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Advancing river modelling in ungauged basins using satellite remote sensing: the case of the Ganges-Brahmaputra-Meghna basin

机译:利用卫星遥感推进非赋权盆地的河流建模:恒河-布拉马普特拉-梅格纳盆地的案例

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River modelling is the process of simulating the water flow dynamics of a stream network against time-varying boundary conditions. Such river models are often an important component of any flood forecasting system that forecasts river levels in flood-prone regions. However, large river basins such as the Ganges, Brahmaputra, and Meghna (GBM), Indus, Irrawaddy, Salween, Mekong, and Niger in the developing world are mostly ungauged as they lack the necessary and routine in situ measurements of river bed depth/slope, bathymetry (river cross section), flood plain mapping, and boundary condition flows for setting up of a river model. For such basins, proxy approaches relying primarily on remote-sensing data from space platforms may be the only way to overcome the lack of in situ data. In this study, we share our experience in setting up the one-dimensional River Analysis System model of the Hydrologic Engineering Center over the stream network of the GBM basin. Good-quality in situ measurements of river hydraulics (cross section, slope, flow) were available only for the basin's downstream and flood-prone region, which comprises 7% of the total basin area. For the remaining 93% of the basin area, data from the following satellite sensors were used to build a functional river model: (a) Shuttle Radar Topography Mission to derive river network and adjust river bed profiles; (b) Landsat-MODIS for updating river network and flow direction generated by elevation data; (c) radar altimetry data to build the depth versus width relationship at river locations; and (d) satellite precipitation-based hydrologic modelling of lateral flows into major rivers. We measured the success of our approach by systematically testing how well the basin-wide river model could simulate river-level dynamics at two measured downstream low-lying locations. This paper summarizes the key hurdles faced and offers a step-by-step 'rule book' approach to setting up river models for large ungauged river basins around the world. By following these rules in a systematic way, the root mean squared error for river-level simulation was reduced from 3 to 1 m. Such a guide can be useful for setting up river hydraulic models for flood forecasting systems in ungauged basins such as the Niger, Mekong, Irrawaddy, and Indus.
机译:河流建模是针对时变边界条件模拟河流网络水流动力学的过程。这样的河流模型通常是任何在洪水多发地区预测河流水位的洪水预报系统的重要组成部分。但是,发展中国家的恒河,雅鲁藏布江和梅格纳河(GBM),印度河,伊洛瓦底江,萨尔温江,湄公河和尼日尔等大型流域由于缺乏必要和常规的河床深度/常规测量方法,因此大多没有人使用坡度,水深(河流横截面),洪水平原测绘和边界条件流,用于建立河流模型。对于这类盆地,主要依靠空间平台遥感数据的代理方法可能是克服缺乏原位数据的唯一方法。在这项研究中,我们分享了在GBM盆地的河流网络上建立水文工程中心的一维河流分析系统模型方面的经验。仅在流域下游和易发洪水地区(占流域总面积的7%),才能进行高质量的河道水力现场测量(横截面,坡度,流量)。对于其余93%的流域面积,来自以下卫星传感器的数据被用于建立功能性河流模型:(a)穿梭雷达地形任务,以得出河流网络并调整河床剖面; (b)Landsat-MODIS,用于更新由高程数据生成的河网和水流方向; (c)雷达测高数据,以建立河流位置的深度与宽度的关系; (d)基于卫星降水的主要河流侧流水文模拟。我们通过系统地测试流域范围内的河流模型在两个测得的下游低洼位置模拟河流水位动态的能力,来衡量该方法的成功。本文总结了面临的主要障碍,并提供了逐步的“规则手册”方法来为世界范​​围内的大面积未开垦流域建立河流模型。通过系统地遵循这些规则,河平面模拟的均方根误差从3 m减少到1 m。这样的指南对于在尼日尔,湄公河,伊洛瓦底江和印度河等非流域的洪水预报系统中建立河流水力模型很有用。

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