پژوهش‌های تغییرات آب و هوایی

پژوهش‌های تغییرات آب و هوایی

کمی‌سازی اثر خشکی زاینده رود بر تغییرات دمای سطح زمین و پوشش گیاهی مجاور آن طی 33 سال اخیر با استفاده از تصاویر ماهواره‌ای

نوع مقاله : مقاله پژوهشی

نویسندگان
محمد منصورمقدم 1
نگار نقی پور 2
مهرانگیز رضایی 3
ایمان روستا 4
1 کاندیدای دکتری سنجش‌ازدور، مرکز مطالعات سنجش‌ازدور و GIS، دانشگاه شهید بهشتی، تهران، ایران
2 کارشناس ارشد سنجش‌ازدور، گروه جغرافیا، دانشگاه یزد، یزد، ایران
3 استادیار جغرافیا و برنامه‌ریزی روستایی، گروه جغرافیا، دانشگاه یزد، یزد، ایران
4 دانشیار اقلیم‌شناسی، گروه جغرافیا، دانشگاه یزد، یزد، ایران
10.30488/ccr.2024.425449.1175
چکیده
پایش تغییرات آبی در سکونتگاه‌های انسانی و به ویژه روستایی به دلیل اهمیت و نقش حیاتی آن در پایداری و همچنین اثرگذاری آن بر محیط طبیعی روستا امری حیاتی است. پژوهش حاضر با بهره‌گیری از تصاویر چندطیفی و حرارتی لندست-5 و لندست-8 به بررسی اثر تغییرات حاصل از خشک شدن رودخانه زاینده‌رود بر دمای سطح زمین و پوشش گیاهی را در سال‌های 1990 تا 2023 پرداخته است. بدین منظور از دو شاخص تفاضلی نرمال شده آب (NDWI) و تفاضلی نرمال شده گیاه (NDVI)، دمای سطح زمین (LST) و هات اسپات (Hot Spot) استفاده و تغییرات آنها در سه سطح حریم رودخانه، محدوده یک کیلومتری رودخانه و سکونتگاه‌های روستایی بررسی شد. بر اساس نتایج، دو سال 2000 و 2008 به‌عنوان سال‌هایی که جریان رودخانه در آنها خشک‌تر از بقیه سال‌ها بوده شناسایی و سال‌های 1990، 2013، 2018، 2022 و 2023 نیز بعنوان سال‌های با جریان آب بیشتر شناسایی شدند. نتایج نشان داد در سال‌های خشک مقادیر NDWI و NDVI میل به مقادیر مثبت کوچک و در سال‌های تر میل به مقادیر منفی کوچکتر داشتند. همچنین سال‌های خشک دارای LST بیشتر بوده و مساحت بیشتری از کلاس‌های گرم دمایی را به خود اختصاص داده بودند. سال‌های خشک همچنین نسبت به سال‌های تر، دارای تعداد بیشتری از نقاط داغ نسبت به نقاط سرد بودند. نتایج حاصل از همبستگی بین پارامترها همچنین بیانگر ارتباط منفی بین LST با NDVI و NDWI در همه سال‌ها و ارتباط مثبت NDVI و NDWI در سال‌های خشک‌تر بود. همچنین همبستگی فاصله از رودخانه صرفا در سال 1990 با LST مثبت و با NDWI منفی و در زیر 100 متر معنادار بود. نتایج مطالعه حاضر به منزله زنگ خطری برای برنامه‌ریزی و مدیریت صحیح منابع آبی و رودخانه‌های کشور مفید است.
کلیدواژه‌ها
شاخص تفاضلی نرمال شده آب (NDWI)
شاخص تفاضلی نرمال شده پوشش گیاهی (NDVI)
دمای سطح زمین (LST)
زاینده رود
سنجش از دور
موضوعات

عنوان مقاله English

Quantifying the Zayandeh Rud River drying effects on land surface temperature and adjacent vegetation cover changes over the past 33 years using satellite images

نویسندگان English

Mohammad Mansourmoghaddam 1
Negar Naghipur 2
Mehrangiz Rezaei 3
Iman Rousta 4
1 1 PhD candidate in Remote Sensing, Center for Remote Sensing and GIS research, Shahid Beheshti University, Tehran Iran
2 M.Sc. in Remote Sensing and GIS, Department of Geography, Yazd University, Yazd, Iran
3 Assistant Professor of Rural Planning, Department of Geography, Yazd University, Yazd, Irann
4 Associate Professor of Climatology, Department of Geography, Yazd University, Yazd, Iran,
چکیده English

Monitoring of water changes in human settlements especially in rural areas is essential because of its importance and vital role in sustainability as well as its effect on the natural environment of the village. The current research has investigated the effects of the Zayandeh Rud River drying on the Land Surface Temperature (LST) and vegetation in the years 1990 to 2023 using Landsat-5 and Landsat-8 multispectral and thermal images. For this purpose, two indices of the Normalized Difference Water Index (NDWI) and Normalized Difference Vegetation Index (NDVI), together with LST, and Hot Spot were calculated, and their changes in three levels of the river, One-kilometer buffer from the river and rural settlements were investigated. Based on the results, the years 2000 and 2008 were identified as the years in which the river flow was drier than the other years, and the years 1990, 2013, 2018, 2022, and 2023 were identified as the years with more water flow. The results showed that in dry years, NDWI and NDVI values tended to have small positive values, and in wet years tended to have smaller negative values. Also, dry years had higher LST and occupied a larger area of warm temperature classes. Dry years also had more hot spots than cold spots compared to wet years. The results of the correlation between parameters also showed a negative relationship between LST and NDVI and NDWI in all years and a positive relationship between NDVI and NDWI in drier years. Also, the correlation of the distance from the river was only significant in 1990 and below 100 meters, positive with LST and negative with NDWI. The results of the present study are useful for the planning and proper management of water resources and rivers in Iran

کلیدواژه‌ها English

Normalized Difference Water Index (NDWI)
Normalized Difference Vegetation Index (NDVI)
Land Surface Temperature (LST)
Zayandeh Rud
Remote Sensing
  1. Agricultural Trade Union of Isfahan. (2013, 2013-12-30). Average annual rainfall in Kohrang from 1350 to 1390 (period of 40 years). Retrieved 2020-11-25 from https://web‌.‌‌org /web/20131230135439/http://www.nskesfahan.org/%D8%B2%D8%A7%DB%8C%D9% 86%D8%AF%D9%87-%D8%B1 %D9%88%D8%AF
  2. Avdan, U., & Jovanovska, G. (2016). Algorithm for automated mapping of land surface temperature using LANDSAT 8 satellite data. Journal of Sensors.
  3. Brown, J. (2018). NDVI, the Foundation for Remote Sensing Phenology. Retrieved 2023-10-27 from https:// www.usgs.gov/special-topics/remote-sensing-phenology/science/ndvi-foundation -remote-sensing-phenology # overview.
  4. Cai, Z., Han, G., & Chen, M. (2018). Do water bodies play an important role in the relationship between urban form and land surface temperature? Sustainable Cities and Society, 39, 487-498.
  5. Dos Santos, A.R., de Oliveira, F. S., da Silva, A. G., Gleriani, J. M., Gonçalves, W., Moreira, G. L., . . . da Silva, R. G. (2017). Spatial and temporal distribution of urban heat islands. Science of the Total Environment, 605, 946-956.
  6. (2021). Zayandeh Rood became "juicy" in the form of boils! Ensaf News. Retrieved 2023-11-02 from https://www.ensafnews.com/?p=335765
  7. (2021). Normalized Difference Water Index. Retrieved 2023-10-15 from https://eos.com/make-an-analysis/ndwi/
  8. (2022). NDVI: Normalized Difference Vegetation Index. Retrieved 2023-11-02 from https://eos.com/make-an-analysis/ndvi/
  9. (2021). Understanding Euclidean distance analysis. Retrieved from https://desktop.arcgis.com/en/arcmap/latest/tools/spatial-analyst-toolbox/understanding-euclidean-distance-analysis.htm#ESRI_SECTION1_ 29048F6D811 B40D0A0B7E2BA0F3 6E92E
  10. (2022). How Hot Spot Analysis (Getis-Ord Gi*) works. Retrieved 2022-0 from https://pro.arcgis.com /en/pro-app/latest/tool-reference /spatial-statistics/h-how-hot-spot-analysis-getis-ord-gi-spatial- stati.htm#:~:text =The%20 Hot% 20Spot%20 Analysis %20tool, the%20 context% 20of%20 neigh boring%20features.
  11. Guha, S., Govil, H., & Besoya, M. (2020). An investigation on seasonal variability between LST and NDWI in an urban environment using Landsat satellite data. Geomatics, Natural Hazards and Risk, 11(1), 1319-1345.
  12. Hereher, M. E. (2017). Effects of land use/cover change on regional land surface temperatures: severe warming from drying Toshka lakes, the Western Desert of Egypt. Natural Hazards, 88(3), 1789-1803.
  13. Hosseini hamid, M., & Akbarinasab, M. (2016). The Calculation of the Optimum Index Factor for Monitoring Water Resources pollution using Satellite Images: A Case Study of the Oman sea. Hydrophysics, 2(1), 35-45. https://www.hydrophysics.ir/article_ 24499_5577a3bc39e 187da63b35717977b24da.pdf
  14. (2011). NDWI: Normalized Difference Water Index. European Drought Observatory (EDO) Retrieved from https://edo.jrc.ec.europa.eu/documents/factsheets/factsheet_ndwi.pdf
  15. (2011). Slow death of a dream. Imna News. Retrieved 2023-10-28 from imna.ir/xfCM
  16. (2022). Releasing Zayandeh Rood water for the fourth time of irrigation. Imna News. Retrieved 2023-11-02 from imna.ir/x6SF7
  17. (2023). Zayandehroud reopening time 1402 + dam condition. Imna News. Retrieved 2023-11-02 from imna.ir/x7WJy
  18. Jafari, R., & Hasheminasab, S. (2017). Assessing the effects of dam building on land degradation in central Iran with Landsat LST and LULC time series. Environmental monitoring and assessment, 189, 1-15.
  19. Khorrambakht, A. (2016). Quantitative Analysis of the Role of Groundwater Qualityto Promote Rural Development IndicatorsBased on Morris Model Case Study: Khonj County. Physical Geography Quarterly, 9(32), 57-70. https://‌ larestan.‌iau.‌ir/article_ 528623_ a6da46495180 e7f17724 d1de9f09564c.pdf
  20. Kumar, D., Singh, A. K., Taloor, A. K., & Singh, D. S. (2021). Recessional pattern of Thelu and Swetvarn glaciers between 1968 and 2019, Bhagirathi basin, Garhwal Himalaya, India. Quaternary International, 575, 227-235.
  21. LANDSAT 8 data user's handbook. (2015). Department of the Interior US Geological Survey.
  22. Li, X., Zhou, Y., Asrar, G. R., Imhoff, M., & Li, X. (2017). The surface urban heat island response to urban expansion: A panel analysis for the conterminous United States. Science of the Total Environment, 605, 426-435.
  23. Mansourmoghaddam, M., Ghafarian Malamiri, H. R., Rousta, I., Olafsson, H., & Zhang, H. (2022). Assessment of Palm Jumeirah Island’s Construction Effects on the Surrounding Water Quality and Surface Temperatures during 2001–2020. Water, 14(4), 634.
  24. Mansourmoghaddam, M., Naghipur, N., Rousta, I., Alavipanah, S. K., Olafsson, H., & Ali, A. A. (2023). Quantifying the Effects of Green-Town Development on Land Surface Temperatures (LST)(A Case Study at Karizland (Karizboom), Yazd, Iran). Land, 12(4), 885.
  25. Mansourmoghaddam, M., Rousta, I., Cabral, P., Ali, A.A., Olafsson, H., Zhang, H., & Krzyszczak, J. (2023). Investigation and Prediction of the Land Use/Land Cover (LU/LC) and Land Surface Temperature (LST) Changes for Mashhad City in Iran during 1990–2030. Atmosphere, 14(4), 741.
  26. Mansourmoghaddam, M., Rousta, I., Zamani, M., Mokhtari, H., Karimi Firozjaei, M., & Alavipanah, S. K. (2021). Study and prediction of land surface temperature changes of Yazd city: assessing the proximity and changes of land cover. Journal of RS and GIS for Natural Resources, 12(4), 1-27.
  27. Mansourmoghaddam, M., Rousta, I., Zamani, M., & Olafsson, H. (2023). Investigating and predicting Land Surface Temperature (LST) based on remotely sensed data during 1987–2030 (A case study of Reykjavik city, Iceland). Urban Ecosystems, 1-23.
  28. Mansourmoghaddam, M., Rousta, I., Zamani, M. S., Mokhtari, M. H., Karimi Firozjaei, M., & Alavipanah, S. K. (2022). Investigating and Modeling the Effect of the Composition and Arrangement of the Landscapes of Yazd City on the Land Surface Temperature Using Machine Learning and Landsat-8 and Sentinel-2 Data. Iranian Journal of Remote Sensing & GIS, 15(3), 1-26.
  29. McFeeters, S. K. (1996). The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features. International Journal of remote sensing, 17(7), 1425-1432
  30. (2014). How did Zayandeh Rood dry up/ when multiple management dried up Zayandeh Rood. Mehr News. Retrieved 2023-10-28 from mehrnews.com /xqYnY.
  31. Module, F. (2009). Atmospheric correction module: QUAC and FLAASH user’s guide. Version, 4, 4.
  32. Ogashawara, I., & Bastos, V.D.S.B. (2012). A quantitative approach for analyzing the relationship between urban heat islands and land cover. Remote Sensing, 4(11), 3596-3618.
  33. Omute, P., Corner, R., & Awange, J.L. (2012). The use of NDVI and its derivatives for monitoring Lake Victoria’s water level and drought conditions. Water resources management, 26, 1591-1613.
  34. Ord, J. K., & Getis, A. (1995). Local spatial autocorrelation statistics: distributional issues and an application. Geographical analysis, 27(4), 286-306.
  35. Rahmani Fazli, A., & Salehian, S. (2018). Investigating the Relationship between the Spreading of Human Settlements and Instability of Agricultural Water resources in the Zayandeh-Rud Basin. Town and Country Planning, 10(1), 167-192. https://doi.‌org/ 10.22059/ jtcp.2018. 257200.669865
  36. Rizvi, R. H., Yadav, R. S., Singh, R., Datt, K., Khan, I., & Dhyani, S. (2009). Spectral analysis of remote sensing image for assessment of agroforestry areas in Yamunanagar district of Haryana. National Symposium on “Advances in Geo-spatial Technologies with Special Emphasis on Sustainable Rainfed Agriculture”, RRSSC.
  37. Rousta, I., Olafsson, H., Nasserzadeh, M. H., Zhang, H., Krzyszczak, J., & Baranowski, P. (2021). Dynamics of daytime land surface temperature (LST) variabilities in the Middle East countries during 2001–2018. Pure and Applied Geophysics, 178(6), 2357-2377.
  38. Rousta, I., Olafsson, H., Zhang, H., Moniruzzaman, M., Baranowski, P., & Krzyszczak, J. Anthropogenic factors affecting the vegetation dynamics in the arid Middle East. Environmental and Climate Technologies, 26(1), 774-805.
  39. Salehian, S., & Rahmani Fazli, A. (2018). Environmental Consequences of Water Resources Instability in the Zayandeh-Rud Basin. Physical Geography Research Quarterly, 50(2), 391-406.
  40. Sarkar, T., Kannaujiya, S., Taloor, A. K., Ray, P. K. C., & Chauhan, P. (2020). Integrated study of GRACE data derived interannual groundwater storage variability over water stressed Indian regions. Groundwater for sustainable development, 10, 100376.
  41. Siqi, J., & Yuhong, W. (2020). Effects of land use and land cover pattern on urban temperature variations: A case study in Hong Kong. Urban Climate, 34, 100693.
  42. Sun, D., & Kafatos, M. (2007). Note on the NDVI‐LST relationship and the use of temperature‐related drought indices over North America. Geophysical Research Letters, 34.
  43. (2018). Zayandeh Rood. Tabnak News. Retrieved 2023-10-28 from https://www.tabnak.ir /fa/tags/2852 /32/%D8%B2%D8%A7%DB%8C%D9%86%D8%AF%D9%87-%D8%B1% D9%88%D8%AF
  44. Taloor, A. K., Manhas, D. S., & Kothyari, G. C. (2021). Retrieval of land surface temperature, normalized difference moisture index, normalized difference water index of the Ravi basin using Landsat data. Applied Computing and Geosciences, 9, 100051.
  45. (2013). The Zayandeh Road series started with political conflicts and ended with the tired hands of farmers. Tasnim News. Retrieved 2023-11-02 from https://tn.ai/100972
  46. (2018a). The thirsty gardens of Isfahan are watered; Release of 30 million cubic meters of water in Zayandeh Rood. Tasnim News. Retrieved 2023-11-02 from https://tn.ai/1791014
  47. (2018b). Water flowing in Zayandeh Rood. Tasnim News. Retrieved 2023-10-28 from https://tn.‌ai /1934716
  48. (2014). OLI and TIRS Calibration Notices. In Landsat 8 Reprocessing to Begin February 3, 2014.
  49. Yue, W., Xu, J., Tan, W., & Xu, L. (2007). The relationship between land surface temperature and NDVI with remote sensing: application to Shanghai Landsat 7 ETM+ data. International Journal of remote sensing, 28(15), 3205-3226.
  50. Ziaul, S., & Pal, S. (2016). Image based surface temperature extraction and trend detection in an urban area of West Bengal, India. Journal of Environmental Geography, 9(3-4), 13-25.