Abstract Anomalies in the frequency of river floods, i.e., flood-rich or -poor periods, cause biases flood risk estimates and thus make climate adaptation measures less efficient. While observations have recently confirmed presence anomalies Europe, their exact causes are not clear. Here we analyse streamflow during 1960-2010 to show that shifts generation processes contribute more occurrence r...

In this contribution, a hybrid multi-contextual Markov model for unsupervised near real-time flood detection in multi-temporal X-band synthetic aperture radar (SAR) data is presented. It incorporates scale-dependent, as well as spatio-temporal contextual information, into the classification scheme, by combining hierarchical marginal posterior mode (HMPM) estimation on directed graphs with nonca...

This paper analyses a number of aspects related to the estimation of the design flood for a dam. A new approach to the estimation of the probable maximum precipitation (PMP) is described which takes advantage of the spatial variability of precipitation by using radar-derived distributed rainfall measurements. Procedures which utilize storm transposition and storm maximization are introduced to ...

Abstract Flood-related image datasets from social media, smartphones, CCTV cameras, and unmanned aerial vehicles (UAVs) present valuable data for the management of flood risk, particularly application modern convolutional neural networks (CNNs) to specific flood-related problems such as extent detection depth estimation. This review discusses increasing role CNNs in research with a growing numb...

The Australian water balance model (AWBM) is a catchment water balance model that calculates runoff from rainfall at daily or hourly time increments. The daily version iss used for water yield and water management studies; the hourly version is used for design flood estimation. This paper describes the origin and development of the AWBM beginning with elementary modelling components of saturati...