I´m sorry, I´don´t, to answer your question

Assuming that by "Sen's test" you mean the calculation of Sen's slope (or the variants by Kendall–Theil, Sen, Siegel), and any associated tests --- There's no reason why you can't use this with data with gaps.

Sen's slope can be used with any bivariate data. It doesn't assume equal spacing on the x-axis.

There are implementations of Sen’s slope for time series data that also take into account the seasonality of the data. You may look into this. But software implementations may not allow for gaps in the data.

There's also a seasonal Mann–Kendall trend test, with the same caveat that software implementations may not allow for gaps in the data.

John Price

Given that the downgradient monitoring well was dry for six consecutive quarters, the groundwater sample collected in the second quarter of calendar year 2025 should be considered the beginning of a new data set. This prolonged data gap may indicate significant hydrogeological changes, such as fluctuations in groundwater levels, flow patterns, or contaminant transport conditions. In line with best practices in groundwater monitoring and trend analysis (e.g., the application of Sen’s test), such a discontinuity undermines the assumption of data continuity and may compromise the reliability of trend interpretation. Therefore, it is recommended that the new sample results be analyzed as a separate time series, with the interruption clearly documented along with the conditions under which sampling resumed. A parallel comparative analysis with historical data may be conducted to assess consistency, but the datasets should not be formally combined unless additional hydrogeological evaluation confirms stable conditions before, during, and after the dry period.

I strongly recommend Dragan Ugrinov's considered response above.