考虑降雨不确定性的洪水概率预报方法  

Probabilistic flood forecasting considering rainfall uncertainty

作　　者：梁忠民[1] 蒋晓蕾[1] 曹炎煦[2] 彭顺风[3] 王凯[3] 王栋[1] 

机构地区：[1]河海大学水文水资源学院,江苏南京210098 [2]淮河水利委员会水资源处,安徽蚌埠233000 [3]淮河水利委员会水文局(信息中心),安徽蚌埠233001

出　　处：《河海大学学报（自然科学版）》2016年第1期8-12,共5页Journal of Hohai University(Natural Sciences)

基　　金：国家自然科学基金(51179046);水利部公益性行业科研专项(201301066;201401034);江苏省普通高校研究生科研创新计划基金(CXZZ12_0240)

摘　　要：基于流域雨量站网布设的抽站法原理,推导以面雨量计算值为条件的面雨量真值的概率分布,用以描述现有测站数目条件下流域面雨量计算的不确定性。在此基础上,结合确定性预报模型,展开洪水概率预报研究。以淮河黄泥庄流域为研究对象,对该方法进行应用,结果表明:该方法不仅可以实现任一时段流域面雨量真值概率分布的估计,描述面雨量计算的不确定性;同时,通过与水文模型(如新安江模型)耦合,结合Monte-Carlo抽样技术,可以实现预报流量概率分布的估计,从而实现洪水概率预报。Based on the principle of the rainfall station sampling method, the probability distribution of the true value of areal rainfall was deduced, using the estimated areal rainfall, in order to describe the uncertainty of areal rainfall calculation under the conditions of existing rainfall stations. Then, probabilistic flood forecasting was performed in combination with deterministic prediction models. Application of this method to the Huangnizhuang Basin of the Huaihe River shows that it can obtain estimates of the probability distribution of the true value of areal rainfall for any periods of time in the basin and describe the uncertainty of the areal rainfall calculation. Furthermore, using a hydrologic model （e.g., the Xinanjiang model） and the Monte-Carlo sampling technique, the probability distribution of the predicted flow rate can be estimated, and probabilistic flood forecasting can be carried out.

关 键 词：抽站法 面雨量 降雨不确定性 Monte-Carlo抽样 洪水概率预报 新安江模型 淮河黄泥庄流域 

分 类 号：P338[天文地球—水文科学]