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首页> 外文期刊>Hydrology and Earth System Sciences >Elevation based correction of snow coverage retrieved from satellite images to improve model calibration
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Elevation based correction of snow coverage retrieved from satellite images to improve model calibration

机译:从卫星图像中检索到的基于海拔的积雪校正,以改善模型校准

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摘要

The most widely used method for snow dynamic simulation relies ontemperature index approach, that makes snow melt and accumulation processesdepend on air temperature related parameters. A recently used approach tocalibrate these parameters is to compare model results with snow coverageretrieved from satellite images. In area with complex topography andheterogeneous land cover, snow coverage may be affected by the presence ofshaded area or dense forest that make pixels to be falsely classified asuncovered. These circumstances may have, in turn, an influence oncalibration of model parameters.In this paper we propose a simple procedure to correct snow coverageretrieved from satellite images. We show that using raw snow coverage tocalibrate snow model may lead to parameter values out of the range acceptedby literature, so that the timing of snow dynamics measured at two groundstations is not correctly simulated. Moreover, when the snow model isimplemented into a continuous distributed hydrological model, we show thatcalibration against corrected snow coverage reduces the error in thesimulation of river flow in an Alpine catchment.
机译:雪动力学模拟中使用最广泛的方法依赖于温度指数方法,该方法使雪融化和积聚过程取决于与空气温度相关的参数。最近使用的校准这些参数的方法是将模型结果与从卫星图像中获取的积雪进行比较。在地形复杂且土地覆盖不均的地区,积雪可能会受到阴影区域或茂密森林的影响,从而使像素被错误分类为未发现。这些情况反过来可能会影响模型参数的校准。 在本文中,我们提出了一种简单的程序来校正从卫星图像中获取的积雪。我们显示,使用原始积雪覆盖范围来校准积雪模型可能会导致参数值超出文献所接受的范围,因此无法正确模拟在两个地面站测量的积雪动力学的时间。此外,当将积雪模型实现为连续分布的水文模型时,我们表明,针对校正后的积雪进行的校准会减少模拟高寒流域中河流流量的误差。

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