Prediction of Groundwater Depth in Arid Regions by Using Wavelet-Support Vector Machine (WA-SVM)

doi:10.7522/j.issn.1000-694X.2015.00125

JOURNAL OF DESERT RESEARCH ›› 2016, Vol. 36 ›› Issue (5): 1435-1442.DOI: 10.7522/j.issn.1000-694X.2015.00125

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Prediction of Groundwater Depth in Arid Regions by Using Wavelet-Support Vector Machine (WA-SVM)

Yu Haijiao^1,2, Wen Xiaohu¹, Feng Qi¹, Yin Zhenliang¹, Chang Zongqiang¹, Yu Tengfei¹, Niu Xiaoyu³

1. Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000, China;
2. University of Chinese Academy of Sciences, Beijing 100049, China;
3. Hydrology and Water Resources Bureau of Gansu Province, Lanzhou 730000, China

Received:2015-06-17 Revised:2015-07-14 Online:2016-09-20 Published:2016-09-20

Abstract

Abstract: Prediction of monthly groundwater depth plays an important role in the reasonable utilization and management of groundwater water resources and ecological environmental protection. In this study, a monthly groundwater depth prediction model was built to predict the groundwater depth in 3 typical groundwater monitoring wells of the Ejin Basin by using wavelet-support vector machine (WA-SVM). In order to test the validity of the developed model, comparison was made between the WA-SVM model and the SVM model in terms of different evaluation criteria during validation period. Results showed that performances obtained by WA-SVM were satisfactory and WA-SVM model performed better than SVM model. Finally, it can be concluded that the WA-SVM model we had developed may be considered as an effective tool to establish a short-term monthly groundwater depth forecasting model in semiarid mountain regions where have few meteorological observatories.

Key words: groundwater depth prediction, wavelet transform, support vector machine

CLC Number:

P641.7

Yu Haijiao, Wen Xiaohu, Feng Qi, Yin Zhenliang, Chang Zongqiang, Yu Tengfei, Niu Xiaoyu. Prediction of Groundwater Depth in Arid Regions by Using Wavelet-Support Vector Machine (WA-SVM)[J]. JOURNAL OF DESERT RESEARCH, 2016, 36(5): 1435-1442.

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Prediction of Groundwater Depth in Arid Regions by Using Wavelet-Support Vector Machine (WA-SVM)

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