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Temporal scales and hydrological regimes: Implications for flood frequency scaling
Author(s) -
Robinson Justin S.,
Sivapalan Murugesu
Publication year - 1997
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/97wr01964
Subject(s) - flood myth , storm , surface runoff , scaling , environmental science , drainage basin , hydrology (agriculture) , dimensionless quantity , climatology , meteorology , geology , geography , physics , mathematics , ecology , geometry , cartography , archaeology , geotechnical engineering , mechanics , biology
This paper investigates the interactions among storm, within‐storm, between‐storm, and seasonal variabilities of rainfall and catchment response time and how these interactions can help identify different hydrological regimes. Using the theoretical framework provided by a simple linear rainfall‐runoff model and intuitive reasoning, five hydrological regimes, ranging from very fast to very slow, are identified on the basis of two dimensionless ratios of the constituent timescales. For each regime, the paper addresses the question of how the interactions between the timescales in rainfall and in the runoff response manifest in the flood peak response and in the shape of the flood frequency curve, and the resulting implications for the scaling of the flood frequency curve between catchments. It is found that, for example, in fast regimes, within‐storm patterns are the important determinant of flood peaks, while in slow regimes multiple storms and seasonality are critical. The latter result is verified by means of simulations with a derived flood frequency model for an actual catchment, Salmon Creek, in Western Australia. Slow regimes are characterized by low values of the coefficient of variation, CV[ Q p ], of the flood peaks, while fast regimes are characterized by higher values of CV[ Q p ]. Analysis of the simulation results on the Salmon catchment, which belongs to the slow regime and exhibits a nonlinear rainfall‐runoff response, also shows that nonlinearity in catchment response substantially increases CV[ Q p ] and may even dominate the scaling of CV[ Q p ] with catchment size. The scaling exponent in the relationship between mean annual flood and catchment size, for a linear runoff response, is higher for slow catchments and lower for fast catchments, and in both cases it remains constant with catchment area. A major conclusion of the paper is that the combined effects of within‐storm patterns, multiple storms, and seasonality have an important control on the observed scaling behavior in empirical flood frequency curves, each being dominant over a different range of catchment sizes.