Geospatial assessment of the Mokra Sura river ecological condition using remote sensing and in situ monitoring data


Keywords: water bodies, industrial agglomeration, pollution, monitoring, remote sensing

Abstract

The use of remote sensing methods for environmental monitoring of the surface water quality is proved. Regression relationships are consistent with ground-based measurements at sampling sites in water bodies and are an effective tool for assessing the ecological status of water bodies. The state of the water bodies of the Mokra Sura river basin varies considerably. The best is the water quality in the upper part of the Mokra Sura river, the worst – in the middle and lower parts. The factors of water pollution are discharges of not enough treated wastewater of industrial enterprises of the Kamyans’koy and Dniprovs’koy industrial agglomeration. The purpose of our search included the following tasks: (a) calculation of integrated environmental water quality indices; b) obtaining satellite information, processing of multispectral satellite images of water bodies using appropriate applied software techniques; c) establishment of statistical dependencies between water quality indexes obtained for biotopically space images and data of actual in situ measurements. The results of systematic hydrochemical control of the Mokra Sura river basin from 2007 to 2011 years were initial data in 4 control areas located in the Dnipropetrovsk region: 1 – the Sursko-Litovske village; 2 – the Bratske village; 3 – the Novomykolayvka village; 4 – the Novooleksandryvka village. Environmental assessment of the water quality of the Mokra Sura river within the Dnipropetrovsk region was based on the calculation the integrated environmental index ( IEI ). Priority pollutants in this case are oil products and ions 2−SO 4, 2 + Mg , 2 + Zn , 6 + Cr . Two images with a difference in three years in April 2015 and May 2017 were used to determine the current changes in the land cover of the study area. Geomorphological assessment of the water network of the Morka Sura river was performed using satellite radar interferometry. Multispectral images of Landsat 5/TM (2007-2011) and Sentinel 2B/MSI (2017) satellite systems were used forremote assessment of water bodies in the study area of the Mokra Sura river basin. The multispectral index TCW (Tasseled Cap Wetness) was used to measure the spectral reflection of the aquatic environment along of the Mokra Sura river flow. The main advantage of the studies is a demonstration of remote sensing capabilities to estimate Mokra Sura river ecological status not only in individual sites, but also throughout the flow – from source to mouth. Follow the necessity to use water from the Mokra Sura river for irrigation, the level of soil water erosion can only increase and enhance the negative processes of eutrophication of reservoirs. Long term technogenic pollution requires information about the state of surface water of fishery, drinking and municipal water use facilities as an integral part of the aquatic ecosystem, the habitat of aquatic organisms and as a resource of drinking water supply. Over 80% of the Mokra Sura river basin surface (IEI 4-12) belong to the classes with the assessment of dirty, very and extremely dirty. The results of studies using remote sensing indicate the need to reduce the streams of not enough treated wastewater to the the Mokra Sura river. The obtained data can be used for ecological assessment of the current and retrospective state of water bodies, development of forecasts of rivers pollution.

Author Biographies

Mykola М. Kharytonov
Dnipro State Agrarian and Economic University
Andriy М. Pugach
Dnipro State Agrarian and Economic University
Sergey А. Stankevich
Scientific Centre for Aerospace Research of Earth, NAS Ukraine
Anna O. Кozlova
Scientific Centre for Aerospace Research of Earth, NAS Ukraine

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Published
2019-01-08
How to Cite
Kharytonov, M., Pugach, A., Stankevich, S., & КozlovaA. (2019). Geospatial assessment of the Mokra Sura river ecological condition using remote sensing and in situ monitoring data. Journal of Geology, Geography and Geoecology, 27(3), 422-430. https://doi.org/https://doi.org/10.15421/111866