Add CAMELS-USA

The caravan datset has already been added PR https://github.com/eWaterCycle/ewatercycle/pull/407 as discussed in #398.
This was relatively simple as we had the NetCDF files availible from the source, we only had to combined them.
The downside is it used era5-Land data, the evaporation can be quite far from realistic.
See [this article on the issue](https://egusphere.copernicus.org/preprints/2024/egusphere-2024-864/).

As part of my thesis I used the original [Camels-USA](https://ncar.github.io/hydrology/datasets/CAMELS_timeseries) dataset, which has better forcing. But the forcing is in text files, split per type: forcing/streamflow/characteristics.
I ran models for all 671 catchments, in the process already making the conversion to netcdf. I only used a 5 year period, there is data for the period 1980-2010 (some cases 14).
I used custom forcing in the [HBV mode](https://github.com/Daafip/ewatercycle-hbv/blob/89537bfcee01a1ba7f5f74d68cd9e3974933bcea/src/ewatercycle_HBV/forcing.py#L138) to achieve this.
It would also be nice to include the catchment characteristics. These are currently spread across different files and comparing your results to them requires a bit of pandas effort as shown in [this messy notebook](https://github.com/Daafip/Msc-Thesis-Notebooks/blob/cd26bd81dfc8af78068905e9e6c7f8b4d54de033/30-43_application_and_analysis/nbs_43_analyse_diff_best_callibrate/43.4%20Compare%20to%20chatchment%20characteristic.ipynb), or if you want to view it online use [this link](https://nbviewer.org/github/Daafip/Msc-Thesis-Notebooks/blob/main/30-43_application_and_analysis/nbs_43_analyse_diff_best_callibrate/43.4%20Compare%20to%20chatchment%20characteristic.ipynb). Definetely doable, but effort.
Loading observations is shown [here](https://github.com/Daafip/Msc-Thesis-Notebooks/blob/cd26bd81dfc8af78068905e9e6c7f8b4d54de033/30-43_application_and_analysis/nbs_39_formalise_algorithm/39_run_formalised.py#L136)

**Tl;dr: original camels forocing is better than the caravan. Code exists but still some effort to polish.**

One main discussion points. Do we:
- update the existing caravan data set? This might be confusing as the forcing is different.
- create a new `_forcing.camels`? Then we have a bit of repeated code but the dataset structure is likley different so kinda needed.

Todo:
- [x] Use exisiting code to make NetCDF files for forcing of the whole data set. Using all three sources: Daymet, NLDAS and Maurer

>
>Summary from my thesis
> - [Daymet](https://daymet.ornl.gov/) has the finest resolution at 1x1km, whilst the other two sources have resolutions of 1/8th a degree.
> - Daymet aims to reproduce the weather conditions in the whole of the USA.
> - [NLDAS](https://ldas.gsfc.nasa.gov/nldas) is more focussed on the soil moisture stores and energy.
> - Both Daymet and NLDAS are products by NASA.
> - The dataset by [Maurer et al](https://www.engr.scu.edu/~emaurer/gridded_obs/index_gridded_obs.html) is a baseline for climate predictions

- [x] Also load in characteristics per catchmetns
- [x] Combine the forcing and characteristics
- [x] merge all 671 catchments
- [x] Optionally load streamflow
- could use the USGS link already availible in ewatercycle
- then again the data is availible and might as well if we go through the effort hand a complete product
- Check errors and flags are handled correctly. See: https://github.com/Daafip/ewatercycle-hbv/issues/59
- [x] Add to OpenDap