Kumar et al. (2026) Deciphering the role of ENSO and IOD in hydro-climate dynamics using SWAT and multi-dimension wavelet analysis

Identification

• Journal: Natural Hazards
• Year: 2026
• Date: 2026-01-01
• Authors: Hanumapura Kumaraswamy Yashas Kumar, Kondeti Poojitha, K. Varija
• DOI: 10.1007/s11069-025-07771-6

Research Groups

• Department of Water Resources and Ocean Engineering, National Institute of Technology (NIT) Karnataka, Mangalore, India

Short Summary

This study investigates the individual and combined influences of El Niño-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) on hydro-climate dynamics in the Aghanashini River Basin, a Ramsar wetland site. It finds that combined ENSO-IOD phases exert a stronger, synergistic control over rainfall, temperature, and streamflow, leading to exacerbated hydrological extremes and altered salinity levels that threaten the fragile river ecosystem.

Objective

• To assess the individual influence of ENSO and IOD on observed hydro-climate variables (precipitation, maximum and minimum temperature, streamflow) using multiscale relationships (Cross Wavelet Transform and Wavelet Coherence Transform) and quantifying percentage changes.
• To assess the combined influence of ENSO and IOD on hydro-climate variables using multiscale relationships (Multiple Wavelet Coherence) and quantifying percentage changes.
• To quantify hydrological changes in each sub-basin under the influence of individual and combined ENSO-IOD phases using an enhanced Soil and Water Assessment Tool (SWAT) hydrological model.

Study Configuration

• Spatial Scale: Aghanashini River Basin (ARB), Western Ghats, India. Area: 1500 km². Divided into 31 sub-basins. Elevations range from 12 to 797 m.
• Temporal Scale: Hydro-climate data from 1991 to 2018 (precipitation, temperature) and 1994 to 2018 (streamflow). ENSO and IOD data for the same period. Land use maps for 2008 and 2024.

Methodology and Data

• Models used:
  • Soil and Water Assessment Tool (SWAT) hydrological model (enhanced with measured soil data).
  • Biwavelet analysis: Cross Wavelet Transform (XWT) and Wavelet Coherence Transform (WTC).
  • Multiwavelet analysis: Multiple Wavelet Coherence (MWC).
  • Spearman’s rank correlation coefficient (rS).
• Data sources:
  • Hydro-climate: Daily precipitation, maximum and minimum temperature from Indian Meteorological Department (IMD, 1991-2018). Daily streamflow from Central Water Commission (CWC, 1994-2018).
  • Climate Oscillations: Monthly Niño 3.4 Sea Surface Temperature (SST) anomaly index (ENSO) from National Centers for Environmental Information (NCEI). Monthly Dipole Mode Index (DMI) (IOD) from NOAA Physical Sciences Laboratory.
  • Topography: 30 m Digital Elevation Model (DEM) from Shuttle Radar Topography Mission (SRTM).
  • Land Use: Land use maps for 2008 (Advanced Land Observation Satellite - ALOS) and 2024 (Landsat 8), prepared using supervised maximum likelihood classification.
  • Soil Data: National Bureau of Soil Survey and Land use Planning (NBSS&LUP) soil database, supplemented with extensive field tests and laboratory analyses (e.g., hydraulic conductivity, soil layer depth, root depth, organic carbon, texture, bulk density, available water content, USLE soil erodibility factor, soil moist albedo).

Main Results

• Individual ENSO and IOD influences show significant interannual coherence (>12 months) with hydro-climate variables, with average wavelet coherence power (AWCP) exceeding 0.5 and over 70% of wavelet power values surpassing the 95% significance threshold during strong influence periods.
• ENSO phases primarily dominate temperature variability (Tmax and Tmin; AWCP values of 0.70 and 0.74, respectively), with positive ENSO leading to warmer conditions (Tmax +0.23%, Tmin +0.52%) and decreased streamflow (-10.02%).
• IOD exerts a stronger influence on precipitation (AWCP = 0.67), with positive IOD phases enhancing precipitation (+11.22%) and streamflow (+12.56%), increasing flood risk. Negative IOD phases reduce precipitation (–12.19%) and streamflow (–11.75%), leading to drought-like conditions.
• Multiple Wavelet Coherence (MWC) analysis reveals synergistic and nonlinear amplification effects from combined ENSO and IOD, with higher coherence values compared to individual oscillations (e.g., AWCP and PoSP95 exceeding 0.70 and 75% for multiple variables).
• Concurrent positive ENSO and IOD phases produce the strongest wet anomalies, with a 12.76% increase in precipitation and substantial rises in streamflow (+2.10%). Mean monthly water yield (WYLD) in July increased to 2.75 × 10^9 m^3 compared to a baseline of 2.36 × 10^9 m^3.
• Concurrent negative ENSO and IOD phases intensify drought risks, with an 8.54% decrease in precipitation and a 3.60% decrease in streamflow. Negative IOD phases reduced WYLD to 0.48 × 10^9 m^3 relative to a baseline minimum of 0.56 × 10^9 m^3.
• The projected increase in frequency and intensity of El Niño events and positive IOD phases poses a significant threat to the Aghanashini River wetland ecosystem, impacting fish populations and migratory birds due to altered streamflow and salinity levels (>30 ppt).

Contributions

• Establishes a teleconnection between large-scale climate oscillations (ENSO and IOD) and hydro-climate dynamics at a finer, basin-level spatial scale (Aghanashini River Basin), addressing a less explored area in existing literature.
• Utilizes advanced multi-dimension wavelet analysis (XWT, WTC, MWC) to comprehensively assess both individual and combined influences of ENSO and IOD, revealing synergistic and nonlinear amplification effects that are crucial for understanding complex hydro-climatic variability.
• Employs an enhanced Soil and Water Assessment Tool (SWAT) hydrological model, incorporating detailed, field-measured soil parameters, which significantly improves simulation accuracy and provides robust predictions of hydrological changes under various climate oscillation scenarios.
• Quantifies the specific hydrological and ecological impacts of ENSO and IOD phases on a Ramsar wetland site and UNESCO biodiversity hotspot, highlighting the vulnerability of this fragile ecosystem and informing adaptive water management strategies.
• Bridges the gap between large-scale teleconnection analyses and basin-level hydrological and ecological dynamics, offering a practical framework for anticipating and managing climate-driven hydrological extremes.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Citation

@article{Kumar2026Deciphering,
  author = {Kumar, Hanumapura Kumaraswamy Yashas and Poojitha, Kondeti and Varija, K.},
  title = {Deciphering the role of ENSO and IOD in hydro-climate dynamics using SWAT and multi-dimension wavelet analysis},
  journal = {Natural Hazards},
  year = {2026},
  doi = {10.1007/s11069-025-07771-6},
  url = {https://doi.org/10.1007/s11069-025-07771-6}
}