Articles | Volume 30, issue 3
https://doi.org/10.5194/hess-30-779-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-30-779-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Uncertainty, temporal variability, and influencing factors of empirical streamflow sensitivities
Sebastian Gnann
CORRESPONDING AUTHOR
Faculty of Environment and Natural Resources, University of Freiburg, Freiburg, 79098, Germany
Bailey J. Anderson
WSL Institute for Snow and Avalanche Research SLF, Davos Dorf, Switzerland
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
Climate Change, Extremes and Natural Hazards in Alpine Regions Research Center CERC, Davos Dorf, Switzerland
Markus Weiler
Faculty of Environment and Natural Resources, University of Freiburg, Freiburg, 79098, Germany
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Hydrol. Earth Syst. Sci., 29, 6069–6092, https://doi.org/10.5194/hess-29-6069-2025, https://doi.org/10.5194/hess-29-6069-2025, 2025
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Hydrol. Earth Syst. Sci., 29, 1319–1333, https://doi.org/10.5194/hess-29-1319-2025, https://doi.org/10.5194/hess-29-1319-2025, 2025
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Robin Schwemmle, Hannes Leistert, Andreas Steinbrich, and Markus Weiler
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Bailey J. Anderson, Manuela I. Brunner, Louise J. Slater, and Simon J. Dadson
Hydrol. Earth Syst. Sci., 28, 1567–1583, https://doi.org/10.5194/hess-28-1567-2024, https://doi.org/10.5194/hess-28-1567-2024, 2024
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Barbara Herbstritt, Benjamin Gralher, Stefan Seeger, Michael Rinderer, and Markus Weiler
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Stefan Seeger and Markus Weiler
Hydrol. Earth Syst. Sci., 27, 3393–3404, https://doi.org/10.5194/hess-27-3393-2023, https://doi.org/10.5194/hess-27-3393-2023, 2023
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This study proposes a low-budget method to quantify the radial distribution of water transport velocities within trees at a high spatial resolution. We observed a wide spread of water transport velocities within a tree stem section, which were on average 3 times faster than the flux velocity. The distribution of transport velocities has implications for studies that use water isotopic signatures to study root water uptake and usually assume uniform or even implicitly infinite velocities.
Andreas Hänsler and Markus Weiler
Hydrol. Earth Syst. Sci., 26, 5069–5084, https://doi.org/10.5194/hess-26-5069-2022, https://doi.org/10.5194/hess-26-5069-2022, 2022
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Spatially explicit quantification of design storms is essential for flood risk assessment and planning. However, available datasets are mainly based on spatially interpolated station-based design storms. Since the spatial interpolation of the data inherits a large potential for uncertainty, we develop an approach to be able to derive spatially explicit design storms on the basis of weather radar data. We find that our approach leads to an improved spatial representation of design storms.
Anne Hartmann, Markus Weiler, Konrad Greinwald, and Theresa Blume
Hydrol. Earth Syst. Sci., 26, 4953–4974, https://doi.org/10.5194/hess-26-4953-2022, https://doi.org/10.5194/hess-26-4953-2022, 2022
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Analyzing the impact of soil age and rainfall intensity on vertical subsurface flow paths in calcareous soils, with a special focus on preferential flow occurrence, shows how water flow paths are linked to the organization of evolving landscapes. The observed increase in preferential flow occurrence with increasing moraine age provides important but rare data for a proper representation of hydrological processes within the feedback cycle of the hydro-pedo-geomorphological system.
Nils Hinrich Kaplan, Theresa Blume, and Markus Weiler
Hydrol. Earth Syst. Sci., 26, 2671–2696, https://doi.org/10.5194/hess-26-2671-2022, https://doi.org/10.5194/hess-26-2671-2022, 2022
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This study is analyses how characteristics of precipitation events and soil moisture and temperature dynamics during these events can be used to model the associated streamflow responses in intermittent streams. The models are used to identify differences between the dominant controls of streamflow intermittency in three distinct geologies of the Attert catchment, Luxembourg. Overall, soil moisture was found to be the most important control of intermittent streamflow in all geologies.
Thomas Lees, Marcus Buechel, Bailey Anderson, Louise Slater, Steven Reece, Gemma Coxon, and Simon J. Dadson
Hydrol. Earth Syst. Sci., 25, 5517–5534, https://doi.org/10.5194/hess-25-5517-2021, https://doi.org/10.5194/hess-25-5517-2021, 2021
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We used deep learning (DL) models to simulate the amount of water moving through a river channel (discharge) based on the rainfall, temperature and potential evaporation in the previous days. We tested the DL models on catchments across Great Britain finding that the model can accurately simulate hydrological systems across a variety of catchment conditions. Ultimately, the model struggled most in areas where there is chalky bedrock and where human influence on the catchment is large.
Benjamin Gralher, Barbara Herbstritt, and Markus Weiler
Hydrol. Earth Syst. Sci., 25, 5219–5235, https://doi.org/10.5194/hess-25-5219-2021, https://doi.org/10.5194/hess-25-5219-2021, 2021
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We scrutinized the quickest currently available method for stable isotope analysis of matrix-bound water. Simulating common procedures, we demonstrated the limits of certain materials currently used and identified a reliable and cost-efficient alternative. Further, we calculated the optimum proportions of important protocol aspects critical for precise and accurate analyses. Our unifying protocol suggestions increase data quality and comparability as well as the method's general applicability.
Jan Greiwe, Markus Weiler, and Jens Lange
Biogeosciences, 18, 4705–4715, https://doi.org/10.5194/bg-18-4705-2021, https://doi.org/10.5194/bg-18-4705-2021, 2021
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We analyzed variability in diel nitrate patterns at three locations in a lowland stream. Comparison of time lags between monitoring sites with water travel time indicated that diel patterns were created by in-stream processes rather than transported downstream from an upstream point of origin. Most of the patterns (70 %) could be explained by assimilatory nitrate uptake. The remaining patterns suggest seasonally varying dominance and synchronicity of different biochemical processes.
Stefan Seeger and Markus Weiler
Biogeosciences, 18, 4603–4627, https://doi.org/10.5194/bg-18-4603-2021, https://doi.org/10.5194/bg-18-4603-2021, 2021
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We developed a setup for fully automated in situ measurements of stable water isotopes in soil and the stems of fully grown trees. We used this setup in a 12-week field campaign to monitor the propagation of a labelling pulse from the soil up to a stem height of 8 m.
We could observe trees shifting their main water uptake depths multiple times, depending on water availability.
The gained knowledge about the temporal dynamics can help to improve water uptake models and future study designs.
Andreas Hänsler and Markus Weiler
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-366, https://doi.org/10.5194/hess-2021-366, 2021
Manuscript not accepted for further review
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Spatially explicit quantification on design storms are essential for flood risk assessment. However this information can be only achieved from substantially long records of rainfall measurements, usually only available for a few stations. Hence, design storms estimates from these few stations are then spatially interpolated leading to a major source of uncertainty. Therefore we defined a methodology to extend spatially explicit weather radar data to be used for the estimation of design storms.
Louise J. Slater, Bailey Anderson, Marcus Buechel, Simon Dadson, Shasha Han, Shaun Harrigan, Timo Kelder, Katie Kowal, Thomas Lees, Tom Matthews, Conor Murphy, and Robert L. Wilby
Hydrol. Earth Syst. Sci., 25, 3897–3935, https://doi.org/10.5194/hess-25-3897-2021, https://doi.org/10.5194/hess-25-3897-2021, 2021
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Weather and water extremes have devastating effects each year. One of the principal challenges for society is understanding how extremes are likely to evolve under the influence of changes in climate, land cover, and other human impacts. This paper provides a review of the methods and challenges associated with the detection, attribution, management, and projection of nonstationary weather and water extremes.
Anne Hartmann, Markus Weiler, Konrad Greinwald, and Theresa Blume
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-242, https://doi.org/10.5194/hess-2021-242, 2021
Manuscript not accepted for further review
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Our field observation-based examination of flow path evolution, soil formation and vegetation succession across ten millennia on calcareous parent material shows how water flow paths and subsurface water storage are linked to the organization of evolving landscapes. We provide important but rare data and observations for a proper handling of hydrologic processes and their role within the feedback cycle of the hydro-pedo-geomorphological system.
Axel Schaffitel, Tobias Schuetz, and Markus Weiler
Geosci. Model Dev., 14, 2127–2142, https://doi.org/10.5194/gmd-14-2127-2021, https://doi.org/10.5194/gmd-14-2127-2021, 2021
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This paper presents FluSM, an algorithm to derive the water balance from soil moisture and metrological measurements. This data-driven water balance framework uses soil moisture as an input and therefore is applicable for cases with unclear processes and lacking parameters. In a case study, we apply FluSM to derive the water balance of 15 different permeable pavements under field conditions. These findings are of special interest for urban hydrology.
Robin Schwemmle, Dominic Demand, and Markus Weiler
Hydrol. Earth Syst. Sci., 25, 2187–2198, https://doi.org/10.5194/hess-25-2187-2021, https://doi.org/10.5194/hess-25-2187-2021, 2021
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A better understanding of the reasons why model performance is unsatisfying represents a crucial part for meaningful model evaluation. We propose the novel diagnostic efficiency (DE) measure and diagnostic polar plots. The proposed evaluation approach provides a diagnostic tool for model developers and model users and facilitates interpretation of model performance.
Cited articles
Addor, N., Newman, A. J., Mizukami, N., and Clark, M. P.: The CAMELS data set: catchment attributes and meteorology for large-sample studies, Hydrol. Earth Syst. Sci., 21, 5293–5313, https://doi.org/10.5194/hess-21-5293-2017, 2017.
Addor, N., Nearing, G., Prieto, C., Newman, A. J., Le Vine, N., and Clark, M. P.: A Ranking of Hydrological Signatures Based on Their Predictability in Space, Water Resour. Res., 54, 8792–8812, https://doi.org/10.1029/2018WR022606, 2018.
Almagro, A., Meira Neto, A. A., Vergopolan, N., Roy, T., Troch, P. A., and Oliveira, P. T. S.: The Drivers of Hydrologic Behavior in Brazil: Insights From a Catchment Classification, Water Resour. Res., 60, e2024WR037212, https://doi.org/10.1029/2024WR037212, 2024.
Anderson, B. J., Slater, L. J., Dadson, S. J., Blum, A. G., and Prosdocimi, I.: Statistical Attribution of the Influence of Urban and Tree Cover Change on Streamflow: A Comparison of Large Sample Statistical Approaches, Water Resour. Res., 58, e2021WR030742, https://doi.org/10.1029/2021WR030742, 2022.
Anderson, B. J., Brunner, M. I., Slater, L. J., and Dadson, S. J.: Elasticity curves describe streamflow sensitivity to precipitation across the entire flow distribution, Hydrol. Earth Syst. Sci., 28, 1567–1583, https://doi.org/10.5194/hess-28-1567-2024, 2024.
Anderson, B. J., Slater, L. J., Rapson, J., Brunner, M. I., Dadson, S. J., Yin, J., and Buechel, M.: Stationarity Assumptions in Streamflow Sensitivity to Precipitation May Bias Future Projections, Earths Future, 13, e2025EF006188, https://doi.org/10.1029/2025EF006188, 2025.
Andréassian, V., Coron, L., Lerat, J., and Le Moine, N.: Climate elasticity of streamflow revisited – an elasticity index based on long-term hydrometeorological records, Hydrol. Earth Syst. Sci., 20, 4503–4524, https://doi.org/10.5194/hess-20-4503-2016, 2016.
Andréassian, V., Guimarães, G. M., Lerat, J., and de Lavenne, A.: Streamflow elasticity as a function of aridity, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2025-4912, 2025a.
Andréassian, V., Guimarães, G. M., de Lavenne, A., and Lerat, J.: Time shift between precipitation and evaporation has more impact on annual streamflow variability than the elasticity of potential evaporation, Hydrol. Earth Syst. Sci., 29, 5477–5491, https://doi.org/10.5194/hess-29-5477-2025, 2025b.
Awasthi, C., Vogel, R. M., and Sankarasubramanian, A.: Regionalization of Climate Elasticity Preserves Dooge's Complementary Relationship, Water Resour. Res., 60, e2023WR036606, https://doi.org/10.1029/2023WR036606, 2024.
Ban, Z., Das, T., Cayan, D., Xiao, M., and Lettenmaier, D. P.: Understanding the Asymmetry of Annual Streamflow Responses to Seasonal Warming in the Western United States, Water Resour. Res., 56, e2020WR027158, https://doi.org/10.1029/2020WR027158, 2020.
Berghuijs, W. R., Hartmann, A., and Woods, R. A.: Streamflow sensitivity to water storage changes across Europe, Geophys. Res. Lett., 43, 1980–1987, https://doi.org/10.1002/2016GL067927, 2016.
Berghuijs, W. R., Larsen, J. R., van Emmerik, T. H. M., and Woods, R. A.: A Global Assessment of Runoff Sensitivity to Changes in Precipitation, Potential Evaporation, and Other Factors, Water Resour. Res., 53, 8475–8486, https://doi.org/10.1002/2017WR021593, 2017.
Budyko, M. I.: Climate and life, No. 18; International Geophysics Series, Academic Press, ISBN 9780080954530, 1974.
Chiew, F. H. S.: Estimation of rainfall elasticity of streamflow in Australia, Hydrol. Sci. J., 51, 613–625, https://doi.org/10.1623/hysj.51.4.613, 2006.
Chiew, F. H. S., Potter, N. J., Vaze, J., Petheram, C., Zhang, L., Teng, J., and Post, D. A.: Observed hydrologic non-stationarity in far south-eastern Australia: implications for modelling and prediction, Stoch. Environ. Res. Risk Assess., 28, 3–15, https://doi.org/10.1007/s00477-013-0755-5, 2014.
Clerc-Schwarzenbach, F., Selleri, G., Neri, M., Toth, E., van Meerveld, I., and Seibert, J.: Large-sample hydrology – a few camels or a whole caravan?, Hydrol. Earth Syst. Sci., 28, 4219–4237, https://doi.org/10.5194/hess-28-4219-2024, 2024.
Coxon, G., Addor, N., Bloomfield, J. P., Freer, J., Fry, M., Hannaford, J., Howden, N. J. K., Lane, R., Lewis, M., Robinson, E. L., Wagener, T., and Woods, R.: CAMELS-GB: hydrometeorological time series and landscape attributes for 671 catchments in Great Britain, Earth Syst. Sci. Data, 12, 2459–2483, https://doi.org/10.5194/essd-12-2459-2020, 2020a.
Coxon, G., Addor, N., Bloomfield, J. P., Freer, J., Fry, M., Hannaford, J., Howden, N. J. K., Lane, R., Lewis, M., Robinson, E. L., Wagener, T., and Woods, R.: Catchment attributes and hydro-meteorological timeseries for 671 catchments across Great Britain (CAMELS-GB), UKCEH [data set], https://doi.org/10.5285/8344e4f3-d2ea-44f5-8afa-86d2987543a9, 2020b.
de Lavenne, A., Andréassian, V., Crochemore, L., Lindström, G., and Arheimer, B.: Quantifying multi-year hydrological memory with Catchment Forgetting Curves, Hydrol. Earth Syst. Sci., 26, 2715–2732, https://doi.org/10.5194/hess-26-2715-2022, 2022.
Dolich, A., Espinoza, E. A., Ebeling, P., Guse, B., Götte, J., Hassler, S., Hauffe, C., Kiesel, J., Heidbüchel, I., Mälicke, M., Müller-Thomy, H., Stölzle, M., Tarasova, L., and Loritz, R.: CAMELS-DE: hydrometeorological time series and attributes for 1582 catchments in Germany (1.0.0), Zenodo [data set], https://doi.org/10.5281/zenodo.13837553, 2024.
Dooge, J. C.: Sensitivity of runoff to climate change: A Hortonian approach, Bulletin of the American Meteorological Society, 73, 2013–2024, 1992.
Dormann, C. F., Elith, J., Bacher, S., Buchmann, C., Carl, G., Carré, G., Marquéz, J. R. G., Gruber, B., Lafourcade, B., Leitão, P. J., Münkemüller, T., McClean, C., Osborne, P. E., Reineking, B., Schröder, B., Skidmore, A. K., Zurell, D., and Lautenbach, S.: Collinearity: a review of methods to deal with it and a simulation study evaluating their performance, Ecography, 36, 27–46, https://doi.org/10.1111/j.1600-0587.2012.07348.x, 2013.
Fowler, K., Zhang, Z., and Hou, X.: CAMELS-AUS v2: updated hydrometeorological timeseries and landscape attributes for an enlarged set of catchments in Australia (2.03), Zenodo [data set], https://doi.org/10.5281/zenodo.14289037, 2024.
Fowler, K. J. A., Zhang, Z., and Hou, X.: CAMELS-AUS v2: updated hydrometeorological time series and landscape attributes for an enlarged set of catchments in Australia, Earth Syst. Sci. Data, 17, 4079–4095, https://doi.org/10.5194/essd-17-4079-2025, 2025.
Fu, G., Charles, S. P., and Chiew, F. H. S.: A two-parameter climate elasticity of streamflow index to assess climate change effects on annual streamflow, Water Resour. Res., 43, https://doi.org/10.1029/2007WR005890, 2007.
Gnann, S.: SebastianGnann/Streamflow_sensitivities: First release (v1.0.0), Zenodo [code], https://doi.org/10.5281/zenodo.18302902, 2026.
Harman, C. J., Troch, P. A., and Sivapalan, M.: Functional model of water balance variability at the catchment scale: 2. Elasticity of fast and slow runoff components to precipitation change in the continental United States, Water Resour. Res., 47, 1–12, https://doi.org/10.1029/2010WR009656, 2011.
Harrigan, S., Hannaford, J., Muchan, K., and Marsh, T. J.: Designation and trend analysis of the updated UK Benchmark Network of river flow stations: the UKBN2 dataset, Hydrol. Res., 49, 552–567, https://doi.org/10.2166/nh.2017.058, 2018.
Institute of Hydrology: Low flow studies report No. 1: Research report, Wallingford, UK: Institute of Hydrology, 1980.
Kratzert, F., Nearing, G., Addor, N., Erickson, T., Gauch, M., Gilon, O., Gudmundsson, L., Hassidim, A., Klotz, D., Nevo, S., Shalev, G., and Matias, Y.: Caravan – A global community dataset for large-sample hydrology, Sci. Data, 10, 61, https://doi.org/10.1038/s41597-023-01975-w, 2023.
Kratzert, F., Nearing, G., Addor, N., Erickson, T., Gauch, M., Gilon, O., Gudmundsson, L., Hassidim, A., Klotz, D., Nevo, S., Shalev, G., and Matias, Y.: Caravan – A global community dataset for large-sample hydrology (1.6), Zenodo [data set], https://doi.org/10.5281/zenodo.7944025, 2025.
Lebecherel, L., Andréassian, V., and Perrin, C.: On regionalizing the Turc–Mezentsev water balance formula, Water Resour. Res., 49, 7508–7517, https://doi.org/10.1002/2013WR013575, 2013.
Lehner, F., Wood, A. W., Vano, J. A., Lawrence, D. M., Clark, M. P., and Mankin, J. S.: The potential to reduce uncertainty in regional runoff projections from climate models, Nat. Clim. Change, 9, 926–933, https://doi.org/10.1038/s41558-019-0639-x, 2019.
Loritz, R., Dolich, A., Acuña Espinoza, E., Ebeling, P., Guse, B., Götte, J., Hassler, S. K., Hauffe, C., Heidbüchel, I., Kiesel, J., Mälicke, M., Müller-Thomy, H., Stölzle, M., and Tarasova, L.: CAMELS-DE: hydro-meteorological time series and attributes for 1582 catchments in Germany, Earth Syst. Sci. Data, 16, 5625–5642, https://doi.org/10.5194/essd-16-5625-2024, 2024.
Matanó, A., Hamed, R., Brunner, M. I., Barendrecht, M. H., and Van Loon, A. F.: Drought decreases annual streamflow response to precipitation, especially in arid regions, Hydrol. Earth Syst. Sci., 29, 2749–2764, https://doi.org/10.5194/hess-29-2749-2025, 2025.
McMillan, H. K., Krueger, T., and Freer, J. E.: Benchmarking observational uncertainties for hydrology: Rainfall, river discharge and water quality, Hydrol. Process., 26, 4078–4111, https://doi.org/10.1002/hyp.9384, 2012.
McMillan, H. K., Westerberg, I. K., and Krueger, T.: Hydrological data uncertainty and its implications, WIREs Water, 5, e1319, https://doi.org/10.1002/wat2.1319, 2018.
Milly, P. C. D. and Dunne, K. A.: Potential evapotranspiration and continental drying, Nat. Clim. Change, 6, 946–949, https://doi.org/10.1038/nclimate3046, 2016.
Němec, J. and Schaake, J.: Sensitivity of water resource systems to climate variation, Hydrol. Sci. J., 27, 327–343, https://doi.org/10.1080/02626668209491113, 1982.
Newman, A. J., Clark, M. P., Sampson, K., Wood, A., Hay, L. E., Bock, A., Viger, R. J., Blodgett, D., Brekke, L., Arnold, J. R., Hopson, T., and Duan, Q.: Development of a large-sample watershed-scale hydrometeorological data set for the contiguous USA: data set characteristics and assessment of regional variability in hydrologic model performance, Hydrol. Earth Syst. Sci., 19, 209–223, https://doi.org/10.5194/hess-19-209-2015, 2015.
Newman, A. J., Sampson, K., Clark, M., Bock, A., Viger, R., Blodgett, D., Addor, N., and Mizukami, M: CAMELS: Catchment Attributes and MEteorology for Large-sample Studies (1.2), Zenodo [data set], https://doi.org/10.5065/D6MW2F4D, 2022.
Nijssen, B., O'Donnell, G. M., Hamlet, A. F., and Lettenmaier, D. P.: Hydrologic Sensitivity of Global Rivers to Climate Change, Clim. Change, 50, 143–175, https://doi.org/10.1023/A:1010616428763, 2001.
Nijzink, R. C. and Schymanski, S. J.: Vegetation optimality explains the convergence of catchments on the Budyko curve, Hydrol. Earth Syst. Sci., 26, 6289–6309, https://doi.org/10.5194/hess-26-6289-2022, 2022.
Peterson, T. J., Saft, M., Peel, M. C., and John, A.: Watersheds may not recover from drought, Science, 372, 745–749, https://doi.org/10.1126/science.abd5085, 2021.
Roderick, M. L. and Farquhar, G. D.: A simple framework for relating variations in runoff to variations in climatic conditions and catchment properties, Water Resour. Res., 47, 1–11, https://doi.org/10.1029/2010WR009826, 2011.
Saft, M., Western, A. W., Zhang, L., Peel, M. C., and Potter, N. J.: The influence of multiyear drought on the annual rainfall-runoff relationship: An Australian perspective, Water Resour. Res., 51, 2444–2463, https://doi.org/10.1002/2014WR015348, 2015.
Sankarasubramanian, A., Vogel, R. M., and Limbrunner, J. F.: Climate elasticity of streamflow in the United States, Water Resour. Res., 37, 1771–1781, https://doi.org/10.1029/2000WR900330, 2001.
Sawicz, K., Wagener, T., Sivapalan, M., Troch, P. A., and Carrillo, G.: Catchment classification: empirical analysis of hydrologic similarity based on catchment function in the eastern USA, Hydrol. Earth Syst. Sci., 15, 2895–2911, https://doi.org/10.5194/hess-15-2895-2011, 2011.
Schaake, J. C.: From climate to flow., John Wiley and Sons Inc., New York, 177–206, ISBN 978-0-471-61838-6, 1990.
Sen, P. K.: Estimates of the Regression Coefficient Based on Kendall's Tau, J. Am. Stat. Assoc., 63, 1379–1389, https://doi.org/10.1080/01621459.1968.10480934, 1968.
Steinschneider, S., Yang, Y.-C. E., and Brown, C.: Panel regression techniques for identifying impacts of anthropogenic landscape change on hydrologic response, Water Resour. Res., 49, 7874–7886, https://doi.org/10.1002/2013WR013818, 2013.
Tang, Y., Tang, Q., Wang, Z., Chiew, F. H. S., Zhang, X., and Xiao, H.: Different Precipitation Elasticity of Runoff for Precipitation Increase and Decrease at Watershed Scale, J. Geophys. Res. Atmospheres, 124, 11932–11943, https://doi.org/10.1029/2018JD030129, 2019.
Tang, Y., Tang, Q., and Zhang, L.: Derivation of Interannual Climate Elasticity of Streamflow, Water Resour. Res., 56, e2020WR027703, https://doi.org/10.1029/2020WR027703, 2020.
Turner, S., Hannaford, J., Barker, L. J., Suman, G., Killeen, A., Armitage, R., Chan, W., Davies, H., Griffin, A., Kumar, A., Dixon, H., Albuquerque, M. T. D., Almeida Ribeiro, N., Alvarez-Garreton, C., Amoussou, E., Arheimer, B., Asano, Y., Berezowski, T., Bodian, A., Boutaghane, H., Capell, R., Dakhaoui, H., Daòhelka, J., Do, H. X., Ekkawatpanit, C., El Khalki, E. M., Fleig, A. K., Fonseca, R., Giraldo-Osorio, J. D., Goula, A. B. T., Hanel, M., Horton, S., Kan, C., Kingston, D. G., Laaha, G., Laugesen, R., Lopes, W., Mager, S., Rachdane, M., Markonis, Y., Medeiro, L., Midgley, G., Murphy, C., O'Connor, P., Pedersen, A. I., Pham, H. T., Piniewski, M., Renard, B., Saidi, M. E., Schmocker-Fackel, P., Stahl, K., Thyer, M., Toucher, M., Tramblay, Y., Uusikivi, J., Venegas-Cordero, N., Visessri, S., Watson, A., Westra, S., and Whitfield, P. H.: ROBIN: Reference observatory of basins for international hydrological climate change detection, Sci. Data, 12, 654, https://doi.org/10.1038/s41597-025-04907-y, 2025.
Wagener, T., Reinecke, R., and Pianosi, F.: On the evaluation of climate change impact models, WIREs Clim. Change, 13, e772, https://doi.org/10.1002/wcc.772, 2022.
Weiler, M., Gnann, S., and Stahl, K.: Streamflow sensitivity regimes of alpine catchments: seasonal relationships with elevation, temperature, and glacier cover, Environ. Res. Lett., 20, 074068, https://doi.org/10.1088/1748-9326/ade26c, 2025.
Woods, R. A.: Analytical model of seasonal climate impacts on snow hydrology: Continuous snowpacks, Adv. Water Resour., 32, 1465–1481, https://doi.org/10.1016/j.advwatres.2009.06.011, 2009.
Xiao, M., Gao, M., Vogel, R. M., and Lettenmaier, D. P.: Runoff and Evapotranspiration Elasticities in the Western United States: Are They Consistent With Dooge's Complementary Relationship?, Water Resour. Res., 56, e2019WR026719, https://doi.org/10.1029/2019WR026719, 2020.
Zhang, L., Dawes, W. R., and Walker, G. R.: Response of mean annual evapotranspiration to vegetation changes at catchment scale, Water Resour. Res., 37, 701–708, https://doi.org/10.1029/2000WR900325, 2001.
Zhang, Y., Viglione, A., and Blöschl, G.: Temporal Scaling of Streamflow Elasticity to Precipitation: A Global Analysis, Water Resour. Res., 58, e2021WR030601, https://doi.org/10.1029/2021WR030601, 2022.
Zhang, Y., Zheng, H., Zhang, X., Leung, L. R., Liu, C., Zheng, C., Guo, Y., Chiew, F. H. S., Post, D., Kong, D., Beck, H. E., Li, C., and Blöschl, G.: Future global streamflow declines are probably more severe than previously estimated, Nat. Water, 1, https://doi.org/10.1038/s44221-023-00030-7, 2023.
Zhou, S., Yu, B., Huang, Y., and Wang, G.: The complementary relationship and generation of the Budyko functions, Geophys. Res. Lett., 42, 1781–1790, https://doi.org/10.1002/2015GL063511, 2015.
Short summary
The extent to which streamflow varies in response to variability in precipitation and potential evaporation is essential for understanding climate change impacts on water resources. This so-called streamflow sensitivity is often estimated directly from observational data, but the robustness of these estimates remains unclear. Through systematic examination of existing approaches, we highlight uncertainties inherent in all approaches and discuss their origins.
The extent to which streamflow varies in response to variability in precipitation and potential...