融雪补给型河流径流概率预报方法

A Probabilistic Forecast Method for the Runoff of Snowmelt Rivers

基于水文模型的径流预报不可避免存在不确定性,特别是融雪型补给河流径流预报结果不确定度更大.分别建立考虑融雪的新安江模型和退水曲线法用于汛期(包括融雪期)和枯季退水期的径流预报,并集成误差自回归校正模型,以提高实时预报精度;综合确定性预报结果和水文不确定性处理器,建立日径流概率预报模型,采用精度评价和可靠度评价两类指标评定概率预报精度.为验证提出的概率预报框架的有效性,以大渡河猴子岩水库以上流域为研究区开展研究.结果表明:新安江日模型在率定期和验证期的多年平均确定性系数均为0.85,整体精度较高;经误差校正后,预报精度得到进一步的提高,在延长预见期的基础上保证了预报精度;日径流模型分布函数中位数的预报精度均在一定程度上优于原始的确定性预报,提供的90%置信区间覆盖率和离散度分别在90%左右和0.40以下,表明其能以相对较窄的区间覆盖大部分实测值,具有较高的可靠度.研究成果可为研究区的防洪发电调度及风险管理提供技术支撑.

Uncertainties are inevitable when using hydrological models for runoff forecasting,especially the runoff forecasting results of snow-melt rechargeable rivers have greater uncertainty.The Xin'anjiang model considering snowmelt and therecession curve method were established respectively for the runoff forecast in the flood season(including the snowmelt season)and in the dry season.The error autoregressive correction model was integrated to improve the real-time forecast accuracy.A probabilistic forecast model of daily runoff was established by combining the deterministic forecast results and the hydrological uncertainty processor,and the probabilistic forecast accuracy was assessed by two types of indicators:precision evaluation and reliability evaluation.In order to verify the validity of the probabilistic forecasting framework,we carried out a case study with the watershed above the Houziyan Reservoir of the Dadu River as the study area.The multi-year average Nash-Sutcliffe efficiency coefficient of the Xin'anjiang model was O.85 in both calibration and validation periods,and the overall accuracy was high.With the error correction,the forecast accuracy was improved,and the forecast accuracy could be guaranteed on the basis of extending the forecast period.The forecast accuracy of the median of the probability distribution function was better than the original deterministic forecast to a certain extent.The coverage rate and dispersion degree of the 90%confidence interval were about 90%and below 0.40,respectively,indicating that it can cover most of the measured discharge values in a relatively narrow interval and has high reliability.The findings can provide technical support for flood control power generation scheduling and risk management in the study area.