Turbidity overestimation Sentinel-2 L1C images with C2X_algorithm

I am using Sentinel L1C images for chlorophyll and turbidity retrieval in shallow and turbid floodplain lakes. In SNAP application the C2X algorithm gives a comparable results about chlorophyll values with in-situ data, but overestimate the turbidity values (TSM - g.m3) comparing EN_872:2006 (TSS - g.m3). Does have some information about?

So, I guess you are actually referring to C2RCC and you use the c2rcc-c2x neural nets for Sentinel-2 data. If so, yes the TSM is overestimated. That’s known and scientists are working on it.

For seperate TSM retrieval this paper might help:

Yes, I am using exactly as you guess! Thank you very much for the reply! It give me a lot of sense! The article is very helpful!