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 […]
Author Archive for: Mikael Mulugeta
About Mikael Mulugeta
This author has yet to write their bio.Meanwhile lets just say that we are proud Mikael Mulugeta contributed a whooping 209 entries.
Entries by Mikael Mulugeta
The results point to increasing trends in heavy rainfall over the northern part of the study domain. Examination of the surface temperature record suggests that these increasing trends occur over the area with the largest increasing trends in temperature and, consequently, with an increase in atmospheric water vapor. Villarini, G., J.A. Smith, M.L. Baeck, R. […]
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 […]
The State of Iowa, located in the Midwestern United States, has experienced an increased frequency of large floods in recent decades. After extreme flooding in the summer of 2008, the Iowa Flood Center (IFC) was established for advanced research and education specifically related to floods. Gilles, D.G., N.C. Young, J.A. Piotrowski, H.S. Schroeder, and Y.J. Chang. “Inundation Mapping Initiatives of […]
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 […]
Accurate calculation of precipitable water vapor (PWV) in the atmosphere has always been a matter of importance for meteorologists. Potential water vapor (POWV) or maximum precipitable water vapor can be an appropriate base for estimation of probable maximum precipitation (PMP) in an area, leading to probable maximum flood (PMF) and flash flood management systems. Varmaghani, […]
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 […]
The goal of this study is to diagnose the manner in which radar‐rainfall input affects peak flow simulation uncertainties across scales. We used the distributed physically based hydrological model CUENCAS with parameters that are estimated from available data and without fitting the model output to discharge observations. Cunha, L.K., P.V. Mandapaka, W.F. Krajewski, R. Mantilla, and A.A. Bradley. “Impact […]
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.
Several studies based on observational records found increasing trends over the central United States. Recently, Villarini et al. (2013) found a large increase in the number of rainfall days exceeding the 95th percentile of the rainfall distribution over the Upper Mississippi River Basin, and a much weaker signal in the Lower Mississippi River Basin. Villarini, G., […]