Kopula Tabanlı Çok Değişkenli Kuraklık İndeksleri: Kuraklık Tahmini için Sıcaklığın Entegrasyonu

Abstract

Kuraklık, etkileri uzun süre devam edebilen yaygın bir doğal afettir. Güvenilir kuraklık tahmini, kuraklıkla ilgili riskleri azaltmaya yönelik etkili stratejilerin geliştirilmesi ve değerlendirilmesinde kilit rol oynamaktadır. Literatürde meteorolojik kuraklık değerlendirmesi için farklı yöntemler bulunmaktadır. Bu yöntemler genellikle yağış ve potansiyel buharlaşma (PET) verilerini gerektirir. Bu çalışmada, standartlaştırılmış yağış indeksi (SPI) ve ortalama hava sıcaklığının kopula fonksiyonları kullanılarak birlikte modellenmesiyle çok değişkenli bir kuraklık indeksi (MDI) tanıtılmıştır. Bu amaçla, 1969-2021 yılları arasında Manavgat, Korkuteli, Finike, Antalya ve Alanya meteoroloji istasyonlarının yağış ve ortalama sıcaklık değerleri kullanılmıştır. İlk olarak, bu istasyonların SPI değerleri dört farklı dönemde (3, 6, 9 ve 12 ay) hesaplanmıştır. Her dönemdeki SPI değerleri ile ortalama sıcaklık arasındaki korelasyonlar incelenmiş ve marjinal dağılımları belirlenmiştir. Her zaman ölçeği için, SPI ve ortalama hava sıcaklığı, alternatif kopula tabanlı bağımlılık yapıları içinde birlikte analiz edildi. Model uygunluğu, bilgi tabanlı ve performans tabanlı kriterlerin bir kombinasyonu kullanılarak değerlendirildi; bunlar AIC, BIC, RMSE ve NSE idi. Seçilen kopula fonksiyonlarına göre, her istasyonun 3, 6, 9 ve 12 aylık dönemlerdeki MDI değerleri hesaplandı. Son olarak, her istasyon için Standartlaştırılmış Yağış Buharlaşma İndeksi (SPEI) değerleri hesaplandı ve MDI, SPI ve SPEI değerleriyle karşılaştırıldı. MDI'nin kurak dönemleri yakalamada başarılı olduğu bulundu.

Keywords

• Kopula tabanlı çok değişkenli kuraklık indeksi
• Standartlaştırılmış Yağış İndeksi (SPI)
• Hava sıcaklığı entegrasyonu
• Meteorolojik kuraklık değerlendirmesi
• Kuraklık izleme ve tahmini

Copula-Based Multivariate Drought Indices: Integrating Temperature for Drought Prediction

Abstract

Drought is a widespread natural hazard whose impacts can persist over long time periods. Reliable drought prediction plays a key role in the development and assessment of effective strategies for mitigating drought-related risks. There are different methods for meteorological drought assessment in literature. These methods generally require precipitation and potential evapotranspiration (PET) data. A multivariate drought index (MDI) is introduced in this study by jointly modeling the standardized precipitation index (SPI) and mean air temperature using copula functions. For this purpose, precipitation and average temperature values of the Manavgat, Korkuteli, Finike, Antalya, and Alanya meteorological stations between 1969 and 2021 were used. First, the SPI values of these stations were calculated in four different periods (3-, 6-, 9- and 12-months). Correlations between SPI values in each period and average temperature were examined, and their marginal distributions were determined. For each time scale, SPI and mean air temperature were jointly analyzed within alternative copula-based dependence structures. Model suitability was evaluated using a combination of information-based and performance-based criteria, namely AIC, BIC, RMSE, and NSE. According to the selected copula functions, the MDI of each station at 3-, 6-, 9- and 12-month periods were calculated. Finally, Standardized Precipitation Evapotranspiration Index (SPEI) values were calculated for each station, and MDI was compared with SPI and SPEI values. MDI was found to be successful in capturing dry periods.

Keywords

• Copula-based multivariate drought index
• Standardized Precipitation Index (SPI)
• Air temperature integration
• Meteorological drought assessment
• Drought monitoring and prediction

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