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ArticleName Prediction of seasonal and annual variation in water inflow in open pit mines using the slope runoff model with concentrated parameters
DOI 10.17580/gzh.2023.05.15
ArticleAuthor Gritsenko K. I., Lesnichi L. I.

Research Center for Geomechanics and Mining Practice Problems, Saint-Petersburg Mining University, Saint-Petersburg, Russia:

K. I. Gritsenko, Leading Engineer,
L. I. Lesnichi, Leading Engineer


Prediction of seasonal variation in water inflow in mines is critical for safe and efficient mining. In open pit mines, water inflow comes from both groundwater and from atmospheric fallout and slope runoff. Eventually, prediction of seasonal variation in water inflow should take into account all of these three components. The present-day practice uses either empirical formulas or mathematical models based on the Darcy law and the equation of continuity. These methods have some limitations which make the prediction of seasonal variations in water inflow rather labor-intensive and not widely accepted. The authors make an attempt to develop a simple and reliable prediction procedure for seasonal variation in water inflow. This research is an initial step toward the analysis of usability of hydrodynamic and stochastic models of water catchment to predict seasonal variation in water flow in mines. The water catchment models are built to predict annual and monthly water inflow. The test subjects were Koashva and Niorkpakhk open pit mines and Kirov mine operating at apatite–nepheline ore deposits in the Khibiny. The result (for the first turn, the water inflow prediction accuracy) proves the validity of the water catchment model in prediction of water inflow in mines in case of the relatively high seasonal variability of water inflow (low water/flood water ratio from 1/5 to 1/3). It is planned further to substantiate theoretically the model applicability in prediction of water inflow in mines located in different geological and climatic conditions. The prediction and prompt adjustment of water-drainage installations enhance efficiency of the equipment.

keywords Water inflow prediction, underground openings, partially infinite modeling, hydrology, underground and surface flows, water catchment model

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