The central hypothesis of a nonlinear geophysical flood theory postulates that, given space‐time rainfall intensity for a rainfall‐runoff event, solutions of coupled mass and momentum conservation differential equations governing runoff generation and transport in a self‐similar river network produce spatial scaling, or a power law, relation between peak discharge and drainage area in the limit […]

The focus of this study is to evaluate: (1) “mixtures” of flood peak distributions, (2) upper tail and scaling properties of the flood peak distributions, and (3) presence of temporal nonstationarities in the flood peak records. Villarini, G., J.A. Smith, M.L. Baeck, and W.F. Krajewski. “Examining Regional Flood Frequency in the U.S. Midwest,” Journal of the American […]

We present a diagnostic framework to assess changes in flood risk across multiple scales in a river network, under nonstationary conditions or in the absence of historical hydro-meteorological data. The framework combines calibration-free hydrological and hydraulic models with urban development information to demonstrate altered flood risk. Cunha, L.K., W.F. Krajewski, and R. Mantilla. “A Framework for Flood Risk […]

We use three statistical methods (Pettitt and Bai‐Perron tests and segmented regression) to detect abrupt shifts in multiple hydrometeorological variable mean and uncertainty fields over the central United States. For surface air temperature and precipitation, we use the Climate Research Unit (CRU) time series data set for comparison. We find that for warm‐season months, there […]

This article examines whether the temporal clustering of flood events can be explained in terms of climate variability or time‐varying land‐surface state variables. Villarini, G., J.A. Smith, R. Vitolo, and D.B. Stephenson. “On the Temporal Clustering of U.S. Floods and Its Relationship to Climate Teleconnection Patterns,” International Journal of Climatology, 33, 3, pp. 629–640, 2013.