Paul et al. (2026) When more rain means more drought: hydroclimatic drivers of increasing drought risk in the world’s wettest region

Identification

• Journal: Theoretical and Applied Climatology
• Year: 2026
• Date: 2026-04-10
• Authors: Ashesh Rudra Paul, Pankaj Kumar Roy
• DOI: 10.1007/s00704-026-06213-y

Research Groups

• Department of Civil Engineering, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal, India
• School of Water Resources Engineering, Jadavpur University, Kolkata, West Bengal, India

Short Summary

This study investigates the paradox of increasing drought risk in the world's wettest region, Meghalaya, by analyzing historical and projected hydroclimatic data (1981–2100). It finds that intensified rainfall events, reduced light rain, and rising temperatures lead to elevated evapotranspiration and decreased infiltration, resulting in an increased frequency of drought events and significant reductions in mean annual streamflow, particularly under high-emission scenarios.

Objective

• To analyze historical and future changes in rainfall intensity and frequency using CMIP6 climate projections.
• To assess the spatiotemporal evolution of drought using the Standardized Precipitation Evapotranspiration Index (SPEI) at seasonal timescales.
• To quantify the hydrological response of major transboundary river basins through streamflow simulations under multiple climate scenarios.

Study Configuration

• Spatial Scale: Meghalaya region in Northeast India, extending into adjacent parts of Bangladesh (latitudes 24.625°N to 26.125°N, longitudes 89.650°E to 92.875°E). Specifically, the Sari-Gowain (840.7 square kilometers) and Surma-Meghna (1525.5 square kilometers) river basins.
• Temporal Scale: 86-year period (1981–2100), divided into a historical period (1981–2014) and three future periods: Near Future (NF: 2015–2040), Mid Future (MF: 2041–2070), and Far Future (FF: 2071–2100).

Methodology and Data

• Models used:
  • Hydrologic Engineering Center’s Hydrologic Modeling System (HEC-HMS) for streamflow simulation.
  • Soil Conservation Service Curve Number (SCS-CN) method for runoff estimation.
  • SCS Unit Hydrograph method for transforming runoff volume to hydrograph.
  • Muskingum routing method for channel flow routing.
  • Standardized Precipitation Evapotranspiration Index (SPEI) at a 3-month timescale for drought assessment.
  • Thornthwaite (1948) method for Potential Evapotranspiration (PET) estimation.
  • Non-parametric Mann–Kendall (MK) test and Sen’s slope estimator for trend analysis.
• Data sources:
  • Daily meteorological data (rainfall, maximum and minimum air temperatures) for 1981–2014 from the India Meteorological Department (IMD) and Bangladesh Meteorological Department (BMD).
  • Monthly reanalysis data (relative humidity, solar radiation, wind speed) from European Centre for Medium-Range Weather Forecasts Reanalysis 5th Generation (ERA5).
  • Streamflow data from the Bangladesh Water Development Board (BWDB) for Kanairghat and Sarighat stations.
  • Future climate projections (2015–2100) from the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) - CMIP6 dataset (14 GCMs) under SSP126, SSP245, SSP370, and SSP585 scenarios.
  • Digital Elevation Model (DEM) for hydrological modeling.

Main Results

• The Simple Daily Intensity Index (SDII) showed an upward trend, with a locally observed maximum rate of 0.08 mm/day per year.
• Light rain events (less than 10 mm/day) and the number of rainy days declined, with an average decrease of -0.40 days per year, leading to longer dry intervals.
• Both maximum and minimum air temperatures exhibited increasing trends, with minimum temperatures rising more significantly (up to 0.08 °C/year).
• SPEI-3 analysis revealed an increasing frequency and intensity of drought events, particularly under high-emission scenarios (SSP585). The annual occurrence of extreme drought events is projected to increase from a baseline of 0.282 to 0.61 in the Far Future under SSP585.
• Hydrological modeling projected significant reductions in mean annual streamflow volume: up to -9.8% for the Sari-Gowain River catchment and up to -11.6% for the Surma-Meghna river basin in the Far Future under SSP585.
• Streamflow exhibited pronounced seasonal variability, peaking during the June-July monsoon period and declining steadily thereafter, indicating increased potential for hydrological drought in later months.

Contributions

• This study provides a systematic and integrated assessment linking rainfall intensification metrics, temperature-driven drought indices, and hydrological responses in one of the world's highest precipitation regions.
• It explicitly addresses the "rainfall-drought paradox" by demonstrating how climate change can simultaneously intensify rainfall extremes and exacerbate drought risk.
• The research integrates multiple hydroclimatic drivers (rainfall intensity/frequency, temperature-induced atmospheric water demand, and river-basin-scale streamflow) using long-term historical observations and CMIP6-based future climate projections under multiple Shared Socioeconomic Pathways (SSPs).
• The findings offer critical insights for climate-resilient water resource planning and challenge conventional assumptions regarding drought vulnerability in high-rainfall regions.

Funding

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

Citation

@article{Paul2026When,
  author = {Paul, Ashesh Rudra and Roy, Pankaj Kumar},
  title = {When more rain means more drought: hydroclimatic drivers of increasing drought risk in the world’s wettest region},
  journal = {Theoretical and Applied Climatology},
  year = {2026},
  doi = {10.1007/s00704-026-06213-y},
  url = {https://doi.org/10.1007/s00704-026-06213-y}
}