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River Flood Forecasting System: An Interdisciplinary Approachстатья Глава в книге
- Авторы: Zelentsov V., Pimanov I., Potryasaev S., Sokolov B., Cherkas S., Alabyan A., Belikov V., Krylenko I.N.
- Сборник: Flood Monitoring through Remote Sensing
- Глава в коллективной монографии
- Год издания: 2018
- Место издания: Springer, Cham Cham
- Первая страница: 81
- Последняя страница: 100
- DOI: 10.1007/978-3-319-63959-8_4
- Аннотация: The chapter presents a holistic system that implements an advanced river flood modeling and forecasting approach. This approach extends traditional methods based on separate satellite monitoring or river physical processes modeling, by integration of different technologies such as satellite and in situ data processing, input data clustering and filtering, digital mapping of river valleys relief, data crowdsourcing, hydrodynamic modeling, inundation visualization, and also duly warning of stakeholders. The software of the suggested system was implemented on the base of open source code and service-oriented architecture (SOA). This allows the use of different program modules for data processing and modeling, integrated into a unified software suite. Forecast results are available as web services. Additionally, a special GIS platform has been developed to visualize the results of forecasting. It does not require the users to have any special skills or knowledge, and all the complexity relating to data processing and modeling is hidden from the users. The results of case studies have shown that the suggested interdisciplinary approach provides highly accurate forecasting due to operational ingestion and integrated processing of the remote sensing and ground-based water flow data in real time. In these case studies, forecasting of flood areas and depths was performed on a time interval of 12–48 h, allowing performing the necessary steps to alert and evacuate the population. In general, the developed software can be considered as a toolkit to create holistic monitoring and flood forecasting systems with an integrated use of diverse satellite and in situ data.
- Добавил в систему: Алабян Андрей Михайлович