Integrating hydrological simulation and paddy yield prediction using SWAT in the Bharathapuzha River basin of South India

This study integrates hydrological simulation and crop yield modeling using the SWAT model to assess paddy production in the Palakkad and Alathur blocks of the Bharathapuzha River basin, South India. A majority of Indians rely on paddy as a staple food, particularly in Kerala; hence, the consequences of a warming planet on paddy productivity are causing concern. Palakkad, known as the granary of Kerala, produces about 34% of the total paddy in the state. The Bharathapuzha River basin’s monthly streamflow was simulated using the robust SWAT (Soil and Water Assessment Tool) model. Irrigation of paddy cultivation in the Palakkad district depends on the water from Malampuzha Irrigation Project, which lies in the Bharathapuzha River basin. Two blocks, Palakkad and Alathur, which completely lie within the Bharathapuzha watershed were considered for checking the model’s paddy yield prediction capacity. The watershed’s streamflow and paddy output were jointly simulated using the SWAT model, integrating hydrological processes with crop yield prediction. The monthly observed discharge at the Kuttipuram River gauge point was used to calibrate the model. The streamflow simulation for calibration gave a Nash Sutcliffe Efficiency (NSE) value of 0.67 during tuning period (1998–2012) and 0.64 for testing duration (2013–2017). The RMSE-observations standard deviation ratio (RSR) value for both training and testing spans was 0.58. Paddy yield prediction was evaluated by checking the performance indices NSE and RSR. The NSE value of 0.80 and RSR value of 0.45 for Palakkad block demonstrate the model’s ability to predict paddy yield reasonably. NSE of 0.68 and RSR value of 0.57 for Alathur suggest that SWAT can predict the paddy yield with good agreement to observed values. The findings provide useful insights for water resource planning and sustainable paddy cultivation in Kerala’s rice-growing regions. This dual integration of hydrological and yield modeling provides a methodological framework for climate-resilient agricultural planning in humid tropical river basins.

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Journal
Scientific Reports
Published
2026-03-28
DOI
https://doi.org/10.1038/s41598-026-45201-0
Primary Topic
Climate change impacts on agriculture
Type
article
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article

Integrating hydrological simulation and paddy yield prediction using SWAT in the Bharathapuzha River basin of South India

Berihu Abadi Berhe, Gulja S. Nair, D. Karunanidhi, T. Subramani
Scientific Reports
Climate change impacts on agriculture
article

Integrating hydrological simulation and paddy yield prediction using SWAT in the Bharathapuzha River basin of South India

Berihu Abadi Berhe, Gulja S. Nair, D. Karunanidhi, T. Subramani
article en

Abstract

This study integrates hydrological simulation and crop yield modeling using the SWAT model to assess paddy production in the Palakkad and Alathur blocks of the Bharathapuzha River basin, South India. A majority of Indians rely on paddy as a staple food, particularly in Kerala; hence, the consequences of a warming planet on paddy productivity are causing concern. Palakkad, known as the granary of Kerala, produces about 34% of the total paddy in the state. The Bharathapuzha River basin’s monthly streamflow was simulated using the robust SWAT (Soil and Water Assessment Tool) model. Irrigation of paddy cultivation in the Palakkad district depends on the water from Malampuzha Irrigation Project, which lies in the Bharathapuzha River basin. Two blocks, Palakkad and Alathur, which completely lie within the Bharathapuzha watershed were considered for checking the model’s paddy yield prediction capacity. The watershed’s streamflow and paddy output were jointly simulated using the SWAT model, integrating hydrological processes with crop yield prediction. The monthly observed discharge at the Kuttipuram River gauge point was used to calibrate the model. The streamflow simulation for calibration gave a Nash Sutcliffe Efficiency (NSE) value of 0.67 during tuning period (1998–2012) and 0.64 for testing duration (2013–2017). The RMSE-observations standard deviation ratio (RSR) value for both training and testing spans was 0.58. Paddy yield prediction was evaluated by checking the performance indices NSE and RSR. The NSE value of 0.80 and RSR value of 0.45 for Palakkad block demonstrate the model’s ability to predict paddy yield reasonably. NSE of 0.68 and RSR value of 0.57 for Alathur suggest that SWAT can predict the paddy yield with good agreement to observed values. The findings provide useful insights for water resource planning and sustainable paddy cultivation in Kerala’s rice-growing regions. This dual integration of hydrological and yield modeling provides a methodological framework for climate-resilient agricultural planning in humid tropical river basins.

Scientific Reports
Sri Venkateswara University (IN), Anna University, Chennai (IN), Mekelle University (ET)
Openalex Percentile: Top 2%
Climate change impacts on agriculture
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