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Estimating degree-day factors from MODIS for snowmelt runoff modeling

机译:利用MODIS估算融雪径流模型的度日因子

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Degree-day factors are widely used to estimate snowmelt runoff in operational hydrological models. Usually, they are calibrated on observed runoff, and sometimes on satellite snow cover data. In this paper, we propose a new method for estimating the snowmelt degree-day factor (DDFsubS/sub) directly from MODIS snow covered area (SCA) and ground-based snow depth data without calibration. Subcatchment snow volume is estimated by combining SCA and snow depths. Snow density is estimated to be the ratio between observed precipitation and changes in the snow volume for days with snow accumulation. Finally, DDFsubS/sub values are estimated to be the ratio between changes in the snow water equivalent and difference between the daily temperature and the melt threshold value for days with snow melt. We compare simulations of basin runoff and snow cover patterns using spatially variable DDFsubS/sub estimated from snow data with those using spatially uniform DDFsubS/sub calibrated on runoff. The runoff performances using estimated DDFsubS/sub are slightly improved, and the simulated snow cover patterns are significantly more plausible. The new method may help reduce some of the runoff model parameter uncertainty by reducing the total number of calibration parameters. This method is applied to the Lienz catchment in East Tyrol, Austria, which covers an area of 1198 kmsup2/sup. Approximately 70% of the basin is covered by snow in the early spring season.
机译:度日因子被广泛用于估算运行水文模型中的融雪径流。通常,它们根据观测的径流进行校准,有时根据卫星积雪数据进行校准。本文提出了一种直接从MODIS积雪面积(SCA)和地面雪深数据估算雪融度日因子(DDF S )的新方法,而无需进行校准。汇水面积积雪量是通过结合SCA和积雪深度来估算的。雪密度估计为观察到的降水与积雪天数中雪量变化之间的比率。最后,DDF S 值被估算为雪水当量变化与融雪天的每日温度和融雪阈值之间的差之比。我们比较了根据积雪数据估算的空间变量DDF S 与利用径流校准的空间均匀DDF S 进行的流域径流和积雪模式的模拟。使用估计的DDF S 的径流性能略有改善,并且模拟的积雪模式明显更合理。新方法可以通过减少校准参数的总数来帮助减少径流模型参数的不确定性。该方法应用于奥地利东蒂罗尔州的利恩茨流域,该流域面积为1198 km 2 。在早春季节,盆地约有70%被雪覆盖。

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