Journal of Earth Science & Climatic Change
Open Access

Abstract

Early warning is a key element for disaster risk reduction. However, the advances in generating hazard risk information have not yet been incorporated into operational forecast systems and consequently, operational forecasts have not been integrated into decision making processes in order to reduce disaster risks. This article aims to design location-specific user-need based flood forecast products and its application on different time scales for reducing flood risks. Using one to ten days multiple weather ensembles (EPS) forecasts of the European Centre for Medium Range Forecasts (ECMWF), integrating hydrological models, and combining these with GIS and local user needs. The decision support system (DSS) is designed to interpret, translate, and communicate science-based risk information into user-friendly early warning information products to assist emergency managers and decision makers. The DSS interface allows users to interactively specify the objectives and criteria that are germane to a particular situation, and obtain the management options (strategies) that are possible, and the exogenous influences (scenarios) that should be taken into account before policy planning and decision making. The proposed framework is applied to a pilot area in the Brahmaputra river basin in Bangladesh for the agricultural sector.

Biography

The Decision Support System for an early warning of an impending flood is useful and helps the community interpret and translate scientific information into risk information. The usage of increased understanding of probabilistic long lead flood forecasting is valuable for society and for the protection of agriculture in flood-prone areas. In order to receive value-added benefits from flood information, requirements of different users should be considered very carefully and met sensibly. The 2011 flood information was delivered to the community and found beneficial for decision making. Accuracy and the lead time of the forecast are very important for the community to establish confidence in the practical utilization of probabilistic information. The integrated flood forecasting DSS for risk management has generated greater interest in people living in the study area. Flood forecast should be more specific so that the forecast will match the real situation more accurately