Παραμετρικό μοντέλο για την εκτίμηση της δυνητικής εξατμοδιαπνοής βασισμένη σε απλουστευμένη διατύπωση της εξίσωσης Penman-Monteith

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.

[Παραμετρικό μοντέλο για την εκτίμηση της δυνητικής εξατμοδιαπνοής βασισμένη σε απλουστευμένη διατύπωση της εξίσωσης Penman-Monteith]

[doc_id=1284]

[Αγγλικά]

Βλέπε επίσης: http://dx.doi.org/10.5772/52927

Εργασίες μας στις οποίες αναφέρεται αυτή η εργασία:

1.	Δ. Κουτσογιάννης, και Θ. Ξανθόπουλος, Τεχνική Υδρολογία, Εκδοση 3, 418 pages, doi:10.13140/RG.2.1.4856.0888, Εθνικό Μετσόβιο Πολυτεχνείο, Αθήνα, 1999.
2.	A. Tsouni, C. Contoes, D. Koutsoyiannis, P. Elias, and N. Mamassis, Estimation of actual evapotranspiration by remote sensing: Application in Thessaly Plain, Greece, Sensors, 8 (6), 3586–3600, 2008.
3.	D. Koutsoyiannis, Seeking parsimony in hydrology and water resources technology (solicited), European Geosciences Union General Assembly 2009, Geophysical Research Abstracts, Vol. 11, Vienna, 11469, doi:10.13140/RG.2.2.20511.97443, European Geosciences Union, 2009.
4.	S. Kozanis, A. Christofides, N. Mamassis, A. Efstratiadis, and D. Koutsoyiannis, Hydrognomon – open source software for the analysis of hydrological data, European Geosciences Union General Assembly 2010, Geophysical Research Abstracts, Vol. 12, Vienna, 12419, doi:10.13140/RG.2.2.21350.83527, European Geosciences Union, 2010.
5.	N. Mamassis, A. Efstratiadis, and E. Apostolidou, Topography-adjusted solar radiation indices and their importance in hydrology, Hydrological Sciences Journal, 57 (4), 756–775, doi:10.1080/02626667.2012.670703, 2012.

Εργασίες μας που αναφέρονται σ' αυτή την εργασία:

1.	A. Efstratiadis, A. D. Koussis, S. Lykoudis, A. Koukouvinos, A. Christofides, G. Karavokiros, N. Kappos, N. Mamassis, and D. Koutsoyiannis, Hydrometeorological network for flood monitoring and modeling, Proceedings of First International Conference on Remote Sensing and Geoinformation of Environment, Paphos, Cyprus, 8795, 10-1–10-10, doi:10.1117/12.2028621, Society of Photo-Optical Instrumentation Engineers (SPIE), 2013.
2.	N. Mamassis, D. Panagoulia, and A. Novcovic, Sensitivity analysis of Penman evaporation method, Global Network for Environmental Science and Technology, 16 (4), 628–639, 2014.
3.	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.
4.	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.
5.	T. Vergou, A. Efstratiadis, and D. Dermatas, Water balance model for evaluation of landfill malfunction due to leakage, Proceedings of ISWA 2016 World Congress, Novi Sad, Ιnternational Solid Waste Association, 2016.
6.	E. Savvidou, A. Efstratiadis, A. D. Koussis, A. Koukouvinos, and D. Skarlatos, A curve number approach to formulate hydrological response units within distributed hydrological modelling, Hydrology and Earth System Sciences Discussions, doi:10.5194/hess-2016-627, 2016.
7.	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.
8.	K. Papoulakos, G. Pollakis, Y. Moustakis, A. Markopoulos, T. Iliopoulou, P. Dimitriadis, D. Koutsoyiannis, and A. Efstratiadis, Simulation of water-energy fluxes through small-scale reservoir systems under limited data availability, Energy Procedia, 125, 405–414, doi:10.1016/j.egypro.2017.08.078, 2017.
9.	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.
10.	E. Savvidou, A. Efstratiadis, A. D. Koussis, A. Koukouvinos, and D. Skarlatos, The curve number concept as a driver for delineating hydrological response units, Water, 10 (2), 194, doi:10.3390/w10020194, 2018.
11.	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.
12.	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.

Άλλες εργασίες που αναφέρονται σ' αυτή την εργασία: Δείτε τις στο Google Scholar ή στο ResearchGate

Άλλες εργασίες που αναφέρονται σ' αυτή την εργασία (αυτός ο κατάλογος μπορεί να μην είναι ενημερωμένος):

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.

Κατηγορίες: Υδρολογικά μοντέλα