python programming language

In the current situation of the country, which is facing numerous droughts, simulation of the performance of different crops in water shortage conditions has attracted the attention of modelers. Among these models, WOFOST has been used in predicting crop yield in numerous researches.In this research, the development of the WOFOST model under the Python language along with how to simulate the performance of major crops in the Tajan plain watershed including rice, wheat, oilseeds, grain corn and tomato during the years 2014-18 was examined. Based on this, at first, the annual crop yield was received from the Agricultural Jihad Organization and the simulation results were compared with these data. The crop yield simulation results of the PCSE Python version showed very little difference with the reported values, so that the RMSE and nRMSE results were reported in the range of less than 10%, which puts it in the good to excellent range. which proves the power of PCSE model in simulation. On the other hand, the results of the T test at the 95% probability level showed that in most of the products, no significant difference was observed between the simulation and observation values, which shows the advantages of theThe outputs of both WOFOST and PCSE models are completely consistent. Comparing the results also shows that there is a small difference between the simulated and observed values. Therefore, it can be concluded that the PCSE model has the ability to simulate the performance of products.