GloFAS – global ensemble streamflow forecasting and flood early warning

Abstract

Anticipation and preparedness for large-scale flood events have a key role in mitigating their impact and optimizing the strategic planning of water resources. Although several developed countries have well-established systems for river monitoring and flood early warning, figures of population affected every year by floods in developing countries are unsettling. This paper presents the Global Flood Awareness System, which has been set up to provide an overview on upcoming floods in large world river basins. The Global Flood Awareness System is based on distributed hydrological simulation of numerical ensemble weather predictions with global coverage. Streamflow forecasts are compared statistically to climatological simulations to detect probabilistic exceedance of warning thresholds. In this article, the system setup is described, together with an evaluation of its performance over a two-year test period and a qualitative analysis of a case study for the Pakistan flood, in summer 2010. It is shown that hazardous events in large river basins can be skilfully detected with a forecast horizon of up to 1 month. In addition, results suggest that an accurate simulation of initial model conditions and an improved parameterization of the hydrological model are key components to reproduce accurately the streamflow variability in the many different runoff regimes of the Earth

Validation of Satellite Rainfall Products over a Mountainous Watershed in a Humid Subtropical Climate Region of Brazil

“…A PSS of greater than 0 means that the number of hits was higher than the number of false alerts and indicates that remote sensing data have some ability to estimate rainfall. An estimate has no predictive ability when PSS ≤ 0 [38]. Figure 4 shows the spatial distributions of the eleven available rain gauge stations, as well as the TRMM 3B42 and Hydroe grid.…”

“…Based on the contingency table, Peirce [40] formulated the Peirce Skill Score (PSS). The PSS accounts for all elements of the contingency table and is calculated as the difference between the probability of detection (POD) and probability of false detection (POFD) [38,39]:…”

Early Flood Detection for Rapid Humanitarian Response: Harnessing Near Real-Time Satellite and Twitter Signals

“…At this point, GFDS and MODIS (see Section 2.1) are the only sources of satellite water detection which are publicly available with a daily time step. One separate development that may be a promising alternative is the progress in global flood forecasting models [39], such as GloFAS (Global Flood Awareness System) [40] and GFMS (Global Flood Monitoring System) [28]. The performance of these systems for taking DRM actions prior to flood events is currently being tested by the Uganda Red Cross, together with the German Red Cross and the Red Cross/Red Crescent Climate Centre [41].…”

Application of Remote Sensing Data to Constrain Operational Rainfall-Driven Flood Forecasting: A Review

“…Most operational fluvial flood forecasting systems only simulate the first three processes, to provide water level and streamflow forecasts [3]. The three processes are typically simulated through coupled rainfall/snowmelt-runoff models and hydrological routing models [3][4][5][6][7][8][9]. Only few systems incorporate more sophisticated hydraulic models to assist streamflow propagation simulation which allows the forecasting of floodplain inundation as well [10].…”