This paper demonstrates, by means of a systematic uncertainty analysis, that the use of outputs from more than one model can significantly improve conditional forecasts of discharges or water stages, provided the models are structurally different. Discharge forecasts from two models and the actual forecasted discharge are assumed to form a three-dimensional joint probability density distributio...

Early flood warning systems protect both infrastructure and human life by issuing accurate flood warnings to public and private entities, enabling emergency personnel to employ strategic procedures. One such system, the RiceU/TMC Flood Alert System (FAS) has proved effective at predicting flood levels along Brays Bayou for 30 major storm events since 1997, including T.S. Allison in 2001. The cu...

Efficient, robust, and accurate early flood warning is a pivotal decision support tool that can help save lives protect the infrastructure in natural disasters. This research builds hybrid deep learning (ConvLSTM) algorithm integrating predictive merits of Convolutional Neural Network (CNN) Long Short-Term Memory (LSTM) to design evaluate forecasting model forecast future occurrence events. Der...

Compound flooding, resulting from a combination of riverine and coastal processes, is complex but important hazard to resolve along urbanized shorelines in the vicinity river mouths. However, inland flooding models rarely consider oceanographic conditions, vice versa for flood models. Here, we describe development an operational, integrated coastal-watershed model address this issue compound hi...