Evaluation of 3-D spatial distribution of dissolved oxygen concentrations in a eutrophic lake


Environmental Science and Pollution Research, vol.30, no.18, pp.54106-54118, 2023 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 30 Issue: 18
  • Publication Date: 2023
  • Doi Number: 10.1007/s11356-023-26143-w
  • Journal Name: Environmental Science and Pollution Research
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, IBZ Online, ABI/INFORM, Aerospace Database, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), BIOSIS, CAB Abstracts, EMBASE, Environment Index, Geobase, MEDLINE, Pollution Abstracts, Veterinary Science Database, Civil Engineering Abstracts
  • Page Numbers: pp.54106-54118
  • Keywords: 3-D kriging, Porsuk Dam Reservoir, SGeMs, Thermocline layer, Water quality, Segmentation
  • Akdeniz University Affiliated: Yes


In this study, three-dimensional (3-D) ordinary kriging of dissolved oxygen (DO) concentrations was performed for a eutrophic reservoir based on 81 sampling points using Stanford Geostatistical Modeling Software (SGeMs). Potential hotspots (problematic zones in terms of water quality with high/low DO concentrations) not only at the surface but also in deeper layers of Porsuk Dam Reservoir (PDR) were evaluated. Moreover, 3-D distributions of DO, and specific conductivity (SC) were examined against the thermocline layer identified using the 3-D temperature data. Thermocline layer existed between 10 and 14 m below the surface based on 3-D temperature data. This result showed that the traditional approach of collecting samples from mid-depths may cause incomplete characterization and evaluation of water quality as thermocline layer may not coincide with mid-depth. Although the variation in SC values and temperatures above and below the thermocline layer were relatively homogeneous, this was not the case for DO. 3-D DO distribution suggested a better location for water withdrawal for domestic purposes. 3-D DO maps generated by predicting data at unmeasured locations at different depths could be used as input for 3-D water quality estimation in the reservoir through model simulations in future. Moreover, the outcomes can also be useful in the segmentation (physical configuration) of the water body for future water quality modeling studies.