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Flooding is one of the natural disasters that affect the livelihood of the people living in the floodplains, like Bangladesh. Here, we proposed to employ SAR satellite images in assessing the flood extent and crop damage with the hydrometeorological observations in the southwestern region of Bangladesh. We observed that the unusual flood of the year 2000 was the combined effect of the huge amount of rainfall in the local areas as well as oncoming water flows from West Bengal in India. During late monsoon of 2000, we experienced that the amount of rainfall was in several magnitudes (250-450%) than the expected over the region. Bangladesh, one of the largest deltas in the world, in general experienced recurrent flood events from the spill of the three mighty rivers in every year. However, we observed that during 2000 the river situation was slightly above the average year conditions and below the moderate level of flood warning conditions, indicating non-riverine flooding. Therefore, we used the SAR images in delineating the flood extent and its damages for the standing aman crops. We observed that the flood extent mapping was having more than 95% agreements with the ground data and crop damage information was about 75% in agreement with the government estimates. The flood extent and crop damage map was found to be useful during the unprecedented flood in the southwestern region of Bangladesh. The use of near real-time SAR imageries thus would be helpful in developing strategies for flood management and disaster mitigation activities and could be utilized on a regular basis. [ABSTRACT FROM AUTHOR]

Flood risk management serves to reduce the negative consequences of flood disaster to a certain extent. In agriculture-dominated countries, the extent of damage incurred in crop land by heavy and frequent floods is quite high. The present study aims to develop an optimal rice planning procedure considering the flood risk through hydrodynamic floodplain modeling in flood-prone delta region of Mahanadi river basin in India. As high-resolution topographic data and surveyed river cross sections are unavailable for the study area, MIKE FLOOD model setup is prepared using river cross sections and floodplain elevation model derived from freely available SRTM DEM. In this study, MIKE FLOOD setup is prepared and flood inundation simulation is carried out. Flood inundation extent obtained is compared with RADARSAT-1 image-based inundation extent. Subsequently, flood risk is evaluated for cropping pattern in floodplains using functional relationships between flood characteristics and the expected damage of different rice varieties. Based on the flood risk, an optimal rice planning model is developed for maximizing the net benefits in the floodplain. The average annual expected net benefit of optimal rice allocation model for the study area is to the tune of INR 601 million compared to INR 432 million for normal rice variety cultivation throughout the study area. [ABSTRACT FROM AUTHOR]

Remote sensing is the most practical method available to managers of flood-prone areas for quantifying and mapping flood impacts. This study explored large inundation areas in the Maghna River Basin, around the northeastern Bangladesh, as determined from passive sensor LANDSAT data and the cloud-penetrating capabilities of the active sensors of the remote imaging microwave RADARSAT. This study also used passive sensor LANDSAT wet and dry images for the year 2000. Spatial resolution was 30 m by 30 m for comparisons of the inundation area with RADARSAT images. RADARSAT images with spatial resolution of 50 m by 50 m were used for frequency analysis of floods from 2000 to 2004. Time series images for 2004 were also used. RADARSAT remote sensing data, GIS data, and ground data were used for the purpose of flood monitoring, mapping and assessing. A supervised classification technique was used for this processing. They were processed for creating a maximum water extent map and for estimating inundation areas. The results of this study indicated that the maximum extent of the inundation area as estimated using RADARSAT satellite imaging was about 29, 900.72 km in 2004, which corresponded well with the heavy rainfall around northeast region, as seen at the Bhairab Bazar station and with the highest water level of the Ganges-Brahmaputra-Meghna (GBM) Rivers. A composite of 5 years of RADARSAT inundation maps from 2000 to 2004, GIS data, and damage data, was used to create unique flood hazard maps. Using the damage data for 2004 and the GIS data, a set of damage maps was also created. These maps are expected to be useful for future planning and flood disaster management. Thus, it has been demonstrated that RADARSAT imaging data acquired over the Bangladesh have the ability to precisely assess and clarify inundation areas allowing for successful flood monitoring, mapping and disaster management. [ABSTRACT FROM AUTHOR]

Earth observation from active microwave satellites such as RADARSAT-1 is an excellent tool to monitor and forecast floods. Two complementary approaches are described in this paper: (a) real time or near-real time monitoring of flood extent and (b) mapping of hydrological properties of drainage basins. Since it can penetrate through clouds, which usually occur during precipitation periods, and due to the fact that it can be programmed with different incidence angles, RADARSAT-1 enables frequent coverage over specific areas of interest. It has been used successfully to monitor a major flood of the Red River in Manitoba in 1997, by providing frequent coverage of the flood during its progression and decrease. Resulting data and images have been useful in planning the emergency measures and in assessing flood damage. RADARSAT has also the ability to characterize hydrological properties of watersheds. It has been used in agricultural catchments in Europe for mapping soil surface roughness, which affects runoff coefficients, concentration time and resistance to erosion processes. Used to complement optical data, RADARSAT has provided information on the status of land use and soil protective cover in drainage basins. This information can then be translated into parameters and coefficients that hydrological models can use for runoff and flood forecasting [ABSTRACT FROM AUTHOR]