TITLE:
Cause Analysis and Prediction of the Groundwater Level in Jinghuiqu Irrigation District
AUTHORS:
Wangxiong Tao, Jie Zhang, Jianying Wang
KEYWORDS:
Jinghuiqu Irrigation District, Groundwater Level, Cause, Prediction, BP Neural Network
JOURNAL NAME:
Journal of Geoscience and Environment Protection,
Vol.3 No.2,
April
1,
2015
ABSTRACT: Groundwater environment
evolution can comprehensively reflect groundwater dynamics. Based on the
relationship between the groundwater system and the external environment in Jinghuiqu
irrigation district, adopting the Principal Component Analysis method, variation
characteristics of environmental factors including climate and human activity
and their impact on groundwater were systematically analyzed. The results show
that groundwater level in Jinghuiqu irrigation district has been significantly dropped
in nearly 34 years; the reduction of surface water irrigation use, which
reduced the amounts of groundwater recharge and destroyed the water balance, is
considered as the most direct cause for falling of regional groundwater level.
Besides, reduction in precipitation, increase of evaporation also accelerated
the declining of the groundwater level at some extent. Finally, a predicting
method of groundwater depth based on BP neural network is developed. The
experimental results show that the predicting model can reasonablely predict
the groundwater level in Jinghuiqu irrigation district with a high precision.