A new easy-to-use tool for grain size distribution analysis

Grain size distribution (GSD) data have been widely used in Earth sciences, especially Quaternary Geology, due to its convenience and reliability. However, the usages of GSD are still oversimplified. The geological information contained in GSD is very abundant, but only some simplified proxies (e.g. mean grain size) are widely used. The most important reason is that GSD data are hard to interpret and visualize directly.

To overcome this, some researchers have developed the methods to unmix the mixed multi-modal GSD to some components to make the interpretation and visualization easier. These methods can be divided into two routes. One is end-member analysis (EMA) which takes a batch of samples for the calculation of the end-members. Another is called single-specimen unmixing (SSU) (Sun et al., 2002) which treats each sample as an individual. The key difference between the two routes is that whether the end-members of a batch of samples are consistent. EMA believes that the end-members between different samples are consistent, the variations of GSD are only caused by the changing of fractions of the end-members. On the contrary, SSU has no assumption on the end-members, i.e. it admits that the end-members may vary between different samples. Some mature tools (Paterson and Heslop, 2015; Dietze and Dietze, 2019) taking the EMA route have appeared, but there is no available public and easy-to-use tool for SSU.

Here we introduce a free and open-source GUI tool which is called QGrain, it can help researchers to analyze the GSD data easily and bring new insights for the interpretation of GSD. QGrain is based on SSU but applied some algorithms (e.g. data preprocessing and global optimization) to improve its precision and robustness. It supports Lognormal or Weibull as the base distribution and it is easy to add more base distributions. QGrain can handle different types of sediments (e.g. aeolian, fluvial and lacustrine deposits). QGrain can export all detailed data and generate the charts automatically.