Prediction intervals for rainfall–runoff models: raw error method and split-sample validation
Prediction intervals for rainfall–runoff models: raw error method and split-sample validation
复制标题
降雨径流模型的预测区间：原始误差法和分割样本验证
DOI：
10.2166/nh.2012.038
复制
发表时间：
2012
影响因子：
2.7
通讯作者：
G. O'Donnell
中科院分区：
文献类型：
--
作者：
J. Ewen;G. O'Donnell
本文提出了一种计算流域流量过程线预测区间的方法（鬼法）。它使用一个经过校准的径流模型和一个包含原始误差的数据集，如观测和模拟之间的残差。在计算预测区间时，从数据集中选择原始误差并应用于模拟过程线。该选择方法是基于匹配模拟的水文条件与原始误差相关的水文条件。为了检验该方法，将Klemes提出并在水文学中广泛应用的分样校准-验证方法加以推广，将可用于校准和检验的数据分为三个部分，即A、B和C期。对模型进行了A期的率定。对于周期B，校准计算预测区间的方法，以给出指定的高水平包容（例如，99%的观测值位于预测区间内）。C期用于测试，以显示在实际问题的操作条件下的预期性能的方式进行。预测区间计算霍德集水区，英格兰西北部。
A method (the ghost method) is developed here that calculates prediction intervals for the discharge hydrograph for a river catchment. It uses a calibrated rainfall–runoff model and a dataset containing raw errors such as residuals between observation and simulation. When calculating prediction intervals, raw errors are selected from the dataset and applied to the simulated hydrograph. The selection method is based on matching the simulated hydrological conditions to the hydrological conditions associated with the raw errors. To test the method, the split-sample calibration-validation approach advocated by Klemes and used widely in hydrology is extended so that the data available for calibrating and testing are divided into three parts rather than two, called periods A, B and C. The rainfall–runoff model is calibrated for period A. For period B, the method by which prediction intervals are calculated is calibrated to give a specified high level of containment (e.g. 99% of observations lie within the prediction interval). Period C is used for testing, carried out in a way that shows the performance expected under operational conditions for real-world problems. Prediction intervals are calculated for the Hodder catchment, northwest England.