PyDRGHT: A comprehensive python package for drought analysis

TERZİ T. B.

Environmental Modelling and Software, vol.197, 2026 (SCI-Expanded, Scopus) identifier

  • Publication Type: Article / Article
  • Volume: 197
  • Publication Date: 2026
  • Doi Number: 10.1016/j.envsoft.2025.106847
  • Journal Name: Environmental Modelling and Software
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, Environment Index, Geobase, Greenfile, INSPEC, Public Affairs Index
  • Keywords: Copula, Drought, Drought analysis, Drought index, Drought monitoring, Extremes
  • Karadeniz Technical University Affiliated: Yes

Abstract

Drought is an escalating environmental hazard with profound societal and ecological impacts, intensified by climate change. Effective monitoring and probabilistic assessment require integrated tools capable of capturing both univariate and multivariate characteristics, including the interdependent behavior of multiple hydroclimatic variables. This study introduces PyDRGHT, an open-source Python package for comprehensive drought analysis. PyDRGHT provides a unified framework for computing standardized univariate and multivariate drought indices, identifying drought characteristics, and conducting univariate and copula-based bivariate frequency analyses to enable transparent and reproducible probabilistic assessments. PyDRGHT's utility is demonstrated using long-term precipitation and streamflow records from the Seyhan River Basin, Türkiye (1965–2011), illustrating robust drought detection and characterization. By offering a flexible and robust platform within the Python ecosystem, PyDRGHT advances drought monitoring, risk assessment, and hydroclimatic research.