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IDENTIFICATION OF HOMOGENEOUS REGIONS FOR RUNOFF ESTIMATION IN UNGAUGED BASINS
Abstract
This paper addresses the problem of defining appropriate characteristic which leads to homogeneous regions identifi cation, required for application of multiple nonlinear regression methodology for interpolation of hydrologic data from gauged to ungauged basins. The underlying methodology of mu ltiple nonlinear regression is based on theory of standardization and normalization of correla tion. In order to obtain synthetic runoff series at ungauged basins, one of the key steps is estimation of spatial correlation function. There are theoretical and empiri cal correlation functions. While empirical correlation function is estimated according to correlation coefficients of runoff series at gauged basins and their mutual distance, its pair - theoretical correlation function is merely a shift of empirical correlation function. This shift is made to achieve correlation coefficient of one for zero distance. However, this shift is acceptable only if performed in homogeneous region comprising of basins which behave in a hydrologically similar way. A basin characteristic that describes hydrol ogical behavior similarity is examined among morphologic characteristic, basin proxi mity, and runoff time series statistics. There are two criteria for homogeneity control. They refer to empirical and theoretical spatial correlation function, and eventually identify donor catchments for ungauged basin. Study area for research is the territory of Republic of Serbia without provinces of Vojvodina and Kosovo. Basins up to area of 1000 km2 are taken into consideration. Within the period 1961-2005, three sub-periods of 15 years each are examined for mean monthly runoff time series simulation potential at ungauged basins.
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References4
Nathan, R.J. and McMahon T.A., (1990) Identification of Homogeneous regions for the Purpose of Regionalisation, Journal of Hydrology 121, pp. 217-238;
Blagojevic B ., S. Prohaska, D.Radivojevic, A. Ilic (2009) Spatial interpolation of mean monthly flow series by nonlinear correlation model applied in the Ibar river basin, University of Nis: Facta Un iversitatis, Series: Architecture and Civil Engineering, Vol.7, No. 1, pp. 83 - 94
McCuen R. H. (2003) Modeling hydrologi c change: statistical methods, CRC Press LLC, Boca Raton, Florida.
Blagojevic B., Plavsic J., Zivkovic N., (2010) Mean flow re gionalization in the territory of Serbia, Proceedings of Faculty of Civil Engineering and Architecture, University of Nis, No. 25, pp.1-8
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