SUPPLEMENTARY MATERIAL
, Joonas Pärn , Marlen Hunt, Siim Tarros, Elve Lode, Pamela Abreldaal The escalating impacts of global climate change significantly affect regional hydrological systems, particularly in northern areas such as Estonia. This study investigates the hydrological sensitivity of Estonian catchments to climatic variability, focusing on the interplay between surface water and groundwater. Using data from 42 river catchments, it employs various statistical methods in hydrology, emphasizing the autocorrelation function, cross-correlation function, baseflow index, and flow duration curve. The analysis spans the years 2012–2022, integrating hydrological, spatial, and water quality parameters. The research identifies four distinct hydrological behavior clusters: plateau, sandstone upland, carbonate upland, and lowland. Key findings include diverse catchment sensitivities to groundwater recharge, the role of baseflow in streamflow stabilization, the memory effect in catchment responses, and insights from the flow duration curve on flow variability and extremes. The LightGBM model, predicting focus parameters, highlights the critical influence of air temperature and snowpack on streamflow characteristics. This study underscores the diverse hydrological sensitivities of Estonian catchments to hydroclimatic changes, emphasizing the importance of considering catchment-specific characteristics in water resource management and policy-making. Contributing to the broader understanding of hydrological processes, it provides valuable insights for future research and environmental planning in the face of climate variability and change.
Babre, A., Popovs, K., Kalvāns, A., Jemeljanova, M. and Dēliņa, A. 2023. Forecasting the groundwater levels in the Baltic through standardized index analysis. Weather and Climate Extremes, 45, 100728.
https://doi.org/10.1016/j.wace.2024.100728
Bailly-Comte, V., Jourde, H., Roesch, A., Pistre, S. and Batiot-Guilhe, C. 2008. Time series analyses for karst/river interactions assessment: case of the Coulazou river (southern France). Journal of Hydrology, 349(1–2), 98–114.
https://doi.org/10.1016/j.jhydrol.2007.10.028
Barnett, T. P., Adam, J. C. and Lettenmaier, D. P. 2005. Potential impacts of a warming climate on water availability in snow-dominated regions. Nature, 438, 303–309.
Beck, H. E., Zimmermann, N. E., McVicar, T. R., Vergopolan, N., Berg, A. and Wood, E. F. 2018. Present and future Köppen–Geiger climate classification maps at 1-km resolution. Scientific Data, 5, 180214.
https://doi.org/10.1038/sdata.2018.214
Berghuijs, W. R., Woods, R. A. and Hrachowitz, M. 2014. A precipitation shift from snow towards rain leads to a decrease in streamflow. Nature Climate Change, 4, 583–586.
https://doi.org/10.1038/nclimate2246
Blöschl, G., Hall, J., Viglione, A., Perdigão, R. A. P., Parajka, J., Merz, B. et al. 2019. Changing climate both increases and decreases European river floods. Nature, 573, 108–111.
https://doi.org/10.1038/s41586-019-1495-6
Cinkus, G., Mazzilli, N. and Jourde, H. 2023. KarstID: an R Shiny application for the analysis of karst spring discharge time series and the classification of karst system hydrological functioning. Environmental Earth Sciences, 82, 136.
https://doi.org/10.1007/s12665-023-10830-5
Cochand, M., Christe, P., Ornstein, P. and Hunkeler, D. 2019. Groundwater storage in high alpine catchments and its contribution to streamflow. Water Resources Research, 55(4), 2613–2630.
https://doi.org/10.1029/2018WR022989
Coppola, E., Nogherotto, R., Ciarlo’, J. M., Giorgi, F., van Meijgaard, E., Kadygrov, N. et al. 2021. Assessment of the European climate projections as simulated by the large EURO-CORDEX regional and global climate model ensemble. Journal of Geophysical Research: Atmospheres, 126(4).
https://doi.org/10.1029/2019JD032356
Costantini, M., Colin, J. and Decharme, B. 2023. Projected climate‐driven changes of water table depth in the world’s major groundwater basins. Earth’s Future, 11(3).
https://doi.org/10.1029/2022EF003068
Donnelly, C., Greuell, W., Andersson, J., Gerten, D., Pisacane, G., Roudier, P. and Ludwig, F. 2017. Impacts of climate change on European hydrology at 1.5, 2 and 3 degrees mean global warming above preindustrial level. Climatic Change, 143, 13–26.
https://doi.org/10.1007/s10584-017-1971-7
Douville, H., Raghavan, K., Renwick, J., Allan, R. P., Arias, P. A., Barlow, M. et al. 2021. Water cycle changes. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S. et al., eds). Cambridge University Press, Cambridge, New York, 1055–1210.
https://doi.org/doi:10.1017/9781009157896.010
Earman, S. and Dettinger, M. 2011. Potential impacts of climate change on groundwater resources – a global review. Journal of Water & Climate Change, 2(4), 213–229.
https://doi.org/10.2166/wcc.2011.034
ESRI. 2023. ArcGIS Pro.
https://www.esri.com/en-us/arcgis/products/arcgis-pro/overview (accessed 2024-10-02).
Estonian Environment Agency. Environmental Monitoring Information System.
https://kese.envir.ee/kese/welcome.action (accessed 2024-10-02).
Estonian Environment Agency.
https://keskkonnaagentuur.ee/ (accessed 2024-10-02).
Estonian Environment Agency. 2014. Hydrological Yearbook 2013. Estonian Environment Agency, Tallinn.
Estonian Land Board. Estonian Land Board Geoportal.
https://geoportaal.maaamet.ee (accessed 2024-10-02).
European Commission. 2000. Directive 2000/60/EC of the European Parliament and of the Council of 23 October 2000 establishing a framework for community action in the field of water policy. Official Journal of the European Communities, L 327, 1–72.
Grogan, D. S., Burakowski, E. A. and Contosta, A. R. 2020. Snowmelt control on spring hydrology declines as the vernal window lengthens. Environmental Research Letters, 15, 114040.
https://doi.org/10.1088/1748-9326/abbd00
Harris, C. R., Millman, K. J., van der Walt, S. J., Gommers, R., Virtanen, P., Cournapeau, D. et al. 2020. Array programming with NumPy. Nature, 585, 357–362.
https://doi.org/10.1038/s41586-020-2649-2
Hunt, M. 2021. Modeling of the water balance in the Selja River basin with the PRMS hydrological model. Master’s thesis. University of Tartu, Estonia.
Hunter, J. D. 2007. Matplotlib: a 2D graphics environment. Computing in Science & Engineering, 9(3), 90–95.
https://doi.org/10.1109/MCSE.2007.55
IPCC (Intergovernmental Panel on Climate Change). 2022. Climate Change 2022: Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, New York.
Jaagus, J. and Mändla, K. 2014. Climate change scenarios for Estonia based on climate models from the IPCC Fourth Assessment Report. Estonian Journal of Earth Sciences, 63(3), 166–180.
https://doi.org/10.3176/earth.2014.15
Jaagus, J., Järvet, A., Roosaare, J., Tamm, T. and Vallner, L. 1998. Integrated assessment of climate change impact on water resources in Estonia. In Country Case Study on Climate Change Impacts and Adaptation Assessments in the Republic of Estonia (Tarand, A. and Kallaste, T., eds). SEI-T & UNEP, Tallinn, 59–76.
Jaagus, J., Sepp, M., Tamm, T., Järvet, A. and Mõisja, K. 2017. Trends and regime shifts in climatic conditions and river runoff in Estonia during 1951–2015. Earth System Dynamics, 8(4), 963–976.
https://doi.org/10.5194/esd-8-963-2017
Järvet, A. 1998. Long-term changes in time series of water balance elements. In Country Case Study on Climate Change Impacts and Adaptation Assessments in the Republic of Estonia (Tarand, A. and Kallaste, T., eds). SEI-T & UNEP, Tallinn, 69−71.
Jefferson, A., Nolin, A., Lewis, S. and Tague, C. 2008. Hydrogeologic controls on streamflow sensitivity to climate variation. Hydrological Processes, 22(22), 4371–4385.
https://doi.org/10.1002/hyp.7041
Jenicek, M., Seibert, J., Zappa, M., Staudinger, M. and Jonas, T. 2016. Importance of maximum snow accumulation for summer low flows in humid catchments. Hydrology and Earth System Sciences, 20(2), 859–874.
https://doi.org/10.5194/hess-20-859-2016
Kalm, V. 2006. Pleistocene chronostratigraphy in Estonia, southeastern sector of the Scandinavian glaciation. Quaternary Science Reviews, 25(9–10), 960–975.
https://doi.org/10.1016/j.quascirev.2005.08.005
Ke, G., Meng, Q., Finley, T., Wang, T., Chen, W., Ma, W. et al. 2017. LightGBM: a highly efficient gradient boosting decision tree. In 31st International Conference on Neural Information Processing Systems, Long Beach, California, USA, 4–9 December 2017 (Luxburg, U. von, Guyon, I., Bengio, S., Wallach, H. and Fergus, R., eds). Curran Associates Inc., New York, 3149–3157.
Killian, C. D., Asquith, W. H., Barlow, J. R. B., Bent, G. C., Kress, W. H., Barlow, P. M. and Schmitz, D. W. 2019. Characterizing groundwater and surface-water interaction using hydrograph-separation techniques and groundwater-level data throughout the Mississippi Delta, USA. Hydrogeology Journal, 27, 2167– 2179.
http://dx.doi.org/10.1007/s10040-019-01981-6
Koit, O. 2022. Surface water and groundwater interaction in shallow karst aquifers of Lower Estonia. PhD thesis. Tallinn University, Estonia.
https://doi.org/10.13140/RG.2.2.13634.86726
Koit, O., Mayaud, C., Kogovšek, B., Vainu, M., Terasmaa, J. and Marandi, A. 2022. Surface water and groundwater hydraulics of lowland karst aquifers of Estonia. Journal of Hydrology, 610, 127908.
https://doi.org/10.1016/j.jhydrol.2022.127908
Kotta, J., Herkül, K., Jaagus, J., Kaasik, A., Raudsepp, U., Alari, V. et al. 2018. Linking atmospheric, terrestrial and aquatic environments: regime shifts in the Estonian climate over the past 50 years. PLoS ONE, 13(12).
https://doi.org/10.1371/journal.pone.0209568
Kottek, M., Grieser, J., Beck, C., Rudolf, B. and Rubel, F. 2006. World map of the Köppen-Geiger climate classification updated. Meteorologische Zeitschrift, 15(3), 259−263.
http://dx.doi.org/10.1127/0941-2948/2006/0130
Ladson, A. R., Brown, R., Neal, B. and Nathan, R. 2013. A standard approach to baseflow separation using the Lyne and Hollick filter. Australasian Journal of Water Resources, 17(1), 25–34.
https://doi.org/10.7158/13241583.2013.11465417
Larocque, M., Mangin, A., Razack, M. and Banton, O. 1998. Contribution of correlation and spectral analyses to the regional study of a large karst aquifer (Charente, France). Journal of Hydrology, 205(3–4), 217–231.
https://doi.org/10.1016/S0022-1694(97)00155-8
Liu, Y., Wagener, T., Beck, H. E. and Hartmann, A. 2020. What is the hydrologically effective area of a catchment? Environmental Research Letters, 15, 104024.
https://doi.org/10.1088/1748-9326/aba7e5
Lumivero. 2023. XLSTAT statistical and data analysis solution.
https://www.xlstat.com/en (accessed 2024-10-02).
Lundberg, S. M. and Lee, S.-I. 2017. A unified approach to interpreting model predictions. In 31st International Conference on Neural Information Processing Systems, Long Beach, California, USA, 4–9 December 2017 (Luxburg, U. von, Guyon, I., Bengio, S., Wallach, H. and Fergus, R., eds). Curran Associates Inc., New York, 4765–4774.
Lyne, V. D. and Hollick, M. 1979. Stochastic time-variable rainfall-runoff modeling. In Hydrology and Water Resources Symposium, Perth, Australia, 10–12 September 1979. Institution of Engineers National Conference, 89–92.
Mangin, A. 1984. The use of autocorrelation and spectral analyses to obtain a better understanding of hydrological systems. Journal of Hydrology, 67(1–4), 25–43.
Markstrom, S. L., Regan, R. S., Hay, L. E., Viger, R. J., Webb, R. M. T., Payn, R. A. and LaFontaine, J. H. 2015. PRMS-IV, the precipitation-runoff modeling system, version 4. In Techniques and Methods 6–B7. US Geological Survey, Reston.
https://doi.org/10.3133/tm6B7
Mayaud, C., Wagner, T., Benischke, R. and Birk, S. 2014. Single event time series analysis in a binary karst catchment evaluated using a groundwater model (Lurbach system, Austria). Journal of Hydrology, 511, 628−639.
https://doi.org/10.1016/j.jhydrol.2014.02.024
McKinney, W. 2010. Data structures for statistical computing in Python. In 9th Python in Science Conference, Austin, USA, 28 June – 3 July 2010 (van der Walt, S. and Millman, J., eds). scipy.org, 51–56.
Meier, H. E. M., Kniebusch, M., Dieterich, C., Gröger, M., Zorita, E., Elmgren, R. et al. 2022. Climate change in the Baltic Sea region: a summary. Earth System Dynamics, 13(1), 457–593.
https://doi.org/10.5194/esd-13-457-2022
Meriö, L.-J., Ala-aho, P., Linjama, J., Hjort, J., Kløve, B. and Marttila, H. 2019. Snow to precipitation ratio controls catchment storage and summer flows in boreal headwater catchments. Water Resources Research, 55(5), 4096–4109.
https://doi.org/10.1029/2018WR023031
Muñoz Sabater, J. 2019. ERA5-Land monthly averaged data from 1950 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS).
https://doi.org/10.24381/cds.68d2bb30
Nõges, T., Vilbaste, S., McCarthy, M. J., Tamm, M. and Nõges, P. 2022. Long-term data reflect nitrogen pollution in Estonian rivers. Hydrology Research, 53(12), 1468–1479.
https://doi.org/10.2166/nh.2022.057
Nygren, M., Giese, M., Kløve, B., Haaf, E., Rossi, P. M. and Barthel, R. 2020. Changes in seasonality of groundwater level fluctuations in a temperate-cold climate transition zone. Journal of Hydrology X, 8, 100062.
https://doi.org/10.1016/j.hydroa.2020.100062
Okkonen, J. and Kløve, B. 2011. A sequential modelling approach to assess groundwater–surface water resources in a snow dominated region of Finland. Journal of Hydrology, 411(1–2), 91–107.
https://doi.org/10.1016/j.jhydrol.2011.09.038
Okkonen, J., Jyrkama, M. and Kløve, B. 2011. A conceptual approach for assessing the impact of climate change on groundwater and related surface waters in cold regions (Finland). Hydrogeology Journal, 18, 429–439.
http://dx.doi.org/10.1007/s10040-009-0529-9
Pärn, J. and Mander, Ü. 2012. Increased organic carbon concentrations in Estonian rivers in the period 1992–2007 as affected by deepening droughts. Biogeochemistry, 108, 351–358.
https://doi.org/10.1007/s10533-011-9604-0
Pärn, J., Walraevens, K., Hunt, M., Koit, O., van Camp, M., Ivask, J. et al. 2024. Unveiling the hydrological response of NO3-rich springs to seasonal snowmelt in a karstic carbonate upland. Journal of Hydrology, 641, 131724.
https://doi.org/10.1016/j.jhydrol.2024.131724
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O. et al. 2011. Scikit-learn: machine learning in Python. Journal of Machine Learning Research, 12(85), 2825–2830.
Protasjeva, M. S. and Eipre, T. (eds). 1972. Ресурсы поверхностных вод СССР (Surface Water Resources of USSR). Gidrometeoizdat, Leningrad.
Ranasinghe, R., Ruane, A. C., Vautard, R., Arnell, N., Coppola, E., Cruz, F. A. et al. 2021. Climate change information for regional impact and for risk assessment. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S. et al., eds). Cambridge University Press, Cambridge, New York, 1767–1926.
https://doi.org/10.1017/9781009157896.014
Raukas, A. and Kajak, K. 1997. Quaternary cover. In Geology and Mineral Resources of Estonia (Raukas, A. and Teedumäe, A., eds). Estonian Academy Publishers, Tallinn, 125–136.
Rodhe, A. 1998. Snowmelt-dominated systems. In Isotope Tracers in Catchment Hydrology (Kendall, C. and McDonnell, J. J., eds). Elsevier, Amsterdam, 391–434.
Roosaare, J., Jaagus, J. and Järvet, A. 1998. Modelling the influence of climate change on river runoff. In Country Case Study on Climate Change Impacts and Adaptation Assessments in the Republic of Estonia (Tarand, A. and Kallaste, T., eds). SEI-T & UNEP, Tallinn, 75–83.
Van Rossum, G. and Drake, F. L. 2009. Python 3 Reference Manual. CreateSpace, Scotts Valley.
Ruosteenoja, K. and Jylhä, K. 2021. Projected climate change in Finland during the 21st century calculated from CMIP6 model simulations. Geophysica, 56(1–2), 39–69.
Ruosteenoja, K., Markkanen, T., Venäläinen, A., Räisänen, P. and Peltola, H. 2018. Seasonal soil moisture and drought occurrence in Europe in CMIP5 projections for the 21st century. Climate Dynamics, 50 (3–4), 1177–1192.
https://doi.org/10.1007/s00382-017-3671-4
Sankarasubramanian, A., Vogel, R. M. and Limbrunner, J. F. 2001. Climate elasticity of streamflow in the United States. Water Resources Research, 37(6), 1771–1781.
https://doi.org/10.1029/2000WR900330
Schuler, P., Campanyà, J., Moe, H., Doherty, D., Williams, N. H. and McCormack, T. 2022. Mapping the groundwater memory across Ireland: a step towards a groundwater drought susceptibility assessment. Journal of Hydrology, 612, 128277.
https://doi.org/10.1016/j.jhydrol.2022.128277
Smerdon, B. D. 2017. A synopsis of climate change effects on groundwater recharge. Journal of Hydrology, 555, 125–128.
https://doi.org/10.1016/j.jhydrol.2017.09.047
Stahl, K., Hisdal, H., Hannaford, J., Tallaksen, L. M., van Lanen, H. A. J., Sauquet, E. et al. 2010. Streamflow trends in Europe: evidence from a dataset of near-natural catchments. Hydrology and Earth System Sciences, 14(12), 2367–2382.
https://doi.org/10.5194/hess-14-2367-2010
Statistics Estonia. 2023. Population Demographics 2023. https://www. stat.ee (accessed 2024-10-02).
Stoelzle, M., Schuetz, T., Weiler, M., Stahl, K. and Tallaksen, L. M. 2020. Beyond binary baseflow separation: a delayed-flow index for multiple streamflow contributions. Hydrology and Earth System Sciences, 24(2), 849–867.
https://doi.org/10.5194/hess-24-849-2020
Sutanto, S. J. and van Lanen, H. A. J. 2022. Catchment memory explains hydrological drought forecast performance. Scientific Reports, 12, 2689.
https://doi.org/10.1038/s41598-022-06553-5
Taylor, R. G., Scanlon, B., Döll, P., Rodell, M., Beek, R. van, Wada, Y. et al. 2013. Ground water and climate change. Nature Climate Change, 3, 322–329.
http://dx.doi.org/10.1038/nclimate1744
Teutschbein, C., Grabs, T., Karlsen, R. H., Laudon, H. and Bishop, K. 2015. Hydrological response to changing climate conditions: spatial streamflow variability in the boreal region. Water Resources Research, 51(12), 9425–9446.
https://doi.org/10.1002/2015WR017337
Teutschbein, C., Quesada Montano, B., Todorović, A. and Grabs, T. 2022. Streamflow droughts in Sweden: spatiotemporal patterns emerging from six decades of observations. Journal of Hydrology: Regional Studies, 42, 101171.
https://doi.org/10.1016/j.ejrh.2022.101171
Vallner, L. 1998. Assessment of climate change impact on groundwater. In Country Case Study on Climate Change Impacts and Adaptation Assessments in the Republic of Estonia (Tarand, A. and Kallaste, T., eds). SEI-T & UNEP, Tallinn, 83–89.
Virbulis, J., Bethers, U., Saks, T., Sennikovs, J. and Timuhins, A. 2013. Hydrogeological model of the Baltic Artesian Basin. Hydrogeology Journal, 21, 845–862.
https://doi.org/10.1007/s10040-013-0970-7
Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy T., Cournapeu, D. et al. 2020. SciPy 1.0: fundamental algorithms for scientific computing in Python. Nature Methods, 17, 261–272.
Viru, B. and Jaagus, J. 2020. Spatio-temporal variability and seasonal dynamics of snow cover regime in Estonia. Theoretical and Applied Climatology, 139(1–2), 759–771.
https://doi.org/10.1007/s00704-019-03013-5
Vogel, R. M. and Fennessey, N. M. 1994. Flow duration curves. I: new interpretation and confidence intervals. Journal of Water Resources Planning and Management, 120(4), 485–504.
Vorobevskii, I., Kronenberg, R. and Bernhofer, C. 2022. Linking different drought types in a small catchment from a statistical perspective – case study of the Wernersbach catchment, Germany. Journal of Hydrology X, 15, 100122.
https://doi.org/10.1016/j.hydroa.2022.100122
Worthington, S. R. H. 2019. How preferential flow delivers pre-event groundwater rapidly to streams. Hydrological Processes, 33(17), 2373–2380.
https://doi.org/10.1002/hyp.13520
Wu, W.-Y., Lo, M.-H., Wada, Y., Famiglietti, J. S., Reager, J. T., Yeh, P. J. et al. 2020. Divergent effects of climate change on future groundwater availability in key mid-latitude aquifers. Nature Communications, 11, 3710.
https://doi.org/10.1038/s41467-020-17581-y
