Dear all,
I have prepared rainfall datasets for SWAT MODEL using 0.25 degree IMD long term gridded rainfall data,
but as I am using it in the model, it is rounding off the co-ordinates value.
eg:- for the latitude 19.75 and longitude 78.50, the name given to the file is PY1975X7850,
but in the textinout folder, the .pcp file for precipitation is rounding off the coordinates to 19.8 and 78.5.
If it is taking co-ordinate values to 1st decimal place only, then can't we use the 0.25 degree rainfall data in the input?
also it is not displaying the input data in the same format.
Kindly, refer to the attached video to understand the query.
Any valuable suggestions are highly appreciated.
Thanks.
Yeah, you are right. The SWAT model rounds the latitude and longitude of any station to only 1 decimal place. So, I think it is better to use the nearest one digit place values (i.e. .3 for .25 degree) and resample your data accordingly before forcing them into the SWAT model. I also did the same for my case, resampled my data from 0.125 degree to 0.1 degree before forcing it to my model.
Hope this will help.
Dear Abhilash Singh Chauhan,
I think the latitude and longitude values printed on the .pcp file don't really matter. Because when you import weather files into SWAT via ArcSWAT interface, SWAT use stations' coordinates in the station description file you edited to calculate the distance from the measuring stations to each sub-basin, thereby, assigns the station closest to the geometrical center of the sub-basin to the * .sub file (see attachment).
Yours sincerely,
ND Liem
Dear Liem Duy Nguyen
So the model is reading the precipitation input at its exact assigned coordinates position, and model showing the output to 1st decimal place is not relevant (maybe it doesn't have the module to show the output to 2nd decimal place) ?
Dear Nishan Kumar Biswas
It is very tedious to resample/extrapolate the long term data series from grid data of around 68 years (1951-2019), just to round off to the coordinates to 1st decimal place, then writing it back to the input file compatible for SWAT model.
For Indian context, the climate data of India Meteorological Department is most credible source, Else i would have used, NOAA-CPC 0.1 degree rainfall data, and rounding off wouldn't be a problem.
Thanks for your valuable suggestions though.
In SWAT, each sub-basin is attached to a single 'met-station'. For high-res data, it means each sub-basin may have multiple 'node' in them, but get attached to only one. Possibly the best/most logical approach in SWAT in this regard is to build 'virtual stations' at the centre of the sub-basin from all the contributing 'node' based on a delaunay triangulation. It is particularly useful for rainfall, where the spatial gradient is rather high. For temperature, it does not matter much. This way, high-resolution information is not lost through interpolation, instead it's integrated.
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