Abstract
Our study is aimed at detection of directional trends in streamflow data observed in large rivers located in different climatic zones and attribution of the detected changes to climate drivers. We consider detection and attribution as interrelated study stages within a suggested hypothesis testing framework with the use of a hydrological model. First, we test the significance of the trends in the observed streamflow data series of 74 to 82 years long and evaluate the model’s ability to reproduce the trends, so that the trends in the simulated data are statistically indistinguishable from the corresponding observed trends. Herewith, the model is forced by the reanalysis climate data. Then, for the basins where the model reproduces the trends, we move to the attribution stage of the study. At this stage, the hydrological model is forced by the counterfactual (detrended) climate data. If the trend is not detected in the counterfactual-climate-forced simulations, we conclude that the detected observed changes are likely to be attributed to the climate trend. The suggested testing procedure is applied for four river basins: Lena, Selenga, Vyatka, and Pechora. The corresponding hydrological models are developed on the basis of the ECOMAG modeling platform. We conclude that the detected trends in the observed annual flow data series for the Lena, Selenga, and Vyatka rivers, as well as the trends in high flow for the Lena and Selenga rivers, can be attributed to climate drivers with a high confidence. Regional differences in basin mechanisms governing the detected changes are analyzed.
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Data Availability
The climate datasets are available in the ISI-MIP Repository https://data.isimip.org/. The Harmonized World Soil Database (HWSD) is available at http://www.fao.org/soils-portal/data-hub/soil-maps-and-databases/harmonized-world-soil-database-v12; the Global Land Cover Characterization (GLCC) datasets are available at https://www.usgs.gov/centers/eros/science/usgs-eros-archive-land-cover-products-global-land-cover-characterization-glcc; HYDRO1k digital elevation model is available at https://www.usgs.gov/centers/eros/science/usgs-eros-archive-digital-elevation-hydro1k. The streamflow datasets analyzed during the current study are not publicly available due to the regular rules of the Russian Agency for Hydrometeorological Monitoring (Roshydromet) but are available from the corresponding author on reasonable request.
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Acknowledgements
The numerical experiments were designed within the framework of the State Assignment theme № FMWZ-2022-0001. The present work was carried out within the framework of the Panta Rhei Research Initiative of the International Association of Hydrological Sciences (IAHS).
Funding
Simulations by the ECOMAG model were financially supported by the Russian Science Foundation (Grant 19-17-00215).
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The study conception was developed by Alexander Gelfan. All authors contributed to the study design and analysis of the results. Material preparation, data collection, and simulations were performed by Andrey Kalugin and Inna Krylenko. The first draft of the manuscript was written by Alexander Gelfan. All authors read and approved the manuscript.
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Gelfan, A., Kalugin, A. & Krylenko, I. Detection, attribution, and specifying mechanisms of hydrological changes in geographically different river basins. Climatic Change 176, 122 (2023). https://doi.org/10.1007/s10584-023-03557-6
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DOI: https://doi.org/10.1007/s10584-023-03557-6