Choudhary et al. (2026) Simulating Streamflow Scenarios Using Hydrological Modeling Integrated with Future Land Use and CMIP6 Climate Projections

Identification

• Journal: Water Resources Management
• Year: 2026
• Date: 2026-02-01
• Authors: Preetam Choudhary, C P Devatha, Adani Azhoni
• DOI: 10.1007/s11269-025-04406-0

Research Groups

• National Institute of Technology Karnataka, Mangalore, India
• National Institute of Technology Manipur, Imphal, India

Short Summary

This study develops a unique modeling framework integrating an ensemble of CMIP6 General Circulation Models (GCMs) with future land use land cover (LULC) projections to assess their combined impacts on the hydrology of the Upper Krishna River sub-basin. It projects significant increases in temperature, precipitation, surface runoff, and water yield, leading to heightened and prolonged flood risks by the end of the century, particularly under high-emission scenarios.

Objective

• To set up a Soil and Water Assessment Tool (SWAT) model to evaluate the water balance in the basin.
• To assess the integrated impact of climate change and LULC dynamics on the variables of the hydrological cycle.
• To predict the streamflow for mid-century (2022–2049) and end-century (2050–2100) scenarios.

Study Configuration

• Spatial Scale: A sub-basin of the Upper Krishna River Basin (UKRB), India. Climate data downscaled to 0.25° resolution, Digital Elevation Model (DEM) at 30 m resolution, and Land Use Land Cover (LULC) maps at 10 m resolution.
• Temporal Scale: Historical baseline (1951–2021 for climate, 1991–2021 for hydrological model calibration/validation); Future projections for mid-century (2022–2049) and end-century (2050–2100).

Methodology and Data

• Models used:
  • Hydrological Model: Soil and Water Assessment Tool (SWAT)
  • Climate Projections: Ensemble mean of selected CMIP6 General Circulation Models (GCMs) (MPI-ESM1-2-HR, EC-Earth3, CanESM5, BCC-CSM2, ACCESS-ESM1-5) for Shared Socioeconomic Pathways (SSP) 2-4.5 and 5-8.5.
  • GCM Selection/Ranking: Modified Technique for Order Preference by Similarity to Ideal Solution (mTOPSIS).
  • LULC Projections: Multi-Layer Perceptron Neural Network (MLPNN) combined with Cellular Automata-Markov Chain (CA-Markov).
  • Bias Correction and Downscaling (GCMs): Empirical Quantile Mapping and bi-linear interpolation.
  • SWAT Calibration/Validation: Sequential Uncertainty Fitting version 2 (SUFI-2) algorithm in SWAT-CUP.
• Data sources:
  • Historical Temperature and Precipitation: India Meteorological Department (IMD) (0.25° for precipitation, 1° for temperature).
  • Digital Elevation Model (DEM): USGS Earth Explorer (SRTM DEM).
  • Land Use Land Cover (LULC): Sentinel imagery (10 m resolution) for 2024, 2049, and 2099.
  • Soil Data: Food and Agriculture Organisation (FAO) portal.
  • Daily Discharge Data: Central Water Commission (CWC) of India (Arjunwad gauge site).
  • Monthly Discharge Data: Chuphal and Mishra (2023) (Almatti Dam outlet).

Main Results

• Climate Projections (Ensemble Mean):
  • Temperature: Historical average daily maximum temperature of 29.3 °C is projected to rise to 30.8 °C under SSP2-4.5 and 31.4 °C under SSP5-8.5 by end-century. Historical average daily minimum temperature of 19.5 °C is projected to rise to 21.1–22.8 °C under SSP2-4.5 and 21.9–24.4 °C under SSP5-8.5, indicating a significant reduction in nocturnal cooling. Annual average maximum temperature anomalies reach +4.5 °C under SSP5-8.5 by end-century.
  • Precipitation: Historical annual average precipitation of 1019.4 mm is projected to increase to 1176.2 mm under SSP2-4.5 and 1397.4 mm under SSP5-8.5 (ensemble means). Annual precipitation anomalies under SSP5-8.5 reach nearly +378 mm/year by end-century, indicating more intense and erratic rainfall events.
• Land Use Land Cover (LULC) Changes (2024 to 2099): Built-up area is projected to increase from 6.53% to 15%, while forest cover declines from 6.27% to 4.93%, and agricultural land decreases from 75.86% to 70.57%.
• Hydrological Responses (Combined Climate and LULC, Ensemble Mean):
  • Surface Runoff: Increases from a historical 422.5 mm to 556.39 mm under SSP2-4.5 and 723.07 mm under SSP5-8.5 by end-century.
  • Water Yield: Increases from a historical 559.2 mm to 753.29 mm under SSP2-4.5 and 1016.89 mm under SSP5-8.5 by end-century.
  • Evapotranspiration (ET): Shows a steady rise from 419.5 mm (2021) to 431.1 mm (2100) under LULC changes alone.
• Streamflow Predictions (Extreme Events):
  • Arjunwad: Under SSP2-4.5, peak flows up to 9600 m³/s (2029) and 11600 m³/s (end-century) are anticipated, with durations exceeding 8000 m³/s for up to 8 days. Under SSP5-8.5, peak flows exceed 12000 m³/s (2051), surpassing a 200-year return period flood.
  • Almatti Dam: Under SSP2-4.5, peak flows up to 11000 m³/s (mid-century) and 13700 m³/s (2082 end-century) are projected. Under SSP5-8.5, the most extreme discharge is 15000 m³/s (2051), with some years experiencing up to 12 consecutive days above the 8000 m³/s threshold.
• Relative Impact: Climate change is identified as the primary driver of hydrological disturbance, with LULC alterations exacerbating these effects.

Contributions

• Presents a unique integrated modeling framework that systematically combines an ensemble of bias-corrected and downscaled CMIP6 GCMs (selected using mTOPSIS) with future LULC scenarios (simulated using MLPNN and CA-Markov).
• Offers a comprehensive assessment of the combined impacts of climate change and land use dynamics on water balance and critical hydrological parameters, particularly streamflow, at a basin scale.
• Provides detailed spatial and temporal analysis of projected hydrological changes, highlighting the intensification of flood threats due to warming and urban growth.
• Enhances understanding of future water resource sustainability and supports more precise water management planning and adaptation strategies in flood-vulnerable basins.

Funding

No funding was received for conducting this study.

Citation

@article{Choudhary2026Simulating,
  author = {Choudhary, Preetam and Devatha, C P and Azhoni, Adani},
  title = {Simulating Streamflow Scenarios Using Hydrological Modeling Integrated with Future Land Use and CMIP6 Climate Projections},
  journal = {Water Resources Management},
  year = {2026},
  doi = {10.1007/s11269-025-04406-0},
  url = {https://doi.org/10.1007/s11269-025-04406-0}
}