Scientific Research and Essay Vol. 4 (4) pp. 217-225, April, 2009 Available online at http://www.academicjournals.org/SRE ISSN 1992-2248 © 2009 Academic Journals Full Length Research Paper Evaluating spatial variability and scale effects on hydrologic processes in a midsize river basin Osman Yıldız 1* and Ana P. Barros 2 1 Kırıkkale University, Faculty of Engineering, Department of Civil Engineering, 71451 Kırıkkale, Turkey. 2 Duke University, Pratt School of Engineering, Department of Civil and Environmental Engineering, Durham, NC 27708. Accepted 16 March, 2009 The impact of spatial variability and scale on the dynamics of hydrologic processes in the Monongahela river basin of USA was investigated using a physically based spatially distributed hydrologic model developed by Yildiz (2001). The hydrologic model simulations were performed at 1 and 5 km spatial scales for a 5 month period from April through August of 1993. Effects of spatial variability in topography, vegetation and hydrogeology and of spatial scale were evaluated through comparisons of the simulated and observed streamflows for the prescribed resolutions at different locations across the river basin. The evaluation of observed and simulated streamflows using the statistical measures of mean, standard deviation, coefficient of variation, root mean square error and bias showed that model statistics of streamflow followed closely the spatial patterns of those of existing observations, that is, the model captured the space-time features of the 1993 flood across the basin. The changes in the nature of the rainfall-runoff response due to changes in the spatial resolution of the model indicated that there was also a change in governing physical processes at different resolutions. Here, this change was expressed in terms of the relative contributions of surface and subsurface flows. Key words: Spatial variability; spatial scale; hydrologic model; streamflow, digital elevation model, stream network. INTRODUCTION The influence of spatial variability and scale on the hydro- logic response of watersheds and their importance in hydrologic modeling have been widely studied by various investigators (e.g., Amorocho 1961; Eagleson, 1970; Dunne and Leopold, 1978; Wood et al., 1988; Entekhabi and Eagleson, 1989; Wood et al., 1990; Seyfried and Wilcox, 1995). In watersheds, spatial variability often results from interactions between ecosystem character- ristics such as topography, vegetation, and geology (Sey- fried and Wilcox, 1995). As the spatial scale of a water- shed increases, the watershed tends to attenuate the complex, local patterns of runoff generation and water fluxes, that is, it functions as a low-pass filter. As pointed out by Amorocho (1961) the runoff generation at large scales becomes somewhat insensitive to rainfall intensity changes recorded at individual gauges and the catch- *Corresponding author. E-mail: osmanyildiz@kku.edu.tr. or osmanyildiz2000@hotmail.com. Tel.: +90 318 357 4242. Fax: +90 318 357 2459. ment-scale rainfall-runoff appears to be governed by macroscale catchment characteristics. Therefore, the transition representing hydrological processes in models using microscale to macroscale parameterization is a highly nonlinear process. As spatial scale increases spatial variability may signi- ficantly affect hydrological processes in watersheds. investigating effects of scale on the hydrologic response of a catchment Wood et al. (1988) proposed the so-called representative elementary area (REA) concept which is considered to be the smallest or critical representation of area at which implicit continuum assumptions can be applied for the spatially variable controls and parameters in physical models and therefore, spatial patterns are no longer needed to be considered explicitly. According to the authors, a REA can be defined in large-scale hydro- logic modeling beyond which spatial heterogeneities in vegetation, topography, and soil can be incorporated into hydrologic models without considering the detailed spatial pattern of such heterogeneity within each grid cell. Conventional lumped rainfall-runoff models generally