Abstract
The objective of this study was to determine the role of spring catchment water storage on the evolution of low flows in central European mountainous catchments. The study analysed 58 catchments for which catchment storage, represented by snow, soil water and groundwater storages, was determined by the HBV hydrological model over a 35-year period. The spring catchment storage was related to several streamflow indices describing low flow periods using the mutual information criterion. The mean runoff in the summer and autumn periods was mostly related to rainfall sums from the respective season. The median relative contribution of rainfall to the total mutual information value was 48.4% in summer, and 44.2% in autumn period, respectively. The relative contribution of soil water and groundwater storages was approximately 25% for each of the components. In contrast, the minimum runoff, its duration and deficit runoff volume, were equally related to both catchment storage and seasonal rainfall, especially in the autumn period.
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Data Availability
The HBV model outputs were published as an open dataset (https://doi.org/10.5281/zenodo.3894699).
References
Andrade NPV, Viola MR, Beskow S et al (2020) Assessment of Spatial and Temporal Soil Water Storage Using a Distributed Hydrological Model. Water Resour Manag 34:5031–5046. https://doi.org/10.1007/s11269-020-02711-4
Berghuijs WR, Hartmann A, Woods RA (2016) Streamflow sensitivity to water storage changes across Europe. Geophys Res Lett 43:1980–1987. https://doi.org/10.1002/2016GL067927
Bergström S (1992) The HBV Model: Its Structure and Applications. Swedish Meteorological and Hydrological Institute, Norrköping
Blahušiaková A, Matoušková M, Jenicek M et al (2020) Snow and climate trends and their impact on seasonal runoff and hydrological drought types in selected mountain catchments in Central Europe. Hydrol Sci J 65:2083–2096
Carroll RWH, Deems JS, Niswonger R et al (2019) The Importance of Interflow to Groundwater Recharge in a Snowmelt-Dominated Headwater Basin. Geophys Res Lett 46:5899–5908. https://doi.org/10.1029/2019GL082447
Cochand M, Christe P, Ornstein P, Hunkeler D (2019) Groundwater Storage in High Alpine Catchments and Its Contribution to Streamflow. Water Resour Res 55:2613–2630. https://doi.org/10.1029/2018WR022989
Dierauer JR, Whitfield PH, Allen DM (2018) Climate Controls on Runoff and Low Flows in Mountain Catchments of Western North America. Water Resour Res 54:7495–7510. https://doi.org/10.1029/2018WR023087
Dusek J, Vogel T (2019) Modeling travel time distributions of preferential subsurface runoff, deep percolation and transpiration at a montane forest hillslope site. Water (Switzerland) 11. https://doi.org/10.3390/w11112396
Fangmann A, Haberlandt U (2019) Statistical approaches for identification of low-flow drivers: Temporal aspects. Hydrol Earth Syst Sci 23:447–463. https://doi.org/10.5194/hess-23-447-2019
Floriancic MG, van Meerveld I, Smoorenburg M et al (2018) Spatio-temporal variability in contributions to low flows in the high Alpine Poschiavino catchment. Hydrol Process 32:3938–3953. https://doi.org/10.1002/hyp.13302
Grosser PF, Schmalz B (2021) Low flow and drought in a german low mountain range basin. Water (switzerland) 13:1–22. https://doi.org/10.3390/w13030316
Hayashi M (2020) Alpine Hydrogeology: The Critical Role of Groundwater in Sourcing the Headwaters of the World. Groundwater 58:498–510. https://doi.org/10.1111/gwat.12965
Hnilica J, Hanel M, Puš V (2019) Technical note: Changes in cross- and auto-dependence structures in climate projections of daily precipitation and their sensitivity to outliers. Hydrol Earth Syst Sci 23:1741–1749. https://doi.org/10.5194/hess-23-1741-2019
Iliopoulou T, Aguilar C, Arheimer B et al (2019) A large sample analysis of European rivers on seasonal river flow correlation and its physical drivers. Hydrol Earth Syst Sci 23:73–91. https://doi.org/10.5194/hess-23-73-2019
Immerzeel WW, Lutz AF, Andrade M et al (2020) Importance and vulnerability of the world’s water towers. Nature 577:364–369. https://doi.org/10.1038/s41586-019-1822-y
Jenicek M, Ledvinka O (2020) Importance of snowmelt contribution to seasonal runoff and summer low flows in Czechia. Hydrol Earth Syst Sci Discuss 1–23. https://doi.org/10.5194/hess-2019-611
Jenicek M, Seibert J, Zappa M et al (2016) Importance of maximum snow accumulation for summer low flows in humid catchments. Hydrol Earth Syst Sci 20:859–874. https://doi.org/10.5194/hess-20-859-2016
Kirchner JW (2009) Catchments as simple dynamical systems: Catchment characterization, rainfall-runoff modeling, and doing hydrology backward. Water Resour Res 45:1–34. https://doi.org/10.1029/2008WR006912
Langhammer J, Bernsteinová J (2020) Which aspects of hydrological regime in mid-latitude montane basins are affected by climate change? Water (Switzerland) 12:2279. https://doi.org/10.3390/w12082279
Mcnamara JP, Tetzlaff D, Bishop K et al (2011) Storage as a Metric of Catchment Comparison. Hydrol Process 25:3364–3371. https://doi.org/10.1002/hyp.8113
Meriö LJ, Ala-aho P, Linjama J et al (2019) Snow to Precipitation Ratio Controls Catchment Storage and Summer Flows in Boreal Headwater Catchments. Water Resour Res 55:4096–4109. https://doi.org/10.1029/2018WR023031
Merz R, Blöschl G (2009) A regional analysis of event runoff coefficients with respect to climate and catchment characteristics in Austria. Water Resour Res 45:1–19. https://doi.org/10.1029/2008WR007163
Moghim S (2020) Assessment of Water Storage Changes Using GRACE and GLDAS. Water Resour Manag 34:685–697. https://doi.org/10.1007/s11269-019-02468-5
Mozny M, Trnka M, Vlach V et al (2020) Past (1971–2018) and future (2021–2100) pan evaporation rates in the Czech Republic. J Hydrol 590:125390. https://doi.org/10.1016/j.jhydrol.2020.125390
Oudin L, Hervieu F, Michel C et al (2005) Which potential evapotranspiration input for a lumped rainfall-runoff model? Part 2 - Towards a simple and efficient potential evapotranspiration model for rainfall-runoff modelling. J Hydrol 303:290–306. https://doi.org/10.1016/j.jhydrol.2004.08.026
Penna D, van Meerveld HJ, Oliviero O et al (2015) Seasonal changes in runoff generation in a small forested mountain catchment. Hydrol Process 29:2027–2042. https://doi.org/10.1002/hyp.10347
Pfister L, Martínez-Carreras N, Hissler C et al (2017) Bedrock geology controls on catchment storage, mixing, and release: A comparative analysis of 16 nested catchments. Hydrol Process 31:1828–1845. https://doi.org/10.1002/hyp.11134
R Core Team (2020) R: A language and environment for statistical computing. R Foundation for Statistical Computing. Vienna, Austria
Rajagopalan B, Lall U, Tarboton DG (1997) Evaluation of kernel density estimation methods for daily precipitation resampling. Stoch Hydrol Hydraul 11:523–547. https://doi.org/10.1007/BF02428432
Sayama T, Mcdonnell JJ, Dhakal A, Sullivan K (2011) How much water can a watershed store? Hydrol Process 25:3899–3908. https://doi.org/10.1002/hyp.8288
Seibert J, Vis MJP (2012) Teaching hydrological modeling with a user-friendly catchment-runoff-model software package. Hydrol Earth Syst Sci 16:3315–3325. https://doi.org/10.5194/hess-16-3315-2012
Sharma A (2000) Seasonal to interannual rainfall probabilistic forecasts for improved water supply management: Part 1 - A strategy for system predictor identification. J Hydrol 239:232–239. https://doi.org/10.1016/S0022-1694(00)00346-2
Sheather SJ, Jones MC (1991) A reliable data-based bandwidth selection method for kernel density estimation. J R Stat Soc B 53(3):683–690
Shukla S, Sheffield J, Wood EF, Lettenmaier DP (2013) On the sources of global land surface hydrologic predictability. Hydrol Earth Syst Sci 17:2781–2796. https://doi.org/10.5194/hess-17-2781-2013
Silverman BW (1998) Density estimation for statistics and data analysis. Chapman and Hall, New York
Šípek V, Daňhelka J (2015) Modification of input datasets for the Ensemble Streamflow Prediction based on large-scale climatic indices and weather generator. J Hydrol 528:720–733. https://doi.org/10.1016/j.jhydrol.2015.07.008
Šípek V, Hnilica J, Vlček L et al (2020) Influence of vegetation type and soil properties on soil water dynamics in the Šumava Mountains (Southern Bohemia). J Hydrol 582:124285. https://doi.org/10.1016/j.jhydrol.2019.124285
Smakhtin VU (2001) Smakhtin 2010- Low flow hydrology.pdf. J Hydrol Hydrol 240:147–186
Sorg A, Bolch T, Stoffel M et al (2012) Climate change impacts on glaciers and runoff in Tien Shan (Central Asia). Nat Clim Chang 2:725–731. https://doi.org/10.1038/nclimate1592
Staudinger M, Stoelzle M, Seeger S et al (2017) Catchment water storage variation with elevation. Hydrol Process 31:2000–2015. https://doi.org/10.1002/hyp.11158
Viviroli D, Dürr HH, Messerli B et al (2007) Mountains of the world, water towers for humanity: Typology, mapping, and global significance. Water Resour Res 43:1–13. https://doi.org/10.1029/2006WR005653
Vlach V, Ledvinka O, Matouskova M (2020) Changing Low Flow and Streamflow Drought Seasonality in Central European Headwaters. Water 12:3575. https://doi.org/10.3390/w12123575
Wada Y, Van Beek LPH, Wanders N, Bierkens MFP (2013) Human water consumption intensifies hydrological drought worldwide. Environ Res Lett 8. https://doi.org/10.1088/1748-9326/8/3/034036
Zahradníček P, Brázdil R, Štěpánek P, Trnka M (2020) Reflections of global warming in trends of temperature characteristics in the Czech Republic, 1961–2019. Int J Climatol 1–19. https://doi.org/10.1002/joc.6791
Acknowledgements
Support from the Czech Science Foundation (18-06217Y) and institutional support from the Czech Academy of Sciences (RVO 67985874) are gratefully acknowledged. Meteorological and hydrological data for the calibration of the HBV model were obtained from the Czech Hydrometeorological Institute and prepared by Ondrej Ledvinka. Many thanks are due to Tracy Ewen for English corrections.
Funding
Grant Agency of the Czech Republic (18-06217Y) and institutional support from the Czech Academy of Sciences (RVO 67985874).
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VŠ and MJ initiated the study. VŠ, MJ, JH developed the methodology. MJ performed hydrological modelling and JH was responsible for statistical analyses. NZ processed output data from the hydrological model. VŠ prepared the manuscript with contributions of MJ and JH.
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Highlights
∙ Catchment storage most considerably affected by elevation
∙ Mean runoff in summer and autumn periods is determined by rainfall amounts
∙ Low flow indices are equally influenced by rainfall and catchment water storage
∙ Catchments storage is more important for low flows in autumn period
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Šípek, V., Jenicek, M., Hnilica, J. et al. Catchment Storage and its Influence on Summer Low Flows in Central European Mountainous Catchments. Water Resour Manage 35, 2829–2843 (2021). https://doi.org/10.1007/s11269-021-02871-x
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DOI: https://doi.org/10.1007/s11269-021-02871-x