Scientific publications

The study is warranted by the need to improve the methods for assessing the ecological and geoecological status of natural features as complex systems for various combinations of their composition, properties, and priorities of evaluative research. Traditionally, when solving the problem of selecting a normalization function as a stage in constructing integral indicators, scientific publications do not discuss the nature of the relationship (direct or inverse) or the possibility of accounting for nonlinearity between the system’s parameters and the property under assessment. This paper demonstrates a comparison of the results of an integrated ecological status assessment obtained by various classification models, taking into account both linear and nonlinear methods of representing the relationship between parameters and system properties in normalization functions. The comparison was performed at the level of quantitative estimates of sub-indices and the final value of the integrated water body ecological status indicator (IESI). The key water body selected for this study is Lake Volkhovskoe (Suuri) on northern Karelian Isthmus. An extensive database was compiled for this lake, including physical, chemical, and biological
arameters related to the trophic status, water quality, toxic contamination, and potential resilience, which allowed for an assessment of its ecological status. The first task was to determine how much the values of the trophic sub-index (TSI) would change upon factoring in a nonlinear relationship between evaluation criteria and the trophic index. The variants considering different degrees of nonlinearity λ in the normalization functions presented in this paper included only positive values: 0.5; 1.0; 1.5; 2.0; 3.0. The main challenge for future assessments is to substantiate an appropriate value for this parameter for each criterion considered. Experiments were conducted in a simplified form. The parameter λ was set to a single value for all criteria included in the TSI sub-index.The second task was to determine how much the IESI would change when accounting for nonlinearity in the TSI index and adjusting the priorities (weights) assigned to TSI during the final convolution stage. Meanwhile, linear relationships between parameters and system properties were maintained for other sub-indices (water quality sub-index WQTPI and potential resilience sub-index WBRI) throughout all convolution steps. The calculations are presented both graphically and in tabular form. The study revealed that a reduction in λ, and thus in nonlinearity, shifts values on the IESI evaluation scale to the right, while an increasing in λ causes a shift to the left on this scale. Variations in both nonlinearity degree and priority (weight) assigned to TSI during IESI assessment were considered.