Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Hydraulic head and groundwater 111cd content interpolations using empirical bayesian kriging (Ebk) and geo-adaptive neuro-fuzzy inference system (geo-ANFIS)
Download
ajol-file-journals_28_articles_159667_submission_proof_159667-325-414693-1-10-20170802.pdf
Date
2017-01-01
Author
Sağır, Çağdaş
Kurtuluş, Bedri
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
115
views
30
downloads
Cite This
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.
Subject Keywords
111Cd
,
Alluvium
,
ANFIS
,
EBK
,
Hydraulic head
,
Interpolation
,
Metal
,
Muğla
URI
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85026864987&origin=inward
https://hdl.handle.net/11511/104986
Journal
Water SA
DOI
https://doi.org/10.4314/wsa.v43i3.16
Collections
Department of Geological Engineering, Article
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
Ç. Sağır and B. Kurtuluş, “Hydraulic head and groundwater 111cd content interpolations using empirical bayesian kriging (Ebk) and geo-adaptive neuro-fuzzy inference system (geo-ANFIS),”
Water SA
, vol. 43, no. 3, pp. 509–519, 2017, Accessed: 00, 2023. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85026864987&origin=inward.