Assessing rain-fed cropland suitability under SSP scenarios: a case study of Qazvin Province, Iran

Articles in Press

Document Type : Original Article

Authors
Mansoureh Kouhi
Ebrahim Asadi Oskouei
Research Institute of Meteorology and Atmospheric Science, Climatological Research Institute (CRI), Mashhad, Islamic Republic of Iran.
Abstract
Rain-fed agricultural productivity is increasingly threatened by rising temperatures and shifting precipitation patterns. This study evaluates the current and future suitability of rain-fed cropland in Qazvin Province, Iran—a region where such an assessment has not been previously conducted. Although Qazvin Plain comprises only 1% of Iran's land area, it contributes approximately 4% of national agricultural production. The study employs the Maximum Entropy (MaxEnt) model, integrating topographic and climatic factors to identify determinants of rain-fed cropland suitability. Suitability was assessed under optimistic (SSP1-2.6) and pessimistic (SSP5-8.5) scenarios using historical data (1985–2014) and future projections (2021–2040) from three CMIP6 models (MPI-ESM1-2, ACCESS-ESM1-5, IPSL-CM6A-LR) and their ensemble. The model demonstrated high predictive accuracy (AUC = 0.67 training, 0.715 testing). Key factors included mean annual temperature, spring and autumn precipitation, slope, soil class and TRASP. Currently, 26.7% of the provinces are unsuitable, while 31.7% is highly suitable. Under future scenarios, unsuitable areas are projected to expand. The ensemble projects suitable area (Moderate, High, Very High) decreasing from 56.1% (baseline) to 50.7% under SSP1-2.6 and 52.0% under SSP5-8.5. However, substantial uncertainty exists across models under SSP1-2.6 (suitable area range: 44.5–52.9%; SD = ±3.1%), while model agreement is tighter under SSP5-8.5 (SD = ±1.0%). The greatest reduction is projected by MPI under SSP1-2.6 (−20.8%). These findings provide essential insights for adaptive strategies including crop redistribution, supplemental irrigation, and rainwater harvesting.
Keywords
CMIP6
MaxEnt
Rain-fed
Spatial Distribution
Subjects
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Available Online from 13 June 2026