Facebook Instagram Twitter RSS Feed PodBean Back to top on side

Comparison of the variability of snow cover parameters of the HBV model using lumped and distributed precipitation inputs and multi-basin calibration

In: Acta Hydrologica Slovaca, vol. 22, no. 1
Adam Brziak - Martin Kubáň - Silvia Kohnová - Ján Szolgay
Detaily:
Rok, strany: 40 - 49
Jazyk: eng
Kľúčové slová:
HBV model, Austria, snow cover parameters, multi- basin calibration
URL originálneho zdroja: http://www.ih.sav.sk/ah
O článku:
Snow cover is a significant source of water supply, mainly in mountainous regions, as snow precipitation fundamentally affects a catchment´s water balance. The correct simulation of the water balance with rainfall-runoff models is therefore important for the effective management of water resources. Three basic factors may affect the efficiency of hydrological models and the quality of the modelled outputs: The spatial representativeness of the input data, the model´s structure, and the uncertainties of the model parameters. A comparison of the variability of snow cover parameters and model efficiency of two versions of the HBV model using spatially lumped and distributed precipitation inputs by a multi-basin calibration exercise was performed in this study. Both the lumped and semi-distributed versions of the HBV model were calibrated for discharges, precipitation, and the air temperature on 180 catchments located all over the territory of Austria using data from the period 1991–2000. The analysis focused on the variability of the parameters controlling the snowmelt and the accumulation of the snow components of the two models. The efficiency of the models based on lumped and spatially distributed inputs was compared. The question as to how the catchment´s mean elevation, and the number of days with an air temperature below zero affects the model´s performance was targeted, too.
O vydaní:
Vydavateľ: Institute of Hydrology SAS, Dúbravská cesta 9, 841 05 Bratislava, Slovakia
Verejná licencia:
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License