Rainfall organization control on the flood response of mild-slope basins

• Published in: Journal of hydrology (Amsterdam) Vol. 510; pp. 565 - 577
• Main Authors: Mei, Yiwen, Anagnostou, Emmanouil N., Stampoulis, Dimitrios, Nikolopoulos, Efthymios I., Borga, Marco, Vegara, Humberto J.
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier B.V 14.03.2014; Elsevier
• Subjects: Basins; Catchments; Earth sciences; Earth, ocean, space; Engineering and environment geology. Geothermics; Exact sciences and technology; Floods; Hydrologic model; Hydrology; Hydrology. Hydrogeology; Mathematical models; Natural hazards: prediction, damages, etc; Organizations; Rainfall; Rainfall moment; River basins; Spatiotemporal variability of rainfall; Storm velocity; Storms; North Carolina; United States; ANW, USA, North Carolina; Spatiotemporal variability of rainfall; Rainfall moment; Storm velocity; Hydrologic model; rivers; floods; rainfall; runoff; slopes; velocity; North America; drainage basins; hydrological modeling; spatiotemporal variations; dispersion; radar methods; errors; hydrographs; storms; statistics
• ISSN: 0022-1694; 1879-2707
• DOI: 10.1016/j.jhydrol.2013.12.013

•Spatio-temporal rainfall variability effects on flood modeling.•Rainfall moments and storm velocity conceptual frameworks.•Experimental framework to assess the conceptual frameworks’ predictability. This study uses a long-term (8years) dataset of radar-rainfall and runoff observations for the Tar River Basin in North Carolina, to explore the rainfall space–time organization control on the flood response of mild-slope (max slope <32 degrees) basins. We employ the concepts of “spatial moments of catchment rainfall” and “catchment scale storm velocity” to quantify the effect of spatial rainfall variability and basin geomorphology on flood response. A calibrated distributed hydrologic model is employed to assess the relevance of these statistics in describing the degree of spatial rainfall organization, which is important for runoff modeling. Furthermore, the Tar River Basin is divided into four nested sub-basins ranging from 1106km2 to 5654km2, in order to investigate the scale dependence of results. The rainfall spatiotemporal distribution represented in the analytical framework is shown to describe well the differences in hydrograph timing (less so in terms of magnitude of the simulated hydrographs) determined from forcing the hydrologic model with lumped vs. distributed rainfall. Specifically, the first moment exhibits a linear relationship with the difference in timing between lumped and distributed rainfall forcing. The analysis shows that the catchment scale storm velocity is scale dependent in terms of variability and rainfall dependent in terms of its value, assuming typically small values. Accordingly, the error in dispersion of simulated hydrographs between lumped and distributed rainfall forcing is relatively insensitive to the catchment scale storm velocity, which is attributed to the spatial variability of routing and hillslope velocities that is not accounted by the conceptual framework used in this study.