A geochemical and 3D-geometry geophysical survey to assess artificial groundwater recharge potential in the Pacific coast of Baja California,Mexico

A geophysical and geochemical study was carried out in the Maneadero aquifer, Baja California, Mexico, with the aim of identifying potential recharge locations for reclaimed water (RW). This coastal aquifer shows a significant decline in water quality, both as a result of salinization and the pollution by nitrates. Total dissolved solids (TDS) in an extreme case increased from 4 g l^?1 in 2000 to 27 g l^?1 in 2011. Nitrate as N–NO₃, reaches 46 mg l^?1. Based on their geochemistry and location, four water-quality zones are identified: (a) fresh water with TDS ≈ 1 g l^?1 in the upper creeks, (b) mixture between seawater and freshwater in the coast-proximal sections, (c) water significantly enriched in nitrate below and adjacent to the town of Maneadero, and (d) brackish water with no signs of current interaction with freshwater. The 3D geophysics identifies the influence of modern recharge areas and also buried flow-paths down to at least 30 m depth. The locations best suitable for aquifer recharge are those with equal or higher TDS concentrations (>2.5 g l^?1) than RW, which are located at the brackish water zone and/or at the coastal limits of the mixing zones.     

Magnetic susceptibility and electrical conductivity as a proxy for evaluating soil contaminated with arsenic,cadmium and lead in a metallurgical area in the San Luis Potosi State,Mexico

A total of 113 samples of waste and soil were collected from a site in the state of San Luis Potosi, Mexico, that was occupied for several years by the metallurgical industry. Specific magnetic susceptibility (MS), electrical conductivity (EC) and pH were determined, as well as the total and available concentrations of potentially toxic elements (PTEs) such as As, Cd, Cu, Fe, Pb and Zn, which may cause a health risk for humans, animals and ecosystems, and the concentrations of major ions in aqueous extracts of soils and wastes. The solid phases of the samples were also characterized. The results revealed that the soils and wastes exhibited elevated values of PTEs, MS and EC. For soils these values decreased with increasing distance from the waste storage sites. The MS values were elevated primarily due to the presence of Fe-oxyhydroxides, such as magnetite, hematite and goethite, which contain PTEs in their structure leading to a high correlation between the value of MS and the As, Cd, Fe and Pb contents (r = 0.57–0.91) as well as between the PTEs values (r = 0.68–0.92). The elevated EC values measured in the metallurgical wastes were the result of presence of the sulfate minerals of Ca, Mg and Fe. The pollution index, which indicates the levels of simultaneous toxicity from elements such as As, Cd and Pb, was determined, with extreme hazard zones corresponding to areas that exhibit high MS values (0.91 correlation). In conclusion, MS measurements can be used as an indirect indicator to evaluate the PTE contamination in metallurgical areas, and EC measurements can aid in the identification of pollution sources.     

Salt and nitrate exports from the sprinkler-irrigated Malfarás creek watershed (Ebro river valley,Spain) during 2010

Irrigated agriculture is a clear source of non-point pollution by salts and nitrogen species. The impact of such pollution should be quantified according to specific cases. The case of the Malfarás creek basin, a sprinkler irrigation district located in the semiarid Ebro valley in northeast Spain, has been evaluated. The main crops in the district were corn, barley and alfalfa, occupying 93 % of the irrigated area. The fate of water, salts and nutrients was evaluated by a daily water balance developed at a field scale for the natural year 2010. The yearly data of the whole set of 101 irrigated fields plus the non-irrigated area compared to the measured drainage produced a basin water balance with a low degree of error. The basin consumed 90 % of the total water input of which 68 % was used for crop evapotranspiration and the rest was lost due to non-productive uses. 16 % of the incoming water left the irrigation area as drainage water. The irrigated area was responsible for 87 % of the drainage. The average volume of drained water was 152 mm year^?1 for the whole basin area. The irrigated area drained 183 mm year^?1. The basin exported 473 kg of salt per hectare during 2010. This value was the lowest of the sprinkler irrigation areas in the Ebro valley, mainly due to the lower soil salinity. All the crops except barley received a nitrogen surplus of 10–50 % above their needs. The extra nitrogen entered the water cycle increasing the nitrate concentration in the aquifer water (150 mg L^?1) and drainage water (98 mg L^?1). In 2010 the mass of nitrogen exported by drainage was 49 kg per irrigated hectare. This value is too high for this type of irrigation system and implies that 17 % of nitrogen applied as a fertilizer was lost to drainage water. The key to decreasing the nitrogen leaching and pollution that it causes could be appropriate time-controlled fertigation along with better irrigation scheduling.     

Can a Training Image Be a Substitute for a Random Field Model?

In most multiple-point simulation algorithms, all statistical features are provided by one or several training images (TI) that serve as a substitute for a random field model. However, because in practice the TI is always of finite size, the stochastic nature of multiple-point simulation is questionable. This issue is addressed by considering the case of a sequential simulation algorithm applied to a binary TI that is a genuine realization of an underlying random field. At each step, the algorithm uses templates containing the current target point as well as all previously simulated points. The simulation is validated by checking that all statistical features of the random field (supported by the simulation domain) are retrieved as an average over a large number of outcomes. The results are as follows. It is demonstrated that multiple-point simulation performs well whenever the TI is a complete (infinitely large) realization of a stationary, ergodic random field. As soon as the TI is restricted to a limited domain, the statistical features cannot be obtained exactly, but integral range techniques make it possible to predict how much the TI should be extended to approximate them up to a prespecified precision. Moreover, one can take advantage of extending the TI to reduce the number of disruptions in the execution of the algorithm, which arise when no conditioning template can be found in the TI.     

Quantifying Asymmetric Parameter Interactions in Sensitivity Analysis: Application to Reservoir Modeling

In this paper, a new generalized sensitivity analysis is developed with a focus on parameter interaction. The proposed method is developed to apply to complex reservoir systems. Most critical in many engineering applications is to find which model parameters and parameter combinations have a significant impact on the decision variables. There are many types of parameters used in reservoir modeling, e.g., geophysical, geological and engineering. Some parameters are continuous, others discrete, and others have no numerical value and are scenario-based. The proposed generalized sensitivity analysis approach classifies the response/decision variables into a limited set of discrete classes. The analysis is based on the following principle: if the parameter frequency distribution is the same in each class, then the model response is insensitive to the parameter, while differences in the frequency distributions indicate that the model response is sensitive to the parameter. Based on this simple idea, a new general measure of sensitivity is developed. This sensitivity measure quantifies the sensitivity to parameter interactions, and incorporates the possibility that these interactions can be asymmetric for complex reservoir modeling. The approach is illustrated using a case study of a West Africa offshore oil reservoir.     

The state of the environment in Mexico

The present work evaluates the state of the environment in Mexico based on indicators of the present status of the country’s natural resource management, social and economical conditions and anthropogenic modifications. The Mexican environment is interpreted as a spatially open system having a historical character that is essentially determined by the continual interaction between nature, society and economy. The landscape approach is followed, considering as units of territorial analysis each one of the 145 biophysical environmental units included in the national physiographic regionalization. The assessment of 16 indicators for each biophysical environmental unit was made considering their regional environmental integrity problems, the degree of disarticulation of their structure and function, and the alteration of their territorial structure, all of which determine whether or not they accomplish their environmental functions and achieve environmental stability. The classification of the state of the environment included 5 categories in 8 combinations represented in the map of the state of the environment in Mexico for the year 2008. The map shows that nearly 47.10% of the country’s surface has an environmental status ranging between unstable and critical, the problematic areas being mostly concentrated in the southeast and center of the national territory.     

Dispersion modeling of air pollutants in the atmosphere: a review

Modeling of dispersion of air pollutants in the atmosphere is one of the most important and challenging scientific problems. There are several natural and anthropogenic events where passive or chemically active compounds are emitted into the atmosphere. The effect of these chemical species can have serious impacts on our environment and human health. Modeling the dispersion of air pollutants can predict this effect. Therefore, development of various model strategies is a key element for the governmental and scientific communities. We provide here a brief review on the mathematical modeling of the dispersion of air pollutants in the atmosphere. We discuss the advantages and drawbacks of several model tools and strategies, namely Gaussian, Lagrangian, Eulerian and CFD models. We especially focus on several recent advances in this multidisciplinary research field, like parallel computing using graphical processing units, or adaptive mesh refinement.