Evaluation of some regression models in the prediction of dissolved oxygen and water temperature of the Jarreh Dam, Iran

The climate change phenomenon has resulted in increased unpredictability regarding water availability in dry and semi-dry areas. This challenge affects not just the amount of water accessible but also intensifies worries about the quality of water. Water quality is impacted by climate change, specifically through extreme fluctuations in precipitation and temperature and, consequently, more runoff and evaporation rates. The warmer temperature and less precipitation affect water temperature as well as ecosystem health. It is essential to consider how changes in water temperature (Tw) and dissolved oxygen (DO) levels are influenced by heat exchange with the surrounding environment to evaluate water quality comprehensively. The primary goal of this research is to assess alterations in Tw and DO utilizing regression models within the Jarreh Dam reservoir in southwestern Iran. The findings indicated that air temperature had a considerable impact on Tw, as the large reservoir of the dam reduced the influence of other weather factors and hydraulic conditions on variations in Tw and DO. The accuracy of Tw estimation increased with longer time scales, and using logistic equations further improved this precision. Additionally, the effects of stage fluctuations on Tw and DO were minimal due to slight variations in relative water depth. Consequently, it was essential to consider both the direct effects of temperature and the indirect influences of factors like water salinity when evaluating the impacts of climate change on dissolved oxygen in rivers. Additionally, of the two evaluated chemical parameters, the electrical conductivity model was important because of its impact on biological activities. In large water reservoirs where high turbulence through modifications is unfeasible, considering chemical and biological parameters may be more effective for optimizing DO levels than just adjusting water levels.