Muraharirao et al. (2025) Regional scale analysis of the internal propagation of groundwater droughts in Andhra Pradesh, India

Identification

• Journal: Theoretical and Applied Climatology
• Year: 2025
• Date: 2025-12-23
• Authors: Prem Chand Muraharirao, Naresh Chinthu
• DOI: 10.1007/s00704-025-05957-3

Research Groups

• Department of Civil Engineering, Indian Institute of Technology Hyderabad, Kandi, Telangana, India.
• Department of Civil Engineering, National Institute of Technology Tiruchirappalli, Tamil Nadu, India.

Short Summary

This study develops the Groundwater Drought Instantaneous Propagation Speed (GDIPS) framework to analyze the internal dynamics of groundwater droughts across Andhra Pradesh, India. The findings reveal that groundwater droughts generally develop faster than they recover, with significant regional variability driven by rainfall patterns and aquifer hydrogeology.

Objective

• To investigate the internal propagation mechanisms of groundwater droughts (transition from development to recovery phases) and characterize drought spatial variability at a regional scale.

Study Configuration

• Spatial Scale: Regional scale covering the state of Andhra Pradesh, India (approximately 163,000 km²), divided into three regions: Rayalaseema (RAY), North Coastal Andhra (NCA), and South Coastal Andhra (SCA).
• Temporal Scale: Monthly analysis from June 2004 to May 2021 (17 years).

Methodology and Data

• Models used: Nonparametric Standardized Groundwater Index (SGI) for drought identification; Groundwater Drought Instantaneous Propagation Speed (GDIPS) framework to calculate Instantaneous Development Speed (IDS) and Instantaneous Recovery Speed (IRS); Modified Mann-Kendall trend test (Hamed and Rao) to account for serial correlation; Drought Frequency Index (DFI).
• Data sources: Monthly water table depth observations from 420 shallow monitoring wells (tapping unconfined aquifers) and rainfall data obtained from the India Water Resources Information System (India-WRIS) portal.

Main Results

• Internal Propagation: Groundwater droughts in the study area typically develop more rapidly than they recover (IDS > IRS). NCA districts show longer development durations but faster recovery, while RAY and SCA districts exhibit rapid development and slower recovery.
• Drought Characteristics: Extreme and long-duration droughts are primarily concentrated in the Rayalaseema and South Coastal regions. Median Drought Development Durations (DDD) reached up to 54 months (Srikakulam), while median Drought Recovery Durations (DRD) peaked at 50.5 months (Kurnool).
• Rainfall Influence: Total Groundwater Duration (TGD) and DRD are significantly negatively correlated with median rainfall (Spearman Rank Correlation of -0.66 and -0.62, respectively), indicating that rainfall is a primary driver of drought recovery resilience.
• Frequency: Most districts are classified under "mild" to "moderate" drought frequency classes based on the DFI.
• Aquifer Memory: A significant positive correlation (PCC > 0.6) exists between drought duration and the maximum autocorrelation lag of the groundwater time series, particularly in alluvial aquifers with higher hydrological memory.

Contributions

• Development of the GDIPS framework, adapting hydrological drought speed concepts specifically for groundwater systems to quantify non-uniform internal propagation.
• Shifting the research focus from external propagation (meteorological-to-groundwater) to internal propagation (development-to-recovery) within the aquifer itself.
• Providing a high-resolution regional assessment of groundwater drought vulnerability in Andhra Pradesh to inform site-specific water management and artificial recharge strategies.

Funding

• The authors reported that no specific funds, grants, or other support were received for the preparation of this manuscript.

Citation

@article{Muraharirao2025Regional,
  author = {Muraharirao, Prem Chand and Chinthu, Naresh},
  title = {Regional scale analysis of the internal propagation of groundwater droughts in Andhra Pradesh, India},
  journal = {Theoretical and Applied Climatology},
  year = {2025},
  doi = {10.1007/s00704-025-05957-3},
  url = {https://doi.org/10.1007/s00704-025-05957-3}
}

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