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Long Term Discharge Prediction in River Hydrometric Profile
Šelepa, Milan ; Menšík, Pavel (referee) ; Marton, Daniel (advisor)
The diploma thesis is focused on the long term prediction of mean monthly flows in hydrometric profile for purposes of reservoir control optimization and optimization of reservoir systems. Discharges were predicted using by artificial neural network method. Predicted flows were statistically evaluated by relevant coefficients and then compared with the measured flows for given river hydrometric profiles.
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Sediment impact on river hydrology
Winkler, Stanislav ; Šelepa, Milan (referee) ; Marton, Daniel (advisor)
The bachelor’s thesis analyze sediments and their impact on hydrology in rivers. This thesis can be used as guide providing necessary theoretic knowledge about methods of measuring sediments and monitoring strategy. As default material have been used methodology for measurement from university BOKU Wien. Their long – standing experience and knowledge in sediment measurement sphere are inestimable and going to be used in project SEDECO – Sediments, ecosystem services and interrelation with floods and droughts in the AT – CZ border region financed through INTERREG AT – CZ.
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Sediment impact on river hydrology
Winkler, Stanislav ; Šelepa, Milan (referee) ; Marton, Daniel (advisor)
The bachelor’s thesis analyze sediments and their impact on hydrology in rivers. This thesis can be used as guide providing necessary theoretic knowledge about methods of measuring sediments and monitoring strategy. As default material have been used methodology for measurement from university BOKU Wien. Their long – standing experience and knowledge in sediment measurement sphere are inestimable and going to be used in project SEDECO – Sediments, ecosystem services and interrelation with floods and droughts in the AT – CZ border region financed through INTERREG AT – CZ.
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Long Term Discharge Prediction in River Hydrometric Profile
Šelepa, Milan ; Menšík, Pavel (referee) ; Marton, Daniel (advisor)
The diploma thesis is focused on the long term prediction of mean monthly flows in hydrometric profile for purposes of reservoir control optimization and optimization of reservoir systems. Discharges were predicted using by artificial neural network method. Predicted flows were statistically evaluated by relevant coefficients and then compared with the measured flows for given river hydrometric profiles.
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