Challenges and Technical Advances in Flood Early Warning Systems (FEWSs)

Abstract

Flood early warning systems (FEWSs)—one of the most common flood-impact mitigation measures—are currently in operation globally. The UN Office for Disaster Risk Reduction (UNDRR) strongly advocates for an increase in their availability to reach the targets of the Sendai Framework for Disaster Risk Reduction and Sustainable Development Goals (SDGs). Comprehensive FEWS consists of four components, which includes (1) risk knowledge, (2) monitoring and forecasting, (3) warning, dissemination, and communication, and (4) response capabilities. Operational FEWSs have varying levels of complexity, depending on available data, adopted technology, and know-how. There are apparent differences in sophistication between FEWSs in developed countries that have the financial capabilities, technological infrastructure, and human resources and developing countries where FEWSs tend to be less advanced. Fortunately, recent advances in remote sensing, artificial intelligence (AI), information technologies, and social media are leading to significant changes in the mechanisms of FEWSs and provide the opportunity for all FEWSs to gain additional capability. These technologies are an opportunity for developing countries to overcome the technical limitations that FEWSs have faced so far. This chapter aims to discuss the challenges in FEWSs in brief and exposes technological advances and their benefits in flood forecasting and disaster mitigation.

Implementation of Flood Emergency Response System with Face Analytics

“…The image receives an arrow in every pixel by repeating this technique for every pixel in the image. These arrows are known as gradients, and they indicate the transition of light to dark throughout the whole image [11][12][13][14][15][16][17][18][19][20]. The upper right most section of the pie charts shows the flood duration in days.…”

“…Weather radars and remotely sensed rainfall have the potential to improve watershed monitoring by providing geographical, real-time, or near real-time data. However, the data they supply is of lesser quality than observed data, and these approaches are too young to have long enough time series to develop credible hydrological models [17].…”

The 2021 Western Germany flood event: The value of flood risk dissemination strategies and social media

“…Furthermore, with the advent of social media, authorities need to also utilise the power embedded in such networks to improve risk management while also putting some safeguards in place to avoid the spread of false information. Mitigation can also be enhanced through the integration of artificial intelligence (AI), remote sensing and social media (Perera et al 2020 ), for example, the use of AI-related tools such as artificial neural networks (ANNs) and fuzzy inference systems (FISs) (Nur Adli Zakaria et al 2021 ). These tools have extensively been used to monitor river levels, therefore presenting an opportunity for authorities to tap into their power as mitigation tools in reducing flood negative impacts.…”

Advanced Technologies for Offering Situational Intelligence in Flood Warning and Response Systems: A Literature Review

“…Such information systems for flood warning and response systems should offer hazard detection, forecasting, warnings, and responses [15]. A study of global early warning systems within developed and developing countries [16,17] has found that the availability of such technology platforms is an important factor that influences the effectiveness of early warning systems in addition to policy, institutional, and societal factors.…”