EGU23-12931
https://doi.org/10.5194/egusphere-egu23-12931
EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Statistical inference methods and stable isotopes as a tool for predicting the quality of marine bathing waters

Davor Mance1 and Diana Mance2
Davor Mance and Diana Mance
  • 1University of Rijeka, Faculty of economics and business, Croatia (davor.mance@efri.hr)
  • 2University of Rijeka, Faculty of physics, Croatia

The movement of water as a scarce resource through the soil is a physical, causal-mechanical process characterized by the ability to continuously transfer a marker in space and time. A process is capable of transferring a marker if the marker, once introduced at a particular location, persists at other locations without further interaction. In this sense, stable isotopes are markers that are transferred from one location to another over time. The analysis of multiple indicators across space and time is known in statistics as longitudinal data analysis or panel data analysis. We show how some of these relatively new inductive statistical inference methods, in conjunction with known deductive nomological models, can be useful in building a predictive model for the quality of marine bathing waters in the Kvarner Bay (Adriatic Sea, Croatia).

This work was supported by the University of Rijeka under the project numbers: uniri-pr-prirod-19-24, UNIRI CLASS – A1-21-8 34.

How to cite: Mance, D. and Mance, D.: Statistical inference methods and stable isotopes as a tool for predicting the quality of marine bathing waters, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-12931, https://doi.org/10.5194/egusphere-egu23-12931, 2023.