A Stochastic Modelling Technique for Groundwater Level Forecasting in an Arid Environment Using Time Series Methods

Author:

Mirzavand Mohammad,Ghazavi Reza

Publisher

Springer Science and Business Media LLC

Subject

Water Science and Technology,Civil and Structural Engineering

Reference39 articles.

1. Adamowski J, Chan HF (2011) A wavelet neural network conjunction model for groundwater level forecasting. J Hydrol 407(1–4):28–40. doi: 10.1016/j.jhydrol.2011.06.013

2. Akkaya Aslan ST, Gundogdu KS (2007) Mapping multi-year groundwater depth patterns from time-series analyses of seasonally lowest depth-to-groundwater maps in irrigation areas. Pol J Environ Stud 16(2):183–190. doi: 10.1002/hyp.6643

3. Alpaydin E (2009) Introduction to machine learning. The MIT Press, Cambridge

4. Arnell NW, Liu C (2001) Hydrology and water resources, in climate change 2001: impacts, adaptation, and vulnerability: contribution of working group II to the third assessment report of the intergovernmental panel on climate change. Cambridge University Press, New York

5. Barnett TP, Adam JC, Lettenmaier DP (2005) Potential impacts of a warming climate on water availability in snow-dominated regions. Nature 438(7066):303–309. doi: 10.1038/nature04141

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