مطالعه و پایش تغییرات سطح آب و تأثیر آن بر دمای سطح تالاب با استفاده از شاخص های NDWI، MNDWI و AWEI (مطالعه موردی: تالاب های شادگان و هورالعظیم)

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی کارشناسی ارشد مهندسی و مدیریت منابع آب، دانشکده مهندسی عمران، دانشگاه صنعتی جندی شاپور دزفول.

2 استادیار گروه عمران آب، دانشکده مهندسی عمران، دانشگاه صنعتی جندی شاپور دزفول

3 دانشجوی دکتری سنجش از دور دانشگاه تهران.

چکیده

پایش و حفاظت از تالاب­ها به­دلیل نقش مهم این منابع در حفظ اکوسیستم و تامین نیازهای افتصادی و اجتماعی جوامع بشری امری لازم و ضروری می­باشد. در این تحقیق با استفاده از سه شاخص NDWI، MNDWI و AWEI میزان سطح تالاب­های هورالعظیم و شادگان واقع در استان خوزستان در بازه زمانی 1397- 1378 مورد بررسی قرار گرفت. پس از فرایند پیش­پردازش بر روی تصاویر لندست، برپایه 200 نقطه تعلیمی حد آستانه هر شاخص در شناسایی سطح تالاب­ها تعیین گردید که با توجه به دقت کلی 5/95 درصد و ضریب کاپای 91 درصد، شاخص MNDWI نسبت به دو شاخص NDWI و AWEI از کارایی بهتر و دقت بالاتری برخوردار است. مساحت تالاب­ها برای ماه­های فروردین، شهریور و دی­ماه در هر سال که معرف تغییرات حجم آب ورودی به تالاب­ها هستند، با استفاده از شاخص­ MNDWI محاسبه شد. بررسی روند تغییرات سطح تالاب­ها با استفاده از آزمون من-کندال نیز نشان داد که میزان تغییر مساحت تالاب­ها در سطح اطمینان 95 درصد دارای روند معنی­دار نیست. این موضوع بیانگر تأثیر دخالت انسان در تنظیم میزان جریان ورودی به این تالاب­ها توسط سدهای بالادست به­خصوص در زمان خشک­سالی و سیلاب می­باشد. به­طوری­که بیشترین تغییرات مربوط به ماه فروردین و کمترین آن در ماه شهریور اتفاق افتاده است. هم­چنین بررسی همبستگی تغییرات دمایی تالاب­ها با تغییر مساحت­ها نشان داد که به­طور متوسط به ازای تغییر هر 1000 هکتار از مساحت تالاب­های هورالعظیم و شادگان میزان دما 4/0± درجه سلسیوس تغییر می­کند.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Study and monitoring of wetland area changes and its impact on wetland surface temperature using NDWI, MNDWI, and AWEI indices (case study: Hor-alazim and Shadegan wetlands)

نویسندگان [English]

  • Khadijeh Amiri 1
  • Hesam Seyed kaboli 2
  • Farhad Mahmoodi-kohan 3
1 M.S. Student of Water Resource Management and Engineering, Faculty of Civil Engineering, Jundi-Shapur University of Technology, Dezful.
2 Assistant professor, Faculty of Civil Engineering, Jundi-Shapur University of Technology, Dezful
3 Ph.D. Candidate of Remote Sensing, University of Tehran.
چکیده [English]

Monitoring and conservation of the wetlands are very important due to their role in eco-system protection and providing the socio-economic needs of the local community. Sarp and Ozcelik (2017); Nandi et. al. (2018); Ali et. al. (2019) used NDWI, MNDWI and AWEI indices to monitor waterbodies changes based on Landsat (ETM+, OLI) dataset. In this study, these indices were applied to monitor area changes of Hor-alazim and Shadegan wetlands in Khuzestan province that were selected as case study areas for period 2000-2018. Wetlans area changes were evaluated for three months, include April, September, and January in any year that represent inflow changes. Mann-Kendall statistics was also used to study the changes in a wetlands area. The  MNDWI index in comparison to NDWI and AWEI has better performance and higher accuracy. The results of Man-Kendall statistics showed that wetlands area changes have no significance relation in 95% confident level. Also, the correlation between temperature and wetland area changes showed that on average, the wetlands temperature changes by ±0.4 C for per 1000-hectare area change.

کلیدواژه‌ها [English]

  • Remote sensing
  • Spectral index
  • Water bodies
  • Mann-Kendall
  • Kappa coecifient
  • Alavipanah, S., Ehsani, A.H. and Omidi, P., 2004. Study of desertification and changes of damghan playa lands using multy specteral and multy temporal data. Journal of Desert (Biaban),9(1), pp.143-154. (In Persian).

 

  • Alesheikh, A., Alimohammadi, A. and Ghorbamali, A., 2011. Uromiyeh lake shoreline change monitoring using remote sensing data. Journal of Geographical Sciences, 4(5), pp. 9-24. (In Persian).

 

  • Ali, M.I., Dirawan, G.D., Hasim, A.H. and Abidin, M.R., 2019. Detection of changes in surface water bodies urban area with ndwi and mndwi methods. International Journal on Advanced Science Engineering Informatioan Technology, 9(3), pp.946-951.

 

  • Arekhi, S. and Niazi, Y., 2010. Assessing different remote sensing techniques to detect land use changes (case study in Dareshahr, Ilam province). Iranian Journal of Range and Desert Research, 17(1), pp.74-93. (In Persian).

 

  • Bastawesy, M.A., Khalaf, F.I. and Arafat, S.M., 2008. The use of remote sensing and GIS for the estimation of water loss from Tushka lakes, southwestern desert, Egypt. Journal of African Earth Sciences, 52(3), pp.73-80.

 

  • Blackmore, D.S., 2016. Use of water indices derived from Landsat OLI imagery and GIS to estimate the hydrologic connectivity of wetlands in the Tualatin river national wildlife refuge (Doctoral dissertation, Portland State University), pp.98-102.

 

  • Bradley, A.P., 1997. The use of the area under the ROC curve in the evaluation of machine learning algorithms. Pattern Recognition, 30(7), pp.1145-1159.

 

  • Campos, J.C., Sillero, N. and Brito, J.C., 2012. Normalized difference water indexes have dissimilar performances in detecting seasonal and permanent water in the Sahara–Sahel transition zone. Journal of Hydrology, 464, pp.438-446.

 

  • Chen, Y.N., Li, W.H., Xu, C.C. and Hao, X.M., 2007. Effects of climate change on water resources in Tarim river basin, northwest China. Journal of Environmental Sciences, 19(4), pp.488-493.

 

  • Cheraghi, M., Aspergham, O. and Nouraei, M.H., 2013. Investigation of wetlands instability in Iran. In first congress of wetlands conservation and aquatics of Iran, Hamandishan mohite ziste farda Corporation, Hamedan, pp.3-6. (In Persian).

 

  • Du, Z., Bin, L., Ling, F., Li, W., Tian, W., Wang, H., Gui, Y., Sun, B. and Zhang, X., 2012. Estimating surface water area changes using time-series Landsat data in the Qingjiang River Basin, China. Journal of Applied Remote Sensing, 6(1), p.063609.

 

  • Fatemi, S.B. and Rezaei, Y., 2012. Remote Sensing Foundations. 3nd ed. Tehran. pp.184-185. (In Persian).

 

  • Feyisa, G.L., Meilby, H., Fensholt, R. and Proud, S.R., 2014. Automated water extraction index: A new technique for surface water mapping using Landsat imagery. Remote Sensing of Environment, 140, pp.23-35.

 

  • Gautam, V.K., Gaurav, P.K., Murugan, P. and Annadurai, M., 2015. Assessment of surface water Dynamicsin Bangalore using WRI, NDWI, MNDWI, supervised classification and KT transformation. Aquatic Procedia, 4, pp.739-746.

 

  • Ghosh, M.K., Kumar, L. and Roy, C., 2015. Monitoring the coastline change of Hatiya Island in Bangladesh using remote sensing techniques. ISPRS Journal of Photogrammetry and Remote Sensing, 101(1), pp.137-144.

 

  • Hobbins, M.T., Ramírez, J.A., Brown, T.C. and Claessens, L.H., 2001. The complementary relationship in estimation of regional evapotranspiration: The complementary relationship areal evapotranspiration and advection‐aridity models. Water Resources Research, 37(5), pp.1367-1387.

 

  • Ji, L., Zhang, L. and Wylie, B., 2009. Analysis of dynamic thresholds for the normalized difference water index. Photogrammetric Engineering & Remote Sensing, 75(11), pp.1307-1317.

 

  • Jiang, W., He, G., Long, T., Ni, Y., Liu, H., Peng, Y., Lv, K. and Wang, G., 2018. Multilayer perceptron neural network for surface water extraction in Landsat 8 OLI satellite images. Remote Sensing, 10(5), pp.755.

 

  • Kohshahi, R., Kaka Shadedi, H., Darabi, S. and Soleimani, k., 2015. Water bodies maps provide by using landsat 8 and NDWI & MNDWI Case study: (Maharlo lake, Fars Province, education and research group of Barvar Gostare Pars Farhangian university, Golestan Provinc., pp.3-6. (In Persian).

 

  • Kumar, R., Pandey, P.C., Maharana, P., Gautam, H. and Pandey, V.K., 2019. Assessing the Impacts of Temperature, Precipitation and Land Use Change on Open Water Bodies of Middle Ghaghara River Basin. In Water Conservation, Recycling and Reuse: Issues and Challenges (pp. 185-202). Springer, Singapore.

 

  • Liu, F., Zhang, H., Qin, Y., Dong, J., Xu, E., Yang, Y., Zhang, G. and Xiao, X., 2016. Semi-natural areas of Tarim basin in northwest China: Linkage to desertification. Science of The Total Environment, 573, pp.178-188.

 

  • 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), pp.1425-1432.

 

  • Mishra, K. and Prasad, P., 2015. Automatic extraction of water bodies from Landsat imagery using perceptron model. Journal of Computational Environmental Sciences, pp.2-6.

 

  • Mozafari, G.A. and Narangifard, M., 2014. The study of rainfall impact on Maharlou lake water surface change using remote sensing data. Wetland Ecobiology. 6 (1), pp.73-82. (In Persian).

 

  • Mustapha, A., 2013. Detecting surface water quality trends using Mann-Kendall tests and Sen’s slope estimates. International Journal of Agriculture Innovations and Research, 1, pp.108-114.

 

  • Nandi, D., Chowdhury, R., Mohapatra, J., Mohanta, K. and Ray, D., 2018. Automatic delineation of water bodies using multiple spectral indices. International Journal of Scientific Research in Science, Engineering and Technology, 4 ,pp.498-510.

 

  • Otsu, N., 1979. A threshold selection method from gray-level histograms. IEEE Transactions on Systems, Man, and Cybernetics, 9(1), pp.62-66.

 

  • Razmi, M., Mohammad, A.H., Dadollahi, S.A., Nazemosadat, S. and Khazaei, S. 2017. Evaluation of the optimum index and mndwi in examining coastline changes in the northern persian Gulf (Case study: Dayyer). Journal of RS and GIS for Natural Resources 1(26), pp.52-65. (In Persian).

 

  • Rezaei, B.M., Rostamzadeh, H. and Feyzzadeh, B., 2008. The study and evaluation of the trend of forest surface changes using the remote sensing and Gis: A case study of arasbaran forests (1987-2005). Journal of Geographical Research Quarterly, 39(62), pp.143-159. (In Persian).

 

  • Rokni, K., Ahmad, A., Selamat, A. and Hazini, S., 2014. Water feature extraction and change detection using multitemporal Landsat imagery. Remote Sensing, 6(5), pp.4173-4189.

 

  • Sarp, G. and Ozcelik, M., 2017. Water body extraction and change detection using time series: A case study of Lake Burdur, Turkey. Journal of Taibah University for Science, 11(3), pp.381-391.

 

  • Tilahun, A. and Teferie, B., 2015. Accuracy assessment of land use land cover classification using google earth. American Journal of Environmental Protection, 4(4), pp.193-198.

 

  • Xu, H., 2006. Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery. International journal of Remote Sensing, 27(14), pp.3025-3033.

 

  • Zamani, R., Mirabbasi, R., Abdollahi, S. and Jhajharia, D., 2017. Streamflow trend analysis by considering autocorrelation structure, long-term persistence, and Hurst coefficient in a semi-arid region of Iran. Theoretical and Applied Climatology, 129(1-2), pp.33-45.

 

  • Yu, S., Sun, L., Sun, Z. and Wu, M., 2016, July. Water body extraction and change analysis based on landsat image in Xinjiang coal-mining regions. In 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) (pp. 6229-6232). IEEE.