摘要
利用江西七一水库水电站2016—2017年水文资料,基于遗传算法对七一水库来水流量新安江模型进行了参数优化率定,并采用参数率定前后2种来水流量模型对七一水库2018年的预报结果进行检验,重点分析了水库来水流量预报结果的日误差、月误差和年误差以及强降水过程流量预报误差等。结果表明:1)遗传算法参数优化后的模型流量预报误差减小;2)日误差在7月中旬以后明显减小;3)月误差在7月之前以正偏差为主,7月以后以负偏差为主;4)参数优化后的年误差整体好于优化前;5)在强降水过程实例流量预报误差分析中,参数优化后的误差明显减小,但不同强降水过程误差程度相差较大,可能与降水空间分布的不连续性、面雨量计算方法的局限性以及降水的天气类型有关。
Based on the data of Jiangxi Qiyi Reservoir Power Station at 2016 and 2017,the parameters of Xin’an Jiang model were optimized for the water inflow in Qiyi Reservior using the genetic algorithm,and the predicted results of the optimized Xin’an Jiang model were compared with those of the original one.The daily error,monthly error,annual error of the predicted water inflow and the error of predicted results during heavy precipitation processes were emphatically discussed.The results indicated that:1)The prediction error was reduced after the parameter was optimized.2)The daily error was significantly reduced after mid-July.3)The monthly error presented positive deviation before July,and the negative deviation mainly appeared after July.4)The annual error obtained from the optimized model was less than that of the original model.5)The forecast errors of water income during the heavy precipitation processes were significantly reduced using the optimized model,but the errors presented great difference during different heavy precipitation processes,which might be owing to the uneven distribution of precipitation,the limitation of the calculation method of surface rainfall and the weather type.
作者
刘志萍
杨华
周雨
詹华斌
曹瑜
Liu Zhiping;Yang Hua;Zhou Yu;Zhan Huabin;Cao Yu(Ji’an Meteorological Bureau,Ji’an 343000,China;Jiangxi Meteorological Service Center,Nanchang 330096,China)
出处
《气象与减灾研究》
2020年第2期149-154,共6页
Meteorology and Disaster Reduction Research
基金
2020年江西省气象局面上项目“中小型水库来水增量预报方法研究”.
关键词
新安江模型
遗传算法
参数优化
来水流量
误差分析
Xin’an Jiang model
genetic algorithm
parameter optimization
water inflow
error analysis
