Deaths and property damage from floods have increased drastically in the past two decades due to various reasons such as increased populations, unplanned developments, and climate change. Such losses from floods can be reduced by issuing timely early warnings and through effective response mechanisms based on situational intelligence during emerging flood situations. This paper presents the outcome of a literature review that was conducted to identify the types and sources of the intelligence required for flood warning and response processes as well as the technology solutions that can be used for offering such intelligence. Twenty-seven different types of intelligence are presented together with the technologies that can be used to extract such intelligence. Furthermore, a conceptual architecture that illustrates how relevant technology solutions can be used to extract intelligence at various stages of a flood cycle for decision-making in issuing early warnings and planning responses is presented.

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.

Flood warning and response systems are essential components of risk reduction strategies with the potential to reduce loss of life and impact on personal assets. However, recent flood incidents have caused significant loss of human lives due to failures in current flood warning and response mechanisms. These failures are broadly related to policies concerning, and governance aspects within, warning generation, the behaviour of communities in responding to early warnings, and weaknesses in associated tools and technologies used in communicating early warnings and responding. Capturing critical failure factors affecting flood warning and response systems can provide opportunities for making corrective measures and for developing a more advanced and futuristic system for early flood warnings. This paper reports the findings of a structured review that was conducted to identify critical failure factors in flood early warning and response systems. This study found twenty-four critical failure factors (CFFs). The interpretive structural modelling (ISM) approach conducted in this study resulted in identifying four different types of failure factors (autonomous, dependent, linkage, and independent) with varying dependence and driving powers. Analysis shows that governance, leadership, finance, standard operating procedures (SoP), and community engagement are the most dominating factors with the highest driving factor, which can overcome other dependent factors. The outcome of this review could be helpful for policymakers and practitioners in overcoming failure factors and implementing effective early warning and response systems.