Hydraulic head and groundwater 111cd content interpolations using empirical bayesian kriging (Ebk) and geo-adaptive neuro-fuzzy inference system (geo-ANFIS)

Sağir Ç., Kurtuluş B.

Water SA, vol.43, no.3, pp.509-519, 2017 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 43 Issue: 3
  • Publication Date: 2017
  • Doi Number: 10.4314/wsa.v43i3.16
  • Journal Name: Water SA
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.509-519
  • Keywords: 111Cd, Alluvium, ANFIS, EBK, Hydraulic head, Interpolation, Metal, Muğla
  • Middle East Technical University Affiliated: No

Abstract

In this study, hydraulic head and111Cd interpolations based on the geo-adaptive neuro-fuzzy inference system (Geo-ANFIS) and empirical Bayesian kriging (EBK) were performed for the alluvium unit of Karabağlar Polje in Muğla, Turkey. Hydraulic head measurements and111Cd analyses were done for 42 water wells during a snapshot campaign in April 2013. The main objective of this study was to compare Geo-ANFIS and EBK to interpolate hydraulic head and111Cd content of groundwater. Both models were applied on the same case study: alluvium of Karabağlar Polje, which covers an area of 25 km2 in Muğla basin, in the southwest of Turkey. The ANFIS method (called ANFISXY) uses two reduced centred pre-processed inputs, which are cartesian coordinates (XY). Geo-ANFIS is tested on a 100-random-data subset of 8 data among 42, with the remaining data used to train and validate the models. ANFISXY and EBK were then used to interpolate hydraulic head and heavy metal distribution, on a 50 m2 grid covering the study area for ANFISXY, while a 100 m2 grid was used for EBK. Both EBK- and ANFISXY-simulated hydraulic head and111Cd distributions exhibit realistic patterns, with RMSE < 9 m and RMSE < 8 µg/L, respectively. In conclusion, EBK can be considered as a better interpolation method than ANFISXY for both parameters.