Palagiri et al. (2026) A Percentile-Based Dynamic Threshold Run Theory (pDTRT) for Characterizing Agricultural Drought Using ESACCI Soil Moisture

Identification

• Journal: Water Resources Management
• Year: 2026
• Date: 2026-01-01
• Authors: Hussain Palagiri, Manali Pal
• DOI: 10.1007/s11269-025-04486-y

Research Groups

• Department of Civil Engineering, National Institute of Technology Warangal, Warangal, India

Short Summary

This study proposes a percentile-based Dynamic Threshold Run Theory (pDTRT) for agricultural drought characterization using the Standardized Soil Moisture Index (SSI) derived from ESACCI Soil Moisture data. The pDTRT applies grid-specific, dynamic thresholds, demonstrating enhanced spatial variability in drought characteristics (duration, frequency, intensity) compared to traditional single-threshold methods, thereby improving the accuracy of drought assessment in heterogeneous regions.

Objective

• To develop and apply a percentile-based Dynamic Threshold Run Theory (pDTRT) for agricultural drought characterization using the Standardized Soil Moisture Index (SSI).
• To better represent localized soil moisture regimes, reduce misclassification of drought duration and frequency, and more accurately capture spatial variability in drought intensity across diverse geographical areas by deriving grid-specific SSI-based thresholds.

Study Configuration

• Spatial Scale: Godavari Basin, India (between 16°19’N to 22°34 N and 73°24′E to 83°4′E), covering an area of 312,812 square kilometers. Data resolution is 0.25° × 0.25°.
• Temporal Scale: 1993–2022 (30 years) for soil moisture data, aggregated to a monthly time scale for SSI-1 computation.

Methodology and Data

• Models used: Percentile-based Dynamic Threshold Run Theory (pDTRT), Standardized Soil Moisture Index (SSI-1), Gamma distribution for fitting soil moisture values, inverse normal transformation for standardization.
• Data sources: European Space Agency’s (ESA) Climate Change Initiative (CCI) Soil Moisture (SM) (ESACCI SM) combined product (version v0.81), providing daily global surface soil moisture at 0–5 centimeters depth.

Main Results

• The pDTRT employs grid-specific, percentile-based thresholds (x1, x2, x3) for drought event identification, which align with transitions between drought categories (e.g., x1 ~ -0.5 for near normal to mild, x2 ~ -1 for mild to moderate, x3 ~ 0.5 for near normal to mild wet conditions).
• These dynamic thresholds exhibit spatial variability across the Godavari basin, reflecting underlying heterogeneity in soil properties, vegetation cover, climate regime, and land use practices.
• pDTRT identifies average annual drought durations ranging from 2 to 4 months, which are shorter and more segmented than the 5 to 6 months identified by single-threshold methods.
• The method captures significant spatial variability in drought frequency and intensity (ranging from -0.8 to -1.8), providing a more nuanced understanding compared to the uniform patterns observed with single-threshold approaches.
• Drought peak (lowest SSI value during an event) remains consistent across pDTRT and single-threshold methods.

Contributions

• Introduces a novel percentile-based Dynamic Threshold Run Theory (pDTRT) that dynamically adjusts drought thresholds based on local soil moisture distributions, addressing the limitations of uniform thresholds in heterogeneous regions.
• Enhances the precision of agricultural drought characterization by improving the detection of drought onset, exclusion of minor events, and merging of adjacent drought periods.
• Demonstrates the effectiveness of satellite-based ESACCI Soil Moisture data for consistent and spatially adaptive agricultural drought assessment over large geographical areas.
• Provides a more realistic representation of agricultural drought dynamics by capturing greater spatial variability in drought duration, frequency, and intensity.

Funding

The authors declare that no funds were received during the preparation of this manuscript.

Citation

@article{Palagiri2026PercentileBased,
  author = {Palagiri, Hussain and Pal, Manali},
  title = {A Percentile-Based Dynamic Threshold Run Theory (pDTRT) for Characterizing Agricultural Drought Using ESACCI Soil Moisture},
  journal = {Water Resources Management},
  year = {2026},
  doi = {10.1007/s11269-025-04486-y},
  url = {https://doi.org/10.1007/s11269-025-04486-y}
}