Yarı Kurak Bölgelerde Hidroklimatik Değişkenliğe Karşı Bitki Örtüsünün Tepkisini Değerlendirme: NDVI–LST–GWL Etkileşimleri

Abstract

Bu çalışmada, 2001–2024 döneminde NDVI, EVI, NDWI, yüzey sıcaklığı (LST) ve yeraltı suyu seviyesi (GWL) arasındaki ilişkiler incelenmiştir. NDVI anomalileri artış göstermiş, özellikle 2015 sonrası daha belirgin pozitif sapmalar görülmüştür. NDVI–EVI arasında güçlü (r=0.84), NDWI–LST arasında ise güçlü negatif korelasyon (r=-0.90) bulunmuştur. NDVI–GWL ilişkisi zayıf kalmış (r=0.22, anomalilerde r=0.16). Doğrusal ve çoklu regresyon analizleri düşük açıklayıcılık göstermiş (R² max=0.049; çoklu regresyon %6.9). Durağanlık testinde NDVI anomalileri kalıcı, LST ve GWL ise durağan bulunmuştur. Granger testi NDVI–GWL arasında öngörücü ilişki göstermemiştir. Sonuçta bitki örtüsü dinamiklerinin esas olarak mevsimsel iklim döngülerinden etkilendiği, yeraltı suyunun küçük ama tutarlı katkı sunduğu, doğrusal korelasyonların sınırlı kaldığı ve yağış, toprak nemi, arazi kullanımı gibi faktörlerin doğrusal olmayan modellerle dahil edilmesi gerektiği ortaya konulmuştur.

Keywords

• Granger Nedensellik
• NDVI
• EVI
• NDWI
• LST
• Yeraltı Su Seviyesi
• Yaşam Kalitesi
• Anomali Tespiti
• Zaman Serisi Analizi

Assessing Vegetation Response to Hydroclimatic Variability in Semi-Arid Regions: NDVI-LST-GWL Interactions

Abstract

This study examined the relationships between NDVI, EVI, NDWI, land surface temperature (LST), and groundwater level (GWL) from 2001 to 2024. NDVI anomalies showed an overall increase, with more pronounced positive deviations after 2015. A strong correlation was found between NDVI and EVI (r=0.84), and a strong negative correlation between NDWI and LST (r=-0.90). The NDVI–GWL relationship was weak (r=0.22; anomalies r=0.16). Linear and multiple regression analyses had low explanatory power (max R²=0.049; multiple regression 6.9%). Stationarity tests showed that NDVI anomalies were persistent, while LST and GWL anomalies were stationary. Granger causality tests indicated no predictive relationship between NDVI and GWL. As a result, vegetation dynamics were mainly influenced by seasonal climate cycles, with groundwater playing a small but consistent role. The weak linear correlations highlight the need to integrate rainfall, soil moisture, and land-use change using nonlinear and lagged modeling approaches.

Keywords

• NDVI
• EVI
• NDWI
• LST
• Groundwater Level
• Quality of life
• Anomaly Detection
• Time Series Analysis
• Granger Causality

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