Development of a flash flood confidence index from disaster reports and geophysical susceptibility

The analysis of historical disaster events is a critical step towards understanding current risk levels and changes in disaster risk over time. Disaster databases are potentially useful tools for exploring trends, however, criteria for inclusion of events and for associated descriptive characteristics is not standardized. For example, some databases include only primary disaster types, such as ‘flood’, while others include subtypes, such as ‘coastal flood’ and ‘flash flood’. Here we outline a method to identify candidate events for assignment of a specific disaster subtype—namely, ‘flash floods’—from the corresponding primary disaster type—namely, ‘flood’. Geophysical data, including variables derived from remote sensing, are integrated to develop an enhanced flash flood confidence index, consisting of both a flash flood confidence index based on text mining of disaster reports and a flash flood susceptibility index from remote sensing derived geophysical data. This method was applied to a historical flood event dataset covering Ecuador. Results indicate the potential value of disaggregating events labeled as a primary disaster type into events of a particular subtype. The outputs are potentially useful for disaster risk reduction and vulnerability assessment if appropriately evaluated for fitness of use.Campus Lima Centr

Application of geospatial technologies in constructing a flash flood warning model in northern mountainous regions of Vietnam: a case study at TrinhTuong commune, Bat Xat district, LaoCai province

The model was constructed based on GIS spatial analyses, combined with Analytic Hierarchy Process (AHP) and Multi-Criterion Analysis method (MCA). The data gathered for the study were mainly from remote-sensing images, statistical data and surveys. Field experiments were conducted in Trinh Tuong Commune, Bat Xat District, Lao Cai province. This is a typical remote mountainous region of Vietnam in which flash floods often occur. The study analyzes and evaluates six primary factors that incite flash flood, namely: geomorphological characteristics, soil properties, forest and fractional vegetation cover types, local drainage basin slopes, maximum average rainfall of various years, and the river/stream density of the region. The zoning map showing flash flood potentials has determined that 19.91% of the area had an extremely high risk of flash flood occurrence, 64.92% of the area had a medium risk, and 15.17% had a low or very low risk. Based on the employment of daily maximum rainfalls as the primary factor, an online flash flood warning model was constructed for areas with a “high” or “very high” risk of flash flood occurrence.

A service-oriented middleware for integrated management of crowdsourced and sensor data streams in disaster management

The increasing number of sensors used in diverse applications has provided a massive number of continuous, unbounded, rapid data and requires the management of distinct protocols, interfaces and intermittent connections. As traditional sensor networks are error-prone and difficult to maintain, the study highlights the emerging role of “citizens as sensors” as a complementary data source to increase public awareness. To this end, an interoperable, reusable middleware for managing spatial, temporal, and thematic data using Sensor Web Enablement initiative services and a processing engine was designed, implemented, and deployed. The study found that its approach provided effective sensor data-stream access, publication, and filtering in dynamic scenarios such as disaster management, as well as it enables batch and stream management integration. Also, an interoperability analytics testing of a flood citizen observatory highlighted even variable data such as those provided by the crowd can be integrated with sensor data stream. Our approach, thus, offers a mean to improve near-real-time applications

Geo-Spatial Analysis in Hydrology

Geo-spatial analysis has become an essential component of hydrological studies to process and examine geo-spatial data such as hydrological variables (e.g., precipitation and discharge) and basin characteristics (e.g., DEM and land use land cover). The advancement of the data acquisition technique helps accumulate geo-spatial data with more extensive spatial coverage than traditional in-situ observations. The development of geo-spatial analytic methods is beneficial for the processing and analysis of multi-source data in a more efficient and reliable way for a variety of research and practical issues in hydrology. This book is a collection of the articles of a published Special Issue Geo-Spatial Analysis in Hydrology in the journal ISPRS International Journal of Geo-Information. The topics of the articles range from the improvement of geo-spatial analytic methods to the applications of geo-spatial analysis in emerging hydrological issues. The results of these articles show that traditional hydrological/hydraulic models coupled with geo-spatial techniques are a way to make streamflow simulations more efficient and reliable for flood-related decision making. Geo-spatial analysis based on more advanced methods and data is a reliable resolution to obtain high-resolution information for hydrological studies at fine spatial scale

Application of remote sensing and geographical information systems in flood management : a review

Floods are one of the most widely distributed hazards around the world and their management is an important issue of concern among all the stakeholders. The aim of this review is to synthesize the state of art literature in the application of Geographical Information Systems (GIS) and Remote Sensing (RS) techniques in all the flood management stages (pre-flood, during flood and post-flood stages). Flood types and common concepts in flood management are precisely explained. Case studies of flood management using GIS and RS are summarized. Current challenges in using GIS and RS techniques for flood management are also given. One lesson we learn from this review is that flood management is very diverse and it requires multidisciplinary involvement. It can also be deduced that RS techniques offer cheaper and faster options of accessing spatial data about the flood event even in the physically inaccessible areas. GIS techniques on the other hand facilitate hydrological models in data collection, analysis, querying and presentation of information in a more simplified format. The present review is expected to contribute to an improved understanding of the potential applications of RS and GIS techniques in flood management, especially among scientists in the developing countries where the use of these techniques particularly in flood management has generally been limited