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The article develops a new method of spatiotemporal modelling of possible locations of ragweed areas and estimation of pollen emission intensity of these areas. The method uses spline approximation with automatic computations of typical pollen production models in the R language. It applies a number of approaches eliminating the uncertainty of various parameters that should be taken into consideration for this modelling. The authors have consolidated some experimental data on the amount of Ambrosia pollen in the air depending on environmental conditions, and found some new possible ragweed pollen sources on the territory of the city of Vinnytsia and the adjacent villages. The study used spline approximation of the first (lines) and second (parabolas) orders were applied. Data of bi-hourly pollen concentrations were obtained at the pollen monitoring site of National Pirogov Memorial Medical University (Vinnytsia). To perform the approximation, wind speed, wind direction and relative humidity were taken into the consideration. The authors used the polar coordinate system to formalize the problem. PRA Finder computer program was developed, which has been successfully tested on real data and for which a certificate of copyright registration has been obtained in Ukraine. As a result of the method application, the known areas were corroborated and new possible plots were revealed. The comparison of the forecasted areas for 2014 with the actual ones showed a close match. However, it should be taken into consideration that the proposed method is viable only when applied under the condition that the wind velocity does not exceed 4 m/sec and the relative humidity is between 20 and 90%.

The article considers the collection, verification and generalization of a large number of expert assessments of the current state of waters, existing environmental problems and influential factors that increase the risk of failure to achieve environmental goals of each volume of water during the development of river basin management plans (RBMPs) or stabilization of good ecological status of water in the water bodies of this basin. The task is complicated by the large number of such volumes of water, as it is extremely difficult to gather reliable information about the objects located in each of them. Creation of a web system with a map of water volumes and the involvement of a large number of experts from among locals who are not indifferent to the problems of their environment will help to solve this problem. However, then there is the problem of verifying the assessments of these experts, taking into account their different qualifications, experience, different views of the objectives of the RBMP, and the problem of how to compare them to identify the most vulnerable regions by different criteria. It is proposed that experts will be required not only expert assessments on the basis of single directories of possible answers, but also - links to text web resources that confirm their assessments to solve this problem. And then it will be analyzed if these sources really confirm each assessment of the appropriate type of problem for a given region. The authors consider various approaches for comparing expert assessments both based on the basis of fuzzy sets and with the help of machine learning and natural language processing (NLP) technologies. Analogues of the system developed by the authors are considered. A method has been developed to identify and verify priority of environmental problems in water bodies of the river basin based on fuzzy expert estimates, taking into account the probabilities that the text materials cited by the expert do correspond to this problem. These probabilities are determined to use models of NLP technologies. The stages of functioning of the expert information web system for the implementation of the proposed technology are described, which will simultaneously collect the most reliable and detailed information about the objects of water bodies and accelerate its processing and ranking. An example of the implementation of an information web system for identifying priority environmental problems in the water bodies of the Southern Bug River basin is given. Examples of calculating the reliability of expert estimates using the author’s program in Python based on NLP-model BERT and logistic regression which were applied to real text information are given.

This work considers the issue of optimizing the water discharge monitoring network in order to increase the accuracy of computing a river water balance, thereby optimizing the water use within such water basin based on the sustainable development and river basin integrated management principles. The authors hereof have developed the multi-criteria method for ranking the river water discharge monitoring stations; such method is to be applied to determine the priorities of their location, under the limited funding conditions, based on a systemic analysis of the water (water management) balance components with due regard to the river network topology and the specifics of water use within such network. The method offered herein differs from the existing methods inasmuch as it discriminates between the phase of the evaluation of the weight of the ranking criteria and the phases of data processing related to the potential water flow gauging stations according to such criteria, thus ensuring complete automation of such data processing and high speed and efficiency of such method. The functionability of the method has been demonstrated in practice. The method is an omni-purpose tool applicable also for optimization of other types of monitoring networks.

The work offers a new method for analyzing and optimizing the topologie observability of cognitive maps of complex spatially distributed systems in terms of various approaches to setting the optimization problems. Such method is based on a new criterion of optimal level of its observability. The method has been elaborated on the basis of the well-known topologic observability analysis technique applicable to complex spatially distributed systems which are formalized in their geo information space of parameters. The work demonstrates an example of application of proposed method.

This work considers the issue of selecting the criteria for ranking of the stations used to monitor the status of spatially distributed systems and the processes within such systems, as well as for establishing the priority for locating such stations. The paper offers a SWOT-based method intended to classify all criteria with regard to internal and external opportunities and threats and to overlay on one another iteratively the results of SWOT analyses in order to generate a unified set of criteria. The criteria, so obtained, are compared with regard to the available databanks and GIS maps, and only those criteria that are supported by the information being sufficient for their evaluation are sorted out. The criteria, so selected, are fit for further multi-criteria optimization of a network of monitoring stations with the use of systems analysis methods; they ensure better accuracy, validity, reliability and information value of such optimization results. The functionability of the method has been demonstrated by the example of designing the network of the surveillance monitoring stations for the surface water quality in line with the objectives of the EU Water Framework Directive.

The article is devoted to the development of the decision support system for the classification of allergic pollen types based on fuzzy expert data of their features on the microscope images and the improvement of the identification method of this system. The genetic algorithm of the classifier training has been improved taking into account the spatial-temporal features of the distribution of pollen in the air, namely: adaptive fitness function for evaluating solutions, tournament selection with elitism and initialization of the initial population, allowing to improve the accuracy of classification. The example of the proposed system and method application based on real expert data of Vinnytsia monitoring station which is the part of European Aeroallergen Network is shown.

The analysis of modern information measuring systems (IMS) for identification model parameters of the air pollution is carried out. That allows to increase the accuracy of this identification due to their complex application. The known model based on the fuzzy knowledge base was adapted to this task. It is specified how the offered IMS can increase the accuracy of the parameters identification. The results of the experiment with the use of the offered IMS in Vinnytsia city presented in the paper.