Jasrotia et al. (2026) Predictive modeling of streamflow in the Chenab basin under anthropogenic and natural forcings

Identification

• Journal: Arabian Journal of Geosciences
• Year: 2026
• Date: 2026-02-12
• Authors: Avtar Singh Jasrotia, Deepika Baru, Retinder Kour
• DOI: 10.1007/s12517-025-12387-y

Research Groups

• Department of Geology, University of Jammu, Jammu, India
• Department of Remote Sensing and GIS, University of Jammu, Jammu, India

Short Summary

This study projects future streamflow in the Chenab basin under climate change (RCP 4.5 and 8.5) and land use changes using VIC and SWAT models, revealing an overall declining trend in streamflow, with sharper reductions projected under RCP 4.5.

Objective

• To project future streamflow in the Chenab basin under anthropogenic (land use/land cover changes) and natural (climate change under RCPs 4.5 and 8.5) forcings using the Variable Infiltration Capacity (VIC) and Soil and Water Assessment Tool (SWAT) hydrological models, supported by Regional Climate Model version 4 (RegCM4) climate projections and Markov-Cellular Automata (Markov-CA) land use simulations.

Study Configuration

• Spatial Scale: Chenab Basin, Western Himalayas, covering an area of approximately 45,000 km².
• Temporal Scale:
  • Baseline period: 1991–2016.
  • Future projection periods: 2020–2040, 2040–2060, 2060–2080, and 2080–2100.
  • Snow Cover Area (SCA) analysis: 2001–2016.
  • Land Use/Land Cover (LU-LC) maps: 1990, 2010, 2020 (observed); 2050, 2080, 2100 (projected).

Methodology and Data

• Models used:
  • Hydrological models: Variable Infiltration Capacity (VIC) model, Soil and Water Assessment Tool (SWAT) model.
  • Climate model: Regional Climate Model version 4 (RegCM4).
  • Land Use/Land Cover (LU-LC) projection model: Hybrid Markov-Cellular Automata (Markov-CA) model.
  • Flow routing model: Lohmann et al. (1998) flow routing model (coupled with VIC).
• Data sources:
  • Streamflow data (1991–2016): Flood Control and Irrigation Department.
  • Meteorological data (temperature, precipitation, 1991–2016): Indian Meteorological Department (IMD) Pune.
  • Future climate projections (minimum/maximum air temperature, precipitation under RCPs 4.5 and 8.5): CORDEX site (RegCM4 variables).
  • LU-LC maps (1990, 2010, 2020): Landsat 4/5 Thematic Mapper and Landsat 8 Operational Land Imager from USGS Earth Explorer.
  • Snow Cover Area (SCA) (2001–2016): MODIS/Terra Snow Cover 8-Day composite images (MOD10A2) from NASA Earthdata portal.
  • Soil type map: Food and Agriculture Organization (FAO) classification system.
  • LU-LC change drivers: Distance to rivers, distance to built-up areas.

Main Results

• Climate Projections:
  • Temperature: Consistent warming trend across all stations under both RCP 4.5 and RCP 8.5, with RCP 8.5 projecting more substantial increases (e.g., Akhnoor annual minimum temperature under RCP 8.5 increases by +1.23 °C to +3.28 °C; Batote annual maximum temperature under RCP 8.5 increases by +8.41 °C to +11.72 °C).
  • Precipitation: Spatially variable trends. Akhnoor, Reasi, and Tandi show annual declines under both RCPs. Batote exhibits an increase under RCP 8.5 but a decrease under RCP 4.5. Reasi shows the highest magnitude of reductions (e.g., -52.38 mm to -51.64 mm under RCP 4.5).
• Snow Cover Area (SCA): Exhibits clear seasonal patterns (lowest in August/September, highest in February/March). A predominantly negative correlation with streamflow was observed (highest negative correlation of -0.44 in 2011), indicating delayed runoff.
• Sensitivity Analysis: Streamflow is more sensitive to variations in precipitation (sensitivity coefficient ranging from 0.43 to -10.58) than to changes in SCA (0.11 to -1.66).
• Land Use/Land Cover (LU-LC) Changes: Projections indicate a sustained expansion of agricultural and urban areas at the expense of water bodies and forests. By 2100, built-up areas are expected to expand significantly (+655.58 km²), while agriculture (-450.76 km²), forest (-424.81 km²), and perennial snow/ice (-41.11 km²) decrease relative to 1990.
• Streamflow Projections: Both VIC and SWAT models project an overall declining trend in streamflow.
  • VIC Model:
    • RCP 4.5: Reductions ranging from -543.34 m³/s (2020–2040) to -931.90 m³/s (2040–2060) compared to baseline.
    • RCP 8.5: Reductions ranging from -246.90 m³/s (2020–2040) to -776.94 m³/s (2040–2060) compared to baseline.
  • SWAT Model:
    • RCP 4.5: Reductions ranging from -421.90 m³/s (2020–2040) to -796.69 m³/s (2040–2060) compared to baseline.
    • RCP 8.5: Reductions ranging from -319.30 m³/s (2020–2040) to -664.90 m³/s (2040–2060) compared to baseline.
• Comparison of RCPs: Streamflow decline is projected to be sharper under RCP 4.5 than under RCP 8.5. This is attributed to slower warming under RCP 4.5 delaying snowmelt, while accelerated snowmelt under RCP 8.5 partially offsets reductions.
• Model Performance: Both VIC and SWAT models perform well, with VIC simulations showing slightly closer alignment with observed runoff (Pearson's r: 0.83–0.87) compared to SWAT (Pearson's r: 0.72–0.75).

Contributions

• Provides a comprehensive, integrated assessment of future streamflow dynamics in the data-scarce and climate-sensitive Chenab Basin, considering both climate change and land use transitions.
• Employs a multi-model approach, combining RegCM4 for fine-scale climate projections, a hybrid Markov-CA model for LU-LC dynamics, and two complementary hydrological models (VIC and SWAT) for robust streamflow simulations.
• Quantifies the combined effects of climatic and anthropogenic drivers on streamflow in a snow-fed river system, addressing a significant research gap.
• Highlights the counterintuitive finding of sharper streamflow decline under RCP 4.5 compared to RCP 8.5, explaining it through snowmelt dynamics.
• Advances hydrological foresight and provides crucial insights for evidence-based water resource planning and management in the Western Himalayas.

Funding

No funding was received for conducting this study.

Citation

@article{Jasrotia2026Predictive,
  author = {Jasrotia, Avtar Singh and Baru, Deepika and Kour, Retinder},
  title = {Predictive modeling of streamflow in the Chenab basin under anthropogenic and natural forcings},
  journal = {Arabian Journal of Geosciences},
  year = {2026},
  doi = {10.1007/s12517-025-12387-y},
  url = {https://doi.org/10.1007/s12517-025-12387-y}
}