Innovative Drought Classification Matrix and Acceptable Time Period for Temporal Drought Evaluation


Creative Commons License

Abu Arra A., ŞİŞMAN E.

Water Resources Management, 2024 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Publication Date: 2024
  • Doi Number: 10.1007/s11269-024-03793-0
  • Journal Name: Water Resources Management
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, PASCAL, ABI/INFORM, Agricultural & Environmental Science Database, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), Biotechnology Research Abstracts, CAB Abstracts, Compendex, Environment Index, Geobase, INSPEC, Pollution Abstracts, Veterinary Science Database, Civil Engineering Abstracts
  • Keywords: Acceptable Time Period (ATP), Drought Assessment, Drought Classification, Drought Evaluation, SPI
  • Yıldız Technical University Affiliated: Yes

Abstract

Evaluating drought is paramount in water resources management and drought mitigation plans. Drought indices are essential tools in this evaluation, which mainly depends on the time period of the original datasets. Investigating the effects of time periods is critical for a comprehensive understanding and evaluation of drought. Also, It holds particular significance for regions facing data availability challenges. The existing literature reveals a gap in drought assessment and comparison analysis using conventional methods based on drought indices only. This research proposes an innovative drought classification matrix to compare drought indices and spatial and temporal scenarios; the proposed matrix depends on any drought classification for comparison procedure. Furthermore, it aims to investigate the differences between several time period scenarios based on the proposed matrix and several statistical metrics (R2, CC, RMSE, HH, and RB) and determine the acceptable/minimum time period. The application of the proposed matrix and selection of an acceptable/minimum time period is presented to three different climates: Durham station in the United Kingdom, Florya station in Türkiye, and Karapinar station in Türkiye. The results show that the time period scenarios are able to catch the reference time period (RTP) scenario reasonably, with strong correlation and negative relative bias. The 10-year time period is sufficient as an acceptable/minimum time period for short timescales, such as meteorological drought. Conversely, for longer timescales, such as hydrological drought, a 20-year time period is the acceptable/minimum time period. The proposed matrix demonstrates a robust and powerful framework for comparison, making it applicable to various drought assessment scenarios globally.