Continuous monitoring of water quality in dam reservoirs is a typically difficult and costly operation. In this study, the results of computer modeling with the CE-QUAL-W2 model were combined with data mining techniques to develop a new method called “delta-normal stress” for identifying the critical temporal and spatial monitoring ranges. For this purpose, long-term variations of three quality parameters including nitrite-nitrate level, dissolved oxygen (DO) level, and water temperature near the outlet of the dam, which is the point of interest for reservoir exploitation, were analyzed. Based on this analysis, the time intervals and depth ranges with the highest frequency of significant variations in terms of each parameter were identified. The results showed that given the difference between the delta-normal stress trend of temperature and that of other parameters in Karkheh Dam Reservoir, temperature can be monitored at much lower sampling resolutions and using cheaper methods and equipment without sacrificing accuracy. Based on the frequency of occurrence of delta-normal stress of more than 20% above the total average, the key sampling times and locations for nitrite-nitrate and DO levels were determined to be the periods of January–February, February–March, and March–April, and depths of 60, 55, 50, and 5 m, respectively.

Keywords