An error model for long-range ensemble forecasts of ephemeral rivers
An error model for long-range ensemble forecasts of ephemeral rivers
复制标题
短暂河流长期集合预报的误差模型
DOI：
10.1016/j.advwatres.2021.103891
复制
发表时间：
2021
影响因子：
4.7
通讯作者：
K. Michael
中科院分区：
文献类型：
--
作者：
J. Bennett;Quan J. Wang;D. Robertson;R. Bridgart;J. Lerat;Ming Li;K. Michael
很少有集合径流预报系统是为短暂河流而设计的。在这项研究中，我们修订了用于生成预测引导随机情景(FoGSS)的误差模型，以生成对短暂河流的统计可靠的长期(12个月)预测。FOGSS的特点是误差模型包括四个阶段：数据转换、偏差校正、自回归误差模型和残差的统计分布。我们对FOGSS的第四阶段进行了修正，采用了一种参数估计方法，该方法使用数据删减来说明观测和预报中的零值。这使得FOGSS即使在高度短暂的河流(50%为零流量)中也能产生统计上可靠的集合预报。我们将FOGSS应用于澳大利亚50个流域的常规集合水文预报(ESP)预报，其中包括26条短暂河流。我们发现，FOGSS在短提前期提高了ESP预报的准确性，而在长提前期，FOGSS预报过渡到气候学预报。FOGSS预测在单个交货期和交货期累计交货量方面是可靠的，即使在非常短暂的河流中也是如此。FOGSS预报为短暂河流的业务长期预报铺平了道路，满足了改善水管理的关键需求。
Few ensemble streamflow forecasting systems are designed to operate for ephemeral rivers. In this study, we revise our error model for generating Forecast Guided Stochastic Scenarios (FoGSS) to produce statistically reliable long-range (12-month) forecasts for ephemeral rivers. FoGSS features an error model with four stages: data transformation, bias-correction, an autoregressive error model and the statistical distribution of residuals. We revise the fourth stage of FoGSS with a parameter estimation method that uses data censoring to account for zero values in both observations and forecasts. This allows FoGSS to produce statistically reliable ensemble forecasts in even highly ephemeral streams (with >50% zero flows). We apply FoGSS to conventional ensemble hydrological prediction (ESP) forecasts for 50 Australian catchments, including 26 ephemeral rivers. We show that FoGSS improves the accuracy of ESP forecasts at short lead times, while at long lead times FoGSS forecasts transition to climatology-like forecasts. FoGSS forecasts are reliable in ensemble spread at individual lead times and for volumes aggregated over lead times, even in highly ephemeral rivers. FoGSS forecasts pave the way for operational long-range forecasts in ephemeral rivers, meeting a key need for improved water management.