Samansiri, S.; Fernando, T.; Ingirige, B. Advanced Technologies for Offering Situational Intelligence in Flood Warning and Response Systems: A Literature Review. Water2022, 14, 2091.
Samansiri, S.; Fernando, T.; Ingirige, B. Advanced Technologies for Offering Situational Intelligence in Flood Warning and Response Systems: A Literature Review. Water 2022, 14, 2091.
Samansiri, S.; Fernando, T.; Ingirige, B. Advanced Technologies for Offering Situational Intelligence in Flood Warning and Response Systems: A Literature Review. Water2022, 14, 2091.
Samansiri, S.; Fernando, T.; Ingirige, B. Advanced Technologies for Offering Situational Intelligence in Flood Warning and Response Systems: A Literature Review. Water 2022, 14, 2091.
Abstract
Deaths and property damage from the flood have increased drastically in the past two decades due to various reasons such as increased population, unplanned development and climate change. Losses from floods can be reduced by having accurate intelligence of an emerging flood situation in order to make timely decisions for issuing early warnings and responding efficiently. This paper presents a thorough analysis of the types and sources of intelligence required for flood warning and response processes and technology solutions that can be used for capturing such intelligence. A structured review, covering a more comprehensive range of published literature on Flood Early Warning and Response Systems (FEWRS), was conducted to identify the necessary intelligence and the technology that can be used to capture intelligence required for various phases of a flood hazard as it develops. Twenty-seven different types of key intelligence required in the flood cycle were identified. A conceptual architecture was identified that illustrates how relevant technology solutions can be used to extract intelligence at various stages of a flood event for decision making for early warnings and response.
Environmental and Earth Sciences, Environmental Science
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
