针对小浪底水库下半段库区出现水质水温分层现象，建立基于标准k－ε紊流双方程的立面二维水质模型对小浪底出库水质进行了预测。通过示踪试验确定水质模型的参数，并将氨氮含量作为预测水质参数，采用实测数据对模型进行了验证，结果表明：小浪底坝下段氨氮含量预测值与实测值相比较平均相对误差为12％，坝前断面垂向氨氮含量预测值与实测值相比平均相对误差为17％，表明该水质模型可以较准确预测小浪底出库水质。应用该模型预测2013—2014年度黄河调水期小浪底出库水质表明：2014年3月10日小浪底出库水氨氮含量将达到1．20 mg／L（超标），应从3月1日开始加大陆浑水库、故县水库闸门开启度，进行稀释调度，以确保调水水质不超标。%Aiming at water temperature and water quality stratification phenomenon occurring in the lower half of the the Xiaolangdi Reservoir dur-ing the Yellow River water diversion and low temperature period,the vertical 2D water quality model was established based on k-εtwo-equation of turbulence,and outlet water quality of Xiaolangdi Reservoir was estimated. Ammonia nitrogen as a forecast water quality parameter,the model was verified by actual value. The result shows the that the outlet water of the Xiaolangdi Reservoir mean relative error of ammonia nitrogen concen-tration between forecast value and actual value is 12%,vertical distribution of ammonia nitrogen concentration in front of Xiaolangdi Reservoir dam mean relative error between forecast value and actual value is 17%. It means the Xiaolangdi Reservoir outflow water quality can be accurately pre-dicted by the?water quality model. The model is used to predict the Xiaolangdi Reservoir outflow water quality during the Yellow River water regu-lation from 2013 to 2014. The result shows that the ammonia nitrogen concentration will reach to 1. 2mg/l (exceed the standards)on March 10, 2014,and the sluice gate opening degree of Luhun Reservoir and Guxian Reservoir should be increased to regulate water supplies for the dilution of the pollution on March 1,in order to ensure the water quality of the regulated water.
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