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An evaluation of potential sampling locations in a reservoir with emphasis on conserved spatial correlation structure

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Abstract

In this study, kernel density estimation (KDE) was coupled with ordinary two-dimensional kriging (OK) to reduce the number of sampling locations in measurement and kriging of dissolved oxygen (DO) concentrations in Porsuk Dam Reservoir (PDR). Conservation of the spatial correlation structure in the DO distribution was a target. KDE was used as a tool to aid in identification of the sampling locations that would be removed from the sampling network in order to decrease the total number of samples. Accordingly, several networks were generated in which sampling locations were reduced from 65 to 10 in increments of 4 or 5 points at a time based on kernel density maps. DO variograms were constructed, and DO values in PDR were kriged. Performance of the networks in DO estimations were evaluated through various error metrics, standard error maps (SEM), and whether the spatial correlation structure was conserved or not. Results indicated that smaller number of sampling points resulted in loss of information in regard to spatial correlation structure in DO. The minimum representative sampling points for PDR was 35. Efficacy of the sampling location selection method was tested against the networks generated by experts. It was shown that the evaluation approach proposed in this study provided a better sampling network design in which the spatial correlation structure of DO was sustained for kriging.

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Acknowledgments

We are grateful to Assoc. Prof. Dr. Elcin Kentel and Asst. Prof. Dr. Emre Alp for their valuable suggestions about this work. This work is partly supported by financial means provided to Dr. Firdes Yenilmez through TUBITAK BIDEB-2211 program.

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Authors and Affiliations

  1. Department of Environmental Engineering, Middle East Technical University, 06800, Ankara, Turkey

    Firdes Yenilmez & Aysegül Aksoy

  2. Department of Environmental Engineering, Akdeniz University, 07058, Antalya, Turkey

    Firdes Yenilmez

  3. Department of Mining Engineering, Middle East Technical University, 06800, Ankara, Turkey

    Sebnem Düzgün

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  1. Firdes Yenilmez
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  2. Sebnem Düzgün
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  3. Aysegül Aksoy
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Correspondence to Aysegül Aksoy.

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Keypoints

• Kernel density estimation and kriging are efficient in sampling network design.

• Spatial correlation structure is lost with small number of sampling points.

• Prediction performance evaluation based on errors only may be insufficient.

• Proposed procedure was superior over experts in sampling network design.

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Yenilmez, F., Düzgün, S. & Aksoy, A. An evaluation of potential sampling locations in a reservoir with emphasis on conserved spatial correlation structure. Environ Monit Assess 187, 4216 (2015). https://doi.org/10.1007/s10661-014-4216-5

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