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Introducing Normalized Surface-adjusted Precipitation Index (NSPI) for regional drought assessment
Preeti Rajput1, Manish Kumar Sinha2, Nikhil Ghodichore3
1Department of Civil Engineering, Government Engineering College Raipur, Raipur 492015, Chhattisgarh, India; Department of Environmental & Water Resources Engineering, University Teaching Department, Chhattisgarh Swami Vivekanand Technical University Bhilai, Bhilai 491107, Chhattisgarh, India.
The Science of the Total Environment
|September 3, 2025
Summary
A new drought index, the Normalized Surface-adjusted Precipitation Index (NSPI), better captures drought evolution by combining climate data with land surface characteristics. This advanced index offers improved drought pattern detection for early warning systems.
Area of Science:
- Hydrology
- Climate Science
- Environmental Monitoring
Background:
- Drought frequency and severity are increasingly influenced by human activity and climate change.
- Traditional drought indices like the Standardized Precipitation Index (SPI) often fail to capture complex interactions between atmospheric and land surface processes.
- Human-induced changes to the hydrological cycle are reshaping drought development and persistence in the Anthropocene.
Purpose of the Study:
- Introduce the Normalized Surface-adjusted Precipitation Index (NSPI) to better represent drought evolution.
- Integrate climate data with catchment-scale surface characteristics for improved drought assessment.
- Address limitations of traditional indices in capturing combined atmospheric and land surface effects on drought.
Main Methods:
- Developed the Normalized Surface-adjusted Precipitation Index (NSPI) by merging climate data with surface characteristics.
- Utilized data from remote sensing, reanalysis datasets, land surface models, and ground-based observations.
- Incorporated a "loss term" and a Composite Variable derived using Principal Component Analysis to account for moisture availability, energy inputs, and moisture transport efficiency.
Main Results:
- NSPI demonstrates superior performance across multiple timescales compared to traditional indices.
- The index accurately reflects drought patterns by aligning with satellite-derived vegetation data (NDVI).
- Application in the Mahanadi River Basin revealed more detailed spatial drought patterns than SPI.
Conclusions:
- NSPI offers a more comprehensive representation of drought dynamics by integrating land surface properties.
- The enhanced accuracy of NSPI provides a stronger foundation for developing effective drought early warning systems.
- NSPI accounts for climate change impacts, such as rising temperatures and wind speeds, on drought conditions.
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