Prediction of Ground Water Level in Arid Environment Using a Non-Deterministic Model

Mohammad Mirzavand, Seyed Javad Sadatinejad, Hoda Ghasemieh, Rasool Imani, Mehdi Soleymani Motlagh

Department of Natural Resources and Geoscience, University of Kashan, Kashan, Iran.
Department of New Sciences and Technologies, University of Tehran, Tehran, Iran.

DOI: 10.4236/jwarp.2014.67064                

Abstract

Modeling 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.

Keywords

Non-Deterministic Models, Akaike Criterion, Ground Water Level, Kashan Aquifer

Conflicts of Interest

The authors declare no conflicts of interest.

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