ASSESSMENT OF THE CURRENT ECOLOGICAL STATE OF THE FASTIV RESERVOIR USING GROUND AND SATELLITE DATA
Abstract
The article presents the results of researches on assessing the ecological state of the Fastiv Reservoir using ground and satellite data according to the developed scientific approach, which provides for the following sequence for a water body with a large area: conducting field observations, involving satellite information, and creating a resulting map of the current ecological state based on a certain set of indicators, which is the goal of the research. The relevance of the research is defined by the significant deterioration of the water condition in the reservoir, which was caused by an increase in air temperature, uneven distribution of precipitation throughout the year, a decrease in the reservoir filling to 92.7% of the design level, intensive increase in water use and discharge of domestic wastewater. In the conducted studies, it was advisable to compensate the lack of spatially concentrated information (from points of field measurements) with spatially distributed information. During field surveys, hydrobiological and physicochemical indicators were determined in 3 sections of the reservoir - points observations, and maps of water depth, temperature, and transparency were created based on the results. Such results of field observations as an increased turbidity and low transparency made it necessary to use satellite data, especially those containing red and infrared ranges, when calculating spectral indices. From the perspective of remote sensing, water bodies have their own spectral characteristics, which depend on the concentration of various substances dissolved and suspended in water - diffuse reflectance. To compensate the lack of information, the Sentinel-2 L2A image was used, which is the closest with no cloud cover to the date of field observations, and spectral indices were calculated in the open software product Land Viewer: NDVI, GCI, NDWI. Only the NDWI map was useful, providing an insight about the transparency within the entire reservoir. The obtained comprehensive information made it possible to create a resulting map of the current ecological state of the Fastiv Reservoir based on the ground and satellite data.
References
2. Godı´nez-AlvarezH., J.E. Herrick, M. Mattocks, D. Toledo&J. VanZee. (2009). Comparison of three vegetation monitoring methods: their relative utility for ecological assessment and monitoring. Ecological indicators, 9, 1001-1008.
3. Demianov, V., & Rakuliak, V. (2008). Kontseptsiia ozdorovlennia ekolohichnoho stanu r. Dnipro v mezhakh m. Dnipropetrovska v umovakh zarehuliuvannia vodoskhovyshchamy Dniprovskoho kaskadu [The concept of improving the ecological state of the Dnipro River within the city of Dnipropetrovsk under the conditions of regulation by the reservoirs of the Dnipro Cascade]. VodnehospodarstvoUkrainy, 3, 10-22. [in Ukrainian].
4. Pichura, V. (2017). Teoretyko-metodolohіchni osnovy baseinovoi orhanizatsii pryrodokorystuvannia na vodozbirnykh terytoriiakh transkordonnykh richok (na prykladi baseinu Dnipra) [Theoretical and methodological foundations of the basin organization of nature management in the catchment areas of transboundary rivers (on the example of the Dnipro basin)]. Dys. Nazdobuttianauk. Stupeniadokt. s.-h. nauk: 03.00.16. Kyiv, 388. Retrieved from: https://dspace.dsau.dp.ua/handle/123456789/7775[in Ukrainian].
5. Trescott, A. (2012). Remote Sensing Models of Algal Blooms and Cyanobacteria in Lake Champlain. Environmental & Water Resources Engineering Masters Projects, 48. Retrieved from:https://doi.org/10.7275/8VD3-A468
6. Mohammad, H., Assefa, M. Melesse, Lakshmi, R. (2016). A Comprehensive Review on Water Quality Parameters Estimation. Using Remote Sensing Techniques. Sensors (Basel), 16, 16(8):1298. Retrieved from: https://www.ncbi.nlm.nih.gov/pubmed/27537896
7. Chengkun, Zhang, Min, Nan. (2015). Mapping Chlorophyll a Concentration in Laizohou Bay using Lansat 8 OLI data. E-proceeding of the 36-th IAHR World Congress. 28 June – 3 July, Yhe Hague, Netrerlands.Retrieved from: https://www.iahr.org/library/infor?pid=7833
8. Mukherjee, N.R., & Samuel, C. (2016). Assessment of the temporal variations of surface water bodies in and around Chennai using Landsat imagery. Indian Journal of Science and Technology, 9 (18), 1-7. Retrieved from:DOI: 10.17485/ijst/2016/v9i18/92089
9. 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), 3025-3033. Retrieved from:DOI: https://doi.org/10.1080/01431160600589179
10. Shevchuk, S., Vyshnevskyi, V., Shevchenko, I., & Kozytskyi,O. (2019). Doslidzhennia vodnykh obiektiv Ukrainy z vykorystanniam danykh dystantsiinoho zonduvannia Zemli [Research of water bodies of Ukraine using the data of remote sensing of the Earth]. Melioratsiia i vodnehospodarstvo, 2, 146-156. Retrieved from: http://nbuv.gov.ua/UJRN/Mivg _2019_2_18 [inUkrainian].
11. Kekliu, R., & Alkish, A. (2021). Novyi statystychnyi pohliad na trofichni indeksy milkovodnykh ozer. [A New Statistical Perspective on Trophic Indexes for Shallow Lakes]. Water Resources 48(2), 324-330. Retrieved from:DOI: 10.1134/S0097807821020123[in Ukrainian].
12. Pro zatverdzhennia Metodyky vidnesennia masyvu poverkhnevykh vod, a takozh istotno zminenoho masyvu poverkhnevykh vod, do odnoho z klasiv ekolohichnoho potentsialu shtuchno abo istotno zminenoho masyvu poverkhnevykh vod. [On the approval of the Method for the assignment of the massif of surface waters, and also the substantially changes massif of surface waters, to one of the classes of ecological potential of artificially or substantially changed massif of surface waters] Retrieved from: https://zakon.rada.gov.ua/laws/show/z0127-19#Text [in Ukrainian].