.3.3. Human operational factors vs. temporal variability of water quality
The preceding results suggest that HOFs and drinking water quality are linked. To delve deeper, the daily data of survey S2 and campaign C2 (involving six systems during six days) were also analyzed to complete the study on the relationship between DWQI and HOFs. The daily variability of DWQI and HOF scores for the six consecutive days is represented in Fig. 6. Among the six systems in survey S2, some present visible similarities between trends observed for DWQI and HOF scores in the short term. HOF scores seem more stable in time than DWQI values, i.e., the same operations are carried out in nearly the same manner by operators in a short observation period. However, minor changes are visible, and the variations of DWQI values match the minor alterations in HOF for four systems (QC1, QC2, NL1, NL3) (Fig. 6). Two systems(QC3, NL2) do not show any link between these two factors During the six days surveyed, the motivation factor had the highest variability, which could be the main factor influencing overall daily HOF scores. Other variable factors were the complexity and the difficulty of daily duties associated with specific tasks accomplished during the day. In order to validate these short-term observations, statistical multivariate regressions were carried out.
.3.3. Human operational factors vs. temporal variability of water quality The preceding results suggest that HOFs and drinking water quality are linked. To delve deeper, the daily data of survey S2 and campaign C2 (involving six systems during six days) were also analyzed to complete the study on the relationship between DWQI and HOFs. The daily variability of DWQI and HOF scores for the six consecutive days is represented in Fig. 6. Among the six systems in survey S2, some present visible similarities between trends observed for DWQI and HOF scores in the short term. HOF scores seem more stable in time than DWQI values, i.e., the same operations are carried out in nearly the same manner by operators in a short observation period. However, minor changes are visible, and the variations of DWQI values match the minor alterations in HOF for four systems (QC1, QC2, NL1, NL3) (Fig. 6). Two systems(QC3, NL2) do not show any link between these two factors During the six days surveyed, the motivation factor had the highest variability, which could be the main factor influencing overall daily HOF scores. Other variable factors were the complexity and the difficulty of daily duties associated with specific tasks accomplished during the day. In order to validate these short-term observations, statistical multivariate regressions were carried out.
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