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<p>Climate is a crucial parameter in determining crop productivity and has a direct impact on regional food security. This study integrates historical and future climate projections with hydrological modeling to assess crop yield variability at the watershed level using the Soil and Water Assessment Tool (SWAT) model. The Indravati River Basin, one of India’s tribal-dominated and less-explored regions, has been chosen as the study area to examine crop yield responses under changing climatic conditions. Coupled Model Intercomparison Project’s (CMIP6) General Circulation Models (GCMs) under two Shared Socioeconomic Pathways (SSP245 and SSP585) were used for future climate data. SWAT model calibration and validation were conducted using the Sequential Uncertainty Fitting (SUFI-2) algorithm in the SWAT-CUP interface, with model performance assessed through statistical indicators including p-factor, r-factor, R², NSE, and PBIAS. Calibration and validation were performed with observed streamflow and crop yield data for the period 1985–2013, and the model showed satisfactory performance. The results indicate that under the SSP245 (low-emission) scenario, climate-resilient crops such as Wheat, Mustard, Pearl Millet, and Lentil maintain relatively stable yields with minimal interannual variability. Conversely, Rice and Corn exhibit greater yield fluctuations. Under the SSP585 (high-emission) scenario, crop yield instability increases across all types. Pearl millet and field pea show some resilience; they are not entirely immune to the effects of extreme climatic conditions. This study underscores the importance of employing semi-distributed process-based hydrological models and ensemble climate projections for long-term agricultural planning.</p>

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Crop yield estimation under future climatic conditions using SWAT model

  • 期刊论文

  • 发表日期：

    2026年2月7日

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  • Anurag Yadav,
  • Raj Mohan Singh

摘要

Climate is a crucial parameter in determining crop productivity and has a direct impact on regional food security. This study integrates historical and future climate projections with hydrological modeling to assess crop yield variability at the watershed level using the Soil and Water Assessment Tool (SWAT) model. The Indravati River Basin, one of India’s tribal-dominated and less-explored regions, has been chosen as the study area to examine crop yield responses under changing climatic conditions. Coupled Model Intercomparison Project’s (CMIP6) General Circulation Models (GCMs) under two Shared Socioeconomic Pathways (SSP245 and SSP585) were used for future climate data. SWAT model calibration and validation were conducted using the Sequential Uncertainty Fitting (SUFI-2) algorithm in the SWAT-CUP interface, with model performance assessed through statistical indicators including p-factor, r-factor, R², NSE, and PBIAS. Calibration and validation were performed with observed streamflow and crop yield data for the period 1985–2013, and the model showed satisfactory performance. The results indicate that under the SSP245 (low-emission) scenario, climate-resilient crops such as Wheat, Mustard, Pearl Millet, and Lentil maintain relatively stable yields with minimal interannual variability. Conversely, Rice and Corn exhibit greater yield fluctuations. Under the SSP585 (high-emission) scenario, crop yield instability increases across all types. Pearl millet and field pea show some resilience; they are not entirely immune to the effects of extreme climatic conditions. This study underscores the importance of employing semi-distributed process-based hydrological models and ensemble climate projections for long-term agricultural planning.