Qualitative evaluation of surface water resources using satellite images in Seymareh dam reservoir

Document Type : Research Article


1 University of Tehran

2 Associate Professor, Faculty of New Sciences & Technologies, University of Tehran


Due to the advances made in remote sensing technology, collecting information on the quality of surface water resources by this technology, while reducing the cost and time of traditional sampling, can cover all surface water areas. To monitor. In this study, the capability of Sentinel-2 and Landsat-8 satellite images to estimate the concentration of water quality parameters including acidity, electrical conductivity, total soluble solids, alkalinity and surface water temperature were investigated. First, the Sentinel-2 and Landsat-8 satellite images were pre-processed and then the appropriate bands were determined to identify a significant relationship between the values of each water quality parameter and the images were determined using linear regression and their accuracy was calculated for the actual values. The results show the superiority of Sentinel-2 images with Pearson coefficient, standard error and RMSe for PH parameter equal to 0.58, 0.28 and 0.29, EC equal to 0.847, 78.7 and 77.22, TDS equal to 0.895, 45.8 and 44.37 and for the alkalinity parameter only through Landsat-8 images with Pearson coefficient, standard error and RMSe equal to 0.473, 22 and 21.8, respectively. Both satellite images can be used for the water surface temperature parameter due to the high Pearson coefficient. These values are 0.871, 2.9 and 2.85 for Landsat-8 and 0.752 for Sentinel-2, respectively. 0, 14.4 and 4.06.


Main Subjects

  • کابلی زاده، م.، ک. رنگزن. و ش. محمدی.1397. کاربرد تلفیق تصاویر ماهواره ای لندست-8 و سنتینل-2 در پایش محیطی. نشریه سنجش از دور و سامانه اطلاعات جغرافیایی در منابع طبیعی (کاربرد سنجش ازدور و GIS منابع طبیعی).9(3): 71-53.
  • میر علیزاده فر، س.ر. و ش. منصوری. ارزیابی شاخصهای سنجش از دور در مطالعات کمی و کیفی آب‎های سطحی با تصاویر ماهوارهای لندست-8 (مطالعه موردی: جنوب استان خوزستان). نشریه سنجش از دور و سامانه اطلاعات جغرافیایی در منابع طبیعی (کاربرد سنجش ازدور و GIS منابع طبیعی). 10(2): 84-63.
  • مومی‏پور، م.1395. مطالعه کیفیت آب‎های ساحلی با تصاویر ماهواره ای فراطیفیHyperion - (مطالعه موردی: ساحل اروندکنار). مجله علوم و فنون دریایی، 15(1): 120-111.
  • محوی ا. جنبه های بهداشتی و زیبایی شناسی کیفیت آب. انتشارات بال گستر; 1375.
  • اسکندری‏ مکوند م. نگرشی بر جوانب بهداشتی آب. عرش اندیشه; 1384. 276
  • فتاحی‎مقدم, م. 1390. ارزیابی قابلیت سنجده هایپریون، فیلداسپک 3 و داده‎های زمینی برای برآورد پارامترهای کیفیت آب در رودخانه کارون مقطع شهر اهواز، پایان‎نامه کارشناسی ارشد، دانشگاه شهید چمران اهواز، دانشکده علوم زمین، گرایش سنجش از دور و اطلاعات جغرافیایی.
  • حسین‎زاده, م. صابری، ع., صفرنژادی، غ., احمدی قراگزلو، رشید. برآورد پارامترهای کیفی آب با استفاده از الگوریتم بهینه سازی pso و سنجش از دور (تصاویر ماهواره,(SENTINEL-2 یازدهمین سمینار بین المللی مهندسی رودخانه. بهمن 1397.
  • Su T-C, Chou H-T. 2015. Application of multispectral sensors carried on unmanned aerial vehicle (UAV) to trophic state mapping of small reservoirs: a case study of Tain-Pu reservoir in Kinmen, Taiwan. Remote Sensing, 7(8): 10078-10097.
  • Chen Q, Wu W, Blanckaert K, Ma J, Huang G. 2012. Optimization of water quality monitoring network in a large river by combining measurements, a numerical model and matterelement analyses. Journal of Environmental Management, 110: 116-124.
  • Liu H, Li Q, Shi T, Hu S, Wu G, Zhou Q. 2017. Application of sentinel 2 MSI images to retrieve suspended particulate matter concentrations in Poyang Lake. Remote Sensing, 9(7): 761-783.
  • Zheng G, DiGiacomo PM. 2017. Uncertainties and applications of satellite-derived coastal water quality products. Progress in Oceanography, 159:45-72.
  • Postel,S., The Last Oasis: Facing Water Scarcity: Routledge, 2014.
  • Viessman, W., Hammer, M. J.E. M. Perez, and P. A. Chadik, “Water Supply and Pollution Control,” 1998.
  • Sowers, J.,Vengosh, A. and Weinthal, E. “Climate Change, Water Resources, and the Politics of Adaptation in the Middle East and North Africa,” Climatic Change, 104, 2011, pp. 599-627.
  • Glasgow, H.B., Burkholder, J.M.,Reed, R.E., Lewitus, A.J. and Kleinman, J.E., “Real-Time Remote Monitoring of Water Quality: A Review of Current Applications, and Advancements in Sensor, Telemetry, and Computing Technologies,” Journal of Experimental MarineBiology and Ecology, vol. 300, 2004, pp. 409-448.
  • Gorchev, H.G., Ozolins, G., “Who Guidelines for Drinking-Water Quality,” WHO Chronicle, vol. 38,No. 3, 2011, pp. 104-108.
  • Chang, N.-B., Imen, S. and Vannah, B., “Remote Sensing for Monitoring Surface Water Quality Status and Ecosystem State in Relation to The Nutrient Cycle: A 40-Year Perspective,” Critical Reviews in Environmental Science and Technology, vol. 45, 2015, pp. 101-166.
  • Xiao X, Jian X, Xiongfei W, Chengfang H, Xuejun C, Zhaohui W, Dengzhong Z. 2015. Evaluation Method of Water Quality for River Based on Multi-Spectral Remote Sensing Data. In: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-7/W3, 2015. 36th International Symposium on Remote Sensing of Environment, 11–15 May 2015, Berlin, Germany. 1517-1523.
  • Clay Barrett D, Frazier A. 2016. Automated method for monitoring water quality using Landsat imagery. Water, 8(6): 257-269.
  • Toming K, Kutser T, Laas A, Sepp M, Paavel B,Nõges T. 2016. First experiences in mapping lake water quality parameters with Sentinel-2 MSI imagery. Remote sensing, 8(8): 640-658.
  • Ritchie JC, Cooper CM. Remote sensing techniques for determining water quality: Applications to TMDLs. TMDL Sci Issues Conf (2001), Water Environ Fed Alexandria, VA. 2001;367–74.
  • Jerry C, R. FS. Monitoring suspended sediments with remote sensing techniques. Hydrol Appl Sp Technol. 1986;(160):233–43.


  • Ritchie JC, Schiebe FR, McHenry JR. Remote sensing of suspended sediments in surface waters. Photogramm Eng Remote Sensing. 1976;42(12):1539–45.
  • Liversedge.Turbidity Mapping and Prediction in Ice Marginal Lakes At the Bering Glasier System, Alaska. university of Michigan; 2007.
  • Song K. Water quality monitoring using Landsat Themate Mapper data with empirical algorithms in Chagan Lake, China. J Appl Remote Sens. 2011;5(1):053506.
  • Song K, Li L, Li S, Tedesco L, Hall B, Li L. Hyperspectral remote sensing of total phosphorus (TP) in three central Indiana water supply reservoirs. Water Air Soil Pollut. 2012;223(4):1481–502.
  • Liu J, Zhang Y, Yuan D, Song X. Empirical estimation of total nitrogen and total phosphorus concentration of urban water bodies in china using high resolution IKONOS multispectral imagery. Water (Switzerland). 2015;7(11):6551–73.
  • Kutser T, Paavel B, Verpoorter C, Ligi M, Soomets T, Toming K, et al. Remote sensing of black lakes and using 810 nm reflectance peak for retrieving water quality parameters of optically complex waters. Remote Sens. 2016;8(6).
  • Giardino C, Bresciani M, Fava F, Matta E, Brando VE, Colombo R. Mapping submerged habitats and mangroves of Lampi Island Marine National Park (Myanmar) from in situ and satellite observations. Remote Sens. 2016;8(1):1–13.
  • Xie H, Tong X, Qiu Y, Zhang H, Zhao J.
    Remote sensing based water quality monitoring and spatial-temporal analysis in Huangpu River, Shanghai. Int Geosci Remote Sens Symp. 2006;1447–50.
  • Bande, Prosper, Elhadi Adam, Mohamed A M Abd Elbasit, and Samuel Adelabu. 2018. “COMPARING LANDSAT 8 AND SENTINEL-2 IN MAPPING WATER QUALITY AT VAAL DAM 1. School of Geography , Archaeology and Environmental Science , University of Witwatersrand , Johannesburg , South Africa 2. Agricultural Research Council – Institute for Soil , Cl.” (July): 9280–83.
  • Masocha, Mhosisi, Chipo Mungenge, and Tamuka Nhiwatiwa. 2018. “Remote Sensing of Nutrients in a Subtropical African Reservoir: Testing Utility of Landsat 8.” Geocarto International 33(5): 458–69.http://dx.doi.org/10.1080/10106049.2016.1265596.
  • Hach, Standard, 8051. Water Analysis HandBook. 2003. p. 1268.
  • ESA, (2012), “Sentinel-2: ESA’s Optical High-Resolution Mission for GMeS Operational Services”, (p. 80).
  • Sharifan H, Dehghani AA, Karimirad I. Correction factor for Hargreaves-Samani method to estimate ETo (case study: Gorgan synoptic station). Water and Soil Conservation. 2012;19(3):227-235. [Persian]
  • Liu,J. , Zhang. Y., Yuan.D., Song.X., 2015, Emprical Estimation of Total Nitrogen and Total Phosphorus Concentration of Urban Water Bodies in china Using High Resolution IKONOS Multispectral Imagery, Journal of Water , 7, 6551-6573.
Volume 8, Issue 4
April 2022
Pages 925-939
  • Receive Date: 03 May 2021
  • Revise Date: 06 November 2021
  • Accept Date: 06 November 2021
  • First Publish Date: 06 November 2021