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<p>Reliable streamflow assessment is essential for sustainable water resource management, particularly in large tropical basins affected by data scarcity, climatic variability, and land-use change. This study evaluates long-term streamflow dynamics in the Lower Godavari River Basin using the Soil and Water Assessment Tool (SWAT) within the ArcSWAT framework. Spatially distributed meteorological, land-use, topographic, and soil datasets were integrated to simulate hydrological processes over a 36-year period. Model calibration (1984–2014) and validation (2015–2020) were performed using the SUFI-2 algorithm in SWAT-CUP, with performance assessed through NSE, R², and RSR statistics. Sensitivity analysis identified the runoff curve number (CN2) and groundwater delay (GW_DELAY) as the most influential parameters controlling streamflow response. The model achieved satisfactory performance, yielding NSE values of 0.86 and 0.84 and R² values of 0.89 and 0.85 for calibration and validation, respectively. Results indicate that SWAT effectively captures the temporal variability and hydrological behaviour of this monsoon-driven, data-scarce basin. The study provides a robust multi-decadal assessment of catchment response and hydrological variability, offering valuable insights for basin-scale water management, climate-resilient planning, and flood risk mitigation in similar tropical and semi-humid river systems.</p>

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Streamflow assessment of the lower Godavari river basin using the SWAT model

  • 期刊论文

  • 发表日期：

    2026年1月6日

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  • Manoj Kumar Diwakar,
  • Katari Vijay

摘要

Reliable streamflow assessment is essential for sustainable water resource management, particularly in large tropical basins affected by data scarcity, climatic variability, and land-use change. This study evaluates long-term streamflow dynamics in the Lower Godavari River Basin using the Soil and Water Assessment Tool (SWAT) within the ArcSWAT framework. Spatially distributed meteorological, land-use, topographic, and soil datasets were integrated to simulate hydrological processes over a 36-year period. Model calibration (1984–2014) and validation (2015–2020) were performed using the SUFI-2 algorithm in SWAT-CUP, with performance assessed through NSE, R², and RSR statistics. Sensitivity analysis identified the runoff curve number (CN2) and groundwater delay (GW_DELAY) as the most influential parameters controlling streamflow response. The model achieved satisfactory performance, yielding NSE values of 0.86 and 0.84 and R² values of 0.89 and 0.85 for calibration and validation, respectively. Results indicate that SWAT effectively captures the temporal variability and hydrological behaviour of this monsoon-driven, data-scarce basin. The study provides a robust multi-decadal assessment of catchment response and hydrological variability, offering valuable insights for basin-scale water management, climate-resilient planning, and flood risk mitigation in similar tropical and semi-humid river systems.