Yarı Kurak Bölgelerde Hidroklimatik Değişkenliğe Karşı Bitki Örtüsünün Tepkisini Değerlendirme: NDVI–LST–GWL Etkileşimleri
Yıl 2025,
Cilt: 10 Sayı: 3, 198 - 212, 30.09.2025
Esra Bayazıt
,
Veysi Kartal
Öz
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.
Etik Beyan
Bu makalenin özgün bir araştırma olduğunu ve daha önce herhangi bir dilde herhangi bir dergide yayınlanmadığını teyit ederiz.
Teşekkür
Yazarlar, sağladığı veriler için Türkiye Su İşleri Genel Müdürlüğü'ne teşekkür eder.
Kaynakça
-
Das, A. C., Shahriar, S. A., Chowdhury, M. A., Hossain, M. L., Mahmud, S., Tusar, M. K., ... & Salam, M. A. (2023). Assessment of remote sensing-based indices for drought monitoring in the north-western region of Bangladesh. Heliyon, 9(2).
-
Mishra, A. K., & Singh, V. P. (2010). A review of drought concepts. Journal of hydrology, 391(1-2), 202-216.
-
Dodman, D., Hayward, B., Pelling, M., Broto, V. C., Chow, W., Chu, E., ... & Muñoz, T. A. (2022). Cities, Settlements and Key Infrastructure. In: Climate Change 2022: Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change.
-
Smith, M. D., Wilkins, K. D., Holdrege, M. C., Wilfahrt, P., Collins, S. L., Knapp, A. K., ... & Sun, W. (2024). The impacts of extreme drought have been underestimated in grasslands and shrublands worldwide. Proceedings of the National Academy of Sciences, 121(4), e2309881120.
-
Buras, A., Rammig, A., & Zang, C. S. (2020). Quantifying impacts of the 2018 drought on European ecosystems in comparison to 2003. Biogeosciences, 17(6), 1655-1672
-
Müller, L. M., & Bahn, M. (2022). Drought legacies and ecosystem responses to subsequent drought. Global Change Biology, 28(17), 5086-5103.
-
Pacione, M. (2003). Urban environmental quality and human wellbeing—a social geographical perspective. Landscape and urban planning, 65(1-2), 19-30.
-
Zhang, X., Chen, N., Sheng, H., Ip, C., Yang, L., Chen, Y., Sang, Z., Tadesse, T., Lim, T., Rajabifard, A., Bueti, C., Zeng, L., Wardlow, B., Wang, S., Tang, S., Xiong, Z., Li, D., & Niyogi, D. (2019). Urban drought challenges to 2030 sustainable development goals. The Science of the Total Environment: 693, 133536.
-
Pizzorni, M., Innocenti, A., & Tollin, N. (2024). Droughts and floods in a changing climate and implications for multi-hazard urban planning: A review. City and Environment Interactions, 24, 100169.
-
Haile, G. G., Tang, Q., Li, W., Liu, X., & Zhang, X. (2020). Drought: Progress in broadening its understanding. Wiley Interdisciplinary Reviews: Water, 7(2), e1407.
-
Lima, L. B., Franca Rocha, W. J. S., Souza, D. T. M., Lobão, J. S. B., de Santana, M. M. M., Cambui, E. C. B., & Vasconcelos, R. N. (2025). Urban Quality: A Remote-Sensing-Perspective Review. Urban Science, 9(2), 31.
-
Lee, A. C. K., Jordan, H. C., & Horsley, J. (2015). Value of urban green spaces in promoting healthy living and wellbeing: prospects for planning. Risk management and healthcare policy, 131-137.
-
Kruize, H., van der Vliet, N., Staatsen, B., Bell, R., Chiabai, A., Muiños, G., Higgins, S., Quiroga, S., Martinez-Juarez, P., Aberg Yngwe, M., Tsichlas, F., Karnaki, P., Lima, M. L., García de Jalón, S., Khan, M., Morris, G., & Stegeman, I. (2019). Urban Green Space: Creating a Triple Win for Environmental Sustainability, Health, and Health Equity through Behavior Change. International Journal of Environmental Research and Public Health, 16(22), 4403.
-
Huete, A., Didan, K., Miura, T., Rodriguez, E. P., Gao, X., & Ferreira, L. G. (2002). Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote sensing of environment, 83(1-2), 195-213.
-
Sobrino, J. A., Jiménez-Muñoz, J. C., & Paolini, L. (2004). Land surface temperature retrieval from LANDSAT TM 5. Remote Sensing of environment, 90(4), 434-440.
-
Mert, A., Tavuç, İ., Özdemir, S., & Ulusan, M. D. (2025). Future Responses of the Burdur Lake to Climate Change and Uncontrolled Exploitation. Journal of the Indian Society of Remote Sensing, 53(4), 1025-1036.
-
Özdemir, S., Özkan, K., & Mert, A. (2020). An ecological perspective on climate change scenarios. Biological Diversity and Conservation, 13(3), 361-371.
-
Famiglietti, J. S. (2014). The global groundwater crisis. Nature climate change, 4(11), 945-948.
-
Rodell, M., Velicogna, I., & Famiglietti, J. S. (2009). Satellite-based estimates of groundwater depletion in India. Nature, 460(7258), 999-1002.
-
Gao, B.-C. 1996. “NDWI – A Normalised Difference Water Index for Remote Sensing of Vegetation Liquid Water from Space.” Remote Sensing of Environment 58: 257–266.
-
Sun, H., Zhao, X., Chen, Y., Gong, A., & Yang, J. (2013). A new agricultural drought monitoring index combining MODIS NDWI and day–night land surface temperatures: A case study in China. International Journal of Remote Sensing, 34(24), 8986-9001.
-
Dickey, D. A., & Fuller, W. A. (1981). Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica: journal of the Econometric Society, 1057-1072.
-
Kwiatkowski, D., Phillips, P. C., Schmidt, P., & Shin, Y. (1992). Testing the null hypothesis of stationarity against the alternative of a unit root: How sure are we that economic time series have a unit root?. Journal of econometrics, 54(1-3), 159-178.
-
Granger, C. W. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica: journal of the Econometric Society, 424-438.
Assessing Vegetation Response to Hydroclimatic Variability in Semi-Arid Regions: NDVI-LST-GWL Interactions
Yıl 2025,
Cilt: 10 Sayı: 3, 198 - 212, 30.09.2025
Esra Bayazıt
,
Veysi Kartal
Öz
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.
Etik Beyan
We confirm that this article is original research and has not been published previously in any journal in any language.
Teşekkür
The author thanks the Türkiye General Directorate of Water Works for the data provided.
Kaynakça
-
Das, A. C., Shahriar, S. A., Chowdhury, M. A., Hossain, M. L., Mahmud, S., Tusar, M. K., ... & Salam, M. A. (2023). Assessment of remote sensing-based indices for drought monitoring in the north-western region of Bangladesh. Heliyon, 9(2).
-
Mishra, A. K., & Singh, V. P. (2010). A review of drought concepts. Journal of hydrology, 391(1-2), 202-216.
-
Dodman, D., Hayward, B., Pelling, M., Broto, V. C., Chow, W., Chu, E., ... & Muñoz, T. A. (2022). Cities, Settlements and Key Infrastructure. In: Climate Change 2022: Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change.
-
Smith, M. D., Wilkins, K. D., Holdrege, M. C., Wilfahrt, P., Collins, S. L., Knapp, A. K., ... & Sun, W. (2024). The impacts of extreme drought have been underestimated in grasslands and shrublands worldwide. Proceedings of the National Academy of Sciences, 121(4), e2309881120.
-
Buras, A., Rammig, A., & Zang, C. S. (2020). Quantifying impacts of the 2018 drought on European ecosystems in comparison to 2003. Biogeosciences, 17(6), 1655-1672
-
Müller, L. M., & Bahn, M. (2022). Drought legacies and ecosystem responses to subsequent drought. Global Change Biology, 28(17), 5086-5103.
-
Pacione, M. (2003). Urban environmental quality and human wellbeing—a social geographical perspective. Landscape and urban planning, 65(1-2), 19-30.
-
Zhang, X., Chen, N., Sheng, H., Ip, C., Yang, L., Chen, Y., Sang, Z., Tadesse, T., Lim, T., Rajabifard, A., Bueti, C., Zeng, L., Wardlow, B., Wang, S., Tang, S., Xiong, Z., Li, D., & Niyogi, D. (2019). Urban drought challenges to 2030 sustainable development goals. The Science of the Total Environment: 693, 133536.
-
Pizzorni, M., Innocenti, A., & Tollin, N. (2024). Droughts and floods in a changing climate and implications for multi-hazard urban planning: A review. City and Environment Interactions, 24, 100169.
-
Haile, G. G., Tang, Q., Li, W., Liu, X., & Zhang, X. (2020). Drought: Progress in broadening its understanding. Wiley Interdisciplinary Reviews: Water, 7(2), e1407.
-
Lima, L. B., Franca Rocha, W. J. S., Souza, D. T. M., Lobão, J. S. B., de Santana, M. M. M., Cambui, E. C. B., & Vasconcelos, R. N. (2025). Urban Quality: A Remote-Sensing-Perspective Review. Urban Science, 9(2), 31.
-
Lee, A. C. K., Jordan, H. C., & Horsley, J. (2015). Value of urban green spaces in promoting healthy living and wellbeing: prospects for planning. Risk management and healthcare policy, 131-137.
-
Kruize, H., van der Vliet, N., Staatsen, B., Bell, R., Chiabai, A., Muiños, G., Higgins, S., Quiroga, S., Martinez-Juarez, P., Aberg Yngwe, M., Tsichlas, F., Karnaki, P., Lima, M. L., García de Jalón, S., Khan, M., Morris, G., & Stegeman, I. (2019). Urban Green Space: Creating a Triple Win for Environmental Sustainability, Health, and Health Equity through Behavior Change. International Journal of Environmental Research and Public Health, 16(22), 4403.
-
Huete, A., Didan, K., Miura, T., Rodriguez, E. P., Gao, X., & Ferreira, L. G. (2002). Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote sensing of environment, 83(1-2), 195-213.
-
Sobrino, J. A., Jiménez-Muñoz, J. C., & Paolini, L. (2004). Land surface temperature retrieval from LANDSAT TM 5. Remote Sensing of environment, 90(4), 434-440.
-
Mert, A., Tavuç, İ., Özdemir, S., & Ulusan, M. D. (2025). Future Responses of the Burdur Lake to Climate Change and Uncontrolled Exploitation. Journal of the Indian Society of Remote Sensing, 53(4), 1025-1036.
-
Özdemir, S., Özkan, K., & Mert, A. (2020). An ecological perspective on climate change scenarios. Biological Diversity and Conservation, 13(3), 361-371.
-
Famiglietti, J. S. (2014). The global groundwater crisis. Nature climate change, 4(11), 945-948.
-
Rodell, M., Velicogna, I., & Famiglietti, J. S. (2009). Satellite-based estimates of groundwater depletion in India. Nature, 460(7258), 999-1002.
-
Gao, B.-C. 1996. “NDWI – A Normalised Difference Water Index for Remote Sensing of Vegetation Liquid Water from Space.” Remote Sensing of Environment 58: 257–266.
-
Sun, H., Zhao, X., Chen, Y., Gong, A., & Yang, J. (2013). A new agricultural drought monitoring index combining MODIS NDWI and day–night land surface temperatures: A case study in China. International Journal of Remote Sensing, 34(24), 8986-9001.
-
Dickey, D. A., & Fuller, W. A. (1981). Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica: journal of the Econometric Society, 1057-1072.
-
Kwiatkowski, D., Phillips, P. C., Schmidt, P., & Shin, Y. (1992). Testing the null hypothesis of stationarity against the alternative of a unit root: How sure are we that economic time series have a unit root?. Journal of econometrics, 54(1-3), 159-178.
-
Granger, C. W. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica: journal of the Econometric Society, 424-438.