and forecasting of the groundwater water table are a major component of
effective planning and management of water resources. One way to predict the
groundwater level is analysis using a non-deterministic model. This study
assessed the performance of such models in predicting the groundwater level at
Kashan aquifer. Data from 36 piezometer wells in Kashan aquifer for 1999 to
2010 were used. The desired statistical interval was divided into two parts and
statistics for 1990 to 2004 were used for modeling and statistics from 2005 to
2010 were used for valediction of the model. The Akaike criterion and
correlation coefficients were used to determine the accuracy of the prediction
models. The results indicated that the AR(2) model more accurately predicted
ground water level in the plains; using this model, the groundwater water table
was predicted for up to 60 mo.
Cite this paper
Mirzavand, M. , Sadatinejad, S. , Ghasemieh, H. , Imani, R. and Motlagh, M. (2014) Prediction of Ground Water Level in Arid Environment Using a Non-Deterministic Model. Journal of Water Resource and Protection
, 669-676. doi: 10.4236/jwarp.2014.67064
 De Gooijer, J.G. and Hyndman, R.J. (2006) 25 Years of Time Series Forecasting. International Journal of Forecasting, 22, 443-473. http://dx.doi.org/10.1016/j.ijforecast.2006.01.001
 Salas, J.D. (1993) Analysis and Modeling of Hydrological Time Series. In: Maidment, D.R., Ed., Handbook of Hydrology, McGraw-Hill, New York, 19.1-19.72.
 Brass, R.L. and Rodriguez-lturbe, L. (1985) Random Functions and Hydrology. Addison-Wesley Publishing Company, Reading.
 Brockwell, P.J. and Davis, R.A. (1987) Time Series: Theory and Methods. Springer-Verlag, New York. http://dx.doi.org/10.1007/978-1-4899-0004-3
 Lin, G.F. and Lee, F.C. (1994) Assessment of Aggregated Hydrologic Time Series Modeling. Journal of Hydrology, 156, 447-458.
 Salas, J.D., Delleur, J.W., Yevjevich, V. and Lane, W.L. (1980) Applied Modeling of Hydrologic Time Series. Water Resources Publications, Littleton.
 Khalili, K., Fakheri Fard, A., Din Pajooh, Y. and Ghorbani, M.A. (2010) Trend and Stationary Analyses of River Flow for Hydrological Time Series Modeling. Journal of Soil and Water Silences, 20, 61-72.
 Karamooz, M. and Aragi Nejad, S. H. (2005) Advanced Hydrology. 1st Edition, Amirkabir University of Technology Press, Tehran, 464.
 Wang, W., Van Gelder, P.H.A.J.M. and Vrijling, J.K. (2005) Trend and Stationary Analysis for Streamflow Processes of Rivers in Western Europe in 20th Century. IWA International Conference on Water Economics, Statistics and Finance, Rethymno, 8-10 July 2005, 11.
 Chen, H.L. and Rao, A.R. (2003) Linearity Analysis on Stationarity Segments of Hydrologic Time Series. Journal of Hydrology, 277, 89-99. http://dx.doi.org/10.1016/S0022-1694(03)00086-6
 Javidi Sabaghian, R. and Sharifi, M.B. (2009) Using Stochastic Models to Simulate River Flow and Forecast Annual Average Flow of the River by Time Series Analysis. First International Conference on Water Resources, Semnan, 16-18 August 2009, 9.
 Golmohammadi, M.H. and Safavi, H.R. (2010) Pridicting of One-Variable Hydrological Time Series Using Fuzzy Systems Based on Adaptive Neural Network. The 5th National Congress on Civil Engineering, Mashhad, 4-6 May 2010, 8 p.
 Nakhaei, M. and Mir Arabi, A. (2010) Flood Forecasting through Sumbar River Discharge Time Series Using the Box —Jenkins Model. Journal of Engineering Geology, 4, 901-915.
 Ahan, H. (2000) Modeling of Groundwater Heads Based on Second Order Difference Time Series Modeling. Journal of Hydrology, 234, 82-94. http://dx.doi.org/10.1016/S0022-1694(00)00242-0
 Saidian, Y. and Ebadi, H. (2004) Time Series Model Determining for Flow Discharge Data (Case Study: Vaniar Hydrometer Station in AjiChay River Basin). 2nd National Student Conference on Water and Soil Resources, Shiraz, 12-13 May 2004, 7.
 Jalali, K. (2002) Jiroft Dam Reservoir Inflow Forecasting Using Time Series Theory. 6th International Seminar on River Engineering, Ahvaz, 8-10 February 2002, 9.
 Alonekyenak, A. (2007) Forecasting Surface Water Level Fluctuations of Lake Van by Artificial Neural Networks. Water Resource Manage, 21, 399-408. http://dx.doi.org/10.1007/s11269-006-9022-6
 Amabyl, V., Gabriel, G. and Bernard, A.E. (2008) Fitting of Time Series Models to Forecast Stream Flow and Groundwater Using Simulated Data from SWAT. Journal of Hydrology Engineering, 13, 554-562. http://dx.doi.org/10.1061/(ASCE)1084-0699(2008)13:7(554)
 Box, G.E.P. and Jenkins, G.M. (1976) Time Series Analysis: Forecasting and Control. Holden Day, San Francisco.
 Knotters, M. and Van Walsum, P.E. (1997) Estimating Fluctuation Quantities from Time Series of Water Table Depths Using Models with a Stochastic Component. Journal of Hydrology, 197, 25-46. http://dx.doi.org/10.1016/S0022-1694(96)03278-7
 Karamooz, M. and Aragi Nejad, S.H. (2010) Advanced Hydrology. 2nd Edition, Amirkabir University of Technology Press, Tehran, 464.
 Hashemi, R. and Jahanshahi, M. (2005) Analyze and Prediction of Annual and Monthly Total Precipitation in Torbat Hedarriye Region of Khorasan. 5th Seminar on Probability and Stochastic Process, Birjand, 1-5 September 2005, 9.