CAJ | 학술논문

　　在灰色微分动态模型的基础之上，采用季节/年际性指数对原始降水和实测径流进行预处理，并引入自记忆函数，构建灰色微分动态自记忆模型，将其应用于滦河流域径流过程的模拟和预测。结果表明：（1）采用预处理前的降水径流数据所构建的DHGM（2，2）模型和DHGM（2，2）自记忆模型在年尺度和月尺度上的径流模拟效果较差，难以反映径流的变化过程，对输入数据进行预处理后，构建的DHGM（2，2）自记忆模型模拟精度得到了很大的提高，三道河子站和滦县站年径流和月径流模拟序列的Nash-Sutcliffe系数和相关系数均达到了0.6以上；（2）模型在年尺度和月尺度的径流预测中具有一定的适用性，且结构简单、计算方便，但需要进一步考虑蒸发、土地利用和人类活动等因素，使模型更为完善。
　　재회색미분동태모형적기출지상，채용계절/년제성지수대원시강수화실측경류진행예처리，병인입자기억함수，구건회색미분동태자기억모형，장기응용우란하류역경류과정적모의화예측。결과표명：（1）채용예처리전적강수경류수거소구건적DHGM（2，2）모형화DHGM（2，2）자기억모형재년척도화월척도상적경류모의효과교차，난이반영경류적변화과정，대수입수거진행예처리후，구건적DHGM（2，2）자기억모형모의정도득도료흔대적제고，삼도하자참화란현참년경류화월경류모의서렬적Nash-Sutcliffe계수화상관계수균체도료0.6이상；（2）모형재년척도화월척도적경류예측중구유일정적괄용성，차결구간단、계산방편，단수요진일보고필증발、토지이용화인류활동등인소，사모형경위완선。
Based on the differential hydrological grey-model, the annual/seasonal indexes were applied to data pre-processing of precipitation and runoff for establishing the Differential Hydrological Grey Self-memo-ry Model with the self-memory theory. The model was used to simulate and predict the runoff in different time scales. The results show that (a) DHGM (2, 2) and Self-memory DHGM (2, 2) which constructed by initial data cannot described the runoff processes in annual and monthly scales. With the pre-processing data of precipitation and runoff, the Self-memory DHGM (2, 2) performed better both in Shandaohezi and Luanxian discharges, and Nash-Sutcliffe and correlation coefficients reached more than 0.6;(b) the model was applicable to predicting the runoff especially on an annual time scale. The structure model was simple and easy to operate,nevertheless,the factors of evaporation,land-use and human activity should be taken into consideration so that the model can be more perfect.