Project risk management in the mining industry is necessary to identify, analyze and reduce uncertainty. The engineering features of mining enterprises, by their nature, require improved risk management tools. This article proves the relevance of creating a simulation model of the production process to reduce uncertainty when making investment decisions. The purpose of the study is to develop an algorithm for deciding on the economic feasibility of creating a simulation experiment. At the same time, the features and patterns of the cases for which the simulation experiment was carried out were studied. Criteria for feasibility assessment of the model introduction based on a qualitative parameters became the central idea for algorithm. The relevance of the formulated algorithm was verified by creating a simulation model of a potassium salt deposit with subsequent optimization of the production process parameters. According to the results of the experiment, the damage from the occurrence of a risk situations was estimated as a decrease in conveyor productivity by 32.6%. The proposed methods made it possible to minimize this risk of stops in the conveyor network and assess the lack of income due to the risk occurrences.

An appraisal of the groundwater potential of Alex Ekwueme Federal University Ndufu Alike was carried out by integrating datasets from geology, geographic information system and electrical resistivity survey of the area. The study area is underlain by the Asu River group of Albian age. The Asu River Group in the Southern Benue Trough comprises of Shales, Limestones and Sandstone lenses of the Abakaliki Formation in Abakaliki and Ikwo areas. The shales are generally weathered, fissile, thinly laminated and highly fractured and varies between greyish brown to pinkish red in colour. Twenty (20) Vertical Electrical Sounding data were acquired using SAS 1000 ABEM Terrameter and processed to obtain layer parameters for the study area. A maximum current electrode spacing (AB) of 300 meters was used for data acquisition. Computer aided iterative modelling using IPI2 Win was used to determine layer parameters. In-situ Hydraulic Conductivity measurements at seven parametric locations within the study area were conducted and integrated with Electrical Resistivity measurements to determine aquifer parameters (e.g., Hydraulic conductivity and Transmissivity) in real time. This technique reduces the attendant huge costs associated with pumping tests and timelines required to carry out the technique. Accurate delineation of aquifer parameters and geometries will aid water resource planners and developers on favourable areas to site boreholes in the area. Several correlative cross-sections were generated from the interpreted results and used to assess the groundwater potential of the study area. Results show that the resistivity of the the aquifer ranges from 7.3 Wm–530 Wm while depth to water ranges from 11.4 m to 55.3 m. Aquifer thicknesses range from 8.7 m at VES 5 to 36.3 m at VES 6 locations. Hydraulic conductivity ranges from 1.55 m/day at VES 15.18, and 19 locations to 9.8 m/day at VES 3 and 4 locations respectively. Transmissivity varies from 17.48 m²/day at VES 19 to 98 m²/day at VES 3 locations respectively. Areas with relatively high transmissivities coupled with good aquifer thicknesses should be the target of water resource planners and developers when proposing sites for drilling productive boreholes within Alex Ekwueme federal University Ndufu Alike.

Rural tourism plays a crucial role in rural development in Indonesia by providing employment opportunities, livelihood, infrastructure, cultural preservation, and environmental preservation. However, it is prone to external shocks such as natural disasters, public health events, and volatility in the national and global economy. This study measures the resilience of rural tourism to external shocks caused by the COVID-19 pandemic in 24 rural tourism destinations in Indonesia covering four years from 2019 to 2022. A synthetic composite index of the Adjusted Mazziotta-Pareto index (AMPI) is used to measure rural tourism resilience followed by clustering analysis to determine the typology of the resilience. The AMPI measure is also compared with the conventional Mazziotta-Pareto index (MPI) method. The resilience index is composed of capacity and performance components related to resilience. The results show that in the first year of COVID-19, most tourism villages in Indonesia were severely affected by the pandemic, yet they were able to recover afterward, as indicated by positive differences in the AMPI index before and after COVID-19. Thus, rural tourism villages in Indonesia have a strong capacity and performance to recover from pandemic shock. Lessons learned from this analysis can be applied to policies related to rural tourism resilience in developing countries.