> For the complete documentation index, see [llms.txt](https://docs.nuvolos.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.nuvolos.com/how-to-guides/application-specific-guides/dndcv.can.md). # DNDCv.CAN **(Non-commercial academic use only)** DNDC (i.e., DeNitrification-DeComposition) is a computer simulation model of carbon and nitrogen biogeochemistry in agro-ecosystems. The model can be used for predicting crop growth, soil temperature and moisture regimes, soil carbon dynamics, nitrogen leaching, and emissions of trace gases including nitrous oxide (N2O), nitric oxide (NO), dinitrogen (N2), ammonia (NH3), methane (CH4) and carbon dioxide (CO2). ### Application setup This Nuvolos application starts a VSCode environment and has WineHQ 9.1 installed in it. Python 3.11 is also installed in a conda environment. VSCode has useful extensions installed, such as Python, Jupyter, and PyLint. ### User's Guide For more information on the model and its applications, please refer to the [DNDC 9.5 User's Guide](http://www.dndc.sr.unh.edu/model/GuideDNDC95.pdf) document. ### How to start DNDCv.CAN: Open a new terminal tab in the VS Code environment and run: ```bash wine start /unix /DNDC/DNDC95.exe ``` File location mapping: * F: maps to `/files` * H: maps to `~` (your personal home area in Nuvolos) --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.nuvolos.com/how-to-guides/application-specific-guides/dndcv.can.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.