中文摘要：

分析了塔里木盆地南缘和田绿洲洛浦灌区地下水位较高的成因，研究了灌区地下水位年内的动态变化规律，利用小波分析的多分辨率功能和人工神经网络的非线性逼近功能，建立了基于小波变换和BP神经网络的地下水埋深动态预测小波神经网络模型。结果表明：灌区地下水位变化具有周期性、季节性的特点，并且可以被小波神经网络模型准确地模拟，模型预测洛浦灌区在未来几年内地下水位会持续上升，年平均升幅为0．1m左右，因此当地应加强舶下水的科学管理。

英文摘要：

In this paper, the reason of high groundwater table of Luopo irrigation region was analyzed in Hetian Oasis, Southern Margin of Tarim Basin. Mayor factors influencing the groundwater table of irrigation region were ascertained and the groundwater table change is simulated based on wavelet transform and BP neural network. Through this model, the groundwater dynamic variation regularities were analyzed. The results of precision test and comparative analysis showed that the precisions of this model were high in fitting and prediction. The results of prediction showed that the groundwater level of Luopu irrigation region would continually descend within the intending several years. The annual ascending extent would be about 0.1 m on average. So local government should reinforce the scientific management towards groundwater.