In this research, vegetation indices (VIs) were analyzed as indicators of the spatio-temporal variation of vegetation in a semi-arid region. For a better understanding of this dynamic, interactions between vegetation and climate should be studied more widely. To this end, the following methodology was proposed: (1) acquire the NDVI, EVI, SAVI, MSAVI, and NDMI by classification of vegetation and land cover categories in a monthly period from 2014 to 2018; (2) perform a geostatistical analysis of rainfall and temperature; and (3) assess the application of ordinary and uncertainty least squares linear regression models to experimental data from the response of vegetation indices to climatic variables through the BiDASys (bivariate data analysis system) program. The proposed methodology was tested in a semi-arid region of Zacatecas, Mexico. It was found that besides the high values in the indices that indicate good health, the climatic variables that have an impact on the study area should be considered given the close relationship with the vegetation. A better correlation of the NDMI and EVI with rainfall and temperature was found, and similarly, the relationship between VIs and climatic factors showed a general time lag effect. This methodology can be considered in management and conservation plans of natural ecosystems, in the context of climate change and sustainable development policies.
The presence of arsenic in groundwater constitutes a hazard for the environment and human health, and the determination of its source has become a global challenge, which can be approached by defining the natural background levels (NBL) in conjunction with the indicator kriging method, with the aim of delineating anthropogenically contaminated areas. However, having a unique value of NBL for large areas can generate interpretation errors. This research integrates the determination of the flow systems present in the Calera Aquifer, and the definition of the natural background levels in each flow system by making estimation maps in ArcGIS using two databases, 10 years apart, to evaluate the spatio-temporal variation of arsenic in groundwater. The results indicate a notable increase in the probability of exceeding the arsenic NBL, mainly in the intermediate flow, which may be due to movement resulting from mining activities as well as a mixture of regional and intermediate flows caused by the extraction of water for agriculture and drinking water supplies. The presented values exceed the maximum limits allowed for human consumption, as stated by the World Health Organization.
One-third of the global population depends on groundwater for drinking, which is an even larger proportion for arid regions. The integration of isotopic and geophysical applications has been very useful in understanding the process of groundwater recharge. The aim of this study is to define a conceptual model that describes groundwater functions within an aquifer located in a semi-arid region by identifying recharge patterns based on the isotopic characteristics of: Rainfall, surface water, shallow and deep groundwater, and incorporating regional geophysical data. We demonstrated that rainfall was affected by sub-cloud evaporation and altitude. Shallow and deep modern groundwater samples were clustered and exhibited similar evolution from rainfall. However, different groups recharged from different precipitation sources compared to the local one. In the current study, we analyzed the isotopic evolution of deep groundwater over a 10-year period, which was mainly affected by the incorporation of different flows with different isotopic signatures and the hydrodynamics of the area. We performed two geoelectrical sections in the study area to improve the understanding of the hydrogeological setting and water movement patterns. The new conceptual model should help stakeholders in the context of water management policies for the study area.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.