Spatially distributed HBV hydrological model with land surface characteristics based on N50 geospatial data from Norwegian Mapping Authority
Spatially distributed HBV hydrological model with general land surface characteristics
Spatially distributed HBV hydrological model with general land surface characteristics and Penman-Monteith equation for evapotranspiration
The spatially distributed HBV hydrological model is used for modelling the water balance and lateral transport of water in the land phase of the hydrological cycle. The spatial distribution and shape of discrete landscape elements and the time steps of the model may be selected according to the problem to be solved. The model structure is based on Beldring et al. (2003). The requirements for running the model and the procedures for setting up the model definition files are described in the documentation, as well as the variables and parameters used for hydrological process simulations. Model parameters remain constant over time, or vary in a manner which may be described using physical principles or empirical relationships. Parameters either represent physically measurable properties of a watershed, or are used to describe hydrological processes. A variable may represent: (i) the state of the different storages in the hydrological system as approximated by the hydrological model; (ii) the input signal which drives the model; or (iii) the output from the model. Variables vary with time. Precipitation-runoff models are used for applications that require simulation of the dynamic water balance of a selected area of the land surface, e.g. a watershed. They provide a capability to predict hydrological state variables and fluxes from atmospheric data, with the purpose of for example hydrological forecasts, hydrological impact simulations or management of water resources. Mathematical models simplify the physical processes and replace them by a set of equations, whose solutions are programmed as a computer code. The results of simulations with the mathematical model are interpreted in terms of the physical system. The structure of the models vary in their level of complexity, however, the major mechanisms involved in conversion of precipitation to discharge at the catchment outlet are considered. In addition to describing the physical processes which govern storage and flow of water as subsurface and overland flow through a catchment, precipitation-runoff models must include the various hydrological and radiative processes at the land surface-atmosphere interface; interception storage, evaporation and transpiration, glacier mass balance, snow accumulation and snowmelt.
Beldring, S., Engeland, K., Roald, L.A., Sælthun, N.R., Voksø, A. 2003. Estimation of parameters in a distributed precipitation-runoff model for Norway. Hydrology and Earth System Sciences 7, 304-316. https://doi.org/10.5194/hess-7-304-2003
Beldring, S., Engen-Skaugen, T., Førland, E.J., Roald, L.A. 2008. Climate change impacts on hydrological processes in Norway based on two methods for transferring regional climate model results to meteorological station sites. Tellus 60A, 439–450. https://onlinelibrary.wiley.com/doi/10.1111/j.1600-0870.2008.00306.x
Wong, W.K., Beldring, S., Engen-Skaugen, T., Haddeland, I., Hisdal, H. 2011. Climate change effects on spatiotemporal patterns of hydroclimatological summer droughts in Norway. Journal of Hydrometeorology 12, 1205-1220. http://dx.doi.org/10.1175/2011JHM1357.1
Li, H., Beldring, S., Xu, C.-Y. 2014. Implementation and testing of routing algorithms in the distributed Hydrologiska Byråns Vattenbalansavdelning model for mountainous catchments. Hydrology Research, 45.3, 322-332. https://doi.org/10.2166/nh.2013.009
Li, H., Beldring, S., Xu, C.-Y., Huss, M., Melvold, K., Jain, S.K. 2015. Integrating a glacier retreat model into a hydrological model – Case studies of three glacierised catchments in Norway and Himalayan region, Journal of Hydrology 527, 656-667. http://dx.doi.org/10.1016/j.jhydrol.2015.05.017
Li, H., Xu, C.-Y., Beldring, S. 2015. How much can we gain with increasing model complexity with the same model concepts? Journal of Hydrology 527, 858-871. http://dx.doi.org/10.1016/j.jhydrol.2015.05.044
Li, H., Xu, C.-Y., Beldring, S., Tallaksen, L.M., Jain, S.K. 2016. Water resources under climate change in Himalayan basins, Water Resources Management 30, 843–859. http://dx.doi.org/10.1007/s11269-015-1194-5
Huang, S., Eisner, S., Magnusson, J., Lussana, C., Yang, X., Beldring, S. 2019. Improvements of the spatially distributed hydrological modelling using the HBV model at 1 km resolution for Norway. Journal of Hydrology 557:123585. https://doi.org/10.1016/j.jhydrol.2019.03.051
Grover, S., Tayal, S., Beldring, S., Li, H. 2020. Modeling Hydrological Processes in Ungauged Snow-Fed Catchment of Western Himalaya. Water Resources 47(6), 987–995. https://doi.org/10.1134/S0097807820060147
Erlandsen, H.B., Beldring, S., Eisner, S., Hisdal, H., Huang, S., Tallaksen, L.M. 2021. Constraining the HBV model for robust water balance assessments in a cold climate. Hydrology Research nh2021132. https://doi.org/10.2166/nh.2021.132
Grover, S., Tayal, S., Sharma, S., Beldring, S. 2022. Effect of changes in climate variables on hydrological regime of Chenab basin, Western Himalaya. Journal of Water and Climate Change 13(1), 357-371. https://doi.org/10.2166/wcc.2021.003
Yuan, Q., Thorarinsdottir, T.L., Beldring, S., Wong, W.K., Xu, C.-Y. 2023. Assessing uncertainty in hydrological projections arising from local-scale internal variability of climate. Journal of Hydrology 620: 129415. https://doi.org/10.1016/j.jhydrol.2023.129415
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