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Dissolved oxygen is an essential controlling factor in the performance of facultative and maturation ponds since both take many advantages of algal photosynthetic oxygenation. The rate of this photosynthesis strongly depends on the time during the day and the location in a pond system, whose roles have been overlooked in previous guidelines of pond operation and maintenance (O&M). To elucidate these influences, a linear mixed effect model (LMM) was built on the data collected from three intensive sampling campaigns in a waste stabilization pond in Cuenca, Ecuador. Within two parallel lines of facultative and maturation ponds, nine locations were sampled at two depths in each pond. In general, the output of the mixed model indicated high spatial autocorrelations of data and wide spatiotemporal variations of the oxygen level among and within the ponds. Particularly, different ponds showed different patterns of oxygen dynamics, which were associated with many factors including flow behavior, sludge accumulation, algal distribution, influent fluctuation, and pond function. Moreover, a substantial temporal change in the oxygen level between day and night, from zero to above 20 mg O 2 ·L −1 , was observed. Algal photosynthetic activity appeared to be the main reason for these variations in the model, as it was facilitated by intensive solar radiation at high altitude. Since these diurnal and spatial patterns can supply a large amount of useful information on pond performance, insightful recommendations on dissolved oxygen (DO) monitoring and regulations were delivered. More importantly, as a mixed model showed high predictive performance, i.e., high goodness-of-fit (R 2 of 0.94), low values of mean absolute error, we recommended this advanced statistical technique as an effective tool for dealing with high autocorrelation of data in pond systems.
Algal photosynthesis plays a key role in the removal mechanisms of waste stabilization ponds (WSPs), which is indicated in the variations of three parameters, dissolved oxygen, pH, and chlorophyll a. These variations can be considerably affected by extreme climatic conditions at high altitude. To investigate these effects, three sampling campaigns were conducted in a high-altitude WSP in Cuenca (Ecuador). From the collected data, the first application of structure equation modeling (SEM) on a pond system was fitted to analyze the influence of high-altitude characteristics on pond performance, especially on the three indicators. Noticeably, air temperature appeared as the highest influencing factors as low temperature at high altitude can greatly decrease the growth rate of microorganisms. Strong wind and large diurnal variations of temperature, 7-20 °C, enhanced flow efficiency by improving mixing inside the ponds. Intense solar radiation brought both advantages and disadvantages as it boosted oxygen level during the day but promoted algal overgrowth causing oxygen depletion during the night. From these findings, the authors proposed insightful recommendations for future design, monitoring, and operation of high-altitude WSPs. Moreover, we also recommended SEM to pond engineers as an effective tool for better simulation of such complex systems like WSPs.
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