SWS Academic Research eLibraryEarth & Planetary Sciences

Scholarly record

ANNUAL AND INTRA-ANNUAL CHANGES OF SURFACE WATER RESOURCES IN EAST-AEGEAN RIVER BASIN IN BULGARIA ACCORDING TO CLIMATE SCENARIOS RCP 2.6, 4.5, AND 8.5

Eram Artinyan, Petko Tsarev

First published: 2026DOI pendingView metrics

Abstract

Studies on the effect of climate change on water resources in the 21st century indicate an increase in intense rainfall, an increase in the duration of the dry season, and a decrease in snowfall and, accordingly, snow cover. Based on data from the EURO-CORDEX project, the average multi-year monthly runoff amounts (Copernicus Climate Change Service, Climate Data Store, 2021) for each 30-year period and for the reference period for a rectangular area covering the territory of Bulgaria have been calculated. Climatic projections of changes in surface runoff for East-Aegean River Basin District are studied in greater detail, because the basin comprises three important cross-border rivers in South Bulgaria flowing to Turkey and Greece: Maritsa, Tundzha and Arda Rivers. Results for East-Aegean River Basin (EARB) area show that projected annual runoff from scenario RCP 2.6 decreases by nearly 8% in the period 2011-2040, for the two considered GCM+RCM+Hydrological model combinations, and for 2071-2100 for one of the combinations, but remains at the reference level and above it for the period 2041-2070. For the second scenario, RCP 4.5, the annual runoff is decreasing by 5% and 2% for the two model combinations for 2011-2040 and nearly 20% relative to the reference period for 2041-2070. That second 30 year period shows the largest projected decrease in runoff in the EARB on an annual basis. For the third scenario, RCP 8.5, with the largest increase in the average annual global air temperature, there is an increase in annual runoff between 3% and 18% for the first two periods 2011-2040 and 2041-2070 and a decrease in the third period between 9% and 12%. Here, the largest projected increase is reported. Projected changes in intra-annual runoff are also function of the climate scenario and the period. According to climate scenarios RCP 2.6, RCP 4.5, and RCP 8.5 in the intra-annual distribution of runoff in EARB will appear a clear shift towards increasing of January and February runoff and decrease in spring and summer months for the three climate periods 2011-2040, 2041-2070, and 2071-2100. The study has the goal to project changes of the surface runoff in the area until the end of 21st century and therefore to assist institutions in taking measures to address water scarcity and minimize the adverse effects of the intra-annual redistribution of water resources.

Publication details

Title
ANNUAL AND INTRA-ANNUAL CHANGES OF SURFACE WATER RESOURCES IN EAST-AEGEAN RIVER BASIN IN BULGARIA ACCORDING TO CLIMATE SCENARIOS RCP 2.6, 4.5, AND 8.5
Authors
Eram Artinyan, Petko Tsarev
Proceedings
SWS 2026 Conference Preprints
Publisher
STEF92 Technology
Year
2026
Pages
Not available yet
ISSN
1314-2704; 1314-2704
ISBN
Not available yet
Language
en
Publication type
Preprint
References15
  1. Berg, P., Photiadou, C., Bartosova, A., Biermann, J., Capell, R., Chinyoka, S., Fahlesson, T., Franssen, W., Hundecha, Y., Isberg, K., Ludwig, F., Mook, R., Muzuusa, J., Nauta, L., Rosberg, J., Simonsson, L., Sjökvist, E., Thuresson, J., and van der Linden, E., (2021): Hydrology related climate impact indicators from 1970 to 2100 derived from bias adjusted European climate projections. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). DOI: 10.24381/cds.73237ad6 (Accessed on 10-Sep-2025)

  2. Kreienkamp, F., Huebener, H., Linke, C. et al. Good practice for the usage of climate model simulation results - a discussion paper. Environ Syst Res 1, 9 (2012). DOI: 10.1186/2193-2697-1-9

  3. Copernicus Climate Change Service, Climate Data Store, (2021): Hydrology related climate impact indicators from 1970 to 2100 derived from bias adjusted European climate projections. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). DOI: 10.24381/cds.73237ad6 (Accessed on 10-Sep-2025)

  4. https://cds.climate.copernicus.eu/datasets/sis-hydrology-variables-derived-projections

  5. https://euro-cordex.net/imperia/md/content/csc/cordex/20180130-eurocordex-simulations.pdf

  6. Droppers, B., Franssen, W. H. P., van Vliet, M. T. H., Nijssen, B., and Ludwig, F. (2020): Simulating human impacts on global water resources using VIC-5, Geosci. Model Dev., 13, 5029-5052, DOI: 10.5194/gmd-13-5029-2020.

  7. Berg, P., Feldmann, H., & Panitz, H. J. (2012). Bias correction of high resolution regional climate model data. Journal of Hydrology, 448, 80-92.

  8. Donnelly, C., W. Greuell, J. Andersson, D. Gerten, G. Pisacane, P. Roudier, and F. Ludwig. (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.

  9. Greuell, W., Andersson, J. C. M., Donnelly, C., Feyen, L., Gerten, D., Ludwig, F., Pisacane, G., Roudier, P., and Schaphoff, S. (2015): Evaluation of five hydrological models across Europe and their suitability for making projections under climate change, Hydrol. Earth Syst. Sci. Discuss., 12, 10289-10330, DOI: 10.5194/hessd-12-10289-2015, 2015.

  10. Hundecha, Y., Arheimer, B., Berg, P., Capell, R., Musuuza, J., Pechlivanidis, I., Photiadou, C. (2020) Effect of model calibration strategy on climate projections of hydrological indicators at a continental scale, Climatic Change, in publication.

  11. Nijssen, B., O'Donnell, G. M., Lettenmaier, D. P., Lohmann, D., & Wood, E. F. (2001). Predicting the Discharge of Global Rivers. Journal of Climate, 14(15), 3307-3323. DOI: 10.1175/1520-0442(2001)014<3307:PTDOGR>2.0.CO;2

  12. Caesar, J., Palin, E., Liddicoat, S., Lowe, J., Burke, E., Pardaens, A., Sanderson, M., & Kahana, R. (2013). Response of the HadGEM2 Earth System Model to Future Greenhouse Gas Emissions Pathways to the Year 2300. Journal of Climate, 26(10), 3275-3284. DOI: 10.1175/JCLI-D-12-00577.1

  13. van Meijgaard, E., van Ulft, L. H., van de Berg, W. J., Bosveld, F. C., van den Hurk, B. J. J. M., Lenderink, G., & Siebesma, A. P. (2008). The KNMI regional atmospheric climate model RACMO, version 2.1 (Technical Report TR-302). Royal Netherlands Meteorological Institute (KNMI), De Bilt, Netherlands

  14. Arheimer, B., Pimentel, R., Isberg, K., Crochemore, L., Andersson, J. C. M., Hasan, A., and Pineda, L. (2020). Global catchment modelling using World-Wide HYPE (WWH), open data and stepwise parameter estimation. Hydrology and Earth System Sciences 24, pp. 535-559.

  15. Joshi, M., Hawkins, E., Sutton, R. et al. (2011). Projections of when temperature change will exceed 2 °C above pre-industrial levels. Nature Clim Change 1, 407-412 (2011). DOI: 10.1038/nclimate1261

Back to publication list