The Calibration of Evaporation Models against the Penman–Monteith Equation on Lake Most
Viktor Dubovský,
Dagmar Dlouhá and
Lukáš Pospíšil
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Viktor Dubovský: Department of Mathematics, Faculty of Civil Engineering, VSB-TU Ostrava, Ludvíka Podéště, 1875/17 Ostrava, Czech Republic
Dagmar Dlouhá: Department of Mathematics, Faculty of Civil Engineering, VSB-TU Ostrava, Ludvíka Podéště, 1875/17 Ostrava, Czech Republic
Lukáš Pospíšil: Department of Mathematics, Faculty of Civil Engineering, VSB-TU Ostrava, Ludvíka Podéště, 1875/17 Ostrava, Czech Republic
Sustainability, 2020, vol. 13, issue 1, 1-17
Abstract:
Evaporation is one of the main components of the water cycle in nature. Our interest in free water surface evaporation is due to the needs of ongoing hydric recultivation of the former Ležáky–Most quarry, i.e., Lake Most, and also other planned hydric recultivations in the region. One of the key components of hydric reclamation planning is the securitization of long-term sustainability, which is based on the capability to keep the final water level at a stable level. In our work, we are interested in the evaporation estimation in the area of Lake Most (Czech Republic, Europe). This lake has been artificially created only a few years ago, and nowadays we are looking for a simple evaporation model, based on which we will be able to decide which measurement devices have to be installed at the location to provide more localized data to the model. In this paper, we calibrate state-of-the-art simplified evaporation models against the Penman–Monteith equation based on the Nash–Sutcliffe efficiency maximization. We discuss the suitability of this approach using real-world climate data from the weather station located one km from the area of interest.
Keywords: free water surface; Nash–Sutcliffe efficiency; optimization; water loss; annual evaporation (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:13:y:2020:i:1:p:313-:d:473101
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