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<p>Global food security and water resources are vulnerable to climatic changes and require evapotranspiration estimation for future crop water requirements. Still, assessment can be challenging to apply to realistic, complex landscapes. Further, agro-meteorological data scarcity in rural areas, drew in use of temperature-based evapotranspiration (TET) models. Therefore, this study developed a region-specific seasonal irrigation demand assessment tool in climate change by calibrating four TET models based on past investigations, with Pan evaporation models for finding the best model. For this purpose, observed climate station and satellite based climate data were utilized. Multilinear Regression (MLR) bias-corrected model was developed for future temperature projections and predictors from 3 General Circulation Model (GCM ) models were used. The model was calibrated using historical data and applied to forecasting water demand for RCP Scenarios. The greatest monthly mean temperature increase (1.4&#xa0;°C) and decrease (0.01&#xa0;°C) changes were for February and September during the 2071–2100 and 2041–2070 periods respectively. The study results revealed a rise in irrigation water demand upto 2.5% and 2.4% for the subsequent seasons till the end of century. The developed integrated model showed that single cropping of water-intensive crop consumes more water than multiple cropping. This type of model provided scientific evidence for policy-making targeted at agronomists and water resource managers. Further robust optimization modeling of crop diversification to climate change while considering the future regional food crop demand and available water resources are focus of future research.</p>

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Assessment of climate change impact on irrigation water demand for food security in rice-fallow cropland areas using an integrated modeling technique

  • 期刊论文

  • 发表日期：

    2025年1月18日

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  • Mridusmita Debnath,
  • Arup Kumar Sarma

摘要

Global food security and water resources are vulnerable to climatic changes and require evapotranspiration estimation for future crop water requirements. Still, assessment can be challenging to apply to realistic, complex landscapes. Further, agro-meteorological data scarcity in rural areas, drew in use of temperature-based evapotranspiration (TET) models. Therefore, this study developed a region-specific seasonal irrigation demand assessment tool in climate change by calibrating four TET models based on past investigations, with Pan evaporation models for finding the best model. For this purpose, observed climate station and satellite based climate data were utilized. Multilinear Regression (MLR) bias-corrected model was developed for future temperature projections and predictors from 3 General Circulation Model (GCM ) models were used. The model was calibrated using historical data and applied to forecasting water demand for RCP Scenarios. The greatest monthly mean temperature increase (1.4 °C) and decrease (0.01 °C) changes were for February and September during the 2071–2100 and 2041–2070 periods respectively. The study results revealed a rise in irrigation water demand upto 2.5% and 2.4% for the subsequent seasons till the end of century. The developed integrated model showed that single cropping of water-intensive crop consumes more water than multiple cropping. This type of model provided scientific evidence for policy-making targeted at agronomists and water resource managers. Further robust optimization modeling of crop diversification to climate change while considering the future regional food crop demand and available water resources are focus of future research.