Multi-objective optimization of groundwater monitoring network using a probability Pareto genetic algorithm and entropy method (case study: Silakhor plain)

Optimal groundwater monitoring networks have an important role in water resources management. For this purpose, two scenarios were presented. The first scenario designs a monitoring network and the second scenario chooses optimal wells from the existing ones in the study area of the monitoring network. At the first step, a database including groundwater elevation in potential wells was produced using the Kriging method. The optimal monitoring network in the first scenario was determined by preset conventions and found by the non-dominated sorting genetic algorithm (NSGA-II). In the second scenario, the optimal monitoring network was determined by entropy theory through calculating entropy for each of the 29 observation wells. Finally, the first scenario obtained a network with 12 observation stations showing root mean square error (RMSE) value given as 0.61 m. Comparison between entropy of rainfall and groundwater level time series in the first scenario had the same variation. The optimal monitoring network in the first scenario has been able to reduce the number of monitoring stations by 60% in comparison with the existing observation network. The second scenario used entropy theory and calculated the energy of each of the 29 observation wells which obtained a monitoring network with 11 stations.

Efficiency assessment of seismological information, monitoring system and seismicity study for the Republic of Armenia

<p>To study the deep structure of the earth it is important to have an optimal monitoring network and reliable seismic baseline database for the investigated area. In addition, the territory of Armenia according to its geology and seismological conditions is a full-scale experimental polygon for seismic problems, in particular the study of Earth's deepest structure by seismic methods. For this purpose, the work aims to assess the effectiveness of the existing seismic monitoring system in Armenia, to offer optimal solutions for the station layout, to evaluate the accuracy of seismic information registered in the RA by performing hypocenter recalculation. Then, within of the work organized modern seismic stations in Armenia and Russia towns with seismic equipment made and produced in Armenia (IGES NAS RA). The work was supported by MESCS Science Committee of the Republic of Armenia (grant № 18SH-1E012).</p>