This study aimed to determine the potential for hypoxia in inland freshwater lakes via examining water quality variables, mainly dissolved oxygen (DO). To this end, field studies including environmental surveying and water column sampling at six stations along two routes in Lake Zarivar, Iran, together with laboratory analysis were conducted. Then, a stepwise multivariate regression analysis was employed to identify existing patterns and effects among variables. To secure the evolved model generalizability, the range of data was adjusted using available measurements from several similar lakes/wetlands with respect to their climate and sampling season. Finally, the evolved models’ reliability was examined using validation samples as well as a comparative performance appraisal with a benchmark model attained by the least squares regression technique. The results indicated that NH and pH have the most significant effect on DO. The greater amount of DO on the lake surface, i.e., wind effect, and its effect on both nitrification and ammonification processes ensure the absence of hypoxia in surface layers. Therefore, in water column monitoring programs, measuring NH and pH would be sufficient. Our results also demonstrated that the potential of hypoxia increases if the amount of NH increases in the lower layers of the water column despite releasing DO with nitrate. Strong relations between DO, as the main factor of hypoxia, with NH and pH, gives us the opportunity to predict the hypoxia potential and its level. Using time delay between nitrification and ammonification processes, one may predict the changes in the amount of oxygen from the changes in nitrogen.

中文翻译：

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确定淡水内陆湖泊缺氧潜力的主要驱动因素

本研究旨在通过检查水质变量（主要是溶解氧（DO））来确定内陆淡水湖泊缺氧的可能性。为此，我们进行了实地研究，包括在伊朗扎里瓦尔湖两条路线沿线的六个站点进行环境调查和水柱采样，并进行实验室分析。然后，采用逐步多元回归分析来确定变量之间的现有模式和影响。为了确保进化模型的普遍性，使用几个类似湖泊/湿地的气候和采样季节的可用测量值来调整数据范围。最后，使用验证样本以及与通过最小二乘回归技术获得的基准模型进行比较性能评估来检查演化模型​​的可靠性。结果表明，NH和pH对DO的影响最为显着。湖面较多的溶解氧（DO），即风效应，及其对硝化和氨化过程的影响，保证了表层不存在缺氧。因此，在水体监测项目中，测量 NH 和 pH 值就足够了。我们的结果还表明，尽管释放了硝酸盐溶解氧，但如果水柱下层的氨含量增加，缺氧的可能性就会增加。 DO 作为缺氧的主要因素，与 NH 和 pH 之间的密切关系使我们有机会预测缺氧潜力及其水平。利用硝化和氨化过程之间的时间延迟，我们可以根据氮的变化来预测氧含量的变化。