Abstract
Groundwater drought, as a form of hydrological drought, embodies the distinctive characteristics of the aquifer and human-induced disruptions within the hydrological system. The intricate nature of groundwater flow systems, coupled with challenges in acquiring field observations related to aquifers, poses significant challenges in quantitatively characterizing groundwater drought. The present paper presents a novel contribution to the time series forecasting of groundwater drought through state-of-the-art integrated GWO-SVM models.
About Hossein Hashemi
Hossein Hashemi received his doctoral degree from the Department of Water Resources Engineering at Lund University in 2014. After completing Ph.D., he was admitted as postdoctoral research fellow at the Center for Groundwater Evaluation and Management in the Geophysics Department at Stanford University (2015-2017). In the postdoctoral research, he mainly focused on remote sensing techniques in water resources, specifically, application of InSAR technique in the field of groundwater evaluation and management in the arid and semi-arid areas.
Hossein’s research interests lie in the field of:
- Groundwater hydrology and management
- Water harvesting systems
- Remote sensing of precipitation and land surface deformation
- Climate change
Hossein teaches courses in hydrology and fluid mechanics. He is also responsible for a master course entitled Environment and Sustainable Development in the Middle East.