10 research outputs found
Simulation of rainfall process in mountainous regions and sports athletes’ fatigue recovery based on convolutional neural network
Agricultural climate change based on GIS and remote sensing image and the spatial distribution of sports public services
Identification of groundwater contamination zones and its sources by using multivariate statistical approach in Thirumanimuthar sub-basin, Tamil Nadu, India
Hydrogeochemical studies have been made in the study area by using multivariate statistical analysis, which is mainly helpful for interpretation of complex data matrices to better understand the geochemical evolution of the area and it allows identifying the possible factors/sources that influence water systems. The spatial distribution of electrical conductivity reveals that an untreated industrial effluents, landfill and anthropogenic activities affecting their groundwater quality in its vicinity and the surrounding area. The dominance of ions was in the order of Na+ > Ca2+ > Mg2+ > K+ = Cl− > HCO3 − > SO4 2− > NO3 − and Ca2+ > Mg2+ > Na+ > K+ = HCO3 − > Cl− > NO3 − > SO4 2− during pre monsoon (PRM) and post monsoon (POM), respectively. The statistical results reveals that the groundwater chemistry gets altered by silicate weathering, ion exchange, leaching, anthropogenic input from agricultural return flow and longer distance of migrating groundwater. The hydrogeochemical regimes are distributed along the upstream side, northwestern, western and eastern parts of the study area. The study highlights the descriptive capabilities of conventional and multivariate techniques as effective tools in groundwater evaluation