R/S分析法与GM(1,1)灰色模型相结合的鸳鸯池水库入库径流量预测

Annual runoff inflow into Yuanyangchi reservoir prediction based on the combination of R/S analysis and GM(1,1) grey model

依据鸳鸯池水库1959-2015年实测入库年径流量系列,利用年代际径流量平均值、径流年内分配集中度分析了入库年径流量年际变化和年内分配特征,同时分别采用基本GM(1,1)、改进GM(1,1)以及R/S分析法与基本GM(1,1)灰色模型相结合的方法预测了入库年径流量。结果表明:入库年径流量时间序列有明显分形特征,H指数为0. 922;径流量时间序列具有状态持续性,即未来年径流量变化趋势与过去一致;年径流量系列长期记忆性以41 a为周期;经R/S分析后采用基本GM(1,1)灰色模型预测得出2013、2014、2015年入库径流量分别为3. 60×108、2. 97×108、3. 67×108m3,与实测值相比,相对误差分别为20. 69%、8. 97%、8. 10%,较基本GM(1,1)、改进GM(1,1)灰色模型的预测精度高。据此预测得出2020年入库径流量将比2015年增加8. 99%。

Based on the measured data of inflow annual runoff to Yuanyangchi Reservoir from 1959 to2015,the interannual variation and annual distribution characteristics of runoff were analyzed using the mean decadal runoff and the concentration degree of annual runoff. The basic GM( 1,1),improved GM( 1,1) and R/S analysis combined with the GM( 1,1) grey model were used to predict the annual runoff. The results show that the time series of annual runoff has obvious fractal characteristics,and the calculated H-index is 0. 922. The runoff time series has state persistence and long-term memory,which means that the runoff changes in the future are consistent with the past trends. The calculated long-term memory of the runoff series is a 41-year cycle. Based on the R/S analysis,the basic GM( 1,1) gray model predicts that the annual runoff are 3. 60 × 108 m3,2. 97 × 108 m3,and 3. 67 × 108 m3 in 2013,2014,and 2015,respectively. The relative errors are 20. 69%,8. 97%,and 8. 10%,respectively compared to the measured values,which shows the accuracy is higher than that of the basic GM( 1,1) and improved GM( 1,1) gray models. The predicted inflow annual runoff to reservoir in 2020 is 8. 99 %higher than that in 2015.