Researchers used a special algorithm to figure out the best settings for a model that predicts soil temperature and moisture. They found that certain soil characteristics have a big impact on how well the model works. By tweaking these characteristics, they were able to improve the accuracy of the model in predicting both soil moisture and temperature. Interestingly, using different types of soil moisture measurements led to different results in the model's predictions. Overall, focusing on specific soil characteristics when calibrating the model led to better simulations of soil conditions.