Event-driven flood management: design and computational modules

Abstract

Flood management is a set of activities that have to be carried out in collaboration with multiple agencies. Advanced flood information with early warning generated using remote sensing satellite technologies can help the agencies to effectively manage the situation on ground. Various environmental parameters and forecasts provided by different agencies can be analyzed and compared with historical flood events for generating probable flood event alerts. The information (environmental parameters) provided by the agencies are heterogeneous and noncompliant to standards and distributed in nature. Synchronization of data from distributed resources and automation of data analysis process for flood management is a primary prerequisite for faster and efficient decision-making. Web 2.0-based web services enable data creation, sharing, communication, and collaboration on web. Spatial data sharing on web 2.0 for making quality of service using open-source software for efficient flood management is a challenge. Available software architectures proposed for risk and environmental crisis management are too generic in nature and needs lot of modification for flood management. An event-driven model coupled with data standardization procedures using service-oriented architecture provides an effective framework for flood management. In this paper, a framework capable of collecting heterogeneous distributed flood-related information for analyzing and alerting probable flood events is proposed. The framework has been implemented to generate automatic flood extent maps, by analyzing the distributed satellite data (as service). The automation of flood delineation process reduces the overall flood product generation time. Open-source web tools have been utilized in development of spatial information system to visualize and analyze the actual situation on ground facilitating overall decision-making process.

Evaluation of IMERG and TRMM 3B43 Monthly Precipitation Products over Mainland China

“…A series of satellite-derived global precipitation datasets have been developed, such as the Climate Precipitation Center morphing method [4], Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks [5], the Global Satellite Mapping of Precipitation Project [6], and TRMM Multi-Satellite Precipitation Analysis (TMPA) [7] products. Among these datasets, TMPA products, which have a relatively high level of accuracy, have been used widely [8][9][10][11][12][13][14][15].…”

Satellite data planning for flood mapping activities based on high rainfall events generated using TRMM, GEFS and disaster news

“…Various news channels and newspapers are providing their live newsfeeds on Internet in Rich Site Summary or Really Simple Syndication (RSS) and Geo RSS formats. Sharma et al (2016) have proposed a framework in which they have used observed TRMM data to generate the probable flood events. The developed system is generating current-day, past 1-day, 2-day and 3-day products over Indian region using TRMM data.…”

“…It will increase the time frame window of current-day and past 3 days products to past 3 days, current-day and future 3 days products. By considering Sharma et al (2016) as a base work, this study has been proposed to generate automated integrated TRMM and GEFS spatial products coupled with live news available as rich site summary (RSS) feeds using open-source technologies to identify probable high rainfall events over Indian region, on which the satellite data can be planned for acquisition. The satellite data planned using the above method can be used for delineating flood using GIS software and techniques.…”

“…By considering Sharma et al (2016) as a base work, this study has been proposed with following design objectives:…”

A Sensor Web and Web Service-Based Approach for Active Hydrological Disaster Monitoring

“…There are four logical layers in the event processing flow, namely, the event generator, the event channel, the event processing engine and the downstream event-driven activity [39]. The event-driven method can play an important role in the management and monitoring of hydrological disasters [40]. Figure 2 illustrates the event-driven mechanism.…”