The model is based on seasonal input data and returns seasonal outputs. The number of seasons per year can be chosen between a minimum of one and a maximum of four. One can distinguish for example dry, wet, cold, hot, irrigation or fallow seasons. Reasons of not using smaller input/output periods are:
#short-term (e.g., daily) inputs would require much information, which, in large areas, may not be readily available;
#short-term outputs would lead to immense output files, which would be difficult to manage and interpret;
#this model is especially developed to predict long-term trends, and predictions for the future are more reliably made on a seasonal (long-term) than on a daily (short-term) basis, due to the high variability of short-term data;
#though the precision of the predictions for the future may be limited, a lot is gained when the trend is sufficiently clear. For example, it need not be a major constraint to the design of appropriate soil salinity control measures when a certain salinity level, predicted by SahysMod to occur after 20 years, will in reality occur after 15 or 25 years.