Work in progress

I am thinking if LLM can be useful in Hydrology. More than thinking actually, it requires some readings and some understanding of the mechanisms through which the statistics behind LLM works. I see some clear applications and their are quite obvious at the moment. LLM are useful for who program their own hydrological model because programming, at least of small chunks of codes and scripting (which is part of the daily activity of who treats data and do modelling) is one known area of success of LLM. Another area of application can be helping the use of models. Models, even those that are component based, can grew quite complicate and learning their use can be a slow process that LLM, maybe a dedicate LLM, can made faster. Image you want to be helped in use and implement GEOframe. You can attend to the summer school, but it would be very nice if you could have a BOT that helps you in the daily task of trying, especially the first time, without bothering a colleague, for instance  a Ph.D. student who is already super-busy. This actually would require learning how to build a custom LLM that ingest all the information about your model (GEOframe) and other information and then return back the information required. You probably do not need all the knowledge under the sky but just the right one plus some other general knowledge that helps the BOT (GEOBOT to manage the requests by humans). 

Different question is if LLM can be used to discover regularity in the data sets, which are not exactly, language data to be treated, help in processes like calibration of model parameters, transform soft information into probable model setups,  transforn, on the basis of information describes with natural language, what has been done in terms of setup in a catchment into another one. This, at present I do not know how it is possible, but, I think it could be interesting to investigate. 

To be continued …..

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