Presented by Arash Modaresi Rad
Computing PhD, Data Science emphasis
City Center Plaza Conference Room 352
Inland waters face unprecedented pressures from climatic and anthropogenic stresses, causing their recession and desiccation globally. Climate change is increasingly blamed for such environmental degradation, but in many regions, direct anthropogenic pressures compound, and sometimes supersede, climatic factors. This study examined a human-environmental system – the terminal Hamun Lakes on the Iran-Afghanistan border – that embodies amplified challenges of inland waters. Satellite and climatic data from 1984-2019 were fused, which documented that the Hamun Lakes lost 89% of their surface area between 1999 and 2001 (3,809 km2 versus 410 km2), coincident with a basin-wide, multi-year meteorological drought. The lakes continued to shrink afterwards and desiccated in 2012, despite the above-average precipitation in the upstream basin. Rapid growth in irrigated agricultural lands occurred in upstream Afghanistan in the recent decade, consuming water that otherwise would have fed the Hamun Lakes. Compounding upstream anthropogenic stressors, Iran began storing flood water that would have otherwise drained to the lakes, for urban and agricultural consumption in 2009. Results from a deep Learning model of Hamun Lakes’ dynamics indicate that the average lakes’ surface area from 2010-2019 would have been 2.5 times larger without increasing anthropogenic stresses across the basin. The Hamun Lakes’ desiccation had major socio-environmental consequences, including loss of livelihood, out-migration, dust-storms, and loss of important species in the region.