Document Type : پژوهشی

Authors

1 - MSc student of Physical Oceanography, Faculty of Marine and Oceanic Sciences, University of Mazandaran, Babolsar, Iran

2 - Assistant Professor of Physical Oceanography Department, Faculty of Marine and Oceanic Sciences, University of Mazandaran, Babolsar, Iran,

3 Assistant Professor of Geography and Urban Planning Department, Faculty of Humanities and Social Sciences, University of Mazandaran, Babolsar, Iran

Abstract

Introduction
Remote Sensing is an effective tool for detecting and monitoring plume areas. Landsat8 satellite can be used for marine applications and the reason that it was used in this study was the need for a higher resolution to detect a Plume. The satellite has a resolution of 30 m and there is a 16-day spatial resolution. It was the first time that the remote sensing was used to detect the Arvand River's Plume. Because of human population growth and industrialization, there is an increasing pressure on coastal areas and it is important to evaluate the quality of water. Accordingly, remote sensing plays an important role. Considering the vast amount of water covering the surface of the earth, using field measures to study water resources is costly. For this reason, it has taken its place in the processing of satellite imagery. An interesting   mesoscale feature of the continental and shelf sea is the plume produced by the continuous discharge of fresh water from a coastal buoyancy source (rivers, estuarine or channel). Coastal plumes resulting from the continuous discharge of brackish or fresh river water are common features ofcontinental and shelf seas. Inside the plumes, a set of physical and chemical processes occur. Plume areas are excellent sources of nutrients. They have a great impact on marine ecosystems. They are identified as water masses with decreased salinity relative to the ambient ocean water. The Arvand River is a permanent river located in the Gulf region and the Oman Sea. The length of its central part is 84 km and its length is about 190 km. The annual average of the discharge is estimated to be 761 to 792 m3 /s. The tides are mixed at the mouth of the Arvand River.
Methodology
In this study, in order to detect the Arvand River plume, Landsat8 satellite images of October 2016 were used. The downloaded images did not have any cloud cover. River plumes with very high sediment loads have been widely studied by remote sensing technology. The suspended sediment increased the radians caused by surface water. It was in the visible and near-infrared region of the electromagnetic spectrum. The amount of impurities based on NDWI index was negative and the water was purer than the positive NDWI. The plume had more suspended sediments than its surrounding waters, so its NDWI index was less than the sea's. The plumes were identified as water masses with decreased salinity relative to the ambient ocean water.
The plume had more radians (energy) than the surrounding waters. Indeed, the NDWI index of the plume had a lower content and the Salinity Ratio Index of the plume was lower. Then, to detect plume verifications, an image of the Sentinel-2 satellite of October 2016 was also produced. The Sentinel-2 satellite in the blue, green, red, and infrared bands had a resolution of 10 m. The Sentinel 2A satellite was launched in 2015. Using the ENVI software, the radiometric correction was first performed on images. After obtaining radiance and reflectance, the NDWI index and Salinity Ratio were calculated. These four conditions were considered for the detection of the plume. Then, using the scatter plot, the thresholds mentioned in the algorithm were determined, Finally, using the decision tree, the subscriptions of these four indicators were extracted and two plume and non-plume were obtained. In addition, in this study, the NSMI index was used to classify suspended material concentration, and the results showed how the plume dispersion was developed based on this index. In addition, to determine the core of the plume and coastal waters, the NSMI index was used. The more the water, the cleaner and purer it is. The NSMI was more negative. When the water had more suspended sediment, the NSMI was more positive. The NSMI had a fluctuation between one to one negative.
Discussion
In this study, the scientific theories in relation to a plume were proved through the indicated indices. Also, through the use of an algorithm and Landsat 8 satellite imagery, successful results were obtained from the Arvand River Plume. In this study, plume and coastal waters were categorized using a decision tree. In addition, four different water zones were determined based on the spectral properties. Providing accurate and up-to-date information on the dynamics of the plume can lead to the better protection of the coast.
Conclusion
The results of this study can be used to monitor water quality. In October, Radian Band 4, Radian Band 2, NDWI, and salinity ratio matched the preconditions. The core of the plume was based on the distance from the river mouth.The Plume Core (the part with the highest concentration of suspended matter) was located adjacent to the mouth of the Arvand River.

Keywords

منابع
ـ اعتماد شهیدی، امیرفرشاد، صبوری، امیرادهم و جواد پارسا (1390)، کنترل نفوذ شوری در خور رودخانه‌ای اروند در شرایط مختلف هیدرولوژیکی، تحقیقات منابع آب ایران، شماره­ی 2، صص 50-60.
ـ فاطمی، سیدباقر و فاطمه صدقی (1395)، بررسی مقایسه‌ای اثر استفاده از مقادیر پیکسل، بازتابش و بازتابندگی در محاسبه‌ی شاخص‌های گیاهی از تصاویر ماهواره‌ای 8 LANDSAT، سنجش از دور و GIS ایران، شماره­ی 3، صص91-104.
ـ مومی‌پور، مهدی (1395)، مطالعه‌ی کیفیت آب‌های ساحلی با تصاویر ماهواره‌ای فراطیفی هایپریون- مطالعه­ی موردی ساحل اروندکنار، علوم و فنون دریایی، شماره­ی 1، صص 113-122.
-Chander, G., Markham, B.L., & Helder, D.L. (2009), Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors, Remote sensing of environment, 113(5), PP.893-903.
-Dehni, A., and Lounis, M. (2012), Remote sensing techniques for salt affected soil mapping: application to the Oran region of Algeria, Procedia Engineering, 33, PP.188-198.
-Fernández-Nóvoa, D., Mendes, R., Dias, J.M., Sánchez-Arcilla, A., and Gómez-Gesteira, M. (2015), Analysis of the influence of river discharge and wind on the Ebro turbid plume using MODIS-Aqua and MODIS-Terra data, Journal of Marine Systems, 142, PP.40-46.
-Guneroglu, A., Karsli, F., and Dihkan, M. (2013), Automatic detection of coastal plumes using Landsat TM/ETM+ images, International journal of remote sensing, 34(13), PP.702-4714.
-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.
-Kang, Y., Pan, D., Bai, Y., He, X., Chen, X., Chen, C.T.A., and Wang, D. (2013), Areas of the global major river plumes, Acta Oceanologica Sinica, 32(1) PP.79-88.
-Mestres, M., Sierra, J.P., and Sánchez-Arcilla, A. (2007), Factors influencing the spreading of a low-discharge river plume, Continental Shelf Research, 27(16), PP.2116-2134.
-Mobasheri, M.R., and Mousavi, H. (2004), Remote sensing of suspended sediments in surface waters using MODIS images, In Proc. XXth ISPRS Congress, Geo-Imagery Bridging Continent, Istanbul, PP.12-23.
-Nezlin, N.P., DiGiacomo, P.M., Diehl, D.W., Jones, B.H., Johnson, S.C., Mengel, M. J., ... and Wang, M. (2008), Stormwater plume detection by MODIS imagery in the southern California coastal ocean, Estuarine, Coastal and Shelf Science, 80(1), PP.141-152.
-Petus, C., Marieu, V., Novoa, S., Chust, G., Bruneau, N., & Froidefond, J. M. (2014), Monitoring spatio-temporal variability of the Adour River turbid plume (Bay of Biscay, France) with MODIS 250-m imagery, Continental Shelf Research, 74, PP.35-49.
-Saldías, G.S., Sobarzo, M., Largier, J., Moffat, C., and Letelier, R. (2012), Seasonal variability of turbid river plumes off central Chile based on high-resolution MODIS imagery, Remote Sensing of Environment, 123, PP.220-233.