Abstract

Floods are the most frequent of natural disasters, affecting millions of people across the globe every year. The anticipation and forecasting of floods at the global scale is crucial to preparing for severe events and providing early awareness where local flood models and warning services may not exist. As numerical weather prediction models continue to improve, operational centers are increasingly using their meteorological output to drive hydrological models, creating hydrometeorological systems capable of forecasting river flow and flood events at much longer lead times than has previously been possible. Furthermore, developments in, for example, modelling capabilities, data, and resources in recent years have made it possible to produce global scale flood forecasting systems. In this paper, the current state of operational large‐scale flood forecasting is discussed, including probabilistic forecasting of floods using ensemble prediction systems. Six state‐of‐the‐art operational large‐scale flood forecasting systems are reviewed, describing similarities and differences in their approaches to forecasting floods at the global and continental scale. Operational systems currently have the capability to produce coarse‐scale discharge forecasts in the medium‐range and disseminate forecasts and, in some cases, early warning products in real time across the globe, in support of national forecasting capabilities. With improvements in seasonal weather forecasting, future advances may include more seamless hydrological forecasting at the global scale alongside a move towards multi‐model forecasts and grand ensemble techniques, responding to the requirement of developing multi‐hazard early warning systems for disaster risk reduction. WIREs Water 2016, 3:391–418. doi: 10.1002/wat2.1137This article is categorized under: Science of Water > Water Extremes

Highlights

  • Flooding has the highest frequency of occurrence of all types of natural disasters across the globe, accounting for 39% of all natural disasters since 2000, with >94 million people affected by floods each year worldwide[1] through displacement from homes, unsafe drinking water, destruction of infrastructure, injury, and loss of life

  • Producing forecasts at the global scale has only become possible in recent years due to the integration of meteorological and hydrological modeling capabilities, improvements in data, satellite observations and land-surface hydrology modeling, and increased resources and computer power.[6,7,8,9,10]

  • The European Flood Awareness System (EFAS) interface provides a map of Europe, with all points forecasting a flood event designated by a color responding to the warning threshold; this allows an overview of forecast flood events across the continent

Read more

Summary

INTRODUCTION

Flooding has the highest frequency of occurrence of all types of natural disasters across the globe, accounting for 39% of all natural disasters since 2000, with >94 million people affected by floods each year worldwide[1] through displacement from homes, unsafe drinking water, destruction of infrastructure, injury, and loss of life. Persistence diagrams showing information about the previous four forecasts give the user additional information on the forecast uncertainty as NWP models should be able to pick up large-scale synoptic weather systems that typically produce severe events in advance, showing a flood risk consistently in each forecast run.[42] The EFAS interface provides a map of Europe, with all points forecasting a flood event designated by a color responding to the warning threshold; this allows an overview of forecast flood events across the continent. Warning Dissemination The final products delivered to the end users include flood watches and warnings and information on current river levels and precipitation, which are disseminated to various users at specified stages in the evolution of a flood event through a dedicated web interface, email, fax, and telephone These are usually text forecasts, an example of which is given in Box 2 for a minor flood event, written by the hydrologists based on the output of the HyFS but can include automated alerts and bulletins for certain users. Major flooding Moderate flooding Minor flooding Below flood level No classification Station details: Station number: 584011 Name: Snowy R at Orbost Flood levels: Minor: 4.20 Moderate: 6.00 Major: 7 .00 Data from the pervious 4 days

Moderate
Gauges: Major flooding 24 Gauges: Moderate flooding 93 Gauges
Improving Data Availability
CONCLUSIONS
47. Completing the Forecast
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call