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Item type:Publication, Applying grey systems to analyze water quality on the river Chira watershed(The World Academy of Research in Science and Engineering, 2020-07-25)Due to people's opposition to any mining company exploiting some ore deposit close to their community, these projects, in some cases, are never carried out properly, resulting in informal miners illegally exploiting these areas and polluting important river watersheds. Hence, a water quality assessment is necessary. In this work, to assess the water quality of the Chira river watershed was used the Grey Clustering method, which is based on grey systems, in which informal miners affected the activity in the Tambogrande area in Piura, Peru. In this case study, 17 monitoring points were determined (1-17), all of them were analyzed using 6 criteria of evaluation (C1-C6). The results of this study showed that there was some level of pollution due to the activity of informal miners, but this does not involve a great negative impact. These results could help to demonstrate that the expulsion of formal mining companies from ore deposits can cause pollution to a higher level than expected. Some monitoring points on the Ecuador -Peru boarder showed high pollution, which could mean illegal mining activity in that area and would be subject for future study.2 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Water Quality Assessment using the Grey Clustering Analysis on a river of Taxco, Mexico(The World Academy of Research in Science and Engineering, 2020-08-25)Mining projects have a constant impact on the environment.One of the environmental factors that are affected is the water.Therefore, it is important to quantify how this factor has been impacted by the extraction activity.For example, the grey clustering method is an interesting alternative for evaluating some water samples, based on a variety of parameters and using artificial intelligence criteria.As a case study, the Taxco River (Mexico), which has been affected by a wastewater leak from a local mining project, will be evaluated.The objective of this study is to determine, according to the parameters established by the Peruvian Ministry of the Environment, how the river has been impacted and how efficiently the leak has been blocked.To this end, four river monitoring points were analyzed.The results showed that monitoring points 1 and 2 have a high level of contamination, even after the leak has been blocked.On the other hand, monitoring point 3, after the leak was blocked, decreased the pollution level.While point 4 has not been affected by the leak.These results could help the company to apply some methods to purify the water in order not to affect the local population in a more centralized way.In addition, the Mexican government could use these results to control pollution caused by mining activity in the area.1 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Water quality analysis in Mantaro River, Peru, before and after the tailing's accident using the Grey clustering method(Insight Society, 2021-01-01)Problems with environmental accidents are increasing worldwide, which generates great damage to the environment. In fact, in July 2019, a tailing spill occurred that flowed into the Mantaro River, contaminating it with thousands of liters of waste. This had environmental consequences and social ones since there were people for and against mining, which is the principal economic activity in the area. In this way, this study proposes to quantify the damage caused by the tailing spill using the grey clustering method, which is based on grey systems theory. For this purpose, two sampling points were chosen for data collection and evaluation both before and after the accident, which allowed to measure the impact of metal concentrations and other physical-chemical parameters caused by accident. The results obtained from the study revealed increases in the concentration levels of metals such as aluminum, arsenic, among others, in some cases very high that exceeded the maximum permitted limits. Such findings could help local and national government authorities, people living and transiting near the river, and activities related to the use of the water in this river; since the quality of the river water can be lethal if the necessary measures are not taken. In addition, the method used in this study showed to be very practical and efficient during its application. Finally, it is advised that future research investigate each point along the Mantaro River and show the areas where the disaster had the most impact to develop some mitigating techniques. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Evaluation of water quality in the lower Huallaga River watershed using the Grey clustering analysis method(Science and Information Organization, 2021-01-01)Currently, the evaluation of water quality is a topic of global interest, due to its socio-cultural, environmental and economic importance, but in recent years this quality is deteriorating due to inadequate management in the conservation, disposal and use of water by the competent authorities, private-state entities and the population itself. An alternative to determine the quality of a water body in an integrated manner is the Grey Clustering Method, which was used in this study taking as an indicator the Prati Quality Index, with the objective of making an objective analysis of the quality of the water bodies under study. The case study is the Lower Watershed of the Huallaga River, located between the region of Loreto and San Martin, along which 12 monitoring stations were established to evaluate its surface water quality, through the analysis of 7 parameters: pH, BOD, COD, Total Suspended Solids (TSS), Ammonia Nitrogen, Substrates and Nitrates. Finally, it was determined that the water quality of eleven monitoring stations in the Lower Huallaga River Watershed are within the "Uncontaminated" category, while one monitoring station is within the "Highly Contaminated" category of the Prati Index, this due to its proximity to a landfill. The results obtained in this study, could be useful for the authorities responsible for the protection and sustainable conservation of the Huallaga River Watershed, in order to propose appropriate measures to improve its quality, additionally, this study could be a reference for future studies since the proposed method allowed to prioritize the quality level of the water bodies and identify critical areas. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Applying Grey systems and inverse distance weighted method to assess water quality from a river(Science and Information Organization, 2021-01-01)The Cañete River basin, in Peru, has suffered an increase in pollution due to various causes, among the main ones being the lack of knowledge, culture of individuals and municipal authorities, economic activities, among others. We analyze this degree of pollution reflected in the upper part of the Cañete river basin through the Grey Clustering method, based on grey systems, which is presented as a good alternative to evaluate water quality in a comprehensive way, making use of Historical data from the monitoring program for the years 2014 and 2015 with nine monitoring points carried out by the National Water Authority (ANA), 6 parameters were defined to evaluate: Hydrogen potential (pH), Biochemical oxygen demand, Chemical demand of Oxygen, Total Suspended Solids, Total Manganese and Total Iron based on the PRATI index. For the spatial distribution, interpolation surfaces of the clustering coefficients were created, using the Spatial Analyst extension of the ArcGIS software, which provides tools to create, analyze and map data in raster format or surfaces. The interpolation method used is Inverse Distance Weighted (IDW). The results of the evaluation showed that in 2014 the monitoring points determined, through the Grey Clustering method, a level of contamination "Uncontaminated" at each point except for point P7 which gives us an "Acceptable" level according to the PRATI indices, while for the year 2015 points P1 and P2 indicate a level of contamination "Moderately contaminated", point 3 an "Acceptable" level, after points P4 to P9 they present a level of "Not contaminated". Finally, the Grey Clustering analysis method will determine the water quality in the 9 monitoring points of the upper-middle basin of the Cañete River in the years 2014 and 2015. Allowing to observe the reduction of water quality in points P1 and P2 for the period of the years 2014 and 2015 respectively, being crucial to achieve water resource management among local governments that can insert awareness and sustainable development policies.1 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Grey clustering method for water quality assessment to determine the impact of mining company, Peru(Science and Information Organization, 2021-01-01)Mining operations have a significant impact on environment, where the quality of water is an important affected issue that need to be controlled. In that way, the Grey Clustering Method based on center-point triangular whitenization weight (CTWF), is an artificial intelligence criterion that evaluates water samples according to selected parameters, in order to realize an effective water quality assessment. In the present study, the analysis is made on the Crisnejas River Basin, by using fifteen monitoring points based on an investigation realized by the National Water Authority (ANA) in 2019, based on the Peruvian law (ECA) about water quality standards. The results reveal that almost all of the monitoring points on the Crisnejas River Basin were classified as “irrigation of vegetables unrestricted”, but only one point was classified as “animal drink”, which is ubicated in an urbanized area. This implies that mining discharges are being well treated by the company, but another deal is the contamination generated in towns. Further, the present study might be helpful to audit processes made by the state or companies, to justify the quality of surface waters using a more accurate methodology.2 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Impact of the mining activity on the water quality in Peru applying the fuzzy logic with the Grey clustering method(Science and Information Organization, 2021-01-01)Mining activity in the department of Junín, Peru, is intense, due to the great existing mining-metallic potential that exists in the place, the Yauli and Andaychagua rivers, located in the Yauli Province, belonging to Junín, receive a large volume of discharges causing deterioration in the quality of the water of these rivers. To evaluate this quality in an integral way, fuzzy logic will be applied with the Grey Clustering methodology, defining the central point triangular whitening weight functions (CTWF), having as grey classes the Environmental Quality Standards for water (ECA-Water), Category 3, which were modified for research purposes. Four monitoring points were evaluated, both upstream (point PY-01) and downstream (PY-02) of the Yauli River; as upstream (PA-01) and downstream (PA-02) of the Andaychagua river. From the analysis it was determined that the water quality in PY-01 is 0.7302, 0.8795 in the dry season and 0.5980 in the wet season; in PY-02, 0.5448, 0.6448 in dry season and 0.5628 in wet season were obtained. At point PA-01 it is 0.8213, 0.8691 in dry season and 0.7902 in wet season; In PA-02, 0.8385, 0.8827 in the dry season and 0.8118 in the wet season were obtained, concluding that there is good water quality, decreasing in wet seasons, this due to the influence of the rains in the contact waters. The research provides an integration of the parameters that are considered in the ECA-Water with other international standards allowing to determine a more precise evaluation of the quality status of the Yauli and Andaychagua rivers after receiving the effluents generated by the mining activity, benefiting the relevant authorities for decision making and providing a methodology that improves the analysis of the results obtained by the specific parameters that are evaluated in the environmental monitoring.1 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, How to determinate water quality using an artificial intelligent model based on grey clustering?(Institute of Advanced Engineering and Science, 2022-10-01)Water quality is an important topic for countries like Peru, where the mining sector is one of the main economic activities, so the study of its impact on water quality is also necessary to have a regular control of benefits and dangers. In this way, to achieve this objective, the chosen methodology was grey clustering, which is based on artificial intelligent theory. Specifically, the central point triangular whitening weight function better known as CTWF, which is an approach from grey clustering, was used. The case study was focused on the Mashcon and Chonta rivers, located in the province of Cajamarca, Peru, these rivers are directly affected by an open pit mine. The study was carried out taking into account thirteen monitoring points taken by National Water Authority (ANA). The results showed that all the points considered were classified as not contaminated, A1 category, this using the parameters of the Peruvian government. With these results, the mining company was able to demonstrate that they are taking the water quality into account and that they are making an effort to keep these rivers as healthy as possible. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Water Quality Assessment from an Environmental Liability Applying Grey Clustering and Harmonic Mean(Seventh Sense Research Group, 2023-01-01)The monitoring of the quality of the mine tailings from the La Tahona mining waste dump in 2018, located east of the city of Hualgayoc, is an important issue that must be analyzed, as it still represents a severe risk to the health of the city's inhabitants. In this way, the Grey Clustering method provides an alternative to evaluate the level of contamination of the sources near the mining tailings, taking into account the monitoring data with file number 0038-2018-DSEM-CMIN, carried out by the Directorate of Environmental Supervision in Energy and Mines of the Environmental Evaluation and Oversight Agency (OEFA), analyzing seven parameters of Prati index and Environmental Quality Standard, pH, Zinc, Suspended Solids, Arsenic, Lead, Iron and Cadmium. The results showed that the monitoring points of the water bodies near the effluent to the environmental liabilities of La Tahona were classified as high risk, which means that the efforts made to remediate the mentioned liabilities by the General Directorate of Mines of the Ministry of Energy and Mines (MINEM) do not comply with the quality parameters. Finally, the results obtained may be of help to OEFA, MINEM and the authorities of the Cajamarca region of Peru in the search for the correct treatment of the tailings effluents mentioned above. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Grey Systems Model to Assess Water Quality in Mantaro River in Peru(Multidisciplinary Digital Publishing Institute (MDPI), 2023-11-01)The section of the Mantaro River that flows through the department of Huancavelica, Peru, has been affected by toxic wastes and mineral residues from industrial and mining activities, which have directly impacted the water quality. In this work, a grey system model, based on the grey clustering method, was used to assess water quality. The grey clustering method was applied using the central point of triangular whitening weight functions (CTWF). In addition, the Prati index and the Environmental Quality Standards for water from the Peru government were revised and used for this study. In the case study, six physicochemical parameters, pH, DO, BOD, Cd, As, and Pb, at nine monitoring points were assessed along the Mantaro River. The results showed that the sixth monitoring point (P6), which is influenced by mining activity, was highly contaminated, while the other points were classified as noncontaminated. Finally, the results obtained by applying the grey clustering method can be useful to competent authorities, for decision making on water management in this watershed.