Abstract
Downscaling of atmospheric climate parameters is a sophisticated tool to develop statistical relationships between large-scale atmospheric variables and local-scale meteorological variables. In this study, the variables selected from the National Centre for Environmental Prediction and National Centre for Atmospheric Research (NCEP/NCAR) reanalysis data set were used as predictors for the downscaling of monthly precipitation in a watershed located in north-western Turkey where station records terminated two decades ago. An Artificial Neural Network (ANN) based approach was used to downscale global climate predictors that are positively correlated to the existing time frame of precipitation data in the basin. The downscaled precipitation information were used to extend the non-existing data from the meteorological station, which were later correlated with groundwater level data obtained from automatic pressure transducers that continuously record depth to groundwater. The results of the study showed that, among a large set of NCEP/NCAR parameters, surface precipitation data recorded at the meteorological station was strongly correlated with precipitation rate, air temperature and relative humidity at surface and air temperature at 850, 500, and 200 hPa pressure levels, and geopotential heights at 850 and 200 hPa pressure levels. The gaps in station data were then filled with the correlations obtained from NCEP/NCAR parameters and a complete precipitation data set was obtained that extended to current time line. This extended precipitation time series was later correlated with the existing groundwater level data from an alluvial plain in order to develop a general relationship that can be used in basin-wide water budget estimations. The proposed methodology is believed to serve the needs of engineers and basin planners who try to create a link between related hydrological variables under data-limited conditions.
Similar content being viewed by others
References
ASCE Task Committee on Artificial Neural Networks in Hydrology (2000) Artificial neural networks in hydrology. II. hydrologic applications. J Hydrol Eng 5(2):124–137
Bardossy A, Bogardi I, Matyasovszky I (2005) Fuzzy rule-based downscaling of precipitation. Theor Appl Climatol 82:119–129. doi:10.1007/s00704-004-0121-0
Benestad RE, Hanssen-Bauer I, Førland EJ (2007) An evaluation of statistical models for downscaling precipitation and their ability to capture long-term trends. Int J Climatol 27:649–655. doi:10.1002/joc.1421
Burger G (1996) Expanded downscaling for generating local weather scenarios. Clim Res 7:111–128
Crane RG, Hewitson BC (1998) Doubled CO2 precipitation changes for the Susquehanna basin: downscaling from the GENESIS general circulation model. Int J Climatol 18:65–76. doi:10.1002/(SICI)1097-0088(199801)18:1<65::AID-JOC222>3.0.CO;2-9
Dibike YB, Coulibaly P (2005) Hydrologic impact of climate change in the Saguenay watershed: comparison of downscaling methods and hydrologic models. J Hydrol 307:145–163. doi:10.1016/j.jhydrol.2004.10.012
Fistikoglu O, Okkan U (2011) Statistical downscaling of monthly precipitation using NCEP/NCAR reanalysis data for Tahtali River Basin in Turkey. J Hydrol Eng 16:157–164. doi:10.1061/(ASCE)HE.1943-5584.0000300)
Fowler HJ, Ekström M, Kilsby CG, Jones PD (2005) New estimates of future changes in extreme rainfall across the UK using regional climate model integrations. 1. Assessment of control climate. J Hydrol 300(1-4):212–233. doi:10.1016/j.jhydrol.2004.06.017
Fowler HJ, Blenkinsop S, Tebaldi C (2007) Linking climate change modelling to impacts studies: recent advances in downscaling techniques for hydrological modelling. Int J Climatol 27:1547–1578. doi:10.1002/joc.1556
Frei C, Christensen JH, Deque M, Jacob D, Jones RG, Vidale PL (2003) Daily precipitation statistics in regional climate models: evaluation and intercomparison for the European Alps. J Geophys Res 108(D3):4124. doi:10.1029/2002JD002287
Frei C, Scholl R, Fukutome S, Schmidli J, Vidale PL (2006) Future change of precipitation extremes in Europe: an intercomparison of scenarios from regional climate models. J Geophys Res-Atmos 111:D06105. doi:10.1029/2005JD005965
Gunduz O, Simsek C (2011) Influence of climate change on shallow groundwater resources: the link between precipitation and groundwater levels in alluvial systems. In Proceedings of the NATO Advanced Research Workshop (ARW) on Climate Change and its Effects on Water Resources, edited by A. Baba, G. Tayfur, O. Gunduz, K.W.F. Howard, M.J. Friedel and A. Chambel, 225–234. doi: 10.1007/978-94-007-1143-3_25
Kalnay E, Kanamitsu M, Kistler R, Collins W, Deaven D, Gandin L, Iredell M, Saha S, White G, Woollen J, Zhu Y, Chelliah M, Ebisuzaki W, Higgins W, Janowiak J, Mo K.C, Ropelewski C, Wang J, Leetmaa A, Reynolds R, Jenne R, Joseph D (1996) The NCEP/NCAR 40-year reanalysis project. Bull Am Meteorol Soc 77:437–471. doi:10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2
Leung RL, Mearns LO, Giorgi F, Wilby RL (2003) Regional climate research: needs and opportunities. Bull Am Meteorol Soc 84:89–95. doi:10.1175/BAMS-84-1-89
Maheras P, Tolika K, Anagnostopoulou C, Vafiadis M, Patrikas I, Flocas H (2004) On the relationships between circulation types and changes in rainfall variability in Greece. Int J Climatol 24:1695–1712. doi:10.1002/joc.1088
Mearns LO, Bogardi I, Giorgi F, Matyasovszky I, Palecki M (1999) Comparison of climate change scenarios generated from regional climate model experiments and statistical downscaling. J Geophys Res 104:6603–6621. doi:10.1029/1998JD200042
Murphy JM (1999) An evaluation of statistical and dynamical techniques for downscaling local climate. J Clim 12:2256–2284. doi:10.1175/1520-0442(1999)012<2256:AEOSAD>2.0.CO;2
Schoof JT, Pryor SC, Robeson SM (2007) Downscaling daily maximum and minimum temperatures in the midwestern USA: a hybrid empirical approach. Int J Climatol 27:439–454. doi:10.1002/joc.1412
Tatli H, Dalfes HN, Mentes SS (2004) A statistical downscaling method for monthly total precipitation over Turkey. Int J Climatol 24:161–180. doi:10.1002/joc.997
Tolika K, Maheras P, Flocas HA, Papadimitriou AA (2006) An evaluation of a general circulation model (GCM) and the NCEP–NCAR reanalysis data for winter precipitation in Greece. Int J Climatol 26:1376–1385. doi:10.1002/joc.1290
von Storch H, Zorita E, Cubasch U (1993) Downscaling of global climate change estimates to regionalscales: an application to Iberian rainfall in wintertime. J Clim 6:1161–1171. doi:10.1175/1520-0442(1993)006<1161:DOGCCE>2.0.CO;2
Wilby RL, Dawson CW, Barrow EM (2002) SDSM—a decision support tool for the assessment of climate change impacts. Environ Model Softw 17:147–159. doi:10.1016/S1364-8152(01)00060-3
Wilby R, Tomlinson O, Dawson C (2003) Multi-site simulation of precipitation by conditional resampling. Clim Res 23:183–194. doi:10.3354/cr023183
Wilby RL, Charles SP, Zorita E et al. (2004). Guidelines for use of climate scenarios developed from statistical downscaling methods, Supporting material of the Intergovernmental Panel on Climate Change, available from the DDC of IPCC TGCIA, 27
Xu CY (1999) From GCMs to river flow: a review of downscaling methods and hydrologic modelling approaches. Prog Phys Geogr 23:229–249. doi:10.1177/030913339902300204
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Fistikoglu, O., Gunduz, O. & Simsek, C. The Correlation Between Statistically Downscaled Precipitation Data and Groundwater Level Records in North-Western Turkey. Water Resour Manage 30, 5625–5635 (2016). https://doi.org/10.1007/s11269-016-1313-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11269-016-1313-y