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

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.

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Journal
Harran Üniversitesi Mühendislik Dergisi
Published
2025-09-29
DOI
https://doi.org/10.46578/humder.1751103
Primary Topic
Climate variability and models
Type
article
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article

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

Veysi Kartal, Esra Bayazıt
Harran Üniversitesi Mühendislik Dergisi
Climate variability and models
article

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

Veysi Kartal, Esra Bayazıt
article en

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.

Harran Üniversitesi Mühendislik DergisiVol. 10(3)
Siirt Üniversitesi (TR)
Openalex Percentile: Top 75%
Climate variability and models
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