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首页> 外文期刊>Nordic hydrology >Predictions in a data-sparse region using a regionalized grid-based hydrologic model driven by remotely sensed data
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Predictions in a data-sparse region using a regionalized grid-based hydrologic model driven by remotely sensed data

机译：使用由遥感数据驱动的基于区域化网格的水文模型对数据稀疏区域进行预测

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The goal of this study was to assess the feasibility of using Tropical Rainfall Measuring Mission (TRMM) and Moderate Resolution Imaging Spectroradiometer (MODIS) products to drive a mesoscale hydrologic model (mHM) in a poorly gauged basin. Other remotely sensed products such as LandSat and Shuttle Radar Topography Mission (SRTM) were also used to complement the local geoinformation. For this purpose, three data blending techniques that combine satellite with in situ observations were implemented and evaluated in the Mod basin (512 km2) in India. The climate of the basin is semi-arid and monsoon-dominated. The rainfall gauging network comprised six stations with daily records spanning 9 years. Daily discharge time series was only 4 years long and incomplete. Lumped and distributed versions of mHM were evaluated. Parameters of the lumped version were obtained through calibration. A multiscale regionalization technique was used to parameterize the distributed version using global parameters from other gauged basins. Both mHM versions were evaluated during six monsoon seasons. Results of numerical experiments indicated that driving mHM with satellite-based products is possible and promising. The distributed model with regionalized parameters was at least 20% more efficient than that of its lumped version, initialization conditions must be carefully considered when the model is only driven by remotely sensed inputs.
机译：这项研究的目的是评估使用热带降雨测量任务（TRMM）和中等分辨率成像光谱仪（MODIS）产品在测量欠佳的盆地中驱动中尺度水文模型（mHM）的可行性。其他遥感产品，例如LandSat和Shuttle雷达地形任务（SRTM），也被用来补充当地的地理信息。为此，在印度的莫德盆地（512 km2）中实施并评估了三种将卫星与现场观测相结合的数据融合技术。流域的气候为半干旱和季风为主。降雨测量网络由六个站组成，每日记录长达9年。每天的出院时间序列只有4年之久，而且还不完整。评估了mHM的集总和分布式版本。集总版本的参数通过校准获得。使用了多尺度区域化技术，使用来自其他规范盆地的全局参数来对分布式版本进行参数化。两个mHM版本均在六个季风季节进行了评估。数值实验结果表明，用基于卫星的产品驱动mHM是可能的并且很有前途。具有区域参数的分布式模型比集总模型的效率至少高20％，当模型仅由遥感输入驱动时，必须仔细考虑初始化条件。

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