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Bioproductivity of Dnieper Reservoirs ANALYSIS by Inductive Methods

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Bioproductivity of Dnieper Reservoirs ANALYSIS by Inductive Methods doi https://doi.org/10.15407/usim.2020.02.066 Udk 519.237.5 H. pIDneBesnA, junior research scientist, international research and training centre of information technologies and Systems of the NaS and meS of Ukraine, glushkov ave., 40, kyiv, 03680, Ukraine, [email protected] BIoproDuCtIVIty oF DnIeper reserVoIrs AnALYSIs By InDuCtIVe metHoDs The task was to determine the factors that have the most significant influence on the state of water in the Dnieper reservoirs by constructing a model of dependence of the concentration of chlorophyll a in phytoplankton according to long-term observations in Kremenchug and Kakhovka reservoirs. The results of observations of the Institute of Sciences in 1976–1993. Various induc- tive methods were used to obtain a satisfactory result. Algorithms: linear regression of (LR), LASSO, combinatorial algorithm of (COMBI) GMDH and correlation-rating algorithm (CRA). Keywords: inductive modeling methods, correlation-rating algorithm CRA, combinatorial algorithm GMDH COMBI, LASSO, phytoplankton, chlorophyll "a" concentration. and errors of measurements of physicochemical Introduction parameters; incomplete knowledge of ecosystem A pressing issue in today’s world is environmental functioning. security and maintaining ecological balance. Water To study the functioning of ecosystems in the resources are extremely important in solving this Dnieper reservoirs, the task was to determine the problem. Investigation of patterns of functioning factors that have the most significant influence on of aquatic ecosystems, formation of their biological the water status, by constructing a model of depen- productivity and influence of natural factors on this dence of chlorophyll "a" concentration in phyto- process under conditions of anthropogenic loading plankton according to long-term observations in are necessary for the development of scientifically Kremenchug and Kakhovka reservoirs. The results methods of management and prediction of water of observations for 1976 –1993 were provided by the quality [1 – 3]. Institute of Hydrobiology of the NAS of Ukraine. The reservoir ecosystem is a complex system. Unfortunately, the difficult economic situation in Water quality in reservoirs depends on many fac- the country and the absence of a laboratory vessel tors. Therefore, it is necessary to identify the most makes it impossible to obtain up-to-date monito- influential ones by constructing models of their ring data. Therefore, it is even more important to functioning. However, environmental modeling is identify the most important factors that affect the a complicated process. Example of problematic is- environmental status of reservoirs. sues are: the uniqueness of each body of water (ri- As mentioned above, the small amount of ob- vers, lakes, reservoirs, etc.); problems of conduc- servational data and measurement errors make ting system studies; small number of observations it difficult to solve the problem. Several methods 66 iSSN 2706-8145, системи керування та комп'ютери, 2020, № 2 Bioproductivity of Dnieper Reservoirs Analysis by Inductive Methods of inductive modeling were applied in the study. sifies. The negative consequences of this process One of the well-known effective approaches to are deterioration of water quality by organoleptic, finding dependencies by short sample data is the hydrochemical and sanitary-microbiological pa- Group Method of Data Handling (GMDH). In rameters, accumulation of biologically active sub- the research, one of the considered algorithms stances (vital secretions of algae and products of is the combinatorial algorithm of GMDH (algo- their decomposition), including toxic, allergenic rithm of complete search). However, the results of and carcinogenic ones. Water gets a bad smell and such analysis are highly dependent on sampling. taste, its transparency decreases, the color increas- Given the small number of measurements, the re- es, the content of dissolved and suspended organic sults of the modeling at different divisions signifi- matter increases. It stimulates the development of cantly differ. To overcome this problem, another saprophytic bacteria (including especially danger- GMDH sorting algorithm was used, a correlation ous pathogens), aquatic fungi, dramatically ex- algorithm with factor rating analysis that uses re- acerbating the epidemiological situation in water sampling, that is, a repeated sample split. In ad- bodies [4, 5]. A high level of eutrophication causes dition, one of the popular modern methods, the fish and other hydrobionts to die. That is, from a LASSO algorithm (Least absolute shrinkage and certain point in time, eutrophication causes deg- selection operator), was performed. radation of lake systems and reservoirs. According to the world statistics, about 40–50% the biological basis of the problem of cases of “flowering” in water accumulate sig- nificant concentrations of compounds that cause The primary autotrophic link of reservoirs is phy- diseases of humans and animals [6]. toplankton (algae of various systematic groups that The use of water bodies during “flowering” of inhabit the water column). By assimilating solar water for recreational purposes and as sources of radiation and converting it into organic matter in drinking water supply significantly increases the the process of photosynthesis, it creates primary risk to human health. It also increases the risk of products. Due to this, there are other aquatic or- the formation of harmful substances also in the ganisms living in water through the supply chain. process of water treatment by existing technologies The response of planktonic algae to the effects of (eg, formation dioxins in the chlorination of wa- natural and anthropogenic factors can be inves- ter contaminated with phenolic compounds). This tigated by the content of chlorophyll a, the main indicates the ecological and social significance of photosynthetic pigment of phytoplankton, since it the problem of anthropogenic eutrophication of is an indicator of the level of vegetation and pri- surface waters. mary production. The increase in organic matter in the water is due to the intensive development of phytoplankton. To a certain extent, this cre- Formulation of task ates the basis for the development of a forage base Our purpose is to study the processes of ecosystem for fish and other aquatic organisms and helps to functioning in the Dnieper reservoirs to determine increase their numbers. When the “flowering” the factors that have the most significant impact on of water (mass development of blue-green algae the water status. We do it by constructing a model – cyanobacteria) begins, the water quality dete- of formation of chlorophyll a concentration in riorates and the oxygen content decreases. Oxygen phytoplankton according to long-term observations deficiency causes processes by which a number in Kremenchuk and Kakhovka reservoirs. of substances are more actively released into the The modeling was based on long-term water. When the content of nitrogen, phospho- observations of mean values ​​of chlorophyll "a" and rus, potassium in water exceeds a critical level, the phytoplankton content per unit volume of water. life processes of aquatic organisms are acceler- The following physicochemical factors were mea- ated, that is, the process of eutrophication inten- sured for the study [7]: iSSN 2706-8145, control systems and computers, 2020, № 2 67 H. Pidnebesna • x – total content of dissolved inorganic nitro- ESS 1 R2 =−1 , gen, mg N/l; TSS • x2 – content of dissolved inorganic phospho- n rus, mg P/l; 2 ESSy=−∑()real yest , • x3 – N/P – ratio of nitrogen content to phos- t=1 phorus content, relative units; n – =− • x4 water temperature, t ° C; TSSy∑()real y , 9 t=1 • x5 – volume of water runoff, m × 10 /month; 2 1 n • x6 – total solar radiation, MJ/m × month. yy= ∑ i . n t=1 DesCrIptIon oF tHe reseArCH Environmental processes forme complex system. In the second stage of the study, modeling was The complex interaction of many factors gives them performed using one of the modern methods of the character of a random process. Therefore, the regression LASSO (Least absolute shrinkage and calculations relating to the study of the laws of the selection operator). It consists of the introduction functioning of water resources are probabilistic, of an additional component of regularization in statistical in nature. A large number of different the optimization functionality of the model, which methods have been developed, which makes the often allows us to obtain a more stable solution [5]. choice of the optimal method of finding patterns This achieves a compromise between the regression for a particular case one of the key problems in error and the complexity of the model structure. designing the statistical model of the process During the minimization, some coefficients under study. become equal to zero, which, in fact, determines The linear regression approach remains the selection of informative features. one of the most powerful tools for analysis. GMDH are well-known class of algorithms Therefore, it is advisable to use regression that work well on short data samples. Therefore, analysis methods in the study of reservoir the next step in the study was to use the COMBI ecological processes. However, it can often combinatorial algorithm [6]. The result of produce erratic results. Regularization me- modeling using the combinatorial algorithm thods prevent unnecessary complexity while main- COMBI GMDH highly depends on the division taining
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