Karstik Dogger Akiferi’nde konumsal hidrolik yük dağılımının Ampirik Bayes Kriging ve ANFIS yöntemleriyle değerlendirilmesi

Year 2020, Volume: 6 Issue: 1, 24 - 41, 01.11.2020

Günseli Erdem , Bedri Kurtuluş

Abstract

Bu çalışmada, karstik bir akiferdeki hidrolik yük dağılımı, Bulanık mantıklı yapay sinir ağları (ANFIS) ve Ampirik Bayes Kriging (EBK) yöntemleri ile değerlendirilmiştir. ANFIS, önceden elde edilmiş kartezyen koordinatları (XY) ve yükseklik datasını (Z) giriş verisi olarak kullanır. EBK, giriş datalarından birçok semi-variogram modelini tahmin ederek ortaya çıkan hatayı hesaba katar ve enterpolasyonda kullanır. İki yöntem sonucunda çıkan modeller aynı çalışma alanındaki hidrolik yük dağılımını incelemede kullanılmıştır: Dogger akiferi, Fransa’nın Poitiers şehrinin güneydoğusunda yer alır ve 445 km2 genişliğinde bir alanı kaplamaktadır. Toplam 113 hidrolik yük verisinin içinden 20 verinin 100 adet rastgele veri alt kümesinde test edilerek modeller elde edilmiştir. Geriye kalan veriler ise modelleri eğitmek ve doğrulamak için kullanılmıştır. ANFISXYZ ve EBK daha sonra çalışma alanını kaplayan 100 m2 büyüklüğünde alana sahip hücrelere ayrılarak her hücredeki hidrolik yükü enterpole etmek için kullanılmıştır. Hem EBK hem de ANFIS enterpolasyonları, ortalama RMSE = 5.2 m ve R2 = 0.80 değerleri ile benzer enterpolasyon sonuçları göstermiştir. Bu iki yaklaşımı birleştirmek hidrolik yük dağılımını daha doğru enterpole etmek için gelişmiş bir seçenek olabilir.

Keywords

ANFIS, Ampirik Bayes Kriging, Hidrolik yük, Dogger, Karst, Fransa

Supporting Institution

TÜBİTAK

Project Number

115Y843

Evaluating of spatial hydraulic head distribution using Empirical Bayesian Kriging and ANFIS methods in Dogger Karst Aquifer

Abstract

In this study, Adaptive Neuro Fuzzy based Inference System (ANFIS) and Empirical Bayesian Kriging (EBK) are evaluated for assessing hydraulic head distribution in a karst aquifer. ANFIS uses three reduced centered preprocessed inputs, which are cartesian coordinates (XY) and the elevation (Z). All models are applied to the same case study: Dogger aquifer, which covers an area of 445 km2 in the south east of Poitiers, France. Models are tested on 100 random data subset of 20 data among 113, the remaining is used to train and validate the models. ANFISXYZ and EBK are then used to interpolate the hydraulic head on a 100 m square - grid covering the study area. Both EBK and ANFIS interpolations exhibit similar patterns, with the average values of RMSE = 5.2 m and R2 = 0.80. Combining these approaches can be an advanced option for interpolating hydraulic head in a more accurate way.

Keywords

ANFIS, Empirical Bayesian Kriging, Hydraulic head, Dogger, Karst, France

Project Number

115Y843

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