In the heart of Iran’s Guilan province, a groundbreaking study led by Maryam Sodori from the Department of Water Engineering at the University of Guilan is revolutionizing our understanding of complex hydrological systems. The research, published in ‘آب و توسعه پایدار’ (Water and Sustainable Development), focuses on the Foumanat Plain aquifer, a shallow alluvial aquifer with intricate interactions between surface water and groundwater.
The study combines two powerful models, MIKE SHE and MIKE 11, to simulate these interactions with unprecedented accuracy. “By integrating these models, we can better understand and predict the behavior of groundwater and surface water systems,” Sodori explains. “This is crucial for managing water resources, especially in regions with multiple rivers and complex hydrological processes.”
The Foumanat Plain aquifer, like many others, faces significant challenges due to its natural heterogeneity. However, the combined model demonstrated remarkable performance, with an absolute error of less than one for groundwater level estimation and less than 0.5 for flow rate estimation. This level of precision is a game-changer for water management, particularly in the energy sector, where accurate hydrological data is essential for planning and operations.
One of the most striking findings of the study is the disparity in evaporation and transpiration (ETa) rates between the wet and dry seasons. During the wet season (October to March), ETa amounts to 0.4 times the total rainfall. In contrast, during the dry season (April to September), ETa equates to 7.3 times the total rainfall, highlighting the significant water loss during this period. “This finding underscores the importance of efficient water management strategies, especially during dry seasons,” Sodori notes. “It’s a call to action for policymakers and industry stakeholders to prioritize water conservation and sustainable practices.”
The implications of this research extend far beyond the Foumanat Plain. As water scarcity becomes an increasingly pressing global issue, the ability to accurately model and predict hydrological processes is invaluable. For the energy sector, which relies heavily on water for cooling and other processes, this research could lead to more efficient water use and better risk management.
The study’s success in calibrating the models using parameters such as saturated hydraulic conductivity, leakage coefficients, and Manning’s roughness coefficient sets a new standard for hydrological modeling. This approach could be replicated in other regions, providing a robust framework for water resource management.
As we look to the future, the integration of MIKE SHE and MIKE 11 models offers a promising path forward. By enhancing our understanding of groundwater-surface water interactions, this research paves the way for more sustainable water management practices. It’s a testament to the power of scientific innovation in addressing real-world challenges, and a call to action for continued investment in hydrological research.
