, limit their predictability.

    Full text: http://www.itia.ntua.gr/en/getfile/2168/1/documents/hydrology-08-00177.pdf (3107 KB)

  1. A. Koskinas, and A. Tegos, StEMORS: A stochastic eco-hydrological model for optimal reservoir sizing, Open Water Journal, 6 (1), 1, 2020.

    Dams design and their operation cause strong environmental alteration and therefore a long-term debate is ongoing for the scale of these projects. At the same time, the concept of Environmental Flow Assessment (EFA) is a crucial element of modified ecosystems featuring large infrastructure such as dams and reservoirs for mitigating potential environmental degradation while they operate. Nowadays, integrated scientific frameworks are required to quantify the risks caused by large infrastructure. Through the use of stochastic analysis, it is possible to quantify these uncertainties, and present a solution that incorporates long-term persistence and environmental sustainability into a balanced reservoir simulation model. In this work, an attempt is made to determine a benchmark reservoir size incorporating hydrological and ecological criteria though stochastic analysis. The primary goal is to ensure the best possible conditions for the ecosystem, and then secondarily to allow a steady supply of water for other uses. Using a synthetic timeseries based on historical inputs, it is possible to determine and preserve essential statistical characteristics of a river’s streamflow, and use these to detect the optimal reservoir capacity that maximizes environmental and local water demand reliability.

    Full text: http://www.itia.ntua.gr/en/getfile/2041/1/documents/StEMORS.pdf (1256 KB)

    See also: https://scholarsarchive.byu.edu/openwater/vol6/iss1/1

  1. A. Koskinas, A. Tegos, P. Tsira, P. Dimitriadis, T. Iliopoulou, P. Papanicolaou, D. Koutsoyiannis, and Τ. Williamson, Insights into the Oroville Dam 2017 spillway incident, Geosciences, 9 (37), doi:10.3390/geosciences9010037, 2019.

    In February 2017, a failure occurring in Oroville Dam’s main spillway risked causing severe damages downstream. A unique aspect of this incident was the fact that it happened during a flood scenario well within its design and operational procedures, prompting research into its causes and determining methods to prevent similar events from reoccurring. In this study, a hydroclimatic analysis of Oroville Dam’s catchment is conducted, along with a review of related design and operational manuals. The data available allows for the comparison of older flood-frequency analyses to new alternative methods proposed in this paper and relevant literature. Based on summary characteristics of the 2017 floods, possible causes of the incident are outlined, in order to understand which factors contributed more significantly. It turns out that the event was most likely the result of a structural problem in the dam’s main spillway and detrimental geological conditions, but analysis of surface level data also reveals operational issues that were not present during previous larger floods, promoting a discussion about flood control design methods, specifications, and dam inspection procedures, and how these can be improved to prevent a similar event from occurring in the future.

    Full text: http://www.itia.ntua.gr/en/getfile/1926/1/documents/geosciences-09-00037-2.pdf (6834 KB)

    Works that cite this document: View on Google Scholar or ResearchGate

  1. A. Tegos, W. Schlüter, N. Gibbons, Y. Katselis, and A. Efstratiadis, Assessment of environmental flows from complexity to parsimony - Lessons from Lesotho, Water, 10 (10), 1293, doi:10.3390/w10101293, 2018.

    Over the last decade, Environmental Flow Assessment (EFA) has focused scientific attention around heavily-modified hydrosystems, such as flow regulated releases downstream of dams. In this light, numerous approaches of varying complexity have been developed, the most holistic of which incorporate hydrological, hydraulic, biological and water quality inputs, as well as socioeconomic issues. Finding the optimal flow releases, informing policy and determining an operational framework are often the main focus. This work exhibits a simplification of the DRIFT framework, and is regarded as the first holistic EFA approach, consisting of three modules, namely hydrological, hydraulic and fish quality. A novel conceptual classification for fish quality is proposed, associating fish fauna requirements with hydraulic characteristics, exported by fish survey analyses. The new methodology was applied and validated successfully at three stream sites in Lesotho, where DRIFT was formerly employed.

    Full text: http://www.itia.ntua.gr/en/getfile/1878/1/documents/water-10-01293.pdf (2633 KB)

    See also: http://www.mdpi.com/2073-4441/10/10/1293/htm

    Other works that reference this work (this list might be obsolete):

    1. Yang, Z., K. Yang, L. Su, and H. Hu, The multi-objective operation for cascade reservoirs using MMOSFLA with emphasis on power generation and ecological benefit, Journal of Hydroinformatics, 21(2), 257-278, doi:10.2166/hydro.2019.064, 2019.
    2. Langat, P. K., L. Kumar, and R. Koech, Identification of the most suitable probability distribution models for maximum, minimum, and mean streamflow, Water, 11, 734, doi:10.3390/w11040734, 2019.
    3. Sahoo, B. B., R. Jha, A. Singh, A. and D. Kumar, Long short-term memory (LSTM) recurrent neural network for low-flow hydrological time series forecasting, Acta Geophysica, 67, 1471-1481, doi:10.1007/s11600-019-00330-1, 2019.
    4. Ding, L., Q. Li, J. Tang, J. Wang, and X. Chen, Linking land use metrics measured in aquatic-terrestrial interfaces to water quality of reservoir-based water sources in Eastern China, Sustainability, 11(18), 4860, doi:10.3390/su11184860, 2019.
    5. Koskinas, A., Stochastics and ecohydrology: A study in optimal reservoir design, Dams and Reservoirs, 30(2), 53-59, doi:10.1680/jdare.20.00009, 2020.
    6. Jo, Y.-J., J.-H. Song, Y. Her, G. Provolo, J. Beom, M. Jeung, Y.-J. Kim, S.-H. Yoo, and K.-S. Yoon, Assessing the potential of agricultural reservoirs as the source of environmental flow, Water; 13(4), 508, doi:10.3390/w13040508, 2021.
    7. Wu, M., H. Wu, A. T. Warner, H. Li, and Z. Liu, Informing environmental flow planning through landscape evolution modeling in heavily modified urban rivers in China, Water, 13(22), 3244, doi:10.3390/w13223244, 2021.
    8. Hoque, M. M., A. Islam, and S. Ghosh, Environmental flow in the context of dams and development with special reference to the Damodar Valley Project, India: a review, Sustainable Water Resources Management, 8, 62, doi:10.1007/s40899-022-00646-9, 2022.
    9. Owusu, A., M. Mul, M. Strauch, P. van der Zaag, M. Volk, and J. Slinger, The clam and the dam: A Bayesian belief network approach to environmental flow assessment in a data scarce region, Science of The Total Environment, 810, 151315, doi:10.1016/j.scitotenv.2021.151315, 2022.
    10. Liu, S., Q. Zhang, Y. Xie, P. Xu, and H. Du, Evaluation of minimum and suitable ecological flows of an inland basin in China considering hydrological variation, Water, 15(4), 649, doi:10.3390/w15040649, 2023.
    11. Nasiri Khiavi, A., R. Mostafazadeh, and F. Ghanbari Talouki, Using game theory algorithm to identify critical watersheds based on environmental flow components and hydrological indicators, Environment, Development and Sustainability, doi:10.1007/s10668-023-04390-8, 2024.

  1. N. Malamos, I. L. Tsirogiannis, A. Tegos, A. Efstratiadis, and D. Koutsoyiannis, Spatial interpolation of potential evapotranspiration for precision irrigation purposes, European Water, 59, 303–309, 2017.

    Precision irrigation constitutes a breakthrough for agricultural water management since it provides means to optimal water use. In recent years several applications of precision irrigation are implemented based on spatial data from different origins, i.e. meteorological stations networks, remote sensing data and in situ measurements. One of the factors affecting optimal irrigation system design and management is the daily potential evapotranspiration (PET). A commonly used approach is to estimate the daily PET for the representative day of each month during the irrigation period. In the present study, the implementation of the recently introduced non-parametric bilinear surface smoothing (BSS) methodology for spatial interpolation of daily PET is presented. The study area was the plain of Arta which is located at the Region of Epirus at the North West Greece. Daily PET was estimated according to the FAO Penman-Monteith methodology with data collected from a network of six agrometeorological stations, installed in early 2015 in selected locations throughout the study area. For exploration purposes, we produced PET maps for the Julian dates: 105, 135, 162, 199, 229 and 259, thus covering the entire irrigation period of 2015. Also, comparison and cross validation against the calculated FAO Penman-Monteith PET for each station, were performed between BSS and a commonly used interpolation method, i.e. inverse distance weighted (IDW). During the leave-one-out cross validation procedure, BSS yielded very good results, outperforming IDW. Given the simplicity of the BSS, its overall performance is satisfactory, providing maps that represent the spatial and temporal variation of daily PET.

    Full text: http://www.itia.ntua.gr/en/getfile/1776/1/documents/EW_2017_59_41_2HOxTxv.pdf (4259 KB)

    See also: http://ewra.net/ew/pdf/EW_2017_59_41.pdf

    Works that cite this document: View on Google Scholar or ResearchGate

    Other works that reference this work (this list might be obsolete):

    1. Ndiaye, P. M., A. Bodian, L. Diop, A. Deme, A. Dezetter, K. Djaman, and A. Ogilvie, Trend and sensitivity analysis of reference evapotranspiration in the Senegal river basin using NASA meteorological data, Water, 12(7), 1957, doi:10.3390/w12071957, 2020.
    2. Ndiaye, P. M., A. Bodian, L. Diop, A. Dezetter, E. Guilpart, A. Deme, and A. Ogilvie, Future trend and sensitivity analysis of evapotranspiration in the Senegal River Basin, Journal of Hydrology: Regional Studies, 35, 100820, doi:10.1016/j.ejrh.2021.100820, 2021.
    3. Dimitriadou S., and K. G. Nikolakopoulos, Reference evapotranspiration (ETo) methods implemented as ArcMap models with remote-sensed and ground-based inputs, examined along with MODIS ET, for Peloponnese, Greece, ISPRS International Journal of Geo-Information, 10(6), 390, doi:10.3390/ijgi10060390, 2021.
    4. #Dimitriadou, S., and K. G. Nikolakopoulos, Development of GIS models via optical programming and python scripts to implement four empirical methods of reference and actual evapotranspiration (ETo, ETa) incorporating MODIS LST inputs, Proc. SPIE 11856, Remote Sensing for Agriculture, Ecosystems, and Hydrology XXIII, 118560K, doi:10.1117/12.2597724, 2021.
    5. Dimitriadou, S., and K. G. Nikolakopoulos, Evapotranspiration trends and interactions in light of the anthropogenic footprint and the climate crisis: A review, Hydrology, 8(4), 163, doi:10.3390/hydrology8040163, 2021.
    6. Dimitriadou, S., and K. G. Nikolakopoulos, Artificial neural networks for the prediction of the reference evapotranspiration of the Peloponnese Peninsula, Greece, Water, 14(13), 2027, doi:10.3390/w14132027, 2022.
    7. Fotia, K., G. Nanos, N. Malamos, M. Giannelos, P. Mpeza, and I. Tsirogiannis, Water footprint and performance assessment of a table olive cultivar (Olea europaea L. “Konservolea”) under various irrigation strategies, Acta Horticulturae, 1373, 57-64, doi:10.17660/ActaHortic.2023.1373.9, 2023.

  1. A. Tegos, N. Malamos, A. Efstratiadis, I. Tsoukalas, A. Karanasios, and D. Koutsoyiannis, Parametric modelling of potential evapotranspiration: a global survey, Water, 9 (10), 795, doi:10.3390/w9100795, 2017.

    We present and validate a global parametric model of potential evapotranspiration (PET) with two parameters which are estimated through calibration, using as explanatory variables temperature and extraterrestrial radiation. The model and the parameters estimation approach were tested over the globe, using the FAO CLIMWAT database that provides monthly averaged values of meteorological inputs at 4300 locations worldwide. A preliminary analysis of these data allowed explaining the major drivers of PET over the globe and across seasons. Next, we developed an automatic optimization software tool to calibrate the model and provide point PET estimations against the given Penman-Monteith values. We also employed extended analysis of model inputs and outputs, including the production of global maps of optimized model parameters and associated performance metrics. Also, we employed interpolated values of the optimized parameters to validate the predictive capacity of our model against monthly meteorological time series, at several stations worldwide. The results were very encouraging, since even with the use of abstract climatic information for model calibration and the use of interpolated parameters as local predictors, the model generally ensures reliable PET estimations. In few cases the model performs poorly in estimating the reference PET, due to irregular interactions between temperature and extraterrestrial radiation, as well as because the associated processes are influenced by additional drivers, e.g. relative humidity and wind speed. However, the analysis of the residuals showed that the model is consistent in terms of parameters estimation and model validation. The provided parameters maps allow the direct use of the parametric model wherever in the world, providing PET estimates in case of missing data, that can be further improved even with a short term acquisition of meteorological data.

    Full text: http://www.itia.ntua.gr/en/getfile/1738/2/documents/water-09-00795.pdf (6428 KB)

    Additional material:

    See also: http://www.mdpi.com/2073-4441/9/10/795

    Works that cite this document: View on Google Scholar or ResearchGate

    Other works that reference this work (this list might be obsolete):

    1. Elferchichi, A., G. A. Giorgio, N. Lamaddalena, M. Ragosta, and V. Telesca, Variability of temperature and its impact on reference evapotranspiration: the test case of the Apulia region (Southern Italy), Sustainability, 9(12), 2337, doi:10.3390/su9122337, 2017.
    2. Li, M., R. Chu, S. Shen, and A. R. T. Islam, Quantifying climatic impact on reference evapotranspiration trends in the Huai River Basin of Eastern China, Water, 10(2), 144, doi:10.3390/w10020144, 2018.
    3. Yan, N., F. Tian, B. Wu, W. Zhu, and M. Yu, Spatiotemporal analysis of actual evapotranspiration and its causes in the Hai basin, Remote Sensing, 10(2), 332; doi:10.3390/rs10020332, 2018.
    4. Li, M., R. Chu, A.R.M.T. Islam, and S. Shen, Reference evapotranspiration variation analysis and its approaches evaluation of 13 empirical models in sub-humid and humid regions: A case study of the Huai River Basin, Eastern China, Water, 10(4), 493, doi:10.3390/w10040493, 2018.
    5. Hao, X., S. Zhang, W. Li, W. Duan, G. Fang, Y. Zhang , and B. Guo, The uncertainty of Penman-Monteith method and the energy balance closure problem, Journal of Geophysical Research – Atmospheres, 123(14), 7433-7443, doi:10.1029/2018JD028371, 2018.
    6. Giménez, P. O., and S. G. García-Galiano, Assessing Regional Climate Models (RCMs) ensemble-driven reference evapotranspiration over Spain, Water, 10(9), 1181, doi:10.3390/w10091181, 2018.
    7. Storm, M. E., R. Gouws, and L. J. Grobler, Novel measurement and verification of irrigation pumping energy conservation under incentive-based programmes, Journal of Energy in Southern Africa, 29(3), 10–21, doi:10.17159/2413-3051/2018/v29i3a3058, 2018.
    8. Tam, B. Y., K. Szeto, B. Bonsal, G. Flato, A. J. Cannon, and R. Rong, CMIP5 drought projections in Canada based on the Standardized Precipitation Evapotranspiration Index, Canadian Water Resources Journal, 44(1), 90-107, doi:10.1080/07011784.2018.1537812, 2019.
    9. Dalezios, N. R., N. Dercas, A. Blanta, and I. N. Faraslis, Remote sensing in water balance modelling for evapotranspiration at a rural watershed in Central Greece, International Journal of Sustainable Agricultural Management and Informatics, 4(3-4), 306-337, doi:10.1504/IJSAMI.2018.099219, 2019.
    10. Gan, G., Y. Liu, X. Pan, X. Zhao, M. Li, and S. Wang, Testing the symmetric assumption of complementary relationship: A comparison between the linear and nonlinear advection-aridity models in a large ephemeral lake, Water, 11(8), 1574, doi:10.3390/w11081574, 2019.
    11. Zhang, T., Y. Chen, and K. Tha Paw U, Quantifying the impact of climate variables on reference evapotranspiration in Pearl River Basin, China, Hydrological Sciences Journal, 64(16), 1944-1956, doi:10.1080/02626667.2019.1662021, 2019.
    12. Hua, D., X. Hao, Y. Zhang, and J. Qin, Uncertainty assessment of potential evapotranspiration in arid areas, as estimated by the Penman-Monteith method, Journal of Arid Land, 12, 166–180, doi:10.1007/s40333-020-0093-7, 2020.
    13. Shirmohammadi-Aliakbarkhani, Z., and S. F. Saberali, Evaluating of eight evapotranspiration estimation methods in arid regions of Iran, Agricultural Water Management, 239, 106243, doi:10.1016/j.agwat.2020.106243, 2020.
    14. Kim, C.-G., J. Lee, J. E. Lee, and H. Kim, Evaluation of improvement effect on the spatial-temporal correction of several reference evapotranspiration methods, Journal of Korea Water Resources Association, 53(9), 701-715, doi:10.3741/JKWRA.2020.53.9.701, 2020.
    15. Gui, Y., Q. Wang, Y. Zhao, Y. Dong, H. Li, S. Jiang, X. He, and K. Liu, Attribution analyses of reference evapotranspiration changes in China incorporating surface resistance change response to elevated CO2, Journal of Hydrology, 599, 126387, doi:10.1016/j.jhydrol.2021.126387, 2021.
    16. Mohanasundaram, S., M. M. Mekonnen, E. Haacker, C. Ray, S. Lim, and S. Shrestha, An application of GRACE mission datasets for streamflow and baseflow estimation in the Conterminous United States basins, Journal of Hydrology, 601, 126622, doi:10.1016/j.jhydrol.2021.126622, 2021.
    17. Gentilucci, M., M. Bufalini, M. Materazzi, M. Barbieri, D. Aringoli, P. Farabollini, and G. Pambianchi, Calculation of potential evapotranspiration and calibration of the Hargreaves equation using geostatistical methods over the last 10 years in Central Italy, Geosciences, 11(8), 348, doi:10.3390/geosciences11080348, 2021.
    18. Dos Santos, A. A., J. L. M. de Souza, and S. L. K. Rosa, Evapotranspiration with the Moretti-Jerszurki-Silva model for the Brazilian subtropical climate, Hydrological Sciences Journal, 66(16), 2267-2279, doi:10.1080/02626667.2021.1988610, 2021.
    19. Stefanidis, S., and V. Alexandridis, Precipitation and potential evapotranspiration temporal variability and their relationship in two forest ecosystems in Greece, Hydrology, 8(4), 160, doi:10.3390/hydrology8040160, 2021.
    20. Saggi, M. K., and S. A. Jain, Survey towards decision support system on smart irrigation scheduling using machine learning approaches, Archives of Computational Methods in Engineering, 29, 4455-4478, doi:10.1007/s11831-022-09746-3, 2022.
    21. Urban, G., L. Kuchar, M. Kępińska-Kasprzak, and E. Z. Łaszyca, A climatic water balance variability during the growing season in Poland in the context of modern climate change, Meteorologische Zeitschrift, 31(5), 349-365, doi:10.1127/metz/2022/1128, 2022.
    22. Hajek, O. L., and A. K. Knapp, Shifting seasonal patterns of water availability: ecosystem responses to an unappreciated dimension of climate change, New Phytologist, 233(1), 119-125, doi:10.1111/nph.17728, 2022.
    23. Al-Asadi, K., A. A. Abbas, A. S. Dawood, and J. G. Duan, Calibration and modification of the Hargreaves–Samani equation for estimating daily reference evapotranspiration in Iraq, Journal of Hydrologic Engineering, 28(5), doi:10.1061/JHYEFF.HEENG-5877, 2023.
    24. Islam, S., and A. K. M. R. Alam, Quantifying spatiotemporal variation of reference evapotranspiration and its contributing climatic factors in Bangladesh during 1981–2018, Russian Meteorology and Hydrology, 48(3), 253-266, doi:10.3103/S1068373923030081, 2023.
    25. Stefanidis, S., A. Tegos, and V. Alexandridis, How has aridity changed at a fir (Abies Borisii-Regis) forest site in Central Greece during the past six decades? Environmental Sciences Proceedings, 26(1), 121, doi:10.3390/environsciproc2023026121, 2023.
    26. Maas, E. D.v.L., and R. A. Lal, A case study of the RothC soil carbon model with potential evapotranspiration and remote sensing model inputs, Remote Sensing Applications: Society and Environment, 29, 100876, doi:10.1016/j.rsase.2022.100876, 2023.
    27. Ruiz-Ortega, F. J., E. Clemente, A. Martínez-Rebollar, and J. J. Flores-Prieto, An evolutionary parsimonious approach to estimate daily reference evapotranspiration, Scientific Reports, 14, 6736, doi:10.1038/s41598-024-56770-3, 2024.

  1. A. Tegos, H. Tyralis, D. Koutsoyiannis, and K. H. Hamed, An R function for the estimation of trend signifcance under the scaling hypothesis- application in PET parametric annual time series, Open Water Journal, 4 (1), 66–71, 6, 2017.

    We present an R function for testing the significant trend of time series. Te function calculates trend significance using a modified Mann-Kendall test, which takes into account the well-known physical behavior of the Hurst-Kolmogorov dynamics. Te function is tested at 10 stations in Greece, with approximately 50 years of PET data with the use of a recent parametric approach. A significant downward trend was detected at two stations. Te R software is now suitable for extensive use in several fields of the scientific community, allowing a physical consistent of a trend analysis.

    Full text: http://www.itia.ntua.gr/en/getfile/1703/1/documents/2017OW_An_R_FunctionForTrendSignificance.pdf (326 KB)

    Additional material:

    See also: http://scholarsarchive.byu.edu/openwater/vol4/iss1/6/

    Works that cite this document: View on Google Scholar or ResearchGate

  1. H. Tyralis, A. Tegos, A. Delichatsiou, N. Mamassis, and D. Koutsoyiannis, A perpetually interrupted interbasin water transfer as a modern Greek drama: Assessing the Acheloos to Pinios interbasin water transfer in the context of integrated water resources management, Open Water Journal, 4 (1), 113–128, 12, 2017.

    Interbasin water transfer is a primary instrument of water resources management directly related with the integrated development of the economy, society and environment. Here we assess the project of the interbasin water transfer from the river Acheloos to the river Pinios basin which has intrigued the Greek society, the politicians and scientists for decades. Te set of criteria we apply originate from a previous study reviewing four interbasin water transfers and assessing whether an interbasin water transfer is compatible with the concept of integrated water resources management. In this respect, we assess which of the principles of the integrated water resources management the Acheloos to Pinios interbasin water transfer project does or does not satisfy. While the project meets the criteria of real surplus and deficit, of sustainability and of sound science, i.e., the criteria mostly related to the engineering part, it fails to meet the criteria of good governance and balancing of existing rights with needs, i.e., the criteria associated with social aspects of the project. Te non-fulfillment of the latter criteria is the consequence of chronic diseases of the Greek society, which become obvious in the case study

    Full text: http://www.itia.ntua.gr/en/getfile/1702/1/documents/2017OW_AcheloosToPiniosInterbasinWaterTransfer.pdf (2744 KB)

    See also: http://scholarsarchive.byu.edu/openwater/vol4/iss1/11/

    Works that cite this document: View on Google Scholar or ResearchGate

  1. P. Dimitriadis, A. Tegos, A. Oikonomou, V. Pagana, A. Koukouvinos, N. Mamassis, D. Koutsoyiannis, and A. Efstratiadis, Comparative evaluation of 1D and quasi-2D hydraulic models based on benchmark and real-world applications for uncertainty assessment in flood mapping, Journal of Hydrology, 534, 478–492, doi:10.1016/j.jhydrol.2016.01.020, 2016.

    One-dimensional and quasi-two-dimensional hydraulic freeware models (HEC-RAS, LISFLOOD-FP and FLO-2d) are widely used for flood inundation mapping. These models are tested on a benchmark test with a mixed rectangular-triangular channel cross section. Using a Monte-Carlo approach, we employ extended sensitivity analysis by simultaneously varying the input discharge, longitudinal and lateral gradients and roughness coefficients, as well as the grid cell size. Based on statistical analysis of three output variables of interest, i.e. water depths at the inflow and outflow locations and total flood volume, we investigate the uncertainty enclosed in different model configurations and flow conditions, without the influence of errors and other assumptions on topography, channel geometry and boundary conditions. Moreover, we estimate the uncertainty associated to each input variable and we compare it to the overall one. The outcomes of the benchmark analysis are further highlighted by applying the three models to real-world flood propagation problems, in the context of two challenging case studies in Greece.

    Works that cite this document: View on Google Scholar or ResearchGate

    Other works that reference this work (this list might be obsolete):

    1. Apel, H., O. Martínez Trepat, N. N. Hung, D. T. Chinh, B. Merz, and N. V. Dung, Combined fluvial and pluvial urban flood hazard analysis: concept development and application to Can Tho city, Mekong Delta, Vietnam, Natural Hazards and Earth System Sciences, 16, 941-961, doi:10.5194/nhess-16-941-2016, 2016.
    2. Papaioannou , G., A. Loukas, L. Vasiliades, and G. T. Aronica, Flood inundation mapping sensitivity to riverine spatial resolution and modelling approach, Natural Hazards, 83, 117-132, doi:10.1007/s11069-016-2382-1, 2016.
    3. #Santillan, J. R., A. M. Amora, M. Makinano-Santillan, J. T. Marqueso, L. C. Cutamora, J. L. Serviano, and R. M. Makinano, Assessing the impacts of flooding caused by extreme rainfall events through a combined geospatial and numerical modeling approach, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XLI-B8, 2016, XXIII ISPRS Congress, Prague, doi:10.5194/isprs-archives-XLI-B8-1271-2016, 2016.
    4. Cheviron, B. and R. Moussa, Determinants of modelling choices for 1-D free-surface flow and morphodynamics in hydrology and hydraulics: a review, Hydrology and Earth System Sciences, 20, 3799-3830, doi:10.5194/hess-20-3799-2016, 2016.
    5. Anees, M.T., K. Abdullah, M.N.M. Nawawi, N. N. N. Ab Rahman, A. R. Mt. Piah, N. A. Zakaria, M.I. Syakir, and A.K. Mohd. Omar, Numerical modeling techniques for flood analysis, Journal of African Earth Sciences, 124, 478–486, doi:10.1016/j.jafrearsci.2016.10.001, 2016.
    6. Skublics, D., G. Blöschl, and P. Rutschmann, Effect of river training on flood retention of the Bavarian Danube, Journal of Hydrology and Hydromechanics, 64(4), 349-356, doi:10.1515/johh-2016-0035, 2016.
    7. Doong, D.-J., W. Lo, Z. Vojinovic, W.-L. Lee, and S.-P. Lee, Development of a new generation of flood inundation maps—A case study of the coastal City of Tainan, Taiwan, Water, 8(11), 521, doi:10.3390/w8110521, 2016.
    8. #Cartaya, S., and R. Mantuano-Eduarte, Identificación de zonas en riesgo de inundación mediante la simulación hidráulica en un segmento del Río Pescadillo, Manabí, Ecuador, Revista de Investigación, 40(89), 158-170, 2016.
    9. Javadnejad, F., B. Waldron, and A. Hill, LITE Flood: Simple GIS-based mapping approach for real-time redelineation of multifrequency floods, Natural Hazards Review, 18(3), doi:10.1061/(ASCE)NH.1527-6996.0000238, 2017.
    10. Shrestha, A., M. S. Babel, S. Weesakul, and Z. Vojinovic, Developing intensity–duration–frequency (IDF) curves under climate change uncertainty: The case of Bangkok, Thailand, Water, 9(2), 145, doi:10.3390/w9020145, 2017.
    11. Roushangar, K., M. T. Alami, V. Nourani, and A. Nouri, A cost model with several hydraulic constraints for optimizing in practice a trapezoidal cross section, Journal of Hydroinformatics, 19(3), 456-468, doi:10.2166/hydro.2017.081, 2017.
    12. Papaioannou, G., L. Vasiliades, A. Loukas, and G. T. Aronica, Probabilistic flood inundation mapping at ungauged streams due to roughness coefficient uncertainty in hydraulic modelling, Advances in Geosciences, 44, 23-34, doi:10.5194/adgeo-44-23-2017, 2017.
    13. Anees, M. T., K. Abdullah, M. N. M. Nawawi, N. N. N. Ab Rahman, A. R. Mt. Piah, M. I. Syakir, A. K. M. Omar, and K. Hossain, Applications of remote sensing, hydrology and geophysics for flood analysis, Indian Journal of Science and Technology, 10(17), doi:10.17485/ijst/2017/v10i17/111541, 2017.
    14. Fuentes-Andino, D., K. Beven, S. Halldin, C.-Y. Xu, J. E. Reynolds, and G. Di Baldassarre, Reproducing an extreme flood with uncertain post-event information, Hydrology and Earth System Sciences, 21, 3597-3618, doi:10.5194/hess-21-3597-2017, 2017.
    15. #Anees, M. T., K. Abdullah, M. N. M. Nordin, N. N. N. Ab Rahman, M. I. Syakir, and M. O. A. Kadir, One- and two-dimensional hydrological modelling and their uncertainties, Flood Risk Management, T. Hromadka and P. Rao (editors), Chapter 11, doi:10.5772/intechopen.68924, 2017.
    16. #Papaioannou, G., A. Loukas, L. Vasiliades, and G. T. Aronica, Sensitivity analysis of a probabilistic flood inundation mapping framework for ungauged catchments, Proceedings of the 10th World Congress of EWRA “Panta Rhei”, European Water Resources Association, Athens, 2017.
    17. Bangira, T., S. M. Alfieri , M. Menenti, A. van Niekerk, and Z. Vekerdy, A spectral unmixing method with ensemble estimation of endmembers: Application to flood mapping in the Caprivi floodplain, Remote Sensing, 9, 1013, doi:10.3390/rs9101013, 2017.
    18. Carisi, F., A. Domeneghetti, M. G. Gaeta, and A. Castellarin, Is anthropogenic land subsidence a possible driver of riverine flood-hazard dynamics? A case study in Ravenna, Italy, Hydrological Sciences Journal, 62(15), 2440-2455, doi:10.1080/02626667.2017.1390315, 2017.
    19. Podhoranyi, M., P. Veteska, D. Szturcova, L. Vojacek, and A. Portero, A web-based modelling and monitoring system based on coupling environmental models and hydrological-related data, Journal of Communications, 12(6), 340-346, doi:10.12720/jcm.12.6.340-346, 2017.
    20. Bhuyian, N. M., A. Kalyanapu, and F. Hossain, Evaluating conveyance-based DEM correction technique on NED and SRTM DEMs for flood impact assessment of the 2010 Cumberland river flood, Geosciences, 7(4), 132; doi:10.3390/geosciences7040132, 2017.
    21. Zin, W., A. Kawasaki, W. Takeuchi, Z. M. L. T. San, K. Z. Htun, T. H. Aye, and S. Win, Flood hazard assessment of Bago river basin, Myanmar, Journal of Disaster Research, 13(1), 14-21, doi:10.20965/jdr.2018.p0014, 2018.
    22. #Siregar, R. I., Hydraulic modeling of flow impact on bridge structures: a case study on Citarum bridge, IOP Conference Series: Materials Science and Engineering, 309, 012015, doi:10.1088/1757-899X/309/1/012015, 2018.
    23. Miranda, D., R. F. Camacho, S. Lousada, and R. A. Castanho, Hydraulic studies and their influence for regional urban planning: a practical approach to Funchal’s rivers, Revista Brasiliera de Planejamento e Desenvolvimento, 7(1), 145-164, doi:10.3895/rbpd.v7n1.7179, 2018.
    24. Liu, W., and H. Liu, Integrating Monte Carlo and the hydrodynamic model for predicting extreme water levels in river systems, Preprints 2018, 2018030088, doi:10.20944/preprints201803.0088.v1, 2018.
    25. #Indrawan, I., and R. I. Siregar, Analysis of flood vulnerability in urban area: a case study in Deli watershed, Journal of Physics Conference Series, 978(1), 012036, doi:10.1088/1742-6596/978/1/012036, 2018.
    26. #Siregar, R. I., Land cover change impact on urban flood modeling (case study: Upper Citarum watershed), IOP Conference Series: Earth and Environmental Science, 126(1), 012027, doi:10.1088/1755-1315/126/1/012027, 2018.
    27. #Ng, Z. F.., J. I. Gisen, and A. Akbari, Flood inundation modelling in the Kuantan river basin using 1D-2D flood modeller coupled with ASTER-GDEM, IOP Conference Series: Materials Science and Engineering, 318(1), 012024, doi:10.1088/1757-899X/318/1/012024, 2018.
    28. Chang, M.-J., H.-K. Chang, Y.-C. Chen, G.-F. Lin, P.-A. Chen, J.-S. Lai, and Y.-C. Tan, A support vector machine forecasting model for typhoon flood inundation mapping and early flood warning systems, Water, 10, 1734, doi:10.3390/w10121734, 2018.
    29. Dysarz, T., Application of Python scripting techniques for control and automation of HEC-RAS simulations, Water, 10(10):1382, doi:10.3390/w10101382, 2018.
    30. Hdeib, R., C. Abdallah, F. Colin, L. Brocca, and R. Moussa, Constraining coupled hydrological-hydraulic flood model by past storm events and post-event measurements in data-sparse regions, Journal of Hydrology, 565, 160-175, doi:10.1016/j.jhydrol.2018.08.008, 2018.
    31. Tan, F. J., E. J. R. Rarugal, and F. A. A. Uy, One-dimensional (1D) river analysis of a river basin in Southern Luzon Island in the Philippines using Lidar Digital Elevation Model, International Journal of Engineering & Technology, 7(3.7), 29-33, doi:10.14419/ijet.v7i3.7.16200, 2018.
    32. Luo, P., D. Mu, H. Xue, T. Ngo-Duc, K. Dang-Dinh, K. Takara, D. Nover, and G. Schladow, Flood inundation assessment for the Hanoi Central Area, Vietnam under historical and extreme rainfall conditions, Scientific Reports, 8, 12623, doi:10.1038/s41598-018-30024-5, 2018.
    33. Indrawan, I., and R. I. Siregar, Pemodelan Penerapan Terowongan Air (Tunnel) dalam Mengatasi Banjir Akibat Luapan Sungai Deli, Jurnal Teknik Sipil, 25(2), 113-120, doi:10.5614/jts.2018.25.2.4, 2018.
    34. Petroselli, A., M. Vojtek, and J. Vojteková, Flood mapping in small ungauged basins: A comparison of different approaches for two case studies in Slovakia, Hydrology Research, 50(1), 379-392, doi:10.2166/nh.2018.040, 2018.
    35. Agudelo-Otálora, L. M., W. D. Moscoso-Barrera, L. A. Paipa-Galeano, and C. Mesa-Sciarrotta, Comparison of physical models and artificial intelligence for prediction of flood levels, Water Technology and Sciences, 9(4), 209-236, doi:10.24850/j-tyca-2018-04-09, 2018.
    36. Kaya, C. M., G. Tayfur, and O. Gungor, Predicting flood plain inundation for natural channels having no upstream gauged stations, Journal of Water and Climate Change, 10(2), 360-372, doi:10.2166/wcc.2017.307, 2019.
    37. Liu, Z., V. Merwade, and K. Jafarzadegan, Investigating the role of model structure and surface roughness in generating flood inundation extents using 1D and 2D hydraulic models, Journal of Flood Risk Management, 12(1), e12347, doi:10.1111/jfr3.12347, 2019.
    38. Tscheikner-Gratl, F., V. Bellos, A. Schellart, A. Moreno-Rodenas, M. Muthusamy, J. Langeveld, F. Clemens, L. Benedetti, M.A. Rico-Ramirez, R. Fernandes de Carvalho, L. Breuer, J. Shucksmith, G.B.M. Heuvelink, and S. Tait, Recent insights on uncertainties present in integrated catchment water quality modelling, Water Research, 150, 368-379, doi:10.1016/j.watres.2018.11.079, 2019.
    39. Zeleňáková, M., R. Fijko, S. Labant, E. Weiss, G. Markovič, and R. Weiss, Flood risk modelling of the Slatvinec stream in Kružlov village, Slovakia, Journal of Cleaner Production, 212, 109-118, doi:10.1016/j.jclepro.2018.12.008, 2019.
    40. Wang, P., G. Zhang, and H. Leung, Improving super-resolution flood inundation mapping for multispectral remote sensing image by supplying more spectral information, IEEE Geoscience and Remote Sensing Letters, 16(5), 771-775, doi:10.1109/LGRS.2018.2882516, 2019.
    41. Tehrany, M. S., S. Jones, and F. Shabani, Identifying the essential flood conditioning factors for flood prone area mapping using machine learning techniques, Catena, 175, 174-192, doi:10.1016/j.catena.2018.12.011, 2019.
    42. Škarpich, V., T. Galia, S. Ruman, and Z. Máčka, Variations in bar material grain-size and hydraulic conditions of managed and re-naturalized reaches of the gravel-bed Bečva River (Czech Republic), Science of The Total Environment, 649, 672-685, doi:10.1016/j.scitotenv.2018.08.329, 2019.
    43. Yang, Z., K. Yang, L. Su, and H. Hu, The multi-objective operation for cascade reservoirs using MMOSFLA with emphasis on power generation and ecological benefit, Journal of Hydroinformatics, 21(2), 257-278, doi:10.2166/hydro.2019.064, 2019.
    44. Dysarz, T., J. Wicher-Dysarz, M. Sojka, and J. Jaskuła, Analysis of extreme flow uncertainty impact on size of flood hazard zones for the Wronki gauge station in the Warta river, Acta Geophysica, 67(2), 661-676, doi:10.1007/s11600-019-00264-8, 2019.
    45. Fleischmann, A., R. Paiva, and W. Collischonn, Can regional to continental river hydrodynamic models be locally relevant? A cross-scale comparison, Journal of Hydrology X, 3, 100027, doi:10.1016/j.hydroa.2019.100027, 2019.
    46. Gyasi-Agyei, Y., Propagation of uncertainties in interpolated rain fields to runoff errors, Hydrological Sciences Journal, 64(5), 587-606, doi:10.1080/02626667.2019.1593989. 2019.
    47. Langat, P. K., L. Kumar, and R. Koech, Identification of the most suitable probability distribution models for maximum, minimum, and mean streamflow, Water, 11, 734, doi:10.3390/w11040734, 2019.
    48. Papaioannou, G., A. Loukas, and L. Vasiliades, Flood risk management methodology for lakes and adjacent areas: The lake Pamvotida paradigm, Proceedings, 7, 21, doi:10.3390/ECWS-3-05825, 2019.
    49. Hosseini, D., M. Torabi, and M. A. Moghadam, Preference assessment of energy and momentum equations over 2D-SKM method in compound channels, Journal of Water Resource Engineering and Management, 6(1), 24-34, 2019.
    50. Oubennaceur, K., K. Chokmani, M. Nastev, Y. Gauthier, J. Poulin, M. Tanguy, S. Raymond, and R. Lhissou, New sensitivity indices of a 2D flood inundation model using Gauss quadrature sampling, Geosciences, 9(5), 220, doi:10.3390/geosciences9050220, 2019.
    51. Pinho, J. L. S., L. Vieira, J. M. P. Vieira, S. Venâncio, N. E. Simões, J. A. Sá Marques, and F. S. Santos, Assessing causes and associated water levels for an urban flood using hydroinformatic tools, Journal of Hydroinformatics, jh2019019, doi:10.2166/hydro.2019.019, 2019.
    52. Saksena, S., V. Merwade, and P. J. Singhofen, Flood inundation modeling and mapping by integrating surface and subsurface hydrology with river hydrodynamics, Journal of Hydrology, 575, 1155-1177, doi:10.1016/j.jhydrol.2019.06.024, 2019.
    53. #Fijko, R., and M., Zelenakova, Verification of the hydrodynamic model of the Slatvinec River in Kružlov, Air and Water Components of the Environment Conference Proceedings, 91-98, Cluj-Napoca, Romania, doi:10.24193/AWC2019_09, 2019.
    54. Luppichini, M., M. Favalli, I. Isola, L. Nannipieri, R. Giannecchini, and M. Bini, Influence of topographic resolution and accuracy on hydraulic channel flow simulations: Case study of the Versilia River (Italy), Remote Sensing, 11(13), 1630, doi:10.3390/rs11131630, 2019.
    55. Liu, Z., and V. Merwade, Separation and prioritization of uncertainty sources in a raster based flood inundation model using hierarchical Bayesian model averaging, Journal of Hydrology, 578, 124100, doi:10.1016/j.jhydrol.2019.124100, 2019.
    56. #Huțanu, E., A. Urzică, L. E. Paveluc, C. C. Stoleriu, and A. Grozavu, The role of hydro-technical works in diminishing flooded areas. Case study: the June 1985 flood on the Miletin River, 16th International Conference on Environmental Science and Technology, Rhodes, 2019.
    57. Chen, Y.-M., C.-H. Liu, H.-J. Shih, C.-H. Chang, W.-B. Chen, Y.-C. Yu, W.-R. Su, and L.-Y. Lin, An operational forecasting system for flash floods in mountainous areas in Taiwan, Water, 11, 2100, doi:10.3390/w11102100, 2019.
    58. Shustikova, I., A. Domeneghetti, J. C. Neal, P. Bates, and A. Castellarin, Comparing 2D capabilities of HEC-RAS and LISFLOOD-FP on complex topography, Hydrological Sciences Journal, 64(14), 1769-1782, doi:10.1080/02626667.2019.1671982, 2019.
    59. Papaioannou, G., G. Varlas, G. Terti, A. Papadopoulos, A. Loukas, Y. Panagopoulos, and E. Dimitriou, Flood inundation mapping at ungauged basins using coupled hydrometeorological-hydraulic modelling: The catastrophic case of the 2006 flash flood in Volos City, Greece, Water, 11, 2328, doi:10.3390/w11112328, 2019.
    60. Liu, W.-C., and H.-M. Liu, Integrating hydrodynamic model and Monte Carlo simulation for predicting extreme water levels in a river system, Terrestrial, Atmospheric & Oceanic Sciences, 30(4), 589-604, doi:10.3319/TAO.2019.01.18.01, 2019.
    61. Costabile, P., C. Costanzo, G. De Lorenzo, and F. Macchione, Is local flood hazard assessment in urban areas significantly influenced by the physical complexity of the hydrodynamic inundation model?, Journal of Hydrology, 580, 124231, doi:10.1016/j.jhydrol.2019.124231, 2020.
    62. Stephens, T. A., and B. P. Bledsoe, Probabilistic mapping of flood hazards: depicting uncertainty in streamflow, land use, and geomorphic adjustment, Anthropocene, 29, 100231, doi:10.1016/j.ancene.2019.100231, 2020.
    63. Papaioannou, G., C. Papadaki, and E. Dimitriou, Sensitivity of habitat hydraulic model outputs to DTM and computational mesh resolution, Ecohydrology, 13(2), e2182, doi:10.1002/eco.2182, 2020.
    64. Saksena, S., S. Dey, V. Merwade, and P. J. Singhofen, A computationally efficient and physically based approach for urban flood modeling using a flexible spatiotemporal structure, Water Resources Research, 56(1), e2019WR025769, doi:10.1029/2019WR025769, 2020.
    65. Annis, A., F. Nardi, E. Volpi, and A. Fiori, Quantifying the relative impact of hydrological and hydraulic modelling parameterizations on uncertainty of inundation maps, Hydrological Sciences Journal, 65(4), 507-523, doi:10.1080/02626667.2019.1709640, 2020.
    66. Syafri, R. R., M. P. Hadi, and S. Suprayogi, Hydrodynamic modelling of Juwana river flooding using HEC-RAS 2D, IOP Conference Series Earth and Environmental Science, 412, 012028, doi:10.1088/1755-1315/412/1/012028, 2020.
    67. Gergeľová, M. B., Ž. Kuzevičová, S. Labant, J. Gašinec, S. Kuzevič, J. Unucka, and P. Liptai, Evaluation of selected sub-elements of spatial data quality on 3D flood event modeling: Case study of Prešov City, Slovakia, Applied Sciences, 10(3), 820, doi:10.3390/app10030820, 2020.
    68. Shaw, J., G. Kesserwani, and P. Pettersson, Probabilistic Godunov-type hydrodynamic modelling under multiple uncertainties: robust wavelet-based formulations, Advances in Water Resources, 137, 103526, doi:10.1016/j.advwatres.2020.103526, 2020.
    69. Li, X., C. Huang, Y. Zhang, J. Pang, and Y. Ma, Hydrological reconstruction of extreme palaeoflood events 9000–8500 a BP in the Danjiang River Valley, tributary of the Danjiangkou Reservoir, China, Arabian Journal of Geosciences, 13, 137, doi:10.1007/s12517-020-5132-3, 2020.
    70. Lousada, S., and L. Loures, Modelling torrential rain flows in urban territories: floods - natural channels (the case study of Madeira island), American Journal of Water Science and Engineering, 6(1), 17-30, doi:10.11648/j.ajwse.20200601.13, 2020.
    71. Pariartha, G., A. Goonetilleke, P. Egodawatta, and H. Mirfenderesk, The prediction of flood damage in coastal urban areas, IOP Conference Series Earth and Environmental Science, 419, 012136, doi:10.1088/1755-1315/419/1/012136, 2020.
    72. Lousada, S., Estudos hidráulicos e a sua influência no planeamento urbano regional: Aplicação prática às Ribeiras do Funchal – Portugal, Revista Americana de Empreendedorismo e Inovação, 2(2), 7-21, 2020.
    73. Gan, B.-R., X.-G. Yang, H.-M. Liao, and J.-W. Zhou, Flood routing process and high dam interception of natural discharge from the 2018 Baige landslide-dammed lake, Water, 12(2), 605, doi:10.3390/w12020605, 2020.
    74. Bellos, V., I. Papageorgaki, I. Kourtis, H. Vangelis, and G. Tsakiris, Reconstruction of a flash flood event using a 2D hydrodynamic model under spatial and temporal variability of storm, Natural Hazards, 101, 711-726, doi:10.1007/s11069-020-03891-3, 2020.
    75. Yalcin, E., Assessing the impact of topography and land cover data resolutions on two-dimensional HEC-RAS hydrodynamic model simulations for urban flood hazard analysis, Natural Hazards, 101, 995-1017, doi:10.1007/s11069-020-03906-z, 2020.
    76. Mateo-Lázaro, J., J. Castillo-Mateo, A. García-Gil, J. A. Sánchez-Navarro, V. Fuertes-Rodríguez, V. Edo-Romero, Comparative hydrodynamic analysis by using two−dimensional models and application to a new bridge, Water, 12(4), 997; doi:10.3390/w12040997, 2020.
    77. Albu, L.-M., A. Enea, M. Iosub, and I.-G. Breabăn, Dam breach size comparison for flood simulations. A HEC-RAS based, GIS approach for Drăcșani lake, Sitna river, Romania, Water, 12(4), 1090, doi:10.3390/w12041090, 2020.
    78. Pal, S., S. Talukdar, and R. Ghosh, Damming effect on habitat quality of riparian corridor, Ecological Indicators, 114, 106300, doi:10.1016/j.ecolind.2020.106300, 2020.
    79. Sarchani, S. K. Seiradakis, P. Coulibaly, and I. Tsanis, Flood inundation mapping in an ungauged basin, Water, 12(6), 1532, doi:10.3390/w12061532, 2020.
    80. Huţanu, E., A. Mihu-Pintilie, A. Urzica, L. E. Paveluc, C. C. Stoleriu, and A. Grozavu, Using 1D HEC-RAS modeling and LiDAR data to improve flood hazard maps’ accuracy: A case study from Jijia floodplain (NE Romania), Water, 12(6), 1624, doi:10.3390/w12061624, 2020.
    81. Fleischmann, A. S., R. C. D. Paiva, W. Collischonn, V. A. Siqueira, A. Paris, D. M. Moreira, F. Papa, A. A. Bitar, M. Parrens, F. Aires, and P. A. Garambois, Trade‐offs between 1D and 2D regional river hydrodynamic models, Water Resources Research, 56(8), e2019WR026812, doi:10.1029/2019WR026812, 2020.
    82. Gralepois, M., What can we learn from planning instruments in flood prevention? Comparative illustration to highlight the challenges of governance in Europe, Water, 12(6), 1841, doi:10.3390/w12061841, 2020.
    83. Rampinelli, C. G., I. Knack, and T. Smith, Flood mapping uncertainty from a restoration perspective: a practical case study, Water, 12(7), 1948, doi:10.3390/w12071948, 2020.
    84. Kalinina, A., M. Spada, D. F. Vetsch, S. Marelli, C. Whealton, P. Burgherr, and B. Sudret, Metamodeling for uncertainty quantification of a flood wave model for concrete dam breaks, Energies, 13(14), 3685, doi:10.3390/en13143685, 2020.
    85. Kitsikoudis, V., B. P. J., Becker, Y. Huismans, P. Archambeau, S. Erpicum, M. Pirotton, and B. Dewals, Discrepancies in flood modelling approaches in transboundary river systems: Legacy of the past or well-grounded choices?, Water Resources Management, 34, 3465-3478, doi:10.1007/s11269-020-02621-5, 2020.
    86. Piacentini, T., C. Carabella, F. Boccabella, S. Ferrante, C. Gregori, V. Mancinelli, A. Pacione, T. Pagliani, and E. Miccadei, Geomorphology-based analysis of flood critical areas in small hilly catchments for civil protection purposes and early warning systems: The case of the Feltrino stream and the Lanciano urban area (Abruzzo, Central Italy), Water, 12(8), 2228, doi:10.3390/w12082228, 2020.
    87. Arseni, M., A. Rosu, M. Calmuc, V. A. Calmuc, C. Iticescu, and L. P. Georgescu, Development of flood risk and hazard maps for the lower course of the Siret river, Romania, Sustainability, 12(16), 6588, doi:10.3390/su12166588, 2020.
    88. Ahmed, M. I., A. Elshorbagy, and A. Pietroniro, A novel model for storage dynamics simulation and inundation mapping in the Prairies, Environmental Modelling & Software, 133, 104850, doi:10.1016/j.envsoft.2020.104850, 2020.
    89. Bellos, V., V. K. Tsakiris, G. Kopsiaftis, and G. Tsakiris, Propagating dam breach parametric uncertainty in a river reach using the HEC-RAS software, Hydrology, 7(4), 72, doi:10.3390/hydrology7040072, 2020.
    90. Demir, V., and A. Ü. Keskin, Obtaining the Manning roughness with terrestrial-remote sensing technique and flood modeling using FLO-2D: A case study Samsun from Turkey, Geofizika, 37, 131-156, doi:10.15233/gfz.2020.37.9, 2020.
    91. Petroselli, A., J. Florek, D. Młyński, L. Książek, and A. Wałęga, New insights on flood mapping procedure: Two case studies in Poland, Sustainability, 12(20), 8454, doi:10.3390/su12208454, 2020.
    92. Beden, N., and A. Ulke Keskin, Flood map production and evaluation of flood risks in situations of insufficient flow data, Natural Hazards, 105, 2381-2408, doi:10.1007/s11069-020-04404-y, 2020.
    93. #Malakeel G. S., K. U. Abdu Rahiman, and S. Vishnudas, Flood risk assessment methods – A review, in: Thomas J., Jayalekshmi B., Nagarajan P. (eds), Current Trends in Civil Engineering. Lecture Notes in Civil Engineering, Vol. 104, Springer, Singapore, doi:10.1007/978-981-15-8151-9_19, 2021.
    94. Musiyam, M., J. Jumadi, Y. A. Wibowo, W. Widiyatmoko, and S. H. Nur Hafida, Analysis of flood-affected areas due to extreme weather in Pacitan, Indonesia, International Journal of GEOMATE, 19(75), 27-34, doi:10.21660/2020.75.25688, 2020.
    95. Ghimire, E., S. Sharma, and N. Lamichhane, Evaluation of one-dimensional and two-dimensional HEC-RAS models to predict flood travel time and inundation area for flood warning system, ISH Journal of Hydraulic Engineering, doi:10.1080/09715010.2020.1824621, 2020.
    96. Lin, X., G. Huang, J. M. Piwowar, X. Zhou, and Y. Zhai, Risk of hydrological failure under the compound effects of instant flow and precipitation peaks under climate change: a case study of Mountain Island Dam, North Carolina, Journal of Cleaner Production, 284, 125305, doi:10.1016/j.jclepro.2020.125305, 2021.
    97. Daksiya, V., P. V. Mandapaka, and E. Y. M. Lo, Effect of climate change and urbanisation on flood protection decision‐making, Journal of Flood Risk Management, 14(1), e12681, doi:10.1111/jfr3.12681, 2021.
    98. Urzică, A., A. Mihu-Pintilie, C. C. Stoleriu, C. I. Cîmpianu, E. Huţanu, C. I. Pricop, and A. Grozavu, Using 2D HEC-RAS modeling and embankment dam break scenario for assessing the flood control capacity of a multi-reservoir system (NE Romania), Water, 13(1), 57, doi:10.3390/w13010057, 2021.
    99. Elhag, M., and N. Yilmaz, Insights of remote sensing data to surmount rainfall/runoff data limitations of the downstream catchment of Pineios River, Greece, Environmental Earth Sciences, 80, 35, doi:10.1007/s12665-020-09289-5, 2021.
    100. Hdeib, R., R. Moussa, F. Colin, and C. Abdallah, A new cost-performance grid to compare different flood modelling approaches, Hydrological Sciences Journal, 66(3), 434-449, doi:10.1080/02626667.2021.1873346, 2021.
    101. Sharma, V. C., and S. K. Regonda, Two-dimensional flood inundation modeling in the Godavari river basin, India – Insights on model output uncertainty, Water, 13(2), 191, doi:10.3390/w13020191, 2021.
    102. Santos, E. D. S., H. S. K. Pinheiro, and H. G. Junior, Height above the nearest drainage to predict flooding areas in São Luiz do Paraitinga, São Paulo, Floresta e Ambiente, 28(2), doi:10.1590/2179-8087-floram-2020-0070, 2021.
    103. Chang, T.-Y., H. Chen, H.-S. Fu, W.-B. Chen, Y.-C. Yu, W.-R. Su, and L.-Y. Lin, An operational high-performance forecasting system for city-scale pluvial flash floods in the southwestern plain areas of Taiwan, Water, 13(4), 405, doi:10.3390/w13040405, 2021.
    104. Naeem, B., M. Azmat, H. Tao, S. Ahmad, M. U. Khattak, S. Haider, S. Ahmad, Z. Khero, and C. R. Goodell, Flood hazard assessment for the Tori levee breach of the Indus river basin, Pakistan, Water; 13(5), 604, doi:10.3390/w13050604, 2021.
    105. Zhu, Y., X. Niu, C. Gu, B. Dai, and L. Huang, A fuzzy clustering logic life loss risk evaluation model for dam-break floods, Complexity, 2021, 7093256, doi:10.1155/2021/7093256, 2021.
    106. #Malakeel, G. S., K. U.Abdu Rahiman, and S. Vishnudas, Flood risk assessment methods—A review, In: Thomas J., Jayalekshmi B., Nagarajan P. (eds), Current Trends in Civil Engineering, Lecture Notes in Civil Engineering, Vol. 104. Springer, Singapore, doi:10.1007/978-981-15-8151-9_19, 2021, 2021.
    107. Liu, W.-C., T.-H. Hsieh, and H.-M. Liu, Flood risk assessment in urban areas of southern Taiwan, Sustainability, 13(6), 3180, doi:10.3390/su13063180, 2021.
    108. Kumar, S., A. Agarwal, V. G. K. Villuri, S. Pasupuleti, D. Kumar, D. R. Kaushal, A. K. Gosain, A. Bronstert, and B. Sivakumar, Constructed wetland management in urban catchments for mitigating floods, Stochastic Environmental Research and Risk Assessment, 35, 2105-2124, doi:10.1007/s00477-021-02004-1, 2021.
    109. Mourato, S., P. Fernandez, F. Marques, A. Rocha, and L. Pereira, An interactive Web-GIS fluvial flood forecast and alert system in operation in Portugal, International Journal of Disaster Risk Reduction, 58, 102201, doi:10.1016/j.ijdrr.2021.102201, 2021.
    110. Dubey, A. K., P. Kumar, V. Chembolu, S. Dutta, R. P. Singh, and A. S. Rajawata, Flood modeling of a large transboundary river using WRF-Hydro and microwave remote sensing, Journal of Hydrology, 598, 126391, doi:10.1016/j.jhydrol.2021.126391, 2021.
    111. de Arruda Gomes, M. M., L. F. de Melo Verçosa, and J. A. Cirilo, Hydrologic models coupled with 2D hydrodynamic model for high-resolution urban flood simulation, Natural Hazards, 108, 3121-3157, doi:10.1007/s11069-021-04817-3, 2021.
    112. Gao, P., W. Gao, and N. Ke, Assessing the impact of flood inundation dynamics on an urban environment, Natural Hazards, 109, 1047-1072, doi:10.1007/s11069-021-04868-6, 2021.
    113. Zhang, X., T. Wang, and B. Duan, Study on the effect of morphological changes of bridge piers on water movement properties, Water Practice and Technology, 16(4), 1421-1433, doi:10.2166/wpt.2021.08, 2021.
    114. Fadilah, S., Istiarto, and D. Legono, Investigation and modelling of the flood control system in the Aerotropolis of Yogyakarta International Airport, IOP Conference Series Materials Science and Engineering, 1173(1), 012015, doi:10.1088/1757-899X/1173/1/012015, 2021.
    115. Baran-Zgłobicka, B., D. Godziszewska, and W. Zgłobicki, The flash floods risk in the local spatial planning (case study: Lublin Upland, E. Poland), Resources, 10(2), 14, doi:10.3390/resources10020014, 2021.
    116. Liang, C.-Y., Y.-H. Wang, G. J.-Y. You, P.-C. Chen, and E. Lo, Evaluating the cost of failure risk: A case study of the Kang-Wei-Kou stream diversion project, Water, 13(20), 2881, doi:10.3390/w13202881, 2021.
    117. Uciechowska-Grakowicz, A., and O. Herrera-Granados, Riverbed mapping with the usage of deterministic and geo-statistical interpolation methods: The Odra River case study, Remote Sensing, 13(21), 4236, doi:10.3390/rs13214236, 2021.
    118. Viquez, S. G., Mesurer le risque d’inondation en ville: Une modélisation sous contraintes, Terrains & Travaux, 38(1), 47-70, doi:10.3917/tt.038.0047, 2021.
    119. Singh G., V. B. S. Chandel, and S. Kahlon, Flood hazard modelling in Upper Mandakini Basin of Uttarakhand, Current World Environment, 16(3), 880-889, doi:10.12944/CWE.16.3.18, 2021.
    120. Liu, J., J. Wang, J. Xiong, W. Cheng, Y. Li, Y. Cao, Y. He, Y. Duan, W. He, and G. Yang, Assessment of flood susceptibility mapping using support vector machine, logistic regression and their ensemble techniques in the Belt and Road region, Geocarto International, doi:10.1080/10106049.2022.2025918, 2022.
    121. Yang, S. Y., C. H. Chang, C. T. Hsu, and S. J. Wu, Variation of uncertainty of drainage density in flood hazard mapping assessment with coupled 1D–2D hydrodynamics model, Natural Hazards, 111, 2297-2315, doi:10.1007/s11069-021-05138-1, 2022.
    122. Yoshida, K., S. Pan, J. Taniguchi, S. Nishiyama, T. Kojima, and T. Islam, Airborne LiDAR-assisted deep learning methodology for riparian land cover classification using aerial photographs and its application for flood modelling, Journal of Hydroinformatics, 24(1), 179-201, doi:10.2166/hydro.2022.134, 2022.
    123. Kasprak, A., P. R. Jackson, E. M. Lindroth, J. W. Lund, and J. R. Ziegeweid, The role of hydraulic and geomorphic complexity in predicting invasive carp spawning potential: St. Croix River, Minnesota and Wisconsin, United States, PLoS ONE, 17(2), e026305, doi:10.1371/journal.pone.0263052, 2022.
    124. Worley, L. C., K. L. Underwood, N. L. V. Vartanian, M. M. Dewoolkar, J. E. Matt, and D. M. Rizzo, Semi‐automated hydraulic model wrapper to support stakeholder evaluation: A floodplain reconnection study using 2D hydrologic engineering center's river analysis system, River Research and Applications, 38(4), 799-809, doi:10.1002/rra.3946, 2022.
    125. Jiang, W., and J. Yu, Impact of rainstorm patterns on the urban flood process superimposed by flash floods and urban waterlogging based on a coupled hydrologic–hydraulic model: a case study in a coastal mountainous river basin within southeastern China, Natural Hazards, 112, 301-326, doi:10.1007/s11069-021-05182-x, 2022.
    126. Mattos, T. S., P. T. S. Oliveira, L. de Souza Bruno, G. A. Carvalho, R. B. Pereira, L. L. Crivellaro, M. C. Lucas, and T. Roy, Towards reducing flood risk disasters in a tropical urban basin by the development of flood alert web application, Environmental Modelling & Software, 151, 105367, doi:10.1016/j.envsoft.2022.105367, 2022.
    127. Papaioannou, G., V. Markogianni, A. Loukas, and E. Dimitriou, Remote sensing methodology for roughness estimation in ungauged streams for different hydraulic/hydrodynamic modeling approaches, Water, 14(7), 1076, doi:10.3390/w14071076, 2022.
    128. Mishra, A., S. Mukherjee, B. Merz, V. P. Singh, D. B. Wright, G. Villarini, S. Paul, D. N. Kumar, C. P. Khedun, D. Niyogi, G. Schumann, and J. R. Stedinger, An overview of flood concepts, challenges, and future directions, Journal of Hydrologic Engineering, 27(6), doi:10.1061/(ASCE)HE.1943-5584.0002164, 2022.
    129. Cea, L., and P. Costabile, Flood risk in urban areas: modelling, management and adaptation to climate change. A review, Hydrology, 9(3), 50, doi:10.3390/hydrology9030050, 2022.
    130. #Karmakar, S., M. A. Sherly, and M. Mohanty, Urban flood risk mapping: A state-of-the-art review on quantification, current practices, and future challenges, Advances in Urban Design and Engineering. Design Science and Innovation, Banerji, P., Jana, A. (eds.), 125-156, Springer, Singapore, doi:10.1007/978-981-19-0412-7_5, 2022.
    131. Kadir, M. A. A., M. R. R. M. A. Zainol, P. Luo, M. Kaamin, and S. N. H. S. Yahya, Advance flood inundation model toward flood nowcasting: A review, International Journal of Nanoelectronics and Materials, 15, 81-100, 2022.
    132. Tegos, A., A. Ziogas, V. Bellos, and A. Tzimas, Forensic hydrology: a complete reconstruction of an extreme flood event in data-scarce area, Hydrology, 9(5), 93, doi:10.3390/hydrology9050093, 2022.
    133. Stephens, T., and B. Bledsoe, Simplified uncertainty bounding: an approach for estimating flood hazard uncertainty, Water, 14(10), 1618, doi:10.3390/w14101618, 2022.
    134. Iroume, J.Y.-A., R. Onguéné, F. Djanna Koffi, A. Colmet-Daage, T. Stieglitz, W. Essoh Sone, S. Bogning, J. M. Olinga Olinga, R. Ntchantcho, J.-C. Ntonga, J.-J. Braun, J.-P. Briquet, and J. Etame, The 21st August 2020 flood in Douala (Cameroon): A major urban flood investigated with 2D HEC-RAS modeling, Water, 14(11), 1768, doi:10.3390/w14111768, 2022.
    135. Jiang, W., J. Yu, Q. Wang, and Q. Yue, Understanding the effects of digital elevation model resolution and building treatment for urban flood modelling, Journal of Hydrology: Regional Studies, 42, 101122, doi:10.1016/j.ejrh.2022.101122, 2022.
    136. Singh, G., V. B. S. Chandel, and S. Kahlon, Flood hazard modelling in Upper Mandakini Basin of Uttarakhand, Current World Environment, 16(3), 880-889, doi:10.12944/CWE.16.3.18, 2022.
    137. Li, Y., D. B. Wright, and Y. Liu, Flood-induced geomorphic change of floodplain extent and depth: A case study of Hurricane Maria in Puerto Rico, Journal of Hydrologic Engineering, 27(10), doi:10.1061/(ASCE)HE.1943-5584.0002199, 2022.
    138. Iroume, J. Y.-A., R. Onguéné, F. Djanna Koffi, A. Colmet-Daage, T. Stieglitz, W. Essoh Sone, S. Bogning, J. M. Olinga Olinga, R. Ntchantcho, J.-C. Ntonga, J.-J. Braun, J.-P. Briquet, and J. Etame, The 21st August 2020 flood in Douala (Cameroon): A major urban flood investigated with 2D HEC-RAS modeling, Water, 14(11), 1768, doi:10.3390/w14111768, 2022.
    139. Ahmad, N. S., and N. A. Ahmad, Propose design of new cross section by using one dimensional HEC-RAS at Maran River, Pahang, Journal of Advancement in Environmental Solution and Resource Recovery, 2(1), 51-59, 2022.
    140. de Sousa, M. M., A. K. Beleño de Oliveira, O. M. Rezende, P. M. Canedo de Magalhães, A. C. Pitzer Jacob, P. C. de Magalhães, and M. G. Miguez, Highlighting the role of the model user and physical interpretation in urban flooding simulation, Journal of Hydroinformatics, 24(5), 976-991, doi:10.2166/hydro.2022.174, 2022.
    141. Kaya, Ç. M., Taşkın Duyarlılık Haritalarının Oluşturulmasında Kullanılan Yöntemler, Turkish Journal of Remote Sensing and GIS, 3(2), 191-209, doi:10.48123/rsgis.1129606, 2022.
    142. Li, Y., D. B. Wright, and Y. Liu, Flood-induced geomorphic change of floodplain extent and depth: a case study of hurricane Maria in Puerto Rico, Journal of Hydrologic Engineering, 27(10), doi:10.1061/(ASCE)HE.1943-5584.0002199, 2022.
    143. Wibowo, Y. A., M. A. Marfai, M. P. Hadi, H. Fatchurohman, L. Ronggowulan and D. A. Arif, Geospatial technology for flood hazard analysis in Comal Watershed, Central Java, Indonesia, IOP Conference Series: Earth and Environmental Science, 1039, 012027, 2022.
    144. Godwin, E., I. Kabenge, A. Gidudu, Y. Bamutaze, and A. Egeru, Differentiated spatial-temporal flood vulnerability and risk assessment in lowland plains in Eastern Uganda, Hydrology, 9(11), 201, doi:10.3390/hydrology9110201, 2022.
    145. Zhou, Y., Z. Wu, H. Xu, and H. Wang, Prediction and early warning method of inundation process at waterlogging points based on Bayesian model average and data-driven, Journal of Hydrology: Regional Studies, 44, 101248, doi:10.1016/j.ejrh.2022.101248, 2022.
    146. de Sousa, M. M., Ο. Μ. Rezende, A. C. P. Jacob, L. B. de França Ribeiro, P. M. C. de Magalhães, G. Maquera, and M. G. Miguez, Flood risk assessment index for urban mobility with the aid of quasi-2D flood model applied to an industrial park in São Paulo, Brazil, Infrastructures, 7(11), 158, doi:10.3390/infrastructures7110158, 2022.
    147. Otmani, A., A. Hazzab, M. Atallah, C. Apollonio, and A. Petroselli, Using volunteered geographic information data for flood mapping – Wadi Deffa El Bayadh Algeria, Journal of Applied Water Engineering and Research, doi:10.1080/23249676.2022.2155716, 2022.
    148. PhamVan, C., and H. Le, Estimation of the daily flow in river basins using the data-driven model and traditional approaches: an application in the Hieu river basin, Vietnam, Water Practice and Technology, 18(1), 215-230, doi:10.2166/wpt.2022.166, 2023.
    149. Worley, L. C., K. L. Underwood, R. M. Diehl, J. E. Matt, K.S. Lawson, R. M. Seigel, and D. M. Rizzo, Balancing multiple stakeholder objectives for floodplain reconnection and wetland restoration, Journal of Environmental Management, 326(A), 116648, doi:10.1016/j.jenvman.2022.116648, 2023.
    150. Xu, K., C. Wang, and L. Bin, Compound flood models in coastal areas: a review of methods and uncertainty analysis, Natural Hazards, 116, 469-496, doi:10.1007/s11069-022-05683-3, 2023.
    151. Daniel, W. B., C. Roth, X. Li, C. Rakowski, T. McPherson, and D. Judi, Extremely rapid, Lagrangian modeling of 2D flooding: A rivulet-based approach, Environmental Modelling & Software, 161, 105630, doi:10.1016/j.envsoft.2023.105630, 2023.
    152. Guirro, M. O., and G. P. Michel, Hydrological and hydrodynamic reconstruction of a flood event in a poorly monitored basin: a case study in the Rolante River, Brazil, Natural Hazards, doi:10.1007/s11069-023-05879-1, 2023.
    153. Kohanpur, A. H., S. Saksena, S. Dey, J. M. Johnson, M. S. Riasi, L. Yeghiazarian, and A. M. Tartakovsky, Urban flood modeling: Uncertainty quantification and physics-informed Gaussian processes regression forecasting, Water Resources Research, 59(3), e2022WR033939, doi:10.1029/2022WR033939, 2023.
    154. Rodas, M., L. Timbe, and L. Campozano, Sensibilidad del coeficiente de Manning en la estimación de los niveles de crecida para el mapeo de inundaciones en un río de la región interandina de Ecuador, Cuadernos de Geografía Revista Colombiana de Geografía, 32(1), doi:10.15446/rcdg.v32n1.94764, 2023.
    155. Wu, S., and Y. Lei, Multiscale flood disaster risk assessment in the Lancang-Mekong river basin: A focus on watershed and community levels, Atmosphere, 14(4), 657, doi:10.3390/atmos14040657, 2023.
    156. Viseh, H., and D. N. Bristow, Residential flood risk in metro Vancouver due to climate change using probability boxes, International Journal of River Basin Management, doi:10.1080/15715124.2023.2200006, 2023.
    157. Moghim, S., M. A. Gharehtoragh, and A. Safaie, Performance of the flood models in different topographies, Journal of Hydrology, 620(A), 129446, doi:10.1016/j.jhydrol.2023.129446, 2023.
    158. Makris, C., Z. Mallios, Y. Androulidakis, and Y. Krestenitis, CoastFLOOD: A high-resolution model for the simulation of coastal inundation due to storm surges, Hydrology, 10(5), 103, doi:10.3390/hydrology10050103, 2023.
    159. Tarpanelli, A., B. Bonaccorsi, M. Sinagra, A. Domeneghetti, L. Brocca, and S. Barbetta, Flooding in the digital twin Earth: The case study of the Enza River levee breach in December 2017, Water, 15(9), 1644, doi:10.3390/w15091644, 2023.
    160. Xafoulis, N., Y. Kontos, E. Farsirotou, S. Kotsopoulos, K. Perifanos, N. Alamanis, D. Dedousis, and K. Katsifarakis, Evaluation of various resolution DEMs in flood risk assessment and practical rules for flood mapping in data-scarce geospatial areas: A case study in Thessaly, Greece, Hydrology, 10(4), 91, doi:10.3390/hydrology10040091, 2023.
    161. da Silva, A. A. C. L., and J. C. Eleutério, Identifying and testing the probability distribution of earthfill dam breach parameters for probabilistic dam breach modeling, Journal of Flood Risk Management, 16(3), e12900, doi:10.1111/jfr3.12900, 2023.
    162. Hajihassanpour, M., G. Kesserwani, P. Pettersson, and V. Bellos, Sampling-based methods for uncertainty propagation in flood modeling under multiple uncertain inputs: Finding out the most efficient choice, Water Resources Research, 59(7), e2022WR034011, doi:10.1029/2022WR034011, 2023.
    163. Biswal, S., B. Sahoo, M. K. Jha, and M. K. Bhuyan, A hybrid machine learning-based multi-dem ensemble model of river cross-section extraction: Implications on streamflow routing, Journal of Hydrology, 625(A), 129951, doi:10.1016/j.jhydrol.2023.129951, 2023.
    164. Wienhold, K. J., D. Li, W. Li, and Z. N. Fang, Flood inundation and depth mapping using unmanned aerial vehicles combined with high-resolution multispectral imagery, Hydrology, 10(8), 158, doi:10.3390/hydrology10080158, 2023.
    165. Aryal, A., and A. Kalra, Application of NEXRAD precipitation data for assessing the implications of low development practices in an ungauged basin, River, doi:10.1002/rvr2.55, 2023.
    166. Bryant, S., H. Kreibich, and B. Merz, Bias in flood hazard grid aggregation, Water Resources Research, 59(9), e2023WR035100, doi:10.1029/2023WR035100, 2023.
    167. Wang, W., G. Sang, Q. Zhao, and L. Lu, Water level prediction of pumping station pre-station based on machine learning methods, Water Supply, 23(10), 4092-4111, doi:10.2166/ws.2023.242, 2023.
    168. Moraru, A., N. Rüther, and O. Bruland, Investigating optimal 2D hydrodynamic modeling of a recent flash flood in a steep Norwegian river using high-performance computing, Journal of Hydroinformatics, 25(5), 1690-1712, doi:10.2166/hydro.2023.012, 2023.
    169. Dasari, I., and V. K. Vema, Assessment of the structural uncertainty of hydrological models and its impact on flood inundation mapping, Hydrological Sciences Journal, 68(16), 2404-2421, doi:10.1080/02626667.2023.2271456, 2023.
    170. Rojpratak, S., and S. Supharatid, Regional-scale flood impacts on a small mountainous catchment in Thailand under a changing climate, Journal of Water and Climate Change, jwc2023527, doi:10.2166/wcc.2023.527, 2023.
    171. Abbas, Z., M. Akhtar, S. Akram, S. Hafeez, and S. R. Ahmad, Flood inundation modeling and damage assessment in Lahore using remote sensing, International Journal of Innovations in Science & Technology, 5(4), 638-647, 2023.
    172. Almeida, I. M., H. A. Santos, O. de Vasconcelos Costa, and V. B. Graciano, Uncertainty reduction in flood areas by probabilistic analyses of land use/cover in models of two-dimensional hydrodynamic model of dam-break, Stochastic Environmental Research and Risk Assessment, doi:10.1007/s00477-023-02635-6, 2023.
    173. Stavi, I., S. Eldad, C. Xu, Z. Xu, Y. Gusarov, M. Haiman, and E. Argaman, Ancient agricultural terrace walls control floods and regulate the distribution of Asphodelus ramosus geophytes in the Israeli arid Negev, Catena, 234, 107588, doi:10.1016/j.catena.2023.107588, 2024.
    174. Tilav, E. S., and S. Gülbaz, Investigation of flooding due to dam failure: A case study of Darlık dam, Journal of Natural Hazards and Environment, 10(1), 49-67, doi:10.21324/dacd.1327805, 2024.
    175. Tunio, I. A., L. Kumar, S. A. Memon, A. A. Mahessar, A. W. Kandhir, Sediment transport dynamics during a super flood: A case study of the 2010 super flood at the Guddu Barrage on the Indus River, International Journal of Sediment Research, doi:10.1016/j.ijsrc.2024.03.002, 2024.
    176. Sajjad, A., J. Lu, X. Chen, S. Yousaf, N. Mazhar, and S. Shuja, Flood hazard assessment in Chenab River basin using hydraulic simulation modeling and remote sensing, Natural Hazards, doi:10.1007/s11069-024-06513-4, 2024.
    177. Ullah, A., S. Haider, and R. Farooq, Sensitivity analysis of a 2D flood inundation model. A case study of Tous Dam, Environmental Earth Sciences, 83, 213. doi:10.1007/s12665-024-11500-w, 2024.

  1. A. Tegos, A. Efstratiadis, N. Malamos, N. Mamassis, and D. Koutsoyiannis, Evaluation of a parametric approach for estimating potential evapotranspiration across different climates, Agriculture and Agricultural Science Procedia, 4, 2–9, doi:10.1016/j.aaspro.2015.03.002, 2015.

    Potential evapotranspiration (PET) is key input in water resources, agricultural and environmental modelling. For many decades, numerous approaches have been proposed for the consistent estimation of PET at several time scales of interest. The most recognized is the Penman-Monteith formula, which is yet difficult to apply in data-scarce areas, since it requires simultaneous observations of four meteorological variables (temperature, sunshine duration, humidity, wind velocity). For this reason, parsimonious models with minimum input data requirements are strongly preferred. Typically, these have been developed and tested for specific hydroclimatic conditions, but when they are applied in different regimes they provide much less reliable (and in some cases misleading) estimates. Therefore, it is essential to develop generic methods that remain parsimonious, in terms of input data and parameterization, yet they also allow for some kind of local adjustment of their parameters, through calibration. In this study we present a recent parametric formula, based on a simplified formulation of the original Penman-Monteith expression, which only requires mean daily or monthly temperature data. The method is evaluated using meteorological records from different areas worldwide, at both the daily and monthly time scales. The outcomes of this extended analysis are very encouraging, as indicated by the substantially high validation scores of the proposed approach across all examined data sets. In general, the parametric model outperforms well-established methods of the everyday practice, since it ensures optimal approximation of potential evapotranspiration.

    Full text: http://www.itia.ntua.gr/en/getfile/1549/1/documents/IRLA_paper.pdf (560 KB)

    See also: http://dx.doi.org/10.1016/j.aaspro.2015.03.002

    Works that cite this document: View on Google Scholar or ResearchGate

    Other works that reference this work (this list might be obsolete):

    1. Stan, F.I., G. Neculau, L. Zaharia, G. Ioana-Toroimac, and S. Mihalache, Study on the evaporation and evapotranspiration measured on the Căldăruşani Lake (Romania), Procedia Environmental Sciences, 32, 281–289, doi:10.1016/j.proenv.2016.03.033, 2016.
    2. Esquivel-Hernández, G., R. Sánchez-Murillo, C. Birkel, S. P. Good, and J. Boll, Hydro-climatic and ecohydrological resistance/resilience conditions across tropical biomes of Costa Rica, Ecohydrology, 10(6), e1860, doi:10.1002/eco.1860, 2017.
    3. Hodam, S., S. Sarkar, A.G.R. Marak, A. Bandyopadhyay, and A. Bhadra, Spatial interpolation of reference evapotranspiration in India: Comparison of IDW and Kriging methods, Journal of The Institution of Engineers (India): Series A, 98(4), 551-524, doi:10.1007/s40030-017-0241-z, 2017.
    4. Deng, H., and J. Shao, Evapotranspiration and humidity variations in response to land cover conversions in the Three Gorges Reservoir Region, Journal of Mountain Science, 15(3), 590-605, doi:10.1007/s11629-016-4272-0, 2018.
    5. Nadyozhina, E. D., I. M. Shkolnik, A. V. Sternzat, B. N. Egorov, and A. A. Pikaleva, Evaporation from irrigated lands in arid regions as inferred from the regional climate model and atmospheric boundary layer model simulations, Russian Meteorology and Hydrology, 43(6), 404-411, doi:10.3103/S1068373918060080, 2018.
    6. Bashir, R., F. Ahmad, and R. Beddoe, Effect of climate change on a monolithic desulphurized tailings cover, Water, 2(9), 2645, doi:10.3390/w12092645, 2020.
    7. Dimitriadou, S., and K. G. Nikolakopoulos, Evapotranspiration trends and interactions in light of the anthropogenic footprint and the climate crisis: A review, Hydrology, 8(4), 163, doi:10.3390/hydrology8040163, 2021.
    8. Dimitriadou, S., and K. G. Nikolakopoulos, Artificial neural networks for the prediction of the reference evapotranspiration of the Peloponnese Peninsula, Greece, Water, 14(13), 2027, doi:10.3390/w14132027, 2022.
    9. Yu, Z., H. Wang, B. Weng, S. Zhang, T. Qin, and D. Yan, Optimized pan evaporation by potential evapotranspiration for water inflow estimation in ungauged inland plain lake, China, Polish Journal of Environmental Studies, 31(6), 5427-5442, doi:10.15244/pjoes/151110, 2022.
    10. Kaissi, O., S. Belaqziz, M. H. Kharrou, S. Erraki, C. El Hachimi, A. Amazirh, and A. Chehbouni, Advanced learning models for estimating the spatio-temporal variability of reference evapotranspiration using in-situ and ERA5-Land reanalysis data, Modeling Earth Systems and Environment, doi:10.1007/s40808-023-01872-62023, 2023.
    11. Latrech, B., T. Hermassi, S. Yacoubi, A. Slatni, F. Jarray, L. Pouget, and M. A. Ben Abdallah, Comparative analysis of climate change impacts on climatic variables and reference evapotranspiration in Tunisian semi-arid region, Agriculture, 14(1), 160, doi:10.3390/agriculture14010160, 2024.

  1. A. Tegos, N. Malamos, and D. Koutsoyiannis, A parsimonious regional parametric evapotranspiration model based on a simplification of the Penman-Monteith formula, Journal of Hydrology, 524, 708–717, doi:10.1016/j.jhydrol.2015.03.024, 2015.

    Evapotranspiration is a key hydrometeorological process and its estimation is important in many fields of hydrological and agricultural sciences. Simplified estimation proves very useful in absence of a complete data set. In this respect, a parametric model based on simplification of the Penman-Monteith formulation is presented. The basic idea of the parametric model is the replacement of some of the variables and constants that are used in the standard Penman-Monteith model by regionally varying parameters, which are estimated through calibration. The model is implemented in various climates on monthly time step (USA, Germany, Spain) and compared on the same basis with four radiation-based methods (Jensen-Haise, McGuiness and Bordne, Hargreaves and Oudin) and two temperature-based (Thornthwaite and Blaney-Criddle). The methodology yields very good results with high efficiency indexes, outperforming the other models. Finally, a spatial analysis including the correlation of parameters with latitude and elevation together with their regionalization through three common spatial interpolation techniques along with a recent approach (Bilinear Surface Smoothing), is performed. Also, the model is validated against Penman-Monteith estimates in eleven stations of the well-known CIMIS network. The total framework which includes the development, the implementation, the comparison and the mapping of parameters illustrates a new parsimonious and high efficiency methodology in the assessment of potential evapotranspiration field.

    Additional material:

    See also: http://dx.doi.org/10.1016/j.jhydrol.2015.03.024

    Works that cite this document: View on Google Scholar or ResearchGate

    Other works that reference this work (this list might be obsolete):

    1. Hodam, S., S. Sarkar, A.G.R. Marak, A. Bandyopadhyay, and A. Bhadra, Spatial interpolation of reference evapotranspiration in India: Comparison of IDW and Kriging methods, Journal of The Institution of Engineers (India): Series A, 98(4), 551-524, doi:10.1007/s40030-017-0241-z, 2017.
    2. Deng, H., and J. Shao, Evapotranspiration and humidity variations in response to land cover conversions in the Three Gorges Reservoir Region, Journal of Mountain Science, 15(3), 590–605, doi:10.1007/s11629-016-4272-0, 2018.
    3. Giménez, P. O., and S. G. García-Galiano, Assessing Regional Climate Models (RCMs) ensemble-driven reference evapotranspiration over Spain, Water, 10(9), 1181, doi:10.3390/w10091181, 2018.
    4. Zhang, T., Y. Chen, and K. Tha Paw U, Quantifying the impact of climate variables on reference evapotranspiration in Pearl River Basin, China, Hydrological Sciences Journal, doi:10.1080/02626667.2019.1662021, 2019.

  1. A. Efstratiadis, A. Tegos, A. Varveris, and D. Koutsoyiannis, Assessment of environmental flows under limited data availability – Case study of the Acheloos River, Greece, Hydrological Sciences Journal, 59 (3-4), 731–750, doi:10.1080/02626667.2013.804625, 2014.

    The lower course of Acheloos River is an important hydrosystem of Greece, heavily modified by a cascade of four hydropower dams, which is now being extended by two more dams in the upper course. The design of the dams and hydropower facilities that are in operation has not considered any environmental criteria. However, in the last fifty years, numerous methodologies have been proposed to assess the negative impacts of such projects to both the abiotic and biotic environment, and to provide decision support towards establishing appropriate constraints on their operation, typically in terms of minimum flow requirements. In this study, seeking for a more environmental-friendly operation of the hydrosystem, we investigate the outflow policy from the most downstream dam, examining alternative environmental flow approaches. Accounting for data limitations, we recommend the Basic Flow Method, which is parsimonious and suitable for Mediterranean rivers, whose flows exhibit strong variability across seasons. We also show that the wetted perimeter – discharge method, which is an elementary hydraulic approach, provides consistent results, even without using any flow data. Finally, we examine the adaptation of the proposed flow policy (including artificial flooding) to the real-time hydropower generation schedule, and the management of the resulting conflicts.

    Additional material:

    See also: http://dx.doi.org/10.1080/02626667.2013.804625

    Works that cite this document: View on Google Scholar or ResearchGate

    Other works that reference this work (this list might be obsolete):

    1. Acreman, M. C., I. C. Overton, J. King, P. Wood, I. G. Cowx, M. J. Dunbar, E. Kendy, and W. Young, The changing role of ecohydrological science in guiding environmental flows, Hydrological Sciences Journal, 59(3–4), 1–18, 2014.
    2. #Egüen, M., M. J. Polo, Z. Gulliver, E. Contreras, C. Aguilar, and M. A. Losada, Flood risk trends in coastal watersheds in South Spain: direct and indirect impact of river regulation, Changes in Flood Risk and Perception in Catchments and Cities, Proc. IAHS, 370, 51-56, doi:10.5194/piahs-370-51-2015, 2015.
    3. Aguilar, C., and M. J. Polo, Assessing minimum environmental flows in nonpermanent rivers: The choice of thresholds, Environmental Modelling and Software, 79, 120-134, doi:10.1016/j.envsoft.2016.02.003, 2016.
    4. Nerantzaki, S. D., G. V. Giannakis, N. P. Nikolaidis, I. Zacharias, G. P. Karatzas, and I. A. Sibetheros, Assessing the impact of climate change on sediment loads in a large Mediterranean watershed, Soil Science, 181(7), 306-314, 2016.
    5. Poncelet, C., V. Andréassian, L. Oudin, and C. Perrin, The Quantile Solidarity approach for the parsimonious regionalization of flow duration curves, Hydrological Sciences Journal, 62(9), 1364-1380, doi:10.1080/02626667.2017.1335399, 2017.
    6. Tegos, M., I. Nalbantis, and A. Tegos, Environmental flow assessment through integrated approaches, European Water, 60, 167-173, 2017.
    7. Gemitzi, A., and V. Lakshmi, Evaluating renewable groundwater stress with GRACE data in Greece, Groundwater, 56(3), 501-514, doi:10.1111/gwat.12591, 2018.
    8. Theodoropoulos, C., N. Skoulikidis, P. Rutschmann, and A. Stamou, Ecosystem-based environmental flow assessment in a Greek regulated river with the use of 2D hydrodynamic habitat modelling, River Research and Applications, 34(6), 538-547, doi:10.1002/rra.3284, 2018.
    9. Zhao, C., S. Yang, J. Liu, C. Liu, F. Hao, Z. Wang, H. Zhang, J. Song, S. M. Mitrovic, and R. P. Lim, Linking fish tolerance to water quality criteria for the assessment of environmental flows: A practical method for streamflow regulation and pollution control, Water Research, 141, 96-108, doi:10.1016/j.watres.2018.05.025, 2018.
    10. Operacz, A., A. Wałęga, A. Cupak, and B. Tomaszewska, The comparison of environmental flow assessment - The barrier for investment in Poland or river protection? Journal of Cleaner Production, 193, 575-592, doi:10.1016/j.jclepro.2018.05.098, 2018.
    11. Książek, L., A. Woś, J. Florek, M. Wyrębek, D. Młyński, and A. Wałęga, Combined use of the hydraulic and hydrological methods to calculate the environmental flow: Wisloka river, Poland: case study, Environmental Monitoring and Assessment, 191:254, doi:10.1007/s10661-019-7402-7, 2019.
    12. Shinozaki, Y., and N. Shirakawa, Current state of environmental flow methodologies: objectives, methods and their approaches, Journal of Japan Society of Civil Engineers – Ser. B1 (Hydraulic Engineering), 75(1), 15-30, doi:10.2208/jscejhe.75.15, 2019.
    13. Kan, H., F. Hedenus, and L. Reichenberg, The cost of a future low-carbon electricity system without nuclear power – The case of Sweden, Energy, 195, 117015, doi:10.1016/j.energy.2020.117015, 2020.
    14. Aryal, S. K., Y. Zhang, and F. Chiew, Enhanced low flow prediction for water and environmental management, Journal of Hydrology, 584, 124658, doi:10.1016/j.jhydrol.2020.124658, 2020.
    15. #Ivanova, E., and D. Myronidis, Spatial interpolation approach for environmental flow assessment in Bulgarian-Greek Rhodope mountain range, Proceeding of the 9th International Conference on Information and Communication Technologies in Agriculture, Food & Environment (HAICTA 2020), 274-285, Thessaloniki, 2020.
    16. Moccia, D., L. Salvadori, S. Ferrari, A. Carucci, and A. Pusceddu, Implementation of the EU ecological flow policy in Italy with a focus on Sardinia, Advances in Oceanography and Limnology, 11(1), doi:10.4081/aiol.2020.8781, 2020.
    17. Koskinas, A., Stochastics and ecohydrology: A study in optimal reservoir design, Dams and Reservoirs, 30(2), 53-59, doi:10.1680/jdare.20.00009, 2020.
    18. Dash, S. S., D. R. Sena, U. Mandal, A. Kumar, G. Kumar, P. K. Mishra, and M. Rawat, A hydrological modelling-based approach for vulnerable area identification under changing climate scenarios, Journal of Water and Climate Change, 12(2), 433-452, doi:10.2166/wcc.2020.202, 2021.
    19. Senent-Aparicio, J., C. George, and R. Srinivasan, Introducing a new post-processing tool for the SWAT+ model to evaluate environmental flows, Environmental Modelling and Software, 136, 104944, doi:10.1016/j.envsoft.2020.104944, 2021.
    20. Operacz, A, Possibility of hydropower development: a simple-to-use index, Energies, 14(10), 2764, doi:10.3390/en14102764, 2021.
    21. Kan, X., L. Reichenberg, and F. Hedenus, The impacts of the electricity demand pattern on electricity system cost and the electricity supply mix: a comprehensive modeling analysis for Europe, Energy, 235, 121329, doi:10.1016/j.energy.2021.121329, 2021.
    22. Greco, M., F. Arbia, and R. Giampietro, Definition of ecological flow Using IHA and IARI as an operative procedure for water management, Environments, 8(8), 77, doi:10.3390/environments8080077, 2021.
    23. #Soulis, K., Hydrological data sources and analysis for the determination of environmental water requirements in mountainous areas, Environmental Water Requirements in Mountainous Areas, E. Dimitriou and C. Papadaki (editors), Chapter 2, 51-98, Elsevier, doi: 10.1016/B978-0-12-819342-6.00007-5, 2021.
    24. #Muñoz-Mas, R., and P. Vezza, Quantification of environmental water requirements; how far can we go?, Environmental Water Requirements in Mountainous Areas, E. Dimitriou and C. Papadaki (editors), Chapter 6, 235-280, Elsevier, doi:10.1016/B978-0-12-819342-6.00001-4, 2021.
    25. Zhang, X.-R., D.-R. Zhang, and Y. Ding, An environmental flow method applied in small and medium-sized mountainous rivers, Water Science and Engineering, 14(4), 323-329, doi:10.1016/j.wse.2021.10.003, 2021.
    26. Owusu, A., M. Mul, M. Strauch, P. van der Zaag, M. Volk, and J. Slinger, The clam and the dam: A Bayesian belief network approach to environmental flow assessment in a data scarce region, Science of The Total Environment, 810, 151315, doi:10.1016/j.scitotenv.2021.151315, 2022.
    27. Hoque, M. M., A. Islam, and S. Ghosh, Environmental flow in the context of dams and development with special reference to the Damodar Valley Project, India: a review, Sustainable Water Resources Management, 8, 62, doi:10.1007/s40899-022-00646-9, 2022.
    28. Kan, X., F. Hedenus, L. Reichenberg, and O. Hohmeye, Into a cooler future with electricity generated from solar photovoltaic, iScience, 25(5), 104208, doi:10.1016/j.isci.2022.104208, 2022.
    29. Colombera, L., and N. P. Mountney, Scale dependency in quantifications of the avulsion frequency of coastal rivers, Earth-Science Reviews, 230, 104043, doi:10.1016/j.earscirev.2022.104043, 2022.
    30. #Sharma, M., C. Prakasam, R. Saravanan, S. C. Attri, V. S. Kanwar, and M. K. Sharma, A review of environmental flow evaluation methodologies – Limitations and validations, Proceedings of International Conference on Innovative Technologies for Clean and Sustainable Development (ICITCSD – 2021), Kanwar, V.S., Sharma, S.K., Prakasam, C. (eds.), Springer, Cham, doi:10.1007/978-3-030-93936-6_63, 2022.
    31. Ivanova, E., and D. Myronidis, Application of an integrated methodology for spatial classification of the environmental flow in the Bulgarian-Greek Rhodope Mountain Range, International Journal of Sustainable Agricultural Management and Informatics, 8(1), 184-103, doi:10.1504/IJSAMI.2022.123045, 2022.
    32. Prakasam, C., and R. Saravanan, Ecological flow assessment using hydrological method and validation through GIS application, Groundwater for Sustainable Development, 19, 100841, doi:10.1016/j.gsd.2022.100841, 2022.
    33. Liu, S., Q. Zhang, Y. Xie, P. Xu, and H. Du, Evaluation of minimum and suitable ecological flows of an inland basin in China considering hydrological variation, Water, 15(4), 649, doi:10.3390/w15040649, 2023.
    34. Verma, R. K., A. Pandey, S. K. Mishra, and V. P. Singh, A procedure for assessment of environmental flows incorporating inter- and intra-annual variability in dam-regulated watersheds, Water Resources Management, 37, 3259-3297, doi:10.1007/s11269-023-03502-3, 2023.
    35. Chen, H., and Q. Li, Testing and applying baseflow approaches to environmental flow needs, Ecological Indicators, 152, 110363, doi:10.1016/j.ecolind.2023.110363, 2023.
    36. Leone, M., F. Gentile, A. Lo Porto, G. F. Ricci, and A. M. De Girolamo, Ecological flow in southern Europe: Status and trends in non-perennial rivers, Journal of Environmental Management, 342, 118097, doi:10.1016/j.jenvman.2023.118097, 2023.
    37. Castellanos-Osorio, G., A. López-Ballesteros, J. Pérez-Sánchez, and J. Senent-Aparicio, Disaggregated monthly SWAT+ model versus daily SWAT+ model for estimating environmental flows in Peninsular Spain, Journal of Hydrology, 129837, doi:10.1016/j.jhydrol.2023.129837, 2023.
    38. Aszódi, A., B. Biró, L. Adorján, A. C. Dobos, G. Illés, N. K. Tóth, D. Zagyi, and Z. T. Zsiborás, The effect of the future of nuclear energy on the decarbonization pathways and continuous supply of electricity in the European Union, Nuclear Engineering and Design, 415, 112688, doi:10.1016/j.nucengdes.2023.112688, 2023.
    39. Bianucci, P., A. Sordo-Ward, B. Lama-Pedrosa, and L. Garrote, How do environmental flows impact on water availability under climate change scenarios in European basins?, Science of The Total Environment, 911, 168566, doi:10.1016/j.scitotenv.2023.168566, 2024.
    40. Manikas, K. S. Skroufouta, and E. Baltas, Simulation and evaluation of pumped hydropower storage (PHPS) system at Kastraki reservoir, Renewable Energy, 222, 119888, doi:10.1016/j.renene.2023.119888, 2024.
    41. Sedghi-Asl, M., and S. J. Poursalehan, Modified ideal point method for estimating minimum environmental flow of rivers, Acta Geophysica, doi:10.1007/s11600-023-01264-5, 2024.
    42. Asadi, S., S. J. Mousavi, A. López-Ballesteros, and J. Senent-Aparicio, Analyzing hydrological alteration and environmental flows in a highly anthropized agricultural river basin system using SWAT+, WEAP and IAHRIS, Journal of Hydrology: Regional Studies, 52, 101738, doi:10.1016/j.ejrh.2024.101738, 2024.

  1. D. Koutsoyiannis, N. Mamassis, and A. Tegos, Logical and illogical exegeses of hydrometeorological phenomena in ancient Greece, Water Science and Technology: Water Supply, 7 (1), 13–22, 2007.

    Technological applications aiming at the exploitation of the natural sources appear in all ancient civilizations. The unique phenomenon in the ancient Greek civilization is that technological needs triggered physical explanations of natural phenomena, thus enabling the foundation of philosophy and science. Among these, the study of hydrometeorological phenomena had a major role. This study begins with the Ionian philosophers in the seventh century BC, continues in classical Athens in the fifth and fourth centuries BC, and advances and expands through the entire Greek world up to the end of Hellenistic period. Many of the theories developed by ancient Greeks are erroneous according to modern views. However, many elements in Greek exegeses of hydrometeorological processes, such as evaporation and condensation of vapour, creation of clouds, hail, snow and rainfall, and evolution of hydrological cycle, are impressive even today.

    Related works:

    • [32] Translation into Greek

    Additional material:

    See also: http://dx.doi.org/10.2166/ws.2007.002

    Works that cite this document: View on Google Scholar or ResearchGate

    Other works that reference this work (this list might be obsolete):

    1. Mays, L.W., A very brief history of hydraulic technology during antiquity, Environmental Fluid Mechanics, 8 (5-6), 471-484, 2008.
    2. Angelakis, A. N., and D. S. Spyridakis, A brief history of water supply and wastewater management in ancient Greece, Water Science and Technology: Water Supply, 10 (4), 618-628, 2010.
    3. #Angelakis, A. N., E. G. Dialynas and V. Despotakis, Evolution of water supply technologies through the centuries in Crete, Greece, Ch. 9 in Evolution of Water Supply Through the Millennia (A. N. Angelakis, L. W. Mays, D. Koutsoyiannis and N. Mamassis, eds.), 227-258, IWA Publishing, London, 2012.

Book chapters and fully evaluated conference publications

  1. P. Dimitriadis, A. Tegos, A. Petsiou, V. Pagana, I. Apostolopoulos, E. Vassilopoulos, M. Gini, A. D. Koussis, N. Mamassis, D. Koutsoyiannis, and P. Papanicolaou, Flood Directive implementation in Greece: Experiences and future improvements, 10th World Congress on Water Resources and Environment "Panta Rhei", Athens, European Water Resources Association, 2017.

    The implementation of the European Directive 2007/60 is a crucial step towards the development of a sophisticated flood management plan for the main River Basin Districts by including any necessary structural measures. For this reason, extensive hydrological and hydraulic analysis is needed under the ubiquitous uncertainty which cannot be eliminated by numerical models. In this study, we present our experience from the directive implementation and we discuss structural components of uncertainty in the flood modelling practice mostly related to the river network. We propose and review some of the most efficient engineering practices by examining issues like: (a) the consistency and accuracy of the required input data of the topography such as the Digital Elevation Model, cross-sectional measurements of the river and maps of land use; (b) the uncertainty components related to the hydrological SCS-CN framework and other hydrological methods for the determination of the input hydrograph; (c) the theoretical framework of each hydraulic model such as the scheme dimension (1d, 2d or coupled 1d/2d), the type of solution of the numerical scheme (explicit or implicit), the boundary conditions and the type of discretization (grid or sectionbased); (d) the uncertainty components related to the flood inundation modelling, such as the roughness coefficient at the river and floodplain; (e) the necessity of validation data such as the flow discharge, the flood inundation area, and the velocity measurements.

  1. N. Malamos, I. L. Tsirogiannis, A. Tegos, A. Efstratiadis, and D. Koutsoyiannis, Spatial interpolation of potential evapotranspiration for precision irrigation purposes, 10th World Congress on Water Resources and Environment "Panta Rhei", Athens, European Water Resources Association, 2017.

    Precision irrigation constitutes a breakthrough for agricultural water management since it provides means to optimal water use. In recent years several applications of precision irrigation are implemented based on spatial data from different origins, i.e. meteorological stations networks, remote sensing data and in situ measurements. One of the factors affecting optimal irrigation system design and management is the daily potential evapotranspiration (PET). A commonly used approach is to estimate the daily PET for the representative day of each month during the irrigation period. In the present study, the implementation of the recently introduced non-parametric bilinear surface smoothing (BSS) methodology for spatial interpolation of daily PET is presented. The study area was the plain of Arta which is located at the Region of Epirus at the North West Greece. Daily PET was estimated according to the FAO Penman-Monteith methodology with data collected from a network of six agrometeorological stations, installed in early 2015 in selected locations throughout the study area. For exploration purposes, we produced PET maps for the Julian dates: 105, 135, 162, 199, 229 and 259, thus covering the entire irrigation period of 2015. Also, comparison and cross validation against the calculated FAO Penman-Monteith PET for each station, were performed between BSS and a commonly used interpolation method, i.e. inverse distance weighted (IDW). During the leave-one-out cross validation procedure, BSS yielded very good results, outperforming IDW. Given the simplicity of the BSS, its overall performance is satisfactory, providing maps that represent the spatial and temporal variation of daily PET.

    Additional material:

    Other works that reference this work (this list might be obsolete):

    1. da Silva Júnior, J. C. , V. Medeiros, C. Garrozi, A. Montenegro, and G. E. Gonçalves, Random forest techniques for spatial interpolation of evapotranspiration data from Brazilian’s Northeast, Computers and Electronics in Agriculture, 166, 105017, doi:10.1016/j.compag.2019.105017, 2019.
    2. Haftcheshmeh, E. I., and F. Bansouleh, Spatial variation of reference evapotranspiration in Kermanshah province, Journal of Agricultural Meteorology, 9(2), 61-66, doi:10.22125/agmj.2021.262567.1106, 2021.

  1. A. Tegos, A. Efstratiadis, and D. Koutsoyiannis, A parametric model for potential evapotranspiration estimation based on a simplified formulation of the Penman-Monteith equation, Evapotranspiration - An Overview, edited by S. Alexandris, 143–165, doi:10.5772/52927, InTech, 2013.

    The article, apart from the introduction (section 1), is organized as follows: In section 2, we review the Penman-Monteith method and its simplifications, which estimate evapotranspiration on the basis of temperature and radiation data. In section 3 we present the new parametric model, which compromises the requirements for parsimony and consistency. In section 4, we calibrate the model at the point scale, using historical meteorological data, and evaluate it against other empirical approaches. In addition, we investigate the geographical distribution of its parameters over Greece. Finally, in section 5 we summarize the outcomes of our research and discuss next research steps.

    Full text: http://www.itia.ntua.gr/en/getfile/1284/1/documents/2013InTech_ParametricModelPET.pdf (819 KB)

    See also: http://dx.doi.org/10.5772/52927

    Works that cite this document: View on Google Scholar or ResearchGate

    Other works that reference this work (this list might be obsolete):

    1. Samaras, D. A., A. Reif, and K. Theodoropoulos, Evaluation of radiation-based reference evapotranspiration models under different Mediterranean climates in Central Greece, Water Resources Management, 28 (1), 207-225, 2014.
    2. Tabari, H., P. H. Talaee, P. Willems, and C. Martinez, Validation and calibration of solar radiation equations for estimating daily reference evapotranspiration at cool semi-arid and arid locations, Hydrological Sciences Journal, 61(3), 610-619, doi:10.1080/02626667.2014.947293, 2016.
    3. Jaber, H. S., S. Mansor, B. Pradhan, and N. Ahmad, Evaluation of SEBAL model for evapotranspiration mapping in Iraq using remote sensing and GIS, International Journal of Applied Engineering Research, 11(6), 3950-3955, 2016.
    4. Kumar, D., J. Adamowski, R. Suresh, and B. Ozga-Zielinski, Estimating evapotranspiration using an extreme learning machine model: case study in North Bihar, India, Journal of Irrigation and Drainage Engineering, 04016032, doi:10.1061/(ASCE)IR.1943-4774.0001044, 2016.
    5. Djaman, K., D. Rudnick, V. C. Mel, and D. Mutiibwa, Evaluation of Valiantzas’ simplified forms of the FAO-56 Penman-Monteith reference evapotranspiration model in a humid climate, Journal of Irrigation and Drainage Engineering, doi:10.1061/(ASCE)IR.1943-4774.0001191, 2017.
    6. Tegos, M., I. Nalbantis, and A. Tegos, Environmental flow assessment through integrated approaches, European Water, 60, 167-173, 2017.
    7. Norström, E., C. Katrantsiotis, R. H. Smittenberg, and K. Kouli, Chemotaxonomy in some Mediterranean plants and implications for fossil biomarker records, Geochimica et Cosmochimica Acta, 219, 96-110, doi:10.1016/j.gca.2017.09.029, 2017.
    8. Hodam, S., S. Sarkar, A.G.R. Marak, A. Bandyopadhyay, and A. Bhadra, Spatial interpolation of reference evapotranspiration in India: Comparison of IDW and Kriging methods, Journal of The Institution of Engineers (India): Series A, doi:10.1007/s40030-017-0241-z, 2017.
    9. Mentzafou, A., S. Wagner, and E. Dimitriou, Historical trends and the long-term changes of the hydrological cycle components in a Mediterranean river basin, Science of The Total Environment, 636, 558-568, doi:10.1016/j.scitotenv.2018.04.298, 2018.
    10. Norström, E., C. Katrantsiotis, M. Finné, J. Risberg, R. H. Smittenberg, S. Bjursäter, Biomarker hydrogen isotope composition (δD) as proxy for Holocene hydroclimatic change and seismic activity in SW Peloponnese, Greece, Journal of Quaternary Science, 33(5), 563-574, doi:10.1002/jqs.3036, 2018.
    11. Mengistu, B., and G. Amente, Three methods of estimating the power of maximum temperature in TM–ET estimation equation, SN Applied Sciences, 1:1403, doi:10.1007/s42452-019-1461-9, 2019.
    12. Mengistu, B., and G. Amente, Reformulating and testing Temesgen-Melesse's temperature-based evapotranspiration estimation method, Heliyon, 6(1), e02954, doi:10.1016/j.heliyon.2019.e02954, 2020.
    13. Středová, H., J. Klimešová, T. Středa, and P. Fukalová, Could the directly measured data of transpiration be replaced by model outputs?, Contributions to Geophysics and Geodesy, 50(1), 33-47, doi:10.31577/congeo.2020.50.1.2, 2020.
    14. Jaiswal, S., and M. S. Ballal, Fuzzy inference based irrigation controller for agricultural demand side management, Computers and Electronics in Agriculture, 175, 105537, doi:10.1016/j.compag.2020.105537, 2020.
    15. Rezaei, M., H. Ghasemieh, and K. Abdollahi, Simplified version of the METRIC model for estimation of actual evapotranspiration, International Journal of Remote Sensing, 42(14), 5568-5599, doi:10.1080/01431161.2021.1925991, 2021.
    16. Dos Santos, A. A., J. L. M. de Souza, and S. L. K. Rosa, Evapotranspiration with the Moretti-Jerszurki-Silva model for the Brazilian subtropical climate, Hydrological Sciences Journal, 66(16), 2267-2279, doi:10.1080/02626667.2021.1988610, 2021.
    17. Ilbay-Yupa, M., F. Ilbay, R. Zubieta, M. García-Mora, and P. Chasi, Impacts of climate change on the precipitation and streamflow regimes in equatorial regions: Guayas River Basin, Water, 13(21), 3138, doi:10.3390/w13213138, 2021.
    18. Dimitriadou, S., and K. G. Nikolakopoulos, Evapotranspiration trends and interactions in light of the anthropogenic footprint and the climate crisis: A review, Hydrology, 8(4), 163, doi:10.3390/hydrology8040163, 2021.
    19. Danielescu, S., Development and application of ETCalc, a unique online tool for estimation of daily evapotranspiration, Atmosphere-Ocean, doi:10.1080/07055900.2022.2154191, 2022.
    20. Pisinaras V., F. Herrmann, A. Panagopoulos, E. Tziritis, I. McNamara, and F. Wendland, Fully distributed water balance modelling in large agricultural areas—The Pinios river basin (Greece) case study, Sustainability, 15(5), 4343, doi:10.3390/su15054343, 2023.
    21. Stefanidis, S., A. Tegos, and V. Alexandridis, How has aridity changed at a fir (Abies Borisii-Regis) forest site in Central Greece during the past six decades? Environmental Sciences Proceedings, 26(1), 121, doi:10.3390/environsciproc2023026121, 2023.

  1. D. Koutsoyiannis, N. Mamassis, and A. Tegos, Logical and illogical exegeses of hydrometeorological phenomena in ancient Greece, Proceedings of the 1st IWA International Symposium on Water and Wastewater Technologies in Ancient Civilizations, edited by A. N. Angelakis and D. Koutsoyiannis, Iraklio, 135–143, doi:10.13140/RG.2.1.4188.4408, International Water Association, 2006.

    Technological applications aiming at the exploitation of the natural sources appear in all ancient civilizations. The unique phenomenon in the ancient Greek civilization is that technological needs triggered physical explanations of the natural phenomena and behaviours, thus enabling the foundation of philosophy and science. Among these, the study of hydrometeorological phenomena had a major role. This study begins with the Ionian philosophers in the seventh century BC, continues in classical Athens in the fifth and fourth centuries BC, and advances and expands through the entire Greek world up to the end of Hellenistic period, when Romans conquered Greece. Many of the theories developed in the course of ancient Greek civilization are erroneous according to modern views. However, many elements in Greek exegeses and interpretations of various hydrometeorological processes, such as the evaporation and condensation of vapour, the creation of clouds, hail, snow and rainfall and the evolution of hydrological cycle, are impressive even today.

    Related works:

    • [15] Revised version of the same article.

    Full text:

    See also: http://dx.doi.org/10.13140/RG.2.1.4188.4408

Conference publications and presentations with evaluation of abstract

  1. A. Tegos, P. Dimitriadis, and D. Koutsoyiannis, Stochastic investigation of the correlation structure and probability distribution of the global potential evapotranspiration, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-17849-3, European Geosciences Union, 2018.

    We investigate the second-order dependence structure and marginal probability distribution of the potential evapotranspiration (PET) determined by a recently proposed parametric model at several locations worldwide. The dependence structure is estimated through the climacogram (i.e. variance of the averaged process vs. scale of averaging), which has some advantages over other stochastic metrics (such as autocovariance and power-spectrum). Furthermore, we discuss stochastic similarities and cross-correlations of the PET with the corresponding temperature, dew-point and wind.

    Full text: http://www.itia.ntua.gr/en/getfile/1815/1/documents/EGU2018-17849-3.pdf (30 KB)

  1. N. Malamos, A. Tegos, I. L. Tsirogiannis, A. Christofides, and D. Koutsoyiannis, Implementation of a regional parametric model for potential evapotranspiration assessment, IrriMed 2015 – Modern technologies, strategies and tools for sustainable irrigation management and governance in Mediterranean agriculture, Bari, doi:10.13140/RG.2.1.3992.0725, 2015.

    Potential evapotranspiration (PET) is key input in water resources, agricultural and environmental modelling. For many decades, several approaches have been proposed for the consistent estimation of PET at several time scales of interest. The most recognized is the Penman‐Monteith formula, which is yet difficult to apply, since it requires simultaneous measurements of four meteorological variables (temperature, sunshine duration, humidity, wind velocity). For this reason, simplified approaches prove very useful in absence of a complete data set and are strongly preferred. In the present study, we implement a recent parametric formula to model PET in the Arta plain, located in the Region of Epirus ‐ Greece, which is based on a simplified formulation of the original Penman‐Monteith expression and requires only mean hourly, daily or monthly temperature data, depending on the desired time step. The methodology is generic, yet parsimonious in terms of the input data, with its parameters adjusted through calibration, to the available PET data. A spatial analysis concerning the regionalization of the parameters and PET estimates of the proposed methodology by implementing interpolation techniques is performed. The results are very satisfactory, illustrating that the proposed framework is efficient and constitutes a reliable alternative in the assessment of potential evapotranspiration field

    Full text: http://www.itia.ntua.gr/en/getfile/1576/1/documents/2015Bari_Implementation_of_a_regional_parametric.pdf (2372 KB)

    See also: http://dx.doi.org/10.13140/RG.2.1.3992.0725

  1. A. Koukouvinos, D. Nikolopoulos, A. Efstratiadis, A. Tegos, E. Rozos, S.M. Papalexiou, P. Dimitriadis, Y. Markonis, P. Kossieris, H. Tyralis, G. Karakatsanis, K. Tzouka, A. Christofides, G. Karavokiros, A. Siskos, N. Mamassis, and D. Koutsoyiannis, Integrated water and renewable energy management: the Acheloos-Peneios region case study, European Geosciences Union General Assembly 2015, Geophysical Research Abstracts, Vol. 17, Vienna, EGU2015-4912, doi:10.13140/RG.2.2.17726.69440, European Geosciences Union, 2015.

    Within the ongoing research project “Combined Renewable Systems for Sustainable Energy Development” (CRESSENDO), we have developed a novel stochastic simulation framework for optimal planning and management of large-scale hybrid renewable energy systems, in which hydropower plays the dominant role. The methodology and associated computer tools are tested in two major adjacent river basins in Greece (Acheloos, Peneios) extending over 15 500 km2 (12% of Greek territory). River Acheloos is characterized by very high runoff and holds ~40% of the installed hydropower capacity of Greece. On the other hand, the Thessaly plain drained by Peneios – a key agricultural region for the national economy – usually suffers from water scarcity and systematic environmental degradation. The two basins are interconnected through diversion projects, existing and planned, thus formulating a unique large-scale hydrosystem whose future has been the subject of a great controversy. The study area is viewed as a hypothetically closed, energy-autonomous, system, in order to evaluate the perspectives for sustainable development of its water and energy resources. In this context we seek an efficient configuration of the necessary hydraulic and renewable energy projects through integrated modelling of the water and energy balance. We investigate several scenarios of energy demand for domestic, industrial and agricultural use, assuming that part of the demand is fulfilled via wind and solar energy, while the excess or deficit of energy is regulated through large hydroelectric works that are equipped with pumping storage facilities. The overall goal is to examine under which conditions a fully renewable energy system can be technically and economically viable for such large spatial scale.

    Full text:

    Additional material:

    See also: http://dx.doi.org/10.13140/RG.2.2.17726.69440

    Other works that reference this work (this list might be obsolete):

    1. Stamou, A. T., and P. Rutschmann, Pareto optimization of water resources using the nexus approach, Water Resources Management, 32, 5053-5065, doi:10.1007/s11269-018-2127-x, 2018.
    2. Stamou, A.-T., and P. Rutschmann, Optimization of water use based on the water-energy-food nexus concept: Application to the long-term development scenario of the Upper Blue Nile River, Water Utility Journal, 25, 1-13, 2020.

  1. A. Tegos, A. Efstratiadis, N. Malamos, N. Mamassis, and D. Koutsoyiannis, Evaluation of a parametric approach for estimating potential evapotranspiration across different climates, IRLA2014 – The Effects of Irrigation and Drainage on Rural and Urban Landscapes, Patras, doi:10.13140/RG.2.2.14004.24966, 2014.

    Potential evapotranspiration (PET) is key input in water resources, agricultural and environmental modelling. For many decades, numerous approaches have been proposed for the consistent estimation of PET at several time scales of interest. The most recognized is the Penman-Monteith formula, which is yet difficult to apply in data-scarce areas, since it requires simultaneous observations of four meteorological variables (temperature, sunshine duration, humidity, wind velocity). For this reason, parsimonious models with minimum input data requirements are strongly preferred. Typically, these have been developed and tested for specific hydroclimatic conditions, but when they are applied in different regimes they provide much less reliable (and in some cases misleading) estimates. Therefore, it is essential to develop generic methods that remain parsimonious, in terms of input data and parameterization, yet they also allow for some kind of local adjustment of their parameters, through calibration. In this study we present a recent parametric formula, based on a simplified formulation of the original Penman-Monteith expression, which only requires mean daily or monthly temperature data. The method is evaluated using meteorological records from different areas worldwide, at both the daily and monthly time scales. The outcomes of this extended analysis are very encouraging, as indicated by the substantially high validation scores of the proposed approach across all examined data sets. In general, the parametric model outperforms well-established methods of the everyday practice, since it ensures optimal approximation of PET.

    Full text: http://www.itia.ntua.gr/en/getfile/1512/1/documents/2014_IRLA_Parametric.pdf (740 KB)

    See also: http://dx.doi.org/10.13140/RG.2.2.14004.24966

  1. N. Bountas, N. Boboti, E. Feloni, L. Zeikos, Y. Markonis, A. Tegos, N. Mamassis, and D. Koutsoyiannis, Temperature variability over Greece: Links between space and time, Facets of Uncertainty: 5th EGU Leonardo Conference – Hydrofractals 2013 – STAHY 2013, Kos Island, Greece, doi:10.13140/RG.2.2.17739.80164, European Geosciences Union, International Association of Hydrological Sciences, International Union of Geodesy and Geophysics, 2013.

    Temperature is strongly linked to the hydrological cycle in numerous ways and mainly with the evapotranspiration. Our aim here is to examine the possible influence of spatial characteristics on the temperature temporal variability of the monthly absolute maxima/minima and the monthly means over Greece. To achieve this, the temperature records of the Hellenic National Meteorological Service station network, which date back to 1950, are analysed. The analysis involved two steps: the determination of regions with similar climatic properties and the investigation of the possible correlations of temperature in time. Thus, the time series are classified in three groups based on their location (continental, coastal and island) and four types regarding the proximity of the station to a city (at the city centre, near the city border, far away from city border) or to an airport. Each one of the time series is then examined for (a) the influence of the city heat island as Greek cities expanded in time, (b) the effect of the general atmospheric circulation (NAO phase), (c) its correlation to the global temperature record and (d) the implied change on evapotranspiration in the area.

    Full text: http://www.itia.ntua.gr/en/getfile/1391/1/documents/Kos_Temperature_poster_.pdf (2010 KB)

    See also: http://dx.doi.org/10.13140/RG.2.2.17739.80164

  1. A. Efstratiadis, A. Koukouvinos, P. Dimitriadis, A. Tegos, N. Mamassis, and D. Koutsoyiannis, A stochastic simulation framework for flood engineering, Facets of Uncertainty: 5th EGU Leonardo Conference – Hydrofractals 2013 – STAHY 2013, Kos Island, Greece, doi:10.13140/RG.2.2.16848.51201, European Geosciences Union, International Association of Hydrological Sciences, International Union of Geodesy and Geophysics, 2013.

    Flood engineering is typically tackled as a sequential application of formulas and models, with specific assumptions and parameter values, thus providing fully deterministic outputs. In this procedure, the unique probabilistic concept is the return period of rainfall, which is set a priori, to represent the acceptable risk of all design variables of interest (peak flows, flood hydrographs, flow depths and velocities, inundated areas, etc.). Yet, a more consistent approach would require estimating the risks by integrating the uncertainties of all individual variables. This option can be offered by stochastic simulation, which is the most effective and powerful technique for analysing systems of high complexity and uncertainty. This presupposes to recognize which of the modelling components represent time-varying processes and which ones represent unknown, thus uncertain, parameters. In the proposed framework both should be handled as random variables. The following computational steps are envisaged: (a) generation of synthetic time series of areal rainfall, through multivariate stochastic disaggregation models; (b) generation of random sets of initial soil moisture conditions; (c) run of hydrological and hydraulic simulation models with random sets of parameter values, picked from suitable distributions; (d) statistical analysis of the model outputs and determination of empirical pdfs; and (e) selection of the design value, which corresponds to the acceptable risk. This approach allows for estimating the full probability distribution of the output variables, instead of a unique value, as resulted by the deterministic procedure. In this context, stochastic simulation also offers the means to introduce the missing culture of uncertainty appreciation in flood engineering.

    Full text: http://www.itia.ntua.gr/en/getfile/1384/1/documents/KosFloodStochSim.pdf (1860 KB)

    See also: http://dx.doi.org/10.13140/RG.2.2.16848.51201

  1. V. Pagana, A. Tegos, P. Dimitriadis, A. Koukouvinos, P. Panagopoulos, and N. Mamassis, Alternative methods in floodplain hydraulic simulation - Experiences and perspectives, European Geosciences Union General Assembly 2013, Geophysical Research Abstracts, Vol. 15, Vienna, EGU2013-10283-2, European Geosciences Union, 2013.

    Floods can simply be defined as the physical phenomena, during which an initially dry land area is covered by water. Floods are normally caused by extreme weather conditions, while their evolution depends mainly on geomorphologic factors, such as soil stability, vegetation cover, as well as the geometrical characteristics of the river basin. To prevent floods’ consequences, we have to study the hydraulic behavior of all the basins. Here, the study is focused on the upstream part of the Rafina basin, located in the east of Athens (Greece). Particularly, a hydraulic simulation is accomplished via the one-dimensional HEC-RAS and the quasi-two-dimensional LISFLOOD-FP and FLO-2D models. Additionally, a sensitivity analysis is carried out to investigate the effects of the floodplain and river roughness coefficients on the flood inundation in conjunction with a modern probabilistic view. Finally, a comparison between the three models is made regarding the simulated maximum water depth and maximum flow velocity.

    Full text:

    Other works that reference this work (this list might be obsolete):

    1. #Μίχας, Σ. Ν., Κ. Ι. Νικολάου, Σ. Λ. Λαζαρίδου, και Μ. Ν. Πικούνης, Σύγκριση μαθηματικών ομοιωμάτων διόδευσης πλημμυρικού κύματος από υποθετική θραύσης φράγματος Αγιόκαμπου, Πρακτικά 2ου Πανελλήνιου Συνεδρίου Φραγμάτων και Ταμιευτήρων, Αθήνα, Αίγλη Ζαππείου, Ελληνική Επιτροπή Μεγάλων Φραγμάτων, 2013.

  1. A. Oikonomou, P. Dimitriadis, A. Koukouvinos, A. Tegos, V. Pagana, P. Panagopoulos, N. Mamassis, and D. Koutsoyiannis, Floodplain mapping via 1D and quasi-2D numerical models in the valley of Thessaly, Greece, European Geosciences Union General Assembly 2013, Geophysical Research Abstracts, Vol. 15, Vienna, EGU2013-10366, doi:10.13140/RG.2.2.25165.03040, European Geosciences Union, 2013.

    The European Union Floods Directive defines a flood as ‘a covering by water of land not normally covered by water’. Human activities, such as agriculture, urban development, industry and tourism, contribute to an increase in the likelihood and adverse impacts of flood events. The study of the hydraulic behaviour of a river is important in flood risk management. Here, we investigate the behaviour of three hydraulic models, with different theoretical frameworks, in a real case scenario. The area is located in the Penios river basin, in the plain of Thessaly (Greece). The three models used are the one-dimensional HEC-RAS and the quasi two-dimensional LISFLOOD-FP and FLO-2D which are compared to each other, in terms of simulated maximum water depth as well as maximum flow velocity, and to a real flood event. Moreover, a sensitivity analysis is performed to determine how each simulation is affected by the river and floodplain roughness coefficient, in terms of flood inundation.

    Full text:

    See also: http://dx.doi.org/10.13140/RG.2.2.25165.03040

    Other works that reference this work (this list might be obsolete):

    1. #Μίχας, Σ. Ν., Κ. Ι. Νικολάου, Σ. Λ. Λαζαρίδου, και Μ. Ν. Πικούνης, Σύγκριση μαθηματικών ομοιωμάτων διόδευσης πλημμυρικού κύματος από υποθετική θραύσης φράγματος Αγιόκαμπου, Πρακτικά 2ου Πανελλήνιου Συνεδρίου Φραγμάτων και Ταμιευτήρων, Αθήνα, Αίγλη Ζαππείου, Ελληνική Επιτροπή Μεγάλων Φραγμάτων, 2013.

  1. A. Varveris, P. Panagopoulos, K. Triantafillou, A. Tegos, A. Efstratiadis, N. Mamassis, and D. Koutsoyiannis, Assessment of environmental flows of Acheloos Delta, European Geosciences Union General Assembly 2010, Geophysical Research Abstracts, Vol. 12, Vienna, 12046, doi:10.13140/RG.2.2.14849.66404, European Geosciences Union, 2010.

    Acheloos, the river with the highest discharge among rivers of Greece, hosts three hydroelectric dams, while two more dams are under construction. In addition, there are plans for partial diversion of the river to a nearby water district, for irrigation and hydroelectric development. The Acheloos Delta is considered to be one of the most significant Mediterranean wetland habitats for its ecological importance, including fish fauna. In this case study we aim to redefine the ecological flow and propose an outflow management policy from the most downstream reservoir (Stratos), in order to preserve the ecosystem at the Acheloos Delta. A hydrological analysis is employed to reconstruct the natural discharge records along the river on a daily basis, accompanied by a detailed evaluation of alternative methodologies for the estimation of the ecological flow. Based on the results of the analyses, the corresponding water management policy is determined, taking into account the characteristics of the hydropower plan and the related hydraulic works.

    Full text:

    See also: http://dx.doi.org/10.13140/RG.2.2.14849.66404

    Other works that reference this work (this list might be obsolete):

    1. #Fourniotis, N. T., M. Stavropoulou-Gatsi and I. K. Kalavrouziotis, Acheloos River: The timeless, and since ancient period, contribution to the development and environmental upgrading of Western Greece, Proceedings 3rd IWA Specialized Conference on Water & Wastewater Technologies in Ancient Civilizations, Istanbul-Turkey, 420-428, 2012.
    2. Fourniotis, N. T., A proposal for impact evaluation of the diversion of the Acheloos River on the Acheloos estuary in Western Greece, International Journal of Engineering Science and Technology, 4(4), 1792-1802, 2012.

  1. A. Tegos, N. Mamassis, and D. Koutsoyiannis, Estimation of potential evapotranspiration with minimal data dependence, European Geosciences Union General Assembly 2009, Geophysical Research Abstracts, Vol. 11, Vienna, 1937, doi:10.13140/RG.2.2.27222.86089, European Geosciences Union, 2009.

    We develop a parametric expression which approximates the Penman-Monteith equation thus providing easy estimation of the potential evapotranspiration with minimal data requirements. Namely, the method requires as inputs the mean temperature and the extraterrestrial radiation, from which only the temperature needs to be measured. The model was applied on a monthly step in 37 meteorological stations of Greece for the periods 1968-1983 (calibration period) and 1984-1989 (validation period). The results are satisfactory as the efficiency is greater than 0.97 for all stations and for both calibration and validation periods. Initially, the parametric expression involves three parameters but regional analysis indicates that reduction to one or two parameters is possible and does not increase the error substantially. Using optimization and geographic interpolation through a geographical information system, the parameter values were mapped for the entire territory of Greece, which makes the method directly applicable to any site in the country, the only requirement being that mean temperature data be available.

    Full text:

    See also: http://dx.doi.org/10.13140/RG.2.2.27222.86089

    Other works that reference this work (this list might be obsolete):

    1. Tabari, H., P. H. Talaee, P. Willems, and C. Martinez, Validation and calibration of solar radiation equations for estimating daily reference evapotranspiration at cool semi-arid and arid locations, Hydrological Sciences Journal, 2014.

  1. A. Efstratiadis, A. Tegos, I. Nalbantis, E. Rozos, A. Koukouvinos, N. Mamassis, S.M. Papalexiou, and D. Koutsoyiannis, Hydrogeios, an integrated model for simulating complex hydrographic networks - A case study to West Thessaly region, 7th Plinius Conference on Mediterranean Storms, Rethymnon, Crete, doi:10.13140/RG.2.2.25781.06881, European Geosciences Union, 2005.

    An integrated scheme, comprising a conjunctive hydrological model and a systems oriented management model, was developed, based on a semi-distributed approach. Geographical input data include the river network, the sub-basins upstream of each river node and the aquifer dicretization in the form of groundwater cells of arbitrary geometry. Additional layers of distributed geographical information, such as geology, land cover and terrain slope, are used to define the hydrological response units. Various modules are combined to represent the main processes at the water basin such as, soil moisture, groundwater, flood routing and water management models. Model outputs include river discharges, spring flows, groundwater levels and water abstractions. The model can be implemented in daily and monthly basis. A case study to the West Thessaly region performed. The discharges of five hydrometric stations and the water levels of eight boreholes were used simultaneously for model calibration. The implementation of the model to the certain region demonstrated satisfactory agreement between the observed and the simulated data.

    Full text:

    See also: http://dx.doi.org/10.13140/RG.2.2.25781.06881

Presentations and publications in workshops

  1. A. Tegos, A. Efstratiadis, A. Varveris, N. Mamassis, A. Koukouvinos, and D. Koutsoyiannis, Assesment and implementation of ecological flow constraints in large hydroelectric works: The case of Acheloos, Ecological flow of rivers and the importance of their true assesment, 2014.

    Full text: http://www.itia.ntua.gr/en/getfile/1455/1/documents/2014_envflows_pres.pdf (1344 KB)

  1. D. Koutsoyiannis, N. Mamassis, and A. Tegos, Hydrometeorological issues in ancient Greek science and philosophy, The Eco-nomy of Water, edited by E Efthymiopoulos and M. Modinos, Hydra island, doi:10.13140/RG.2.2.25574.63040, Hellenica Grammata, 2009.

    Technological applications aiming at the exploitation of the natural sources appear in all ancient civilizations. The unique phenomenon in the ancient Greek civilization is that technological needs triggered physical explanations of natural phenomena, thus enabling the foundation of philosophy and science. Among these, the study of hydrometeorological phenomena had a major role. This study begins with the Ionian philosophers in the seventh century BC, continues in classical Athens in the fifth and fourth centuries BC, and advances and expands through the entire Greek world up to the end of Hellenistic period. Many of the theories developed by ancient Greeks are erroneous according to modern views. However, many elements in Greek exegeses of hydrometeorological processes, such as evaporation and condensation of vapour, creation of clouds, hail, snow and rainfall, and evolution of hydrological cycle, are impressive even today.

    Related works:

    • [15] English text (publication in Water Science and Technology: Water Supply)

    Full text:

    See also: http://dx.doi.org/10.13140/RG.2.2.25574.63040

Various publications

  1. A. Tegos, Acheloos, 2009.

    Full text: http://www.itia.ntua.gr/en/getfile/937/1/documents/acheloos_tegos_2.pdf (271 KB)

  1. A. Tegos, Acheloos: Does the water belong only to fish?, March 2009.

    Full text: http://www.itia.ntua.gr/en/getfile/935/1/documents/axelwos_tegos1.pdf (200 KB)

Academic works

  1. A. Tegos, State-of-the-art approach for potential evapotranspiration assessment, PhD thesis, 123 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, Athens, November 2019.

    The aim of the PhD thesis is the foundation of a new temperature-based model since simplified PET estimation proves very useful in absence of a complete data set. In this respect, the Parametric model is presented based on a simplified formulation of the well-established Penman-Monteith expression, which only requires mean daily or monthly temperature data. The model was applied at both global and local regions and the outcomes of this new approach are very encouraging, as indicated by the substantially high validation scores of the proposed approach across all examined data sets. In general, the parametric model outperforms well-established methods of the everyday practice. A second analysis which was examined as part of this thesis is related to which spatial techniques is the optimal in order to transform the point scale estimate in regional. A thorough analysis of different geostatistical model was carried out (Kriging, IDW, NN, BSS) and it can be concluded that the IDW even is the most simplify geostatistical model, it can be produce consistent spatial PET results. Another part of the thesis was the development of an R function for testing the trend significance of time series. The function calculates the trend significance using a modified Mann- Kendall test, which takes into account the well-known physical behavior of the Hurst-Kolmogorov dynamics. The function is tested in 10 stations in Greece, with approximately 50 years of PET data with the use of a recent parametric model. Finally, a number of hydrological, agronomist and climatologist applications are presented for lighting the robustness of the new Parametric approach in multidiscipline areas.

    Full text:

  1. A. Tegos, Simplification of evapotranspiration estimation in Greece, Postgraduate Thesis, Department of Water Resources and Environmental Engineering – National Technical University of Athens, Athens, 2007.

    The scope of the study is the development of a new model, in order to estimate the potential evaportranspiration. The new model is based on the formulation of a parametric equation, that is adapted in a sample calculated at Penman- Monteith data. The adaptation becomes with the method of minimal square and the new model requires the medium temperature and the extraterrestrial radiation, as entry data, which only the temperature needs to be measured. The model was applied in 37 meteorological stations of Greece for the periods 1968-1983 and 1984-1989, in monthly step. The first decade refers to the calibration period, whereas the second one is the validation period, in which the forecasting capacity of the model was tested. Through optimization the initial parameters were reduced, so as to simplify the mathematic equation. The results were particularly satisfactory. Finally, geographic interpolation of parameters was realized, with the use of G.I.S, on the inference of parameters in all the Hellenic space.

    Full text:

    Additional material:

    Other works that reference this work (this list might be obsolete):

    1. Papadavid, G. C., A. Agapiou, S. Michaelides and D. G.Hadjimitsis, The integration of remote sensing and meteorological data for monitoring irrigation demand in Cyprus, Nat. Hazards Earth Syst. Sci., 9, 2009-2014, 2009.
    2. Hadjimitsis, D. G., and G. Papadavid, Integrated approach of remote sensing and micro-sensor technology for estimating evapotranspiration in Cyprus, Agric Eng Int: CIGR Journal 12 (3-4), 1-11, 2010.
    3. Papadavid, G., D. Hadjimitsis, S. Michaelides and A. Nisantzi, Crop evapotranspiration estimation using remote sensing and the existing network of meteorological stations in Cyprus, Adv. Geosci., 30, 39-44, doi: 10.5194/adgeo-30-39-2011, 2011.
    4. #Hadjimitsis, D. G. and G. Papadavid, Remote Sensing for Determining Evapotranspiration and Irrigation Demand for Annual Crops, Remote Sensing of Environment - Integrated Approaches, 10.5772/39305, 2013.

  1. A. Tegos, Combined simultation of hydrological-hydrogeological processes and operation of Western Thessaly hydrosystem, Diploma thesis, 132 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, September 2005.

    The scope of the study is the integrated simulation of the hydrological cycle in the Western Thessaly region, through the HYDROGEIOS model. First, the raw data for the hydrosystem was collected (data from hydrometric and pluviometric stations, groundwater data, agricultural data). Next, we proceeded to the schematisation of the physical and artificial system. For the adaptation of the model, i.e. the estimation of its parameters, an objective function was formulated, based on field measurements for surface and groundwater resources. The function comprises 16 components. Through optimisation, we attemted to find the minimum distance between the observed and simulated time series. The study refers to the period 1972-73 to 1992-93. The first decade refers to the calibration period, whereas the second one is the validation period, in which the forecasting capacity of the model was tested. Taking into account thecomplexity of the problem, the adaptation of the model was satisfactory, while useful conclusions were derived, which may be used for management purposes.

    Full text: http://www.itia.ntua.gr/en/getfile/679/1/documents/2005tegos.pdf (8166 KB)

    Additional material:

Research reports

  1. A. Koukouvinos, A. Efstratiadis, D. Nikolopoulos, H. Tyralis, A. Tegos, N. Mamassis, and D. Koutsoyiannis, Case study in the Acheloos-Thessaly system, Combined REnewable Systems for Sustainable ENergy DevelOpment (CRESSENDO), 98 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, October 2015.

    This report describes the validation of methodologies and computer tools that have been developed in the context of the research project, in the interconnected river basin system of Acheloos and Peneios. The study area is modelled as a hypothetically closed and autonomous (in terms of energy balance) system, in order to investigate the perspectives of sustainable development at the peripheral scale, merely based on renewable energy.

    Related project: Combined REnewable Systems for Sustainable ENergy DevelOpment (CRESSENDO)

    Full text: http://www.itia.ntua.gr/en/getfile/1613/1/documents/Report_EE4a.pdf (8010 KB)

  1. N. Mamassis, R. Mavrodimou, A. Efstratiadis, M. Heidarlis, A. Tegos, A. Koukouvinos, P. Lazaridou, M. Magaliou, and D. Koutsoyiannis, Investigation of alternative organisations and operations of a Water Management Body for the Smokovo projects, Investigation of management scenarios for the Smokovo reservoir, Report 2, 73 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, March 2007.

    The framework regarding the establishment and operation of a water management body for the Smokovo reservoir and the related projects is investigated. The study area, as well as the responsibility area within it, is defined, and a short description of the characteristics for the physical and artificial system is made. The current legal and institutional framework is examined, on the basis of which various alternative schemes are proposed for the management body. Its legal and administrative status, the competence and the organogram are specified, and an initial financial analysis is attempted, to validate its viability. Finally, the next actions are proposed, regarding the organization of deliberations with the related organs.

    Related project: Investigation of management scenarios for the Smokovo reservoir

    Full text: http://www.itia.ntua.gr/en/getfile/720/1/documents/Smo_teyx2ekd3.pdf (2847 KB)

    Additional material:

  1. A. Efstratiadis, A. Tegos, G. Karavokiros, I. Kyriazopoulou, and I. Vazimas, Master Plan for water resources management for the area of Karditsa, Integrated Management of Hydrosystems in Conjunction with an Advanced Information System (ODYSSEUS), Report 16, 132 pages, NAMA, Athens, December 2006.

    The present report refers to the Master Plan for water resources management for the area of Karditsa and was elaborated by NAMA's research team in cooperation with DEYA Karditsa and the National Technical University of Athens. This deliverable is part of Work Package 8 with title "Pilot Applications". The Pilot Applications aim to test and evaluate the product (from methodology and software efficiency viewpoints) on hydrosystems with totally different characteristics, in terms of their hydroclimatic regime, structure scale, and institutional and administrative framework of management. After the completion of the pilot applications, the product was re-examined at all levels (theoretical background, software design and implementation), before assuming its final form. This report will include the following main sections, according to the Technical Addendum of the Contract: (a) description of the study area, (b) description of the hydrosystem, (c) data and processing, (d) water needs assessment, (e) hydrological inflow assessment, (f) management of the hydrosystem, (g) simulation of quality parameters, (h) financial analysis and (i) conclusions and proposals.

    Related project: Integrated Management of Hydrosystems in Conjunction with an Advanced Information System (ODYSSEUS)

    Full text: http://www.itia.ntua.gr/en/getfile/769/1/documents/report_16.pdf (5557 KB)

    Additional material:

    Other works that reference this work (this list might be obsolete):

    1. #Strosser P., J. Roussard, B. Grandmougin, M. Kossida, I. Kyriazopoulou, J. Berbel, S. Kolberg, J. A. Rodríguez-Díaz, P. Montesinos, J. Joyce, T. Dworak, M. Berglund, and C. Laaser, EU Water saving potential (Part 2 – Case Studies), Berlin, Allemagne, Ecologic – Institute for International and European Environmental Policy, 101 pp., 2007.

  1. A. Efstratiadis, A. Koukouvinos, E. Rozos, A. Tegos, and I. Nalbantis, Theoretical documentation of model for simulating hydrological-hydrogeological processes of river basin "Hydrogeios", Integrated Management of Hydrosystems in Conjunction with an Advanced Information System (ODYSSEUS), Contractor: NAMA, Report 4a, 103 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, December 2006.

    The subject of the report is the development of the software system HYDROGEIOS, which represents the hydrological and hydrogeological processes as well as the water resource management practices of a river basin. After a short review of the most recognized hydrological models and a general overview of the problem, we describe the theoretical background of the approach, comprising the combined operation of three models: (a) a conceptual soil moisture accounting model, with different parameters for each hydrological response unit, which estimates the transformation of precipitation to evapotranspiration, surface runoff and percolation; (b) a multicell groundwater model, which estimates the spatial distribution of the water table, the baseflow (spring runoff) and the underground losses; and (c) a water resources allocation model, which for given hydrological inflows along the river network, given characteristics of technical facilities (aqueducts, wells) and given targets and constraints, estimates the abstractions and the water balance at all hydrosystem control points, selecting the economical optimal management. The spatial analysis assumes a semi-distributed schematisation of the basin and its underlying aquifer, and also a rough description of the technical works, all employed via the use of geographical information systems. The time step of simulation is monthly or daily; in the last case, a routing model is optionally incorporated, based on the well-known Muskingum-Cunge method. Specific emphasis is given to the estimation of model parameters, by using statistical and empirical goodness-of-fit measures and evolutionary algorithms for single- and multi-objective optimisation. Finally, we present an application of the model to the Western Thessaly area.

    Related project: Integrated Management of Hydrosystems in Conjunction with an Advanced Information System (ODYSSEUS)

    Full text: http://www.itia.ntua.gr/en/getfile/755/1/documents/report_4a.pdf (3877 KB)

    Other works that reference this work (this list might be obsolete):

    1. #Πετροπούλου, Μ., Ε. Ζαγγάνα, Ν. Χαριζόπουλος, Μ. Μιχαλοπούλου, Α. Μυλωνάς, και Κ. Περδικάρης, Εκτίμηση του υδρολογικού ισοζυγίου της λεκάνης απορροής του Πηνειού ποταμού Ηλείας με χρήση του μοντέλου «Ζυγός», 14ο Πανελλήνιο Συνέδριο της Ελληνικής Υδροτεχνικής Ένωσης (ΕΥΕ), Βόλος, 2019.