This study describes the sensitivity of irrigation scheduling model (Mehran) carried out by changing input weather parameters (Temperatures, Wind velocity, Rainfall, and Sunshine hours) to see model sensitivity in computation / estimations (output) for Transpiration (T), Evaporation (E), and allocation of irrigation (I) water. Sensitivity analysis depends on the site and environmental conditions, and is therefore an essential step in model validation and application. Mehran Model is weather based crop growth simulation model, which uses daily input data of max and min temperatures (temp), dew point temp (humidity), wind speed, daily sunshine hours (radiation) and computes Tc, Es , and allocates irrigation accordingly. The input and output base values are taken as an average of three years actual field data used during the Mehran Model testing and calibration on wheat and cotton crops. The model sensitivity of specific input parameter was obtained by varying its value and keeping other input parameters at their base values. The input base values varied by +10 and +25%. The model was run for each modified input parameter, and output was compared statistically with base outputs. The results reveal that the model is most sensitive with variations in temperature. The 10 and 25% increase in temperature resulted increase in Cotton crop’s Tc by 12.18 and 28.54%, corresponding Es by 22.32 and 37.88% and irrigation water allocation by 18.41 and 47.83% respectively increased from average base values.