Algorithm-based segmentation of temperature-depth profiles: Examples from a mine

• Published in: Environmental modelling & software : with environment data news Vol. 180; p. 106143
• Main Authors: Gökpinar, Thorsten, Heinze, Thomas
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.09.2024
• Subjects: algorithms; computer software; data collection; Geothermal; Groundwater; Limnology; Mine water; quantitative analysis; Stratification; surface water; Temperature profiles; water temperature; Limnology; Temperature profiles; Groundwater; Stratification; Geothermal; Mine water
• ISSN: 1364-8152; 1873-6726
• DOI: 10.1016/j.envsoft.2024.106143

Temperature can be a valuable indicator for the identification and quantification of water fluxes in surface and subsurface water bodies. Therefore, the measurement and analysis of vertical temperature profiles is an important part of the characterization of a water body. Besides its easy application and widespread use, the analysis of temperature profiles can be complex due to its nature as a non-stationary measurement in a dynamic system. This work presents a data-based algorithm to process and segment vertical water temperature profiles avoiding subjectivity in the quantitative analysis of these profiles. Special emphasis is given to studying the reproducibility and precision of the method from data acquisition to data processing and analysis. The presented method provides a blueprint for adjacent applications and showcases the explanatory power of vertical profiles of water temperature to study water fluxes. •Reproducibility of vertical water temperature profiles in a mine shaft is studied.•An automated segmentation workflow is presented for a data-driven analysis.•Changes in water temperature can be related to mine geometry and known water fluxes.•Repeated measurements allow identification of seasonal variations in water sources.