Investigating the effectiveness of the maximum entropy model in measuring the potential of areas prone to hydrological drought of underground water resources (case study: Jiroft Plain)

Drought is one of the natural disasters that can occur in any climate. In recent decades, Iran has been continuously affected by severe and widespread droughts and has imposed harmful effects on various economic sectors, including the country's water resources. One of the needs for the growth and development of every country is water. On the other hand, due to the lack of permanent or even seasonal surface water flows in many plains of the country, one of the most important sources of water harvesting is the use of underground water reserves. Therefore, it is very important to investigate the status of these resources and determine the influencing factors on them. In this research, it has been tried to identify the areas that are exposed to severe groundwater drought and the impact of the factors affecting groundwater drought using the maximum entropy model and using MaxEnt software in the basin. The Jiroft plain watershed should be identified. To implement the maximum entropy model, 70% of the data were used for model training and 30% for model testing. The results of this study, based on the jackknife test, showed that the most important factors affecting groundwater drought are altitude, distance from the river, and soil moisture, and the model shows the most sensitivity to these parameters. gave Also, the results showed that the model has an acceptable accuracy in identifying groundwater drought, so that the accuracy of the model was estimated at 0.76.