Maryam et al. (2025) Nonstationarity impacts on the assessment of drought conditions across diverse climate zones of Pakistan

Identification

• Journal: Theoretical and Applied Climatology
• Year: 2025
• Date: 2025-10-20
• Authors: Maryam Maryam, Rizwan Aziz, İsmail Yücel, Mahnoosh Moghaddasi, Muhammad Awais
• DOI: 10.1007/s00704-025-05835-y

Research Groups

• College of Earth and Environmental Sciences, University of the Punjab, Lahore, Pakistan
• Civil Engineering Department, Middle East Technical University, Ankara, Türkiye
• Department of Water Science and Engineering, Faculty of Agriculture and Environment, Arak University, Arak, Iran
• Research Institute for Water Science and Engineering, Arak University, Arak, Iran

Short Summary

This study quantifies the impacts of nonstationarity on drought assessment across diverse climate zones of Pakistan using the Reconnaissance Drought Index (RDI). It reveals significant zonal and temporal shifts in drought and wet conditions, with nonstationarity generally increasing drought severity in northern and agricultural plains and decreasing it in western and coastal regions during the later period (1986–2021).

Objective

• To quantify the impacts of nonstationarity on drought assessment across Pakistan by estimating stationary and nonstationary Reconnaissance Drought Index (RDI).

Study Configuration

• Spatial Scale: Pakistan, covering five homogenous climatic zones, with analyses performed on 120 grid points at a 0.5° × 0.5° spatial resolution. The elevation ranges from 0 to 8611 meters.
• Temporal Scale: Monthly data from 1951 to 2021 (71 years), divided into two distinct periods: Period-1 (October 1951 to September 1986) and Period-2 (October 1986 to September 2021). A 12-month aggregation time window was used for drought index calculation.

Methodology and Data

• Models used:
  • Stationary and nonstationary Reconnaissance Drought Index (RDI).
  • Gamma distribution for fitting RDI values (selected over log-normal distribution based on Global Deviance, Akaike Information Criterion, and Schwartz’s Bayesian Criterion).
  • Generalized Additive Models for Location, Scale, and Shape (GAMLSS) package in R-Programming Language for modeling time-variant location parameters in nonstationary RDI.
• Data sources:
  • Climatic Research Unit’s gridded time series (CRU-TS) for monthly precipitation (millimeters per month) and daily potential evapotranspiration (millimeters per day).

Main Results

• The gamma distribution provided a better fit for RDI values than the log-normal distribution, and the nonstationary gamma distribution showed an improved fit compared to its stationary counterpart across all climatic zones.
• A significant reversal effect of nonstationarity was observed in drought and wet conditions between Period-1 (1951–1986) and Period-2 (1986–2021).
• During Period-2 (1986–2021):
  • Northern high mountains, sub-mountainous, and agricultural plain areas (Zones A, B, and D) experienced increased drought conditions under nonstationarity: extreme droughts increased by up to +4.05%, severe droughts by +5.95%, and moderate droughts by +7.62%. Conversely, wet conditions in these regions decreased by -2.38% (extreme), -5.48% (severe), and -10.00% (moderate).
  • Western mountainous and coastal regions (Zones C and E) experienced a decrease in drought conditions under nonstationarity: extreme droughts decreased by up to -7.14%, severe droughts by -11.43%, and moderate droughts by -9.29%. Conversely, wet conditions in these areas increased by up to +0.48% (extreme), +8.33% (severe), and +11.90% (moderate).
• Nonstationary impacts were more pronounced during the identified dry months (October to December for Zones A, B, D, E; September to November for Zone C) compared to the overall monthly series.

Contributions

• This is the first study to quantify the effects of nonstationarity on drought assessment in Pakistan, addressing a critical research gap.
• It provides a robust framework for estimating drought risk under changing climatic conditions using a nonstationary Reconnaissance Drought Index.
• The research highlights significant zonal and temporal shifts in drought and wet conditions, emphasizing the crucial role of accounting for nonstationarity in improved drought assessments.
• The developed nonstationary RDI serves as a valuable tool for disaster managers, agriculturalists, researchers, and policymakers in developing preparedness and mitigation strategies for drought challenges.

Funding

The author(s) received no specific funding for this work.

Citation

@article{Maryam2025Nonstationarity,
  author = {Maryam, Maryam and Aziz, Rizwan and Yücel, İsmail and Moghaddasi, Mahnoosh and Awais, Muhammad},
  title = {Nonstationarity impacts on the assessment of drought conditions across diverse climate zones of Pakistan},
  journal = {Theoretical and Applied Climatology},
  year = {2025},
  doi = {10.1007/s00704-025-05835-y},
  url = {https://doi.org/10.1007/s00704-025-05835-y}
}