Investigating the relationship between groundwater level variations and geologic drought factor using MODFLOW and wavelet theory (case study: Southern Iran)

This study employs a combination of hydrological relationships, numerical models, vulnerability indices, and segmentation techniques to extract the precipitation-drought relationships within the Bushkan Aquifer, a selected area in southern Iran. Determination of the volume and nature of groundwater flow distribution, which serves as the focal point of hydrological drought, is accomplished through regional analysis and extraction of historical return period droughts, along with examining hydrographs derived from the MODFLOW model. The outcomes of hydrological investigations prepared based on physiographic elements serve as inputs for groundwater flow distribution models in the specified region. Sentinel-2 satellite imagery processing is utilized to derive the normalized difference water index (NDWI) as a standardized indicator of water structure changes and land cover, establishing a framework for identifying drought-prone areas. Machine learning classification and Earth Object methods generate a refined land structure layer. This land structure layer, called "Geology," is the criterion for classifying regions regarding groundwater drought priority. The accuracy assessment of this method involves the creation of a correlation table between NDWI changes and Geology layer classes. While no correlation is observed in the Geology layer classes regarding elevation changes, an analysis of the trend and frequency (wavelet) of temporal water variation series reveals a clear relationship with groundwater level decline. The results suggest that geological diversity should be a fundamental criterion in conjunction with regional agricultural development to identify drought-prone regions or groundwater drought factors. Based on the descriptions provided in this research, spatial ranges are classified to obtain the maximum NDWI changes using Sentinel satellite imagery. These spatial ranges facilitate decision-making for implementing flow diversion structures and even cultivation restrictions to mitigate agricultural-induced climate resilience against drought impacts.