基于主成分-时间序列模型的地下水位预测

发布时间：2018-12-11 05:05

【摘要】：地下水位预测是区域水资源管理的重要依据。针对地下水位在时间序列上表现出高度的随机性和滞后性,建立了基于主成分分析与多变量时间序列CAR(Controlled Auto-Regressive)模型耦合的地下水位预报模型,将该模型应用于济南市陡沟灌区地下水位预测,结果显示,模型模拟值与实测值的决定系数R~2和Nash-Suttcliffe系数Ens均达到0.90以上;以2011年为基准年,当降水量减少10%~20%,蒸发量和生活用水量增加10%~20%,调入27.39万~137.0万m~3地表水用于农业灌溉时,到2030年灌区地下水位将维持在30.99~31.29 m,较基准年上升0.12~0.42 m。在区域水资源紧缺的背景下,适当引入地表水灌溉,减少地下水的开采,灌区地下水位将逐步回升,对于灌区的可持续发展和区域水资源的合理利用具有重要意义。
[Abstract]:Groundwater level prediction is an important basis for regional water resources management. Aiming at the high randomness and lag of groundwater level in time series, a groundwater level prediction model based on the coupling of principal component analysis (PCA) and multivariable time series (CAR (Controlled Auto-Regressive) model is established. The model is applied to the prediction of groundwater level in steep gully irrigation area of Jinan city. The results show that the determining coefficient Ru 2 and the Nash-Suttcliffe coefficient Ens of the simulated value and the measured value are both above 0.90; Taking 2011 as the base year, when precipitation is reduced by 10 to 20, evaporation and household water consumption are increased by 10 to 20, and 273900 ~ 1.37 million mm3 surface water is transferred for agricultural irrigation, the groundwater level in irrigation areas will be maintained at 30.99 ~ 31.29 mg. by 2030. An increase of 0.12 / 0.42 m over the base year was recorded. Under the background of regional water resources shortage, it is important for the sustainable development of irrigation areas and rational utilization of regional water resources to introduce surface water irrigation properly and reduce the exploitation of groundwater.
【作者单位】：河海大学水利水电学院;河海大学南方地区高效灌排与农业水土环境教育部重点实验室;山东省水利科学研究院;
【基金】：国家自然科学基金资助项目(51179050) 山东省水生态文明试点科技支撑计划(ZC201450519)~~
【分类号】：P641.8

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