What is a better approach for cross-validation with time-related predictors
Your approach 1) is correct, use n ordered data to predict n+1.
You will have to identify the correct window for prediction and a model not too flexible if you feel the amount of data you have is little.

Do not forget about feature engineering and data preparation. The seasonality you mention can be removed if you identity it correctly.

Validation of the model is done as usual, with a square loss function