基于小波分析理论组合模型的农业需水量预测  

Application of a combined model based on wavelet analysis for predicting crop water requirement

作　　者：佟长福[1,2] 史海滨[1] 包小庆[2] 李和平[2] 

机构地区：[1]内蒙古农业大学水利与土木建筑工程学院,呼和浩特010018 [2]水利部牧区水利科学研究所,呼和浩特010020

出　　处：《农业工程学报》2011年第5期93-98,共6页Transactions of the Chinese Society of Agricultural Engineering

基　　金：水利部公益性行业科研专项项目(200801034);中国水科院科研专项(内蒙古牧区典型饲草料作物需水变化规律和预测研究)

摘　　要：为了提高农业需水量(非平稳时间序列)的预测精度,该文运用小波分析理论,将农业需水量这一时间序列用小波分解到不同尺度上以减少原始序列的随机性,然后用灰色预测法和时间序列预测法对重构后的时间序列进行预测。将小波分析理论、灰色预测理论和时间序列预测法组合进行需水量的预测,为原始非平稳时间序列的预测应用拓展了空间。以鄂尔多斯市的农业需水量预测为例对该方法作了验证,2009年数据检验结果表明该组合预测模型精度较高,相对误差小于3%,为农业需水量的预测提供了一种新方法,对鄂尔多斯市的水资源合理地利用、规划和管理以及促进区域社会经济的可持续发展具有重要的意义。Wavelet analysis was used to reconstruct the time series of the crop water requirement into different scales in order to reduce the randomicity,and then the reconstructed time series was predicted using grey and time series prediction method to increase the prediction accuracy of agricultural water requirement（non-stationary time series）.The space of prediction and application of non-stationary time series were expanded through the combined model of wavelet analysis,gray and time series prediction methods.The crop water requirement in Erdos was validate by the method,and the results showed that the prediction accuracy was high and relative error less than 3%（2009）.It can provide a new method for prediction of agricultural water requirement and has great significance to Erdos for rational use of water resources,planning and management,promoting social and economic sustainable development.

关 键 词：小波分析 模型 水资源 灰色预测模型 ARMA模型 需水量预测 

分 类 号：TV214[水利工程—水文学及水资源] S274.4[农业科学—农业水土工程]