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Raoof Mostafazadeh on Muck Rack

Raoof Mostafazadeh

As seen in: Nature, MDPI, Taylor & Francis Online
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Articles

Reference evapotranspiration trends and climate sensitivity in a semi-arid basin

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By Raoof Mostafazadeh, Hedieh Ahmadpari, Khaustov Vitaly
| Taylor & Francis Online
?Mathematical formulae have been encoded as MathML and are displayed in this HTML version using MathJax in order to improve their display. Uncheck the box to turn MathJax off. This feature requires Javascript. Click on a formula to zoom. ABSTRACT This study examines the long-term trends and climatic sensitivity of reference evapotranspiration (ET0) in a representative semi-arid basin using 25 years of meteorological data.
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Predicting the flood susceptibility under land use and climate change scenarios using deep learning algorithms

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By Raoof Mostafazadeh, Ali Nasiri Khiavi, Shahnaz Mirzaei
| Nature Verified
Abstract Flood risk in semi-arid, snow-fed basins is increasingly influenced by both land-use and climate change, yet their combined future effects remain poorly quantified. This study predicts future flood generation potential (FGP) under combined land-use and climate scenarios in the Gharesou Watershed (Iran) using deep learning.
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Spatial hotspot analysis of soil erosion rate and classification of homogeneous zones using GIS in a mountainous contrasting land-use watershed - Scientific Reports

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By Raoof Mostafazadeh, Nazila Alaei, Fatemeh Saeedi Nazarlu, Hassan Khavarian Nehzak
| Nature Verified
Abstract Soil erosion poses a significant challenge to environmental sustainability, especially in regions with varying land-use patterns and topography. Soil erosion is a major environmental threat affecting soil quality, reservoir sedimentation, agricultural land, and watershed hydrology. This study aims to identify and classify homogeneous sub-watersheds in a mountainous watershed in Iran using GIS.
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