Abstract
The groundwater level has continuously decreased due to the rapid increase of paddy field acreage in area of well irrigation paddy in Sanjiang Plain in recent years, some time happen such things as more and more “hanging pump” and local overdraft. The authors took 853 Farm as an example and established the dynamic prediction model of groundwater depth by using the multi-resolution function of wavelet analysis and nonlinear approximation ability of artificial neural network in order to solve above problems. The results of dynamic variation regularities analysis and precision inspection and comparison showed that the model had high accuracy in fitting and prediction. The prediction results also showed the groundwater level will descend continually in the future years and has an average annual downrange of about 0.66m. Therefore, the local government should reinforce the scientific groundwater management. This model revealed the dynamic variation regularities of regional groundwater and provided the scientific basis for sustainable utilization of groundwater resource in area of well irrigation paddy in 853 Farm and even entire Sanjiang Plain.
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Ding, H., Liu, D., Zhao, Ff. (2010). Variation Trend Analysis of Groundwater Depth in Area of Well Irrigation in Sanjiang Plain Based on Wavelet Neural Network. In: Zeng, Z., Wang, J. (eds) Advances in Neural Network Research and Applications. Lecture Notes in Electrical Engineering, vol 67. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12990-2_96
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DOI: https://doi.org/10.1007/978-3-642-12990-2_96
Publisher Name: Springer, Berlin, Heidelberg
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