Identifying Persistent Drought Regions for Mediterranean Basin Using Simple Coincidence Deficit Index Approach

Akan G. C., ŞAHİN A. U., ÖZKAYA A.

Water (Switzerland), vol.17, no.5, 2025 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 17 Issue: 5
  • Publication Date: 2025
  • Doi Number: 10.3390/w17050752
  • Journal Name: Water (Switzerland)
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Agricultural & Environmental Science Database, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), CAB Abstracts, Compendex, Environment Index, Food Science & Technology Abstracts, Geobase, INSPEC, Pollution Abstracts, Veterinary Science Database, Directory of Open Access Journals
  • Keywords: coincidence index, drought, GLDAS, groundwater storage, Mediterranean basin
  • Ankara Yıldırım Beyazıt University Affiliated: Yes

Abstract

This study introduces the Simple Coincidence Deficit Index (SCDI) and employs Drought Severity Analysis (DSA) to enhance drought detection and assess patterns and persistency across the Mediterranean basin. Utilizing the Global Land Data Assimilation System (GLDAS) based multi-satellite data for precipitation (P) and groundwater storage (GWS), this research applies both SCDI and DSA to visualize and interpret hydrological event time series across the region. The SCDI uniquely combines precipitation and groundwater levels to provide a comprehensive view of drought intensity. DSA tracks the persistence of water deficit and allows straightforward analysis without requiring transformation or normalization, making it easier to use with remote sensing data. The DSA determines the longest drought periods across various time windows, quantifying the number of months a hydrological deficit persists based on groundwater and precipitation data. Findings show that significant deficits are observed in specific months, which become less apparent in shorter time windows ( (Formula presented.) = 1) due to their rarity. Conversely, in broader time windows ( (Formula presented.) = 12), the cumulative effects of these deficits significantly impact seasonal and yearly averages, with implications extending from lower to higher latitudes. Additionally, as time windows extend, the variability in SCDI values increases across all regions, rendering long-term drought conditions more visible, particularly in North Africa. These findings form the basis of future studies focusing on understanding of drought phenomena and enhancing drought predictability using remote sensing data. The proposed DSA and SCDI methodologies represent a significant advancement over traditional indices by offering new tools for more effective drought analysis.