Monitoring environmental changes in the Bakhtegan Basin based on analysis of daily and nighttime LST trends using MODIS-Aqua

Document Type : Research Article

Author

Associate Professor, Department of Physical Geography, University of Isfahan, Isfahan, Iran

Abstract

Environmental changes, driven by both natural and human factors, rank among the most significant challenges of the current century. Due to its high sensitivity to fluctuations in water resources, vegetation, and land use, Land Surface Temperature (LST) serves as an effective indicator for monitoring environmental changes. This study aimed to investigate and monitor environmental changes in the Maharloo-Bakhtegan watershed based on LST temporal trends. To this end, daily and nighttime LST data from the MODIS/Aqua sensor were utilized for the period spanning 2002 to 2020. LST trends were analyzed on a pixel-by-pixel basis using the non-parametric Mann-Kendall test at a 95% confidence level, and the magnitude of these trends was estimated using Sen’s slope estimator. The results indicated that the spatial patterns of LST trends effectively reflect environmental changes across the basin. Daytime LST was primarily influenced by topography and elevation, whereas nighttime LST variations showed a stronger correlation with the status of water bodies, soil moisture, and land-use changes. Increasing trends in daytime LST—at an average rate of approximately 0.4°C—were observed mainly in dried-up water bodies and wetlands (including Lakes Bakhtegan, Tashk, Maharlu, and Kaftar) as well as along the Shadkam River. These trends reflect the consequences of water scarcity, reduced surface runoff, and declining soil moisture. Conversely, downward trends in nighttime LST—at a rate of approximately 0.2°C—were identified in parts of these regions, linked to the drying up of water sources and the subsequent changes in their thermal regimes. Furthermore, upward trends in nighttime LST—averaging approximately 0.1°C—were observed in the city of Shiraz, the agricultural lands upstream and downstream of the Doroodzan Dam, and the vicinity of the Molasadra Dam. These patterns align with the expansion of human activities, agricultural development, and the formation of urban heat islands.

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References (in Persian)
Bagheri, M. H.; Bagheri, A. and Sahouli, Gh. A.  2016, Analysis of changes in the Bakhtegan lake water body under the influence of natural and human factors. Iran-Water Resources Research, Volume 12, Issue 3, Number 37,1-11. https://www.iwrr.ir/article_41333.html. [In Persian]
Iran Water Resources Management Company. 2012, Guidelines and criteria for the division and coding of watersheds and study areas at the national level. No, 310. [In Persian]
ertdhk, B., Khan-Ahmadi-Bafghi, H., & Daneshkar-Arasateh, P. 2021, Forecasting the Area of the Bakhtegan and Tashk Lake Using Remote Sensing and Climatic Factors. Iran-Water Resources Research. Volume 17, Issue 1, 56, 151-165. doi: 20.1001.1.17352347.1400.17.1.9.0. [In Persian]
Torabi, Gh., Aghamohammadi Zanjirabad, H., & Behzadi, S. 2018, Monitoring the status of Bakhtegan Lake and surrounding areas using satellite imagery and computational intelligence. Ecohydrology, Volume 5, Issue 1, 251-263. doi: 10.22059/ije.2018.244595.767. [In Persian]
References (in English)
Ayenew, T. 2004, Environmental implications of changes in the levels of lakes in the Ethiopian Rift. Regional Environmental Change, 4(4), 192–204. https://doi.org/10.1007/s10113-004-0083-x
Du, C., Ren, H., Qin, Q., Meng, J., & Zhao, S. 2015, A practical split-window algorithm for estimating land surface temperature from Landsat 8 data. Remote Sensing, 7(1), 647-665.‏ https://doi.org/10.3390/rs70100647
Firoozi, F., Mahmoudi, P., Jahanshahi, S. M. A., Tavousi, T., Liu, Y., & Liang, Z. 2020, Modeling changes trend of time series of land surface temperature (LST) using satellite remote sensing productions (case study: Sistan plain in east of Iran). Arabian Journal of Geosciences, 13(10), 367.‏ https://doi.org/10.1007/s12517-020-05314-w
Han, Y., Huang, B., & Gao, H. 2024, Constructing a High Temporal Resolution Global Lakes Dataset via Swin-Unet with Applications to Area Prediction. arXiv preprint arXiv:2408.10821. https://doi.org/10.48550/arXiv.2408.10821
Hojabri, J., & Aydin, Y. 2025, Spatio-temporal Dynamics of Land Surface Temperature and Land Use and Land Cover Changes in the Urmia Lake Basin: Exploring Land-Atmosphere Interactions Through Satellite Data and Ground Observations (2000–2023). Earth Systems and Environment, 1-20. https://doi.org/10.1007/s41748-025-00808-7
Lian, D., Yuan, B., Li, X., Shi, Z., Ma, Q., Hu, T., ... & Liu, Y. 2024, The contrasting trend of global urbanization-induced impacts on day and night land surface temperature from a time-series perspective. Sustainable Cities and Society, 109, 105521.‏ https://doi.org/10.1016/j.scs.2024.105521
Lillesand, T., Kiefer, R. W., & Chipman, J. 2015, Remote sensing and image interpretation. John Wiley & Sons.‏
Logan, T. M., Zaitchik, B., Guikema, S., & Nisbet, A. 2020, Night and day: The influence and relative importance of urban characteristics on remotely sensed land surface temperature. Remote Sensing of Environment, 247, 111861.‏ doi:10.1016/j.rse.2020.111861
Lu, Z., Chen, Z., Zhou, M., Lei, D., & Chen, Y. 2025, Spatiotemporal patterns of water and vegetation in Poyang Lake from 2013 to 2021 using remote sensing data. Plos one, 20(7), e0327579.‏ https://doi.org/10.1371/journal.pone.0327579
Mashala, M. J., Dube, T., Mudereri, B. T., Ayisi, K. K., & Ramudzuli, M. R. 2023, A systematic review on advancements in remote sensing for assessing and monitoring land use and land cover changes impacts on surface water resources in semi-arid tropical environments. Remote Sensing, 15(16), 3926.‏ https://doi.org/10.3390/rs15163926
Mozafari, M., Hosseini, Z., Fijani, E., Eskandari, R., Siahpoush, S., & Ghader, F. 2022, Effects of climate change and human activity on lake drying in Bakhtegan Basin, southwest Iran. Sustainable Water Resources Management, 8(4), 109.‏ https://doi.org/10.1007/s40899-022-00707-z
Nasiri, A., Khosravian, M., Zandi, R., Entezari, A., & Baaghide, M. 2023, Monitoring the physical changes of lakes Bakhtegan and Tashk through land surface temperature and groundwater-level changes using remote-sensing technology. Environmental Earth Sciences, 82(19), 454.‏ https://doi.org/10.1007/s12665-023-11117-5
Nasiri, A., Khosravian, M., Zandi, R., Entezari, A., & Baaghide, M. 2023, Analysis of physical changes in Fars province water zones related to climatic parameters using remote sensing, Bakhtegan, Tashk, Iran. The Egyptian Journal of Remote Sensing and Space Sciences, 26(3), 851-861.‏ https://doi.org/10.1016/j.ejrs.2023.09.003
‏Nwilo, P., Umar, A., Adepoju, M., & Okolie, C. 2019, Spatio-temporal assessment of changing land surface temperature and depleting water in the Lake Chad area. South African Journal of Geomatics, 8(2), 144-159. doi: 10.4314/sajg.v8i2.3
Pekel, J. F., Cottam, A., Gorelick, N., & Belward, A. S. 2016, High-resolution mapping of global surface water and its long-term changes. Nature, 540(7633), 418-422.‏ https://doi.org/10.1038/nature20584
Rahimabadi, P. D., Liu, B., Azarnivand, H., Malekian, A., & Damaneh, H. E. 2024, The nexus between land use/cover changes and land surface temperature: Remote sensing-based two-decadal analysis in Tashk–Bakhtegan–Maharloo basin. Journal of Arid Environments, 225, 105269.  https://doi.org/10.1016/j.jaridenv.2024.105269
‏Shakiba, F., Rousta, I., Mazidi, A., & Olafsson, H. 2024, Spatial and temporal variation of daytime and nighttime land surface temperature and its drivers over Iran’s watersheds using remote sensing. Earth Science Informatics, 17(4), 3567-3587.‏ doi:10.1007/s12145-024-01344-0
Shi, K., Zhang, Y., Zhu, G., Qin, B., & Pan, D. 2018, Deteriorating water clarity in shallow waters: Evidence from long-term MODIS and in-situ observations. International journal of applied earth observation and geoinformation, 68, 287-297. https://doi.org/10.1016/j.jag.2017.12.015
‏Shi, W., & Wang, M. 2015, Decadal changes of water properties in the Aral Sea observed by MODIS‐Aqua. Journal of Geophysical Research: Oceans, 120(7), 4687-4708. https://doi.org/10.22059/jesphys.2021.323427.1007318
Smith, A. M., Wooster, M. J., Drake, N. A., Dipotso, F. M., Falkowski, M. J., & Hudak, A. T. 2005, Testing the potential of multi-spectral remote sensing for retrospectively estimating fire severity in African Savannahs. Remote sensing of environment, 97(1), 92-115. https://doi.org/10.1016/j.rse.2005.04.014
Weng, Q., Lu, D., & Schubring, J. 2004, Estimation of land surface temperature–vegetation abundance relationship for urban heat island studies. Remote Sensing of Environment, 89(4), 467-483. https://doi.org/10.1016/j.rse.2003.11.005.

Articles in Press, Accepted Manuscript
Available Online from 10 August 2026
  • Receive Date: 20 June 2026
  • Revise Date: 27 July 2026
  • Accept Date: 10 August 2026
  • First Publish Date: 10 August 2026
  • Publish Date: 10 August 2026