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首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >Inter-comparison study of water level estimates derived from hydrodynamic-hydrologic model and satellite altimetry for a complex deltaic environment
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Inter-comparison study of water level estimates derived from hydrodynamic-hydrologic model and satellite altimetry for a complex deltaic environment

机译:从水动力水文模型和卫星测高仪得出的复杂三角洲环境中水位估算值的比对研究

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Riverine deltas are hydrologically one of the most active terrestrial bodies supporting an intricate network of rivers, a highly unsteady flow regime, high agricultural productivity and large population centers. Understanding the complex hydrology of riverine deltas is challenging due to the paucity of conventional ground-based measurements on river water levels and flows that result in large spatial and temporal sampling gaps. One way to bridge this sampling issue is to employ hydrodynamic models in combination with remotely-sensed water level elevation data from satellite altimetry in a data assimilation framework. However, a good understanding of the performance of models and altimetry is required beforehand. Using Bangladesh as an example of a complex delta, an inter-comparison study was therefore performed for water level estimates derived from the two methods: 1) satellite altimetry and 2) hydrodynamic-hydrologic modeling framework. The Envisat mission was selected for satellite altimetry-based water level data. For the modeling framework, a calibrated 1-D hydrodynamic model, HEC-RAS, was set up for the major rivers of Bangladesh using in-situ river bathymetry, gaged stream flow and water level data. Envisat water level estimates were generally found to be exceeded by the model-based values by 0.20 m and 1.90 m for Monsoon and dry seasons, respectively. In general, the average RMSE between Envisat and modeled estimates is more than 2.0. m. The closest agreement with altimetry was observed during the high flow Monsoon season over the Brahmaputra river. Envisat estimates are found to disagree most with model-based estimates for small to medium-sized river basins that are mountainous and flashy. This inter-comparison study provides preliminary guidance on the relative weights to assign for each type of estimate when designing a data assimilation scheme for optimal water level prediction in ungaged basins.
机译:河流三角洲在水文学上是最活跃的陆地机构之一,支持复杂的河流网络,高度不稳定的水流状况,高农业生产力和大量人口中心。由于缺乏常规的基于地面的河流水位和流量测量方法,因此无法理解河流三角洲复杂的水文学,这会导致较大的时空采样间隙。解决这一采样问题的一种方法是在数据同化框架中将流体动力学模型与来自卫星测高仪的遥感水位高程数据结合起来使用。但是,事先需要对模型和测高仪的性能有充分的了解。因此,使用孟加拉国作为复杂三角洲的一个例子,对从两种方法得出的水位估算进行了比较研究:1)卫星测高法和2)水动力水文模拟框架。选择Envisat任务用于基于卫星测高仪的水位数据。对于建模框架,使用原位河测深法,量表流量和水位数据,为孟加拉国的主要河流建立了经过校准的一维水动力模型HEC-RAS。通常发现,季风季和旱季的Envisat水位估计值分别超出模型值0.20 m和1.90 m。通常,Envisat和建模估计之间的平均RMSE大于2.0。米在雅鲁藏布江上的季风旺季期间,观察到与高度法最接近的协议。发现Envisat估计与山区多雨的中小型流域的基于模型的估计最不符。当设计数据同化方案以最佳地预测非手术盆地的最佳水位时,这项比较研究为每种类型的估计分配的​​相对权重提供了初步指导。

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