Comparison of Groundwater Level Estimation Using Neuro-fuzzy and Ordinary Kriging

Water level in aquifer plays the main role in groundwater modeling as one of the input data. In practice, due to aspects of time and cost, data monitoring of water levels is conducted at a limited number of sites, and interpolation technique such as kriging is widely used for estimation of this variable in unsampled sites. In this study, the efficiency of the ordinary kriging (OK) and adaptive network-based fuzzy inference system (ANFIS) was investigated in interpolation of groundwater level in an unconfined aquifer in the north of Iran. The results showed that ANFIS model is more efficient in estimating the groundwater level than OK.

[1]  Yong-Huang Lin,et al.  The strategy of building a flood forecast model by neuro‐fuzzy network , 2006 .

[2]  A. Mukhopadhyay.  Spatial Estimation of Transmissivity Using Artificial Neural Network , 1999 .

[3]  Chi-Bin Cheng,et al.  Applying fuzzy adaptive network to fuzzy regression analysis , 1999 .

[4]  Marios Sophocleous,et al.  Geostatistical Applications in Ground-Water Modeling in South-Central Kansas , 1999 .

[5]  A. Salski,et al.  Geostatistical regionalization of glacial aquitard thickness in northwestern Germany, based on fuzzy kriging , 1996 .

[6]  K. P. Sudheer,et al.  A neuro-fuzzy computing technique for modeling hydrological time series , 2004 .

[7]  Michael Edward Hohn,et al.  An Introduction to Applied Geostatistics: by Edward H. Isaaks and R. Mohan Srivastava, 1989, Oxford University Press, New York, 561 p., ISBN 0-19-505012-6, ISBN 0-19-505013-4 (paperback), $55.00 cloth, $35.00 paper (US) , 1991 .

[8]  R. Reyment,et al.  Statistics and Data Analysis in Geology. , 1988 .

[9]  Yan-xin Wang,et al.  Geostatistical and geochemical analysis of surface water leakage into groundwater on a regional scale: a case study in the Liulin karst system, northwestern China , 2001 .

[10]  Uzay Kaymak,et al.  Modelling electrical conductivity of groundwater using an adaptive neuro-fuzzy inference system , 2006, Comput. Geosci..

[11]  Phil Diamond.  Interval-valued random functions and the kriging of intervals , 1988 .

[12]  Li-Chiu Chang,et al.  Intelligent control for modelling of real‐time reservoir operation , 2001 .

[13]  S. H. Ahmadi,et al.  Geostatistical analysis of sorptivity for a soil under tilled and no-tilled conditions , 2005 .

[14]  Ladislau Martin-Neto,et al.  Carbon sequestration in two Brazilian Cerrado soils under no-till , 2006 .

[15]  Michio Sugeno,et al.  Fuzzy identification of systems and its applications to modeling and control , 1985, IEEE Transactions on Systems, Man, and Cybernetics.

[16]  E.Stanley Lee.  Neuro-Fuzzy Estimation in Spatial Statistics , 2000 .

[17]  C. Jang,et al.  Geostatistical analysis and conditional simulation for estimating the spatial variability of hydraulic conductivity in the Choushui River alluvial fan, Taiwan , 2004 .

[18]  M. SETNES,et al.  Transparent Fuzzy Modelling , 1998, Int. J. Hum. Comput. Stud..

[19]  Fakhri Karray,et al.  Minimizing variance of reservoir systems operations benefits using soft computing tools , 2003, Fuzzy Sets Syst..

[20]  F ROSENBLATT,et al.  The perceptron: a probabilistic model for information storage and organization in the brain. , 1958, Psychological review.

[21]  K. Cameron,et al.  Using spatial models and kriging techniques to optimize long‐term ground‐water monitoring networks: a case study , 2002 .

[22]  J. Nash,et al.  River flow forecasting through conceptual models part I — A discussion of principles☆ , 1970 .

[23]  Jyh-Shing Roger Jang,et al.  ANFIS: adaptive-network-based fuzzy inference system , 1993, IEEE Trans. Syst. Man Cybern..

[24]  C Logan,et al.  On the kriging of water table elevations using collateral information from a digital elevation model , 2002 .

[25]  Y. Nagayama,et al.  Reservoir operation using the neural network and fuzzy systems for dam control and operation support , 2002 .

[26]  G. Marsily,et al.  Application of Kriging Techniques in Groundwater Hydrology , 1987 .