Geology topics

Arash Modaresi Rad

Publications and source records attributed to Arash Modaresi Rad.

3 recordsLinked to original sources

USGS2023

Human and infrastructure exposure to large wildfires in the United States

An increasing number of wildfire disasters have occurred in recent years in the United States. Here we demonstrate that cumulative primary human exposure—the population residing within the perimeters of large wildfires—was 594,850 people from 2000 to 2019 across the contiguous United States (CONUS), 82% of which occurred in the western United States. Primary population exposure increased by 125% in the CONUS in the past two decades; it was noted that there were large statistical uncertainties in the trend analysis due to the short study timeline. Population dynamics from 2000 to 2019 alone accounted for 24% of the observed increase rate in human exposure, and an increased wildfire extent drove the majority of the observed trends. In addition, we document the widespread exposure of roads (412,155 km) and transmission powerlines (14,835 km) to large wildfires in the CONUS, with a relative increase of 58% and 70% in the past two decades, respectively. Our results highlight that deliberate mitigation and adaptation efforts to help societies cope with wildfires are ever more needed.

Nature Sustainability↗

USGS2022

Anthropogenic stressors compound climate impacts on inland lake dynamics: The case of Hamun Lakes

Inland lakes 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 to 2019 were fused, which documented that the Hamun Lakes lost 89% of their surface area between 1999 and 2001 (3809 km 2 versus 410 km 2 ), 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 to 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.

Science of the Total Envionrment↗

USGS2021

Augmented normalized difference water index for improved monitoring of surface water

We present a comprehensive critical review of well-established satellite remote sensing water indices and offer a novel, robust Augmented Normalized Difference Water Index (ANDWI). ANDWI employs an expanded set of spectral bands, RGB, NIR, and SWIR 1-2 , to maximize the contrast between water and non-water pixels. Further, we implement a dynamic thresholding method, the Otsu algorithm, to enhance ANDWI's performance. Applied to a variety of environmental conditions, ANDWI with Otsu-thresholding offered the highest overall accuracy (accuracy = 0.98, F1 = 0.98, and Kappa = 0.96) compared to other indices (NDWI, MNDWI, AWEI, WI). We also propose a novel cloud filtering algorithm that substantially increases the number of useable images compared to the conventional cloud-free composites (124% increased observations in the studied area) and resolves inappropriate masking of water bodies and hot sands as clouds by conventional methods. Finally, we develop a Google Earth Engine App to readily delineate 16-day surface water bodies across the globe.

Environmental Modeling and Software↗