Methods for evaluating the ecological condition of freshwater objects based on space geomonitoring and statistical criteria with virtual standards (rationale and testing)

Authors

  • Oleksandr Fedorovsky Scientific Centre for Aerospace Research of the Earth of the Institute of Geological Sciences of the National Academy of Sciences of Ukraine, Oles Honchar st, 55-B, 01054, Kyiv, Ukraine https://orcid.org/0000-0003-3611-546X
  • Anna Khizhnyak Scientific Centre for Aerospace Research of the Earth of the Institute of Geological Sciences of the National Academy of Sciences of Ukraine, Oles Honchar st, 55-B, 01054, Kyiv, Ukraine https://orcid.org/0000-0002-8637-3822
  • Olha Tomchenko Scientific Centre for Aerospace Research of the Earth of the Institute of Geological Sciences of the National Academy of Sciences of Ukraine, Oles Honchar st, 55-B, 01054, Kyiv, Ukraine https://orcid.org/0000-0001-6975-9099
  • Anatolii Porushkevych Scientific Centre for Aerospace Research of the Earth of the Institute of Geological Sciences of the National Academy of Sciences of Ukraine, Oles Honchar st, 55-B, 01054, Kyiv, Ukraine https://orcid.org/0000-0001-6418-4775
  • Ludmyla Pidgorodetska Space Research Institute National Academy of Sciences of Ukraine and State Space Agency of Ukraine, 03680, Glushkov Ave, 40, 4/1, Kyiv, Ukraine https://orcid.org/0000-0002-7021-3648

DOI:

https://doi.org/10.36023/ujrs.2020.27.174

Keywords:

RS — remote sensing, geomonitoring, NTC - natural territorial complexes, aquatic vegetation, water quality, water consumption, water supply

Abstract

В статье обосновывается предложений способ оценки экологического состояния пресноводных водоемов на основе космического геомониторинга и статистического критерия одновременно по нескольким эталонам, каждый из которых представляет соответствующий уровень техногенного или антропогенной нагрузки. Для этого по каждому изучаемому объекту (водоему) вычисляют вероятности соответствия их информативных признаков информативным признакам каждого эталона. В результате получают количественную оценку влияния нагрузки в относительных единицах или баллах. Приведены примеры апробации предложенного метода для исследования изменения экологического состояния водоемов на примере Киевского водохранилища и озера Свитязь.
Для обоснования предложенного способа было определено соответствие полученных результатов на основе статистического критерия оценкам реальной рекреационной нагрузки и оценкам влияния нагрузок полученных методами МКО и МАИ. Для этого были подсчитаны коэффициенты корреляции между этими результатами за соответствующие годы, который в среднем был ровен 0,8, что вполне приемлемо для практических оценок результатов нагрузки на экосистему водоемов. Установлено, что водные объекты представляют собой сложные системы, анализ которых происходит на разных уровнях абстрактного описания с учетом взаимосвязи их составляющих: ландшафтных комплексов (ПТК или биотопов), гидрологических, гидробиологических и гидрохимических характеристик. В ходе исследования выяснено что рекреационная нагрузка на озеро Свитязь постоянно растет и соответственно негативно влияет на его экологическое состояние. Также выявлено, что зарастание акватории верховья Киевского водохранилища высшей водной растительностью также увеличивается, что в свою очередь ослабляет эффективность водохранилища для нужд водопотребления.

The article substantiates the method of assessing the ecological status of freshwater reservoirs using space geomonitoring and statistical criteria with several standards simultaneously, each of which represents the level of technogenic or anthropogenic load. To achieve this, the probabilities of the affiliation of their informative features to the informative features of each standard are calculated for each studied object (reservoir). The result is a quantitative estimation of the load, which is given in relative units or points. The approbation of the offered method for research of the changes in ecological conditions of reservoirs is done over the Kyiv Reservoir and lake Svityaz.
During the study of the method, the correspondence of the obtained results using the statistical criterion to the real estimates of recreational load made by the method of multi-criteria optimization (MCO) and method of analysis of hierarchies (MAH) was determined. For this purpose, the correlation coefficient between the obtained result and recreational load, as well as the results of assessments based on MKO and MAH for the respective years was calculated, which averaged 0.8, which is quite acceptable for practical assessments of water ecosystem load. It was determined that water bodies are complex systems and their analysis takes place at different levels of abstractions, taking into account the relationship of their components: landscape complexes (LC), hydrological, hydrobiological and hydrochemical characteristics. The study found that the recreational load on Lake Svityaz is constantly increasing and has negative impact on its ecological condition. It was also found that the overgrowing of the upper springhead of the Kyiv Reservoir with higher aquatic vegetation is also currently increasing, which weakens the efficiency of the reservoir for purposes of water consumption.

References

Arkhipov, A. I., Glazunov, N. M. & Khyzhniak, A. V. (2018). Heuristic Criterion for Class Recognition by Spectral Brightness. Cybernetics and Systems Analysis, 54 (1), 94–98. DOI 10.1007/s10559-018-0010-7.

Ecological passport. Volyn region. 2014. Volyn Regional State Administration. (2015). Retrieved from http://www.menr.gov.ua/ index.php/protection/protection1/volynska.

Ecological passport. Volyn region. 2018. Volyn Regional State Administration. (2019). Retrieved from https://voladm.gov.ua/ category/ekologichni-pasporti/1/.

Fedorovsky, O. D., Khyzhnyak, A. V., Tomchenko, O. V., Zub, L. M., Podgorodetska, L.V., Dyachenko, T. M., Shevchenko, O. M., Vlasova, E. V., Khodorovsky, A. Ya., & Yakymchuk, V. H. (2015). The multidisciplinary analysis of the aerospace and ground information while assessing the status of water ecosystems based on the methods of system analysis. Ukrajinsjkyj zhurnal dystancijnogho zonduvannja Zemli. 7, 27–42. Retrieved from http://ujrs.org.ua/ujrs/article/view/ 61/79. (in Ukrainian).

Fedorovsky, O. D., Khyzhnyak, A. V., Zub, L. M., Tomchenko,O. V., Khodorovsky, A. Ya. & Podgorodetska, L. V. (2018). Assessment of the state of aquatic ecosystems based on methods of systematic analysis of aerospace and ground information. Ekologhichni nauky: naukovo-praktychnyj zhurnal, 4 (23), 106–111. Retrieved from http:/ /ecoj.dea.kiev.ua/archives/2018/4/25.pdf. (in Ukrainian).

Ostapiv, V. V., Pindus, N. M., Chekhovskyi, S. A. & Klochko, N. B. (2016). Virtual standards as a means of improving measurement accuracy. Systemy obrobky informaciji. 6 (143), 108–111. (in Ukrainian).

Podgorodetskaia, L. V, Zub, L. N, Fedorovskyi, O. D. (2010). The use of remote sensing data for estimation of ecological state of water bodies by the example of the Svityaz lake. Kosm. nauka tehnol, 16 (4), 51–56. Retrieved from https://doi.org/10.15407/knit2010.04.051. (in Ukrainian).

Tomchenko, O.V., Podgorodetska, L. V. & Fedorovsky, O. D. (2013). The complex assessment of the ecological state of water bodies using remotely sensing data (from example Lake Svityaz and upper Kyiv Reservoir). Ghidroakustychnyj zhurnal, 10, 111–117. Retrieved from http://nbuv.gov.ua/UJRN/gaj_2013_10_16. (in Ukrainian).

Tomchenko O. V. (2015). Substantiation of wetland system analysis methods using remote sensing data and ground observations (in the upper Kyiv reservoir case study) (Extended abstract of candidate thesis). State institution Scientific center for aerospace researches of the Earth of IGS NAS of Ukraine, Kyiv, Ukraine. (in Ukrainian).

Shitikov, V. K., Rosenberg, G. S., Zinchenko, T. D. (2003). Quantitative hydroecology: methods of system identification. Togliatti: IEVB RAS. (in Russian).

Vishnevsky, V. I. & Shevchuk, S. A. (2018). Use of remote sensing data of the Earth in studies of water bodies of Ukraine. Kyiv: Interpress LTD. (in Ukrainian).

Published

2020-12-10

Issue

Section

Earth observation data applications: Challenges and tasks