Abstract
This study investigates the climate change impact on the changes of mean and extreme flows under current and future climate conditions in the Omerli Basin of Istanbul, Turkey. The 15 regional climate model output from the EU-ENSEMBLES project and a downscaling method based on local implications from geophysical variables were used for the comparative analyses. Automated calibration algorithm is used to optimize the parameters of Hydrologiska Byråns Vattenbalansavdel-ning (HBV) model for the study catchment using observed daily temperature and precipitation. The calibrated HBV model was implemented to simulate daily flows using precipitation and temperature data from climate models with and without downscaling method for reference (1960–1990) and scenario (2071–2100) periods. Flood indices were derived from daily flows, and their changes throughout the four seasons and year were evaluated by comparing their values derived from simulations corresponding to the current and future climate. All climate models strongly underestimate precipitation while downscaling improves their underestimation feature particularly for extreme events. Depending on precipitation input from climate models with and without downscaling the HBV also significantly underestimates daily mean and extreme flows through all seasons. However, this underestimation feature is importantly improved for all seasons especially for spring and winter through the use of downscaled inputs. Changes in extreme flows from reference to future increased for the winter and spring and decreased for the fall and summer seasons. These changes were more significant with downscaling inputs. With respect to current time, higher flow magnitudes for given return periods will be experienced in the future and hence, in the planning of the Omerli reservoir, the effective storage and water use should be sustained.
Similar content being viewed by others
References
Bergström, S. (1992). The HBV model—its structure and applications. SMHI Reports RH, No. 4, Norrköping.
Beven. (2011). I believe in climate change but how precautionary do we need to be in planning for the future? Hydrological Processes, 25, 1517–1520.
Booij, M. J. (2005). Impact of climate change on river flooding assessed with different spatial model resolutions. Journal of Hydrology, 303, 176–198. doi:10.1016/j.jhydrol.2004.07.013.
Bostan, P. A., Heuvelink, G. B. M., & Akyurek, S. Z. (2012). Comparison of regression and kriging techniques for mapping the average annual precipitation of turkey. International Journal of Applied Earth Observation and Geoinformation, 19, 115–126.
Bozkurt, D., & Sen, O. L. (2013). Climate change impacts in the Euphrates–Tigris basin based on different model and scenario simulations. Journal of Hydrology, 480, 149–161.
Brundson, C., Fotheringham, A., & Charlton, M. (1996). Geographically weighted regression: a method for exploring spatial nonstationarity. Geographical Analysis, 28, 281–298.
Carrrera-Hernandez, J. J., & Gaskin, S. J. (2007). Spatio temporal analysis of daily precipitation and temperature in the basin of Mexico. Journal of Hydrology, 336, 231–249.
Chen, H., Xu, C. Y., & Guo, S. (2012). Comparison and evaluation of multiple GCMs, statistical downscaling and hydrological models in the study of climate change impacts on runoff. Journal of Hydrology, 434–435, 36–45.
Christensen, J. H., & Christensen, O. B. (2003). Climate modelling: severe summertime flooding in Europe. Nature, 421, 805–806.
Christensen, J. H., Carter, T. R., Rummukainen, M., & Amanatidis, G. (2007). Evaluating the performance and utility of regional climate models: the PRUDENCE project. Climate Change, 81, 1–6.
Daly, C., Gibson, W. P., Taylor, G. H., Johnson, G. L., & Pasteris, P. (2002). A knowledge-based approach to the statistical mapping of climate. Climate Research, 22, 99–113.
Daly, C., Halbleib, M., Smith, J. I., Gibson, W. P., Doggett, M. K., Taylor, G. H., Curtis, J., & Pasteris, P. P. (2008). Physiographically sensitive mapping of climatological temperature and precipitation across the conterminous united states. International Journal of Climatology, 28, 2031–2064.
Dankers, R., Feyen, L. (2008). Climate change impact on flood hazard in Europe: an assessment based on high resolution climate simulations. Journal of Geophysical Research, 113(D19105)
Doherty, J. (2004). PEST: model independent parameter estimation. Fifth edition of user manual. Brisbane, Australia: Watermark Numerical Computing.
ESRI (Environmental Systems Research Institute). (2014). ArcGIS help 10.1. ArcGIS Resources: http://resources.arcgis.com/en/help/main/10.1/index.html#/What_are_geostatistical_interpolation_techniques/003100000031000000/. Accessed: June 24, 2014.
Feidas, H., Kontos, T., Soulakellis, N., & Lagouvardos, K. (2007). A GIS tool for the evaluation of the precipitation forecasts of a numerical weather prediction model using satellite data. Computers & Geosciences, 33, 989–1007.
Fotheringham, A. S., Brunsdon, C., & Charlton, M. E. (2002). Geographically weighted regression: the analysis of spatially varying relationships. Chichester: Wiley.
Fowler, H. J., Blenkinsop, S., & Tebaldi, C. (2007). Linking climate change modelling to impacts studies: recent advances in downscaling techniques for hydrological modelling. International Journal of Climatology, 27, 1547–1578.
Fu, C., Chen, J., Dong, L., & Jiang, H. (2012). Field investigation and modeling of runoff generation in a granitic catchment in Zhuhai, China. Journal of Hydrology, 458–459, 87–102.
Garcia-Ruiz, J. M., Lopez-Moreno, J. I., Vicente-Serrano, S. M., Lasanta-Martinez, T., & Begueria, S. (2011). Mediterranean water resources in a global change scenario. Earth-Science Reviews, 105, 121–139.
Graham, L. P., Andréasson, J., & Carlsson, B. (2007). Assessing climate change impacts on hydrology from an ensemble of regional climate models, model scales and linking methods—a case study on the Lule river basin. Climate Change, 81, 293–307. doi:10.1007/s10584-006-9215-2.
Ho, H. C., Knudby, A., Sirovyak, P., Xu, Y., Hodul, M., & Herderson, S. B. (2014). Mapping maximum urban air temperature on hot summer days. Remote Sensing of Environment, 154, 38–45.
Hurkmans, R. T. W. L., Terink, W., Uijlenhoet, R., Torfs, P. J. J. F., Jacob, D., & Troch, P. A. (2010). Changes in streamflow dynamics in the Rhine basin under three high-resolution climate scenarios. Journal of Climate, 23, 679–699. doi:10.1175/2009JCLI3066.1.
IBB (Istanbul Metropolitan Municipality). (2014). İstanbul İl ve İlçe Alan Bilgileri. June 15. Accessed September 08, 2014. http://www.ibb.gov.tr/tr-tr/kurumsal/pages/ilceveilkkademe.aspx.
IPCC. (2014). Climate change 2014: impact, adaptation, and vulnerability. Contribution of working group II to the fifth assessment report of the intergovernmental panel on climate change. Cambridge, United Kingdom and New York, NY, USA: Cambridge University Press.
Jia, Q. Y., & Sun, F. H. (2012). Modeling and forecasting process using the HBV model in Liao river delta. Procedia Environmental Sciences, 13, 122–128.
Kamarianakis, Y., Feidas, H., Kokolatos, G., Chrysoulakis, N., & Karatzias, V. (2008). Evaluating remotely sensed rainfall estimates using nonlinear mixed models and geographically weighted regression. Environmental Modelling and Software, 23, 1438–1447.
Kara, F., Yucel, I., Akyurek, Z. (2015). A comparison of different regional climate models and a downscaling method for extreme rainfall estimation under climate change. Hydrol Sciences Journal (under review).
Kay, A. L., Reynard, N. S., & Jones, R. G. (2006). RCM rainfall for UK flood frequency estimation. I. Method and validation. Journal of Hydrology, 318, 151–162.
Kleinn, J., Frei, C., Gurtz, J., Lüthi, D., Vidale, P. L., & Schär, C. (2005). Hydrologic simulations in the Rhine basin driven by a regional climate model. Journal of Geophysical Research, 110, D04102. doi:10.1029/2004JD005143.
Krause, P., Boyle, D. P., & Base, F. (2005). Comparison of different efficiency criteria for hydrological model assessment. Advances in Geosciences, 5, 89–97.
Kult, J., Choi, W., & Choi, J. (2014). Sensitivity of the Snowmelt Runoff Model to snow covered area and temperature inputs. Applied Geography, 55, 30–38.
Lawrence, D., Haddeland, I., Langsholt, E. (2009). Calibration of HBV hydrological models using PEST parameter estimation. OSLO: Norwegian Water Resources and Energy Directorate.
Lespinas, F., Ludwig, W., & Heussner, S. (2014). Hydrological and climatic uncertainties associated with modeling the impact of climate change on water resources of small Mediterranean coastal rivers. Journal of Hydrology, 511, 403–422.
Lindström, G., & Rodhe, A. (1992). Transit times of water in soil lysimeters from modelling of oxygen-18. Water, Air, and Soil Pollution, 65, 83–100.
Lopez-Moreno, J. I., Vicente-Serrano, S. M., Moran-Tejeda, E., Zabalza, J., Lorenzo-Lacruz, J., & Garcia-Ruiz, J. M. (2011). Impact of climate evolution and land use changes on water yield in the ebro basin. Hydrology and Earth System Sciences, 15, 311–322.
Maraun, D., Wetterhall, F., Ireson, A. M., Chandler, R. E., Kendon, E. J., Widmann, M., Brienen, S., Rust, H. W., Sauter, T., Venema, V. K. C., Chun, K. P., Goodess, C. M., Jones, R. G., Onof, C., Vrac, M., & Thiele-Eich, I. (2010). Precipitation downscaling under climate change. Recent developments to bridge the gap between dynamical models and the end user. Reviews of Geophysics, 48, 1–34.
Marquinez, J., Lastra, J., & Garcia, P. (2003). Estimation models for precipitation in mountainous regions: the use of GIS and multivariate analysis. Journal of Hydrology, 270, 1–11.
Ott, I., Duethmann, D., Liebert, J., Berg, P., Feldmann, H., Ihringer, J., Kunstmann, H., Merz, B., Schaedler, G., & Wagner, S. (2013). High-resolution climate change impact analysis on medium-sized river catchments in Germany: an ensemble assessment. Journal of Hydrometeorology, 14, 1175–1193. doi:10.1175/JHM‐D‐12‐091.1.
Propastin, P. (2012). Modifying geographically weighted regression for estimating aboveground biomass in tropical rainforests by multispectral remote sensing data. International Journal of Applied Earth Observation and Geoinformation, 18, 82–90.
Rojas, R., Feyen, L., Bianchi, A., & Dosio, A. (2012). Assessment of future flood hazard in Europe using a large ensemble of bias corrected regional climate simulations. Journal of Geophysical Research. doi:10.1029/2012JD017461.
Sælthun, N. S. (1996). The nordic HBV model. NVE Publication no. 07, 26 pp.
Sunyer, M., Hundecha, Y., Lawrence, D., Madsen, H., Willems, P., Martinkova, M., Vormoor, K., Bürger, G., Kriaučiūnienė, J., Loukas, A., Osuch, M., Yücel, I., & Hanel, M. (2015). Inter-comparison of statistical downscaling methods for projection of extreme precipitation in Europe. Hydrology and Earth System Sciences, 19, 1827–1847.
Tahir, A. A., Chevallier, P., Arnaud, Y., Neppel, L., & Ahmad, B. (2011). Modeling snowmelt-runoff under climate scenarios in the Hunza River basin, Karakoram Range, Northern Pakistan. Journal of Hydrology, 409, 104–117.
Talei, A., Chua, L. H. C., Quek, C., & Jansson, P. E. (2013). Runoff forecasting using a Takagi–Sugeno neuro-fuzzy model with online learning. Journal of Hydrology, 488, 17–32.
TUIK. (2014). Main statistics. Retrieved from Turkish statistical institute official web site: http://www.turkstat.gov.tr/UstMenu.do?metod=temelist
USGS. (2014). NLCD 92 land cover class definitions. retrieved from the USGS land cover institute (LCI): http://landcover.usgs.gov/classes.php
Van der Linden, P., & Mitchell, J. (2009). ENSEMBLES: climate change and its impacts: summary of research and results from the ENSEMBLES project. Exeter, UK: Met Office Hadley Centre.
Varis, O., Kajander, T., & Lemmelä, R. (2004). Climate and water: from climate models to water resources management and vice versa. Climatic Change, 66, 321–344.
Wang, S., Jiao, S., & Xin, H. (2013). Spatio-temporal characteristics of temperature and precipitation in Sichuan province, southwestern china, 1960–2009. Quaternary International, 286, 103–115.
Willems, P. (2009). A time series tool to support the multi-criteria performance evaluation of rainfall-runoff models. Environmental Modelling & Software, 24(3), 311–321.
Yilmaz, K. K., & Yazicigil, H. (2011). Potential impacts of climate change on Turkish water resources: a review. In A. Baba, G. Tayfur, O. Gündüz, K. W. F. Howard, M. J. Friedel, & A. Chambel (Eds.), Climate change and its effects on water resources (pp. 105–114). Netherland: Springer.
Yucel, I., Guventurk, A., & Sen, O. L. (2015). Climate change impacts on snowmelt runoff for mountainous transboundary basins in eastern Turkey. International Journal of Climatology, 35, 215–228.
Zhao, C., Wang, W., & Xing, W. (2012). Regional analysis of extreme temperature indices for the Haihe river basin from 1960 to 2009. Procedia Engineering, 28, 604–607.
Acknowledgments
This study is supported by the European procedures for flood frequency estimation (FloodFreq) Cost Action (ES0901) and TÜBİTAK ARDEB ÇAYDAG Scientific and Technological Research Project Program (1001) with Project No. 110Y036. Authors thank to Deborah Lawrence from Hydrological Modelling Section of Norwegian Water Resources and Energy Directorate on the efforts of calibrating the HBV model.
Compliance with ethical standards
ᅟ
Funding
This study was funded by TUBITAK Cost Action (ES0901) (grant number 110Y036).
Conflict of interest
The authors declare that they have no conflict of interest.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Kara, F., Yucel, I. Climate change effects on extreme flows of water supply area in Istanbul: utility of regional climate models and downscaling method. Environ Monit Assess 187, 580 (2015). https://doi.org/10.1007/s10661-015-4808-8
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s10661-015-4808-8