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Integrating Remotely Sensed Data Using a Simple Vegetation Parameter Aggregation Method Applicable to a Distributed Rainfall-Runoff Model

机译:使用适用于分布式降雨-径流模型的简单植被参数聚合方法集成遥感数据

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摘要

The specification of the land cover characteristics is essential to have runoff simulated by a rainfall-runoff (RR) model in watershed hydrology. The recent availability of land cover map from remotely sensed data makes the specification of the land cover characteristics easier but it is unlikely that the RR models incorporate all spatial scales of the land cover map in need of application. This paper proposes a simple but physically based aggregation method to upscale natural vegetative heterogeneity, which is represented by Manning's roughness coefficient, to the grid scale used in typical RR model, and it compares the strength of the new method with the conventional methods and uses a hydrologic model to test the sensitivity of using different methods. The results show the new method provides better performance in terms of both the amount and time to peak flow in relative terms. The proposed method provides a reasonably realistic description of area-averaged vegetation nature and characteristics.
机译:土地覆盖特征的规范对于通过流域水文学中的降雨径流(RR)模型进行模拟是至关重要的。从遥感数据获得的土地覆盖图的最新可用性使土地覆盖特征的规范更加容易,但是RR模型不太可能需要应用所有土地覆盖图的空间比例。本文提出了一种简单但基于物理的聚集方法,以将以曼宁粗糙度系数表示的自然营养异质性提高到典型RR模型中使用的网格规模,并将新方法的强度与常规方法进行比较,并使用水文模型使用不同方法测试灵敏度。结果表明,相对于峰值流量而言,该新方法提供了更好的性能。所提出的方法为面积平均植被的性质和特征提供了合理,逼真的描述。

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