Department of Applied Mathematics and Computer Science, Technical University of Denmark, Denmark.
Water Sci Technol. 2013;68(3):584-90. doi: 10.2166/wst.2013.284.
Merging of radar rainfall data with rain gauge measurements is a common approach to overcome problems in deriving rain intensities from radar measurements. We extend an existing approach for adjustment of C-band radar data using state-space models and use the resulting rainfall intensities as input for forecasting outflow from two catchments in the Copenhagen area. Stochastic grey-box models are applied to create the runoff forecasts, providing us with not only a point forecast but also a quantification of the forecast uncertainty. Evaluating the results, we can show that using the adjusted radar data improves runoff forecasts compared with using the original radar data and that rain gauge measurements as forecast input are also outperformed. Combining the data merging approach with short-term rainfall forecasting algorithms may result in further improved runoff forecasts that can be used in real time control.
将雷达降雨数据与雨量计测量数据合并是一种常用的方法，可以解决从雷达测量中得出降雨强度的问题。我们扩展了一种现有的使用状态空间模型调整 C 波段雷达数据的方法，并将得到的降雨强度作为输入，用于预测哥本哈根地区两个流域的出流。随机灰箱模型被应用于创建径流预测，为我们提供了不仅是一个点预测，而且还有预测不确定性的量化。通过评估结果，我们可以表明，与使用原始雷达数据相比，使用调整后的雷达数据可以提高径流预测的准确性，并且将雨量计测量数据作为预测输入也可以提高预测的准确性。将数据合并方法与短期降雨预测算法相结合，可能会得到进一步改进的径流预测结果，这些结果可以实时使用。
