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Abstract:Having the ability to forecast groundwater levels is very significant because of their vital role in basic functions related to efficiency and the sustainability of water supplies. The uncertainty which dominates our understanding of the functioning of water supply systems is of great significance and arises as a consequence of the time-unbalanced water consumption rate and the deterioration of the recharge conditions of captured aquifers. The aim of this paper is to present a hybrid model based on fuzzy C-mean clustering and singular spectrum analysis to forecast the weekly values of the groundwater level of a groundwater source. This hybrid model demonstrates how the fuzzy C-mean can be used to transform the sequence of the observed data into a sequence of fuzzy states, serving as a basis for the forecasting of future states by singular spectrum analysis. In this way, the forecasting efficiency is improved, because we predict the interval rather than the crisp value where the level will be. It gives much more flexibility to the engineers when managing and planning sustainable water supplies. A model is tested by using the observed weekly time series of the groundwater source, located near the town ofČačak in south-western Serbia.

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The paper proposes a problem-solving approach in the area of underground mining, related to the evaluation and selection of the optimal mining method, employing fuzzy multiple-criteria optimization. The application of fuzzy logic to decision-making in multiple-criteria optimization is particularly useful in cases where not enough information is available about a given system, and where expert knowledge and experience are an important aspect. With a straightforward objective, multiple-criteria decision-making is used to rank various mining methods relative to a set of criteria and to select the optimal solution. The considered mining methods represent possible alternatives. In addition, various criteria and subcriteria that influence the selection of the best available solution are defined and analyzed. The final decision concerning the selection of the optimal mining method is made based on mathematical optimization calculations. The paper demonstrates the proposed approach as applied in a case study.

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Heavy rainfall and slow movement of the cyclone Tamara caused record floods in May 2014 across Serbia. As a result, levees were breached, a large portion of the open-pit lignite mine Tamnava-West Field was flooded and a flood lake was created. Due to an active hydraulic link with aquifers, the water table rose and the amount of stored groundwater increased dramatically. Based on in situ surveys and hydrodynamic modeling, three distinct periods of the groundwater regime are identified and the flood impact on the groundwater regime in the study area quantified. The paper describes correlations between flood lake water levels and the water table, and shows calculated groundwater volumes as a result of flooding and those of residual groundwater after dewatering of the open-pit mine. This extreme historical flood in Serbia had disastrous economic and social consequences, given that the studied open-pit mine supports more than 25% of Serbia's electric power output. The assessment of the flood wave and its impact on the groundwater regime is an important example of the groundwater system response to an extreme rainfall and flood event. The paper presents the operating algorithm which leads to the approach of assessing the impact of floods on increasing the volume of accumulated groundwater. The paper presents a developed methodology for groundwater level status exploration in the wider area of open-pit mine Tamnava-West Field during the flooding that occurred in this mine. The developed method encompasses the creation and calibration of a groundwater model and fate and transport model for groundwater state prior to the flooding, a verification model for groundwater level during the extreme floods and a control verification model which corresponds to the period after the passing of the flood wave. The applied operational algorithm offers reliable bases for adopting a strategy for groundwater management during floods.

When considering data and parameters in hydrogeology, there are often questions of uncertainty, vagueness, and imprecision in terms of the quantity of spatial distribution. To overcome such problems, certain data may be subjectively expressed in the form of expert judgment, whereby a heuristic approach and the use of fuzzy logic are required. In this way, decision-making criteria relating to an optimal groundwater control system do not always have a numerical value. Groundwater control scenarios (alternatives) are identified through hydrodynamic modeling of the aquifer, providing an indication of their effectiveness. The paper develops a fuzzy-stochastic multi-criteria decision-making model to deal with a topical problem: selection of the most suitable groundwater control system for an open-cast mine. Both real numerical and linguistic variables are used to express the values of all criteria that affect the final decision. In particular, it should be pointed out that the values of the criteria are varied over a predefined time horizon. For mathematical calculations, fuzzy dynamic TOPSIS and the stochastic diffusion process—geometric Brownian motion—were used. The proposed method is tested in a case study: the selection of an optimal groundwater control system for an open-cast mine.