Propagation and compound risk of meteorological-agricultural droughts: insights from lag correlations and copula-based dependence modeling
PHYSICS AND CHEMISTRY OF THE EARTH, cilt.144, 2026 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 144
- Basım Tarihi: 2026
- Doi Numarası: 10.1016/j.pce.2026.104630
- Dergi Adı: PHYSICS AND CHEMISTRY OF THE EARTH
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Chimica, Compendex, Geobase, INSPEC
- Karadeniz Teknik Üniversitesi Adresli: Evet
Özet
Compound droughts arising from the co-occurrence of meteorological and agricultural water deficits can intensify crop water stress and adversely affect agricultural production under climate variability. Yet, drought assessments often consider individual drought types in isolation, limiting understanding of their joint behavior and propagation characteristics. This study examines compound drought dynamics in the & Ccedil;oruh River Basin using standardized drought indices and three complementary approaches: lagged correlation analysis, copulabased dependence modeling, and the Multivariate Standardized Drought Index (MSDI). Meteorological drought is represented by the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI), whereas agricultural drought is represented by the Standardized Soil Moisture Index (SSI). Lagged correlation analyses are used to quantify drought propagation from meteorological to agricultural systems across multiple timescales. Alternative copula families are used to characterize the dependence between drought types, including their tendency to co-occur under extreme dry conditions. Results indicate strong propagation from meteorological to agricultural drought at 3-9-month timescales, with peak correlations occurring at zero-month lag. The dependence analysis further indicates an elevated likelihood of concurrent extreme drought events. Although some copulas yield lower information-criterion values, the Clayton copula was selected because it explicitly represents lower-tail dependence, with coefficients of 0.279 for SPI-SSI and 0.33 for SPEI-SSI. MSDI-based analyses further reveal differences in drought frequency, duration, and severity between SPI- and SPEI-based compound droughts. These findings underscore the importance of explicitly accounting for dependence structures and compound behavior in agricultural drought monitoring, environmental management, and risk assessment frameworks.