Examining Observed Rainfall, Soil Moisture, and River Network Variabilities on Peak Flow Scaling of Rainfall-Runoff Events with Implications on Regionalization of Peak Flow Quantiles

The scaling of peak flows associated with a probability of exceedance (Q_p) or a specific rainfall-runoff event (Q_R) with respect to drainage area (A) is known as flood scaling and it has been widely used in peak flow regionalization. The attenuation and aggregation processes within the hillslopes and river network in a rainfall-runoff event, provide a framework to test the scaling of Q_R. Although scaling of Q_p has been reported in empirical studies, its physical interpretation is compromised, since Q_p at each site could come from different rainfall-runoff events. To address this problem, the authors explored the effect of actual variabilities of rainfall and soil moisture fields, and the effect of the river network structure, in the scaling of peak flows of 85 rainfall-runoff events and peak flow quantiles that were observed in the Iowa River Basin at 43 streamflow gauges. The authors established empirical evidence that addresses two questions: (1) What does control the performance of the scaling of observed Q_R? (2) What is the interplay between sampling errors and the selection of explanatory variables in the construction of regional regression models for Q_R and Q_p? For the first question, the authors found that the slope magnitude in the scaling of the rainfall intensity fields with respect to A controls the scaling' performance of Q_R. Regarding the second question, the authors demonstrate that the inclusion of river network descriptors should improve the regional equations to estimate peak flow quantiles unless stream gauging sampling errors affect the analysis.