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首页> 外文期刊>Zeitschrift fur Arznei- und Gewurzpflanzen >Hydrodynamic Modeling for Flood Hazard Assessment in a Data Scarce Region: a Case Study of Bharathapuzha River Basin
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Hydrodynamic Modeling for Flood Hazard Assessment in a Data Scarce Region: a Case Study of Bharathapuzha River Basin

机译:数据稀缺区域洪水危害评估的流体动力学建模 - 以Bharathapuzha河流域为例

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摘要

Flood hazard is assessed for the data scarce lower Bharathapuzha basin in Kerala, India, using a hydrologic-hydraulic approach. L-moment-based regional flood frequency analysis along with a non-dimensional analysis of hydrographs is used to generate scenarios for flood hazard assessment. A fully hydrodynamic 1D river flow model is calibrated for the rivers of lower Bharathapuzha basin for the year 1992 and validated for the year 1994. The widely available SRTM DEM is used to extract river cross-sections and the limited available discharge and water level data are used to carefully calibrate the 1D river flow model. Subsequently, a coupled 1D-2D flood inundation model is used to simulate the flood inundation extent for the year 2002. In the absence of LIDAR data, a cartographic DEM derived from readily available topo maps is used as an input in the coupled 1D-2D model. Further, in the absence of microwave Synthetic Aperture Radar (SAR) data, the flood inundation extent is validated using the readily available optical IRS-1D WiFS sensor data which is mainly intended for vegetation and drought monitoring. A suitable methodology is used to delineate flood inundation extent from the partial cloud-covered WiFS image. The regional flood frequency estimates and the calibrated and validated flood inundation model are then used to assess the flood hazard.
机译:利用水文液压方法评估了洪水危害,为印度喀拉拉邦的数据稀缺的Bharathapuzha盆地评估。基于L-MOCEL的区域洪水频率分析以及对水文的非尺寸分析用于生成洪水危害评估的情景。为1992年的Bharathapuzha盆地河流校园校准了一个完全流体动力学1D河流模型,并验证了1994年的验证。广泛可用的SRTM DEM用于提取河流横截面,有限的可用排放和水位数据用于仔细校准1D河流模型。随后,使用耦合的1D-2D洪水淹没模型来模拟2002年的洪水淹没程度。在没有LIDAR数据的情况下,从易于获得的Topo地图导出的制图DEM被用作耦合的1D-2D中的输入模型。此外,在没有微波合成孔径雷达(SAR)数据的情况下,使用易于获得的光IRS-1D WIFS传感器数据来验证洪水淹没程度,该传感器数据主要用于植被和干旱监测。合适的方法用于从部分云覆盖的WIFS图像描绘洪水淹没程度。然后使用区域泛频估计和校准和验证的洪水淹没模型来评估洪水危害。

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