ARIMA和ANN模型的干旱预测适用性研究

doi:10.12118/j.issn.1000-6060.2018.05.06

摘要/Abstract

摘要： 开展干旱预测是有效应对干旱风险的前提基础，根据1960-2016年三江平原7个站点逐日降水和气温数据，利用ARIMA和ANN模型对不同时间尺度标准化降水蒸散指数（SPEI）序列进行分析建模预测。借助相关系数R、纳什效率系数NSE、Kendall秩相关系数τ、均方误差MSE和Kolmogorov-Smirnov （K-S）检验对模型的有效性进行了判定，然后分别用ARIMA和ANN模型进行12步预测，并将预测值与实际值进行比较。结果表明：（1） ARIMA模型和ANN模型对SPEI的预测能力都随时间尺度的增加而逐渐提高。（2）两种模型对3、6个月尺度SPEI的预测精度偏低，9、12、24个月的SPEI的预测精度在70%以上；（3）SPEI-9、SPEI-12、SPEI-24三个时间尺度ANN模型的预测精度优于ARIMA模型。

关键词: 干旱, ARIMA模型, ANN模型, SPEIs, 三江平原

Abstract: Drought is one of the major natural disasters,whose occurrence is linked to a sustained lack of precipitation.The drought forecast provides vital evidence and support for preventing losses of drought disasters,and therefore it is of great significance.In this study,a series of the standard precipitation evapotranspiration index (SPEI) at different time scales were calculated based on the daily precipitation and temperature data from 7 meteorological stations in Sanjiang Plain,northeast China from 1960 to 2016 and were used to forecast the drought using ARIMA and ANN models.In the stage of training and testing,the fitting degrees of the models were evaluated and validated and the optimal ARIMA and ANN models were chosen with the help of 6 fitting evaluation methods:the correlation coefficient (R),Nash-Sutcliffe efficiency coefficient (NSE),Kendall,rank correlation coefficient,the mean square error (MSE) and Kolmogorov-Smirnov (K-S) test.Then 12 values for the 12 months in 2016 were predicted by the optimal models and were compared with the corresponding observations.The results are shown as follows:(1) The prediction ability of ARIMA and ANN models based on SPEI were both increased with the increase of time scale in Sanjiang Plain.(2) The two models had poor prediction accuracy for SPEI 3 and SPEI 6.For the SPEI value of 9,12 and 24 months,all models worked well with accuracy more than 70%.(3) For the SPEI value of 9,12 and 24 months,the prediction accuracy of ANN model is better than that of ARIMA model.In particular,the prediction accuracy for one month forecast of SPEI 12 and 24 at all stations were more than 80%.All these showed that the prediction model of ANN has strong maneuverability and can effectively predict the drought at a large time scale in Sanjiang Plain.The drought prediction at small time scale (3 and 6 months) needs to be improved in future studies.

Key words: drought, ARIMA model, ANN model, SPEIs, Sanjiang Plain

中图分类号:

杨慧荣, 张玉虎, 崔恒建, 高峰, 陈秋华. ARIMA和ANN模型的干旱预测适用性研究[J]. 干旱区地理, 2018, 41(5): 945-953.

YANG Hui-rong, ZHANG Yu-hu, CUI Heng-jian, GAO Feng, CHEN Qiu-hua. Applicability of ARIMA and ANN models for drought forecasting[J]. 干旱区地理, 2018, 41(5): 945-953.

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