基于ARIMA时序模型的灌区供需水量预测研究OA
Research on water supply and demand forecasting in irrigation areas based on the ARIMA time series mode
为实现茨淮新河灌区水量分配与管理的科学预测,基于1991-2023年灌区抽水量实采数据建立灌区水量供需平衡分析体系.利用灰色关联度分析和ARIMA时序模型分析农业、生活、航运等场景的需水量指标对总抽水量的影响,并预测灌区未来水量需求.结果表明,灌溉需水与实际抽水量的关联度最高达到 0.8983,通过多重检验和模型训练,ARIMA模型的预测准确率达到了88.587%,可以为灌区水量供需与调度提供有效参考.该预测方法可推广至其他水资源紧张区域,为水量供需的优化管理提供借鉴与参考.
To achieve scientific prediction for water allocation and management in the Cihuai New River Irrigation Area,an ana-lytical system for the balance of water supply and demand was established in the irrigation area,using the actual water extrac-tion data from 1991 to 2023.Using grey relational analysis and the ARIMA time series model,the impact of water demand indi-cators such as agriculture,domestic use,and navigation on total water extraction and forecasts future water demand were ana-lyzed.The results showed that the highest correlation degree between irrigation water demand and actual pumping amount was 0.8983.Through multiple tests and model training,the ARIMA model achieved a prediction accuracy of 88.587%,and provided an effective reference for water supply and scheduling in the irrigation area.The prediction method proposed in this paper could be extended to other water-scarce regions,offering a reference for the optimization management of water supply and demand.
张书宝
安徽省茨淮新河工程管理局,安徽 蚌埠 233400
水利科学
灌区水量管理ARIMA模型灰色关联度分析水量预测
irrigation water managementARIMA modelgrey relational analysiswater volume prediction
《江淮水利科技》 2024 (004)
28-33 / 6
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