Query on Use of Single LULC Dataset for Long-Term Cotton Yield Calibration in SWAT-CUP

[Sarangan K]

Dear SWAT-CUP User Group,

I hope you are doing well.

I am currently working on SWAT model calibration for cotton yield using SWAT-CUP. I have access to district-level observed cotton yield statistics for a long-term period (approximately 30 years). However, I only have a single Land Use/Land Cover (LULC) dataset (recent year-2023) available for my study area.

In my current setup, when I use this single LULC map for the entire simulation period, the cotton area remains constant across all years. This raises a concern regarding the reliability of long-term yield calibration, as the actual cultivated area and cropping patterns may have varied over time.

I would like to seek your guidance on the following:

1. Is it acceptable to use a single LULC dataset for long-term (multi-decadal) calibration of crop yield in SWAT-CUP?

2. How does this assumption impact the accuracy and reliability of simulated yield results?

3. Are there any recommended approaches or best practices to address this limitation when historical LULC data is unavailable?

4. Would adjusting management practices (e.g., planting, irrigation, fertilizer) or focusing only on yield (rather than area) be a valid workaround in this case?

5.   Is it possible (or supported) to use multiple LULC maps within a single SWAT project, such that each simulation year uses a different LULC dataset (i.e., year-wise dynamic LULC)?  

My objective is to ensure that the calibration approach remains scientifically sound and defensible for research purposes.

I would greatly appreciate any suggestions, references, or experiences you could share regarding this issue.

Thank you for your time and support.

Best regards,
Sarangan K