A possible useful (free and relevant to your context) resource for you is at https://pubs.usgs.gov/twri/twri4a3/pdf/chapter12.pdf

....or for the complete (free) book, see https://pubs.usgs.gov/twri/twri4a3/

The above links are for:

Helsel, D.R. and R. M. Hirsch, 2002. Statistical Methods in Water Resources Techniques of Water Resources Investigations, Book 4, chapter A3. U.S. Geological Survey. 522 pages.

Hello Lodhi

check this page I think it can be helpful

https://help.xlstat.com/customer/en/portal/articles/2062303

Regards

Mann-Kendall Test tests whether 2 groups of random variables are independent. As long as you have X1, ...Xn~F1 i.i.d. and Y1, ...Yn~F2 i.i.d., with the same sample size n in both groups, you can use Mann-Kendall Test. I do not know what are the 2 groups in your case. I think this assumption can help you answer Q2 and Q3, and maybe Q4 since the deviation from this assumption can be one of the reasons.

1- Can i run Mann-Kendall test on XL-Stat, an excel analysis add in that has a standard Mann-Kendall test or should go for any other software and did it really matter?

If you want to see the Tau-statistics and all the test statistics-use R. Or XLSTAT will suffice. I suggest using MAKESENS - It is way simpler.

2- Do Mann-Kendall test compensate for normality, multicollinearity and other time series conditions?

Nope. Mann-Kendall is a non parametric test and doesn't address the issues with normal distribution assumptions.

3- I have already distributed my data in annual and seasonal means. Can i use the standard Mann-Kendall test on my seasonal data and not use the seasonal option within Mann-Kendall Test?

Yes...Proceed with simple Mann-Kendall test.

4- What are the obvious reasons that often distort the Mann-Kendall test results?

First and foremost- Serial Correlation in data and then Homogeneity of the data. Some other factors involve manual errors.

You may use the package - 'modifiedmk' in R to perform the tests.