Assessing the Effects of Climate Change and Land‐Use Changes on Extreme Discharge in the Western Watershed of Lake Urmia, Iran

ABSTRACT This study investigates the impacts of climate change and land‐use changes on peak discharge and runoff behavior in the western watersheds of Lake Urmia, Iran. Employing machine learning algorithms (e.g., SVM), stochastic models (e.g., CA‐MARKOV), ERA5 reanalysis climate data, and the large‐scale hydrological VIC model, we assessed these effects across multiple sub‐basins. Our analysis revealed that a 2°C rise in average minimum winter temperature over the past 50 years has reduced frost days by nearly 80 days, diminished mountain snow volume, and shifted precipitation from snow to a mix of snow, rain, and snowmelt. Consequently, peak discharge timing has advanced from May to March and April, amplifying flood intensity and frequency, with some sub‐basins showing up to 30% higher peak flows. Furthermore, land‐use change assessments indicated that expanding orchards and irrigated and rain‐fed agricultural lands will significantly elevate future peak discharge, with differences exceeding 10 m 3 /s in sub‐basins like Nazlochay and Barandozchay, driven by reduced infiltration and increased runoff rates. Modeling with these tools confirmed that climate and land‐use changes synergistically alter flood dynamics, a pattern consistent with regional studies. These findings underscore the urgent need to integrate these factors into flood management strategies for this flood‐prone region, offering a robust framework for sub‐basin‐scale hydrological planning.