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

Yıl 2020, Cilt: 6 Sayı: 1, 24 - 41, 01.11.2020

Öz

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.

Destekleyen Kurum

TÜBİTAK

Proje Numarası

115Y843

Kaynakça

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

Yıl 2020, Cilt: 6 Sayı: 1, 24 - 41, 01.11.2020

Öz

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.

Proje Numarası

115Y843

Kaynakça

  • Kurtulus, B., Flipo, N., Goblet, P., Vilain, G., Tournebize, J., Tallec, G., (2011). Hydraulic head interpolation in an aquifer unit using anfis and ordinary kriging. In: Madani K et al. (eds) Computational intelligence. 1st edn,. P. 265–276. Berlin, Heidelberg, Springer. https://doi.org/10.1007/978-3-642-20206-3_18.
  • Flipo, N., Monteil, C., Poulin, M., Fouquet, C., Krimissa, M., (2012). Hybrid fitting of a hydrosystem model: Long term insight into the Beauce aquifer functioning (France). Water Resources Research 48(5). https://doi.org/10.1029/2011WR011092.
  • Amini, M., Abbaspour, K.C., Johnson, C.A., (2010). A comparison of different rule-based statistical models for modeling geogenic groundwater contamination. Environmental Modelling & Software 25(12): 1650-1657. https://doi.org/10.1016/j.envsoft.2010.05.014.
  • Yeganeh, B., Hewson, M.G., Clifford, S., Knibbs, L.D., Morawska, L., (2017). A satellite-based model for estimating PM2.5 concentration in a sparsely populated environment using soft computing techniques. Environmental Modelling & Software 88: 84-92, https://doi.org/10.1016/j.envsoft.2016.11.017.
  • Rivest, M., Marcotte, D., Pasquier, P., (2008). Hydraulic head field estimation using kriging with an external drift: A way to consider conceptual model information. Journal of Hydrology 361(3): 349–361. https://doi.org/10.1016/j.jhydrol.2008.08.006.
  • Perkins, S.P., Sophocleous, M., (1999). Development of a comprehensive watershed model applied to study stream yield under drought conditions. Ground Water 37(3): 418–426. https://doi.org/10.1111/j.1745-6584.1999.tb01121.x.
  • Flipo, N., Jeannée, N., Poulin, M., Even, S., Ledoux, E., (2007). Assessment of nitrate pollution in the Grand Morin aquifers (France): Combined use of geostatistics and physically-based modeling. Environmental Pollution 146(1):241–256. https://doi.org/10.1016/j.envpol.2006.03.056.
  • Flipo, N., Mourhi, A., Labarthe, B., Biancamaria, S., Rivière, A., Weill, P., (2014). Continental hydrosystem modelling : the concept of nested stream-aquifer interfaces. Hydrology and Earth System Sciences 18(8)3121–3149. doi:10.5194/hess-18-3121-2014.
  • Kurtulus, B., Flipo, N., (2012). Hydraulic head interpolation using anfis - model selection and sensitivity analysis. Computer & Geosciences 38(1): 43–51, https://doi.org/10.1016/j.cageo.2011.04.019.
  • Mouhri, A., Flipo, N., Rejiba, F., Fouquet, C., Bodet, L., Goblet, P., Kurtulus, B., Ansart, P., Tallec, G., Durand, V., Jost, A., (2013). Designing a multi-scale sampling system of stream-aquifer interfaces in a sedimentary basin. Journal of Hydrology 504: 194–206, https://doi.org/10.1016/j.jhydrol.2013.09.036.
  • Tóth, J., (2002). József Tóth: An autobiographical sketch. Ground Water 40(3): 320–324. https://doi.org/10.1111/j.1745-6584.2002.tb02661.x.
  • Cressie, N., (1990). The origins of kriging. Mathematical Geology 22(2): 239–252, https://doi.org/10.1007/BF00889887.
  • Rouhani, S., Myers, D.E., (1990). Problems in space-time kriging of geohydrological data. Mathematical Geology 22(5): 611–623, https://doi.org/10.1007/BF00890508.
  • Weber, D.D., Englung, E.J., (1994). Evaluation and comparison of spatial interpolators II. Mathematical Geology 26: 589–604, https://doi.org/10.1007/BF02089243.
  • Zimmerman, D., Pavlik, C., Ruggles, A., Armstrong, M.P., (1999). An experimental comparison of ordinary and universal kriging and inverse distance weighting. Mathematical Geology 31(4): 375–390, https://doi.org/10.1023/A:1007586507433.
  • Brochu, Y., Marcotte, D., (2003). A simple approach to account for radial flow and boundary conditions when kriging hydraulic head fields for confined aquifers. Mathematical Geology 35(2): 111–139, https://doi.org/10.1023/A:1023231404211.
  • Theodossiou, N., Latinopoulos, P., (2006). Evaluation and optimisation of groundwater observation networks using the kriging methodology. Environmental Modelling & Software 21(7): 991–1000, https://doi.org/10.1016/j.envsoft.2005.05.001.
  • Lyon, S.W., Seibert, J., Lembo, A.J., Walter, M.T., Steenhuis, T.S., (2006) Geostatistical investigation into the temporal evolution of spatial structure in a shallow water table. Hydrology and Earth System Sciences 10: 113–125.
  • Ahmadi, S.H., Sedghamiz, A., (2007). Geostatistical analysis of spatial and temporal variations of groundwater level. Environmental Monitoring and Assessment 129(1-3): 277–294, https://doi.org/10.1007/s10661-006-9361-z.
  • Abedini, M.J., Nasseri, M., Ansari, A., (2008). Cluster-based ordinary kriging of piezometric head in West Texas/New Mexico - Testing of hypothesis. Journal of Hydrology 351(3): 360–367, https://doi.org/10.1016/j.jhydrol.2007.12.030.
  • Renard, F., Jeannée, N., (2008). Estimating transmissivity fields and their influence on flow and transport: The case of Champagne mounts. Water Resources Research 44(11): 1–12, https://doi.org/10.1029/2008WR007033.
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Toplam 74 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Bölüm Araştırma Makalesi
Yazarlar

Günseli Erdem 0000-0002-4061-4336

Bedri Kurtuluş 0000-0001-6646-9280

Proje Numarası 115Y843
Yayımlanma Tarihi 1 Kasım 2020
Gönderilme Tarihi 30 Aralık 2019
Kabul Tarihi 4 Şubat 2020
Yayımlandığı Sayı Yıl 2020 Cilt: 6 Sayı: 1

Kaynak Göster

APA Erdem, G., & Kurtuluş, B. (2020). Evaluating of spatial hydraulic head distribution using Empirical Bayesian Kriging and ANFIS methods in Dogger Karst Aquifer. Turkish Journal of Maritime and Marine Sciences, 6(1), 24-41.

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