Multivariate and Spatial Analysis of Physicochemical Parameters in an Irrigation District, Chihuahua, Mexico

Nanomechanical properties of kidney stones, gallstones and oral stones compared with tap water scale by depth sensing indentation

This article focuses on a description of research performed to identify structural and mechanical properties differences between calculi in stones, such as gallstones, kidney stones, dental tartar, and saliva gland sialolite, were analyzed and compared with tap water stone, in order to set interrelations. In this study, biological hard pebble-like structures were analyzed and compared among them using Scanning Electron Microscopy (SEM), X-Ray diffraction (XRD), and Atomic Force Microscopy (AFM). In addition, Nanoindentation was used to obtain values as example in kidney stones the in; stiffness S = 27,827 ± 620 N/nm elastic modulus E = 27.3 ± 4.5 GPa, hardness H = 1.5 ± 0.5 GPa. Samples with the highest amounts of calcium and magnesium oxides were; Tap water stone (39.60%), followed by dental tartar (39.40%), saliva gland sialolite (29.20%), kidney stones (27.70%), and lastly the gallstones (0.30%). Kidney stones showed in particular, whewellite and kaoulinite crystallographic phases, that confers characteristics of greater crystallization with respect to the other stones. Kidney stones positioned in the major hardness stone in human body with 1.5 GPa. In general, samples with the highest amount of calcium oxides, also showed the highest mechanical properties of H and E. Microstructural characteristics and nano-hardness of tap water stone from drinking water where similar to those of dental tartar and saliva gland sialolite, more research still required to associate health concerns and tap water scale derived from drinking water known as hardwater.

Assessment of Spatial and Vertical Variability of Water Quality: Case Study of a Polymictic Polish Lake

UE regulations focus on methods of water quality monitoring and their use in rational management practices. This study investigated horizontal and vertical variations of electrical conductivity (EC), pH, dissolved oxygen (DO), and chlorophyll a (Chl-a) in a shallow polymictic lake. Monitoring of short-term variability of physical and chemical lake water parameters is a critical component in lake management, as it influences aquatic life. Based on the field research, maps of spatial distribution of the parameters were drawn. Using two methods: (1) a classical approach to water column measurements, from the top to the bottom (TB), in which the reference point is always a surface layer (SL), and (2) a newly introduced method of lake water quality monitoring based on a nearest neighbor (NN) approach; a comparison of higher and lower layers of the water column. By subtracting partial maps of spatial variability for different depths, final raster images were obtained. The NN method is rather absent in the limnology literature worldwide. Vertical and horizontal variability of the tested parameters in the polymictic, shallow Lake Bikcze (Poland) was presented in the results. In the presented paper, the commonly used TB method emphasized the role of the surface layer in shaping the variability of physicochemical parameters of lake waters. It shows a general trend of parameters’ changes from the top, to the bottom. The newly presented NN method, which has a major advantage in its simplicity and objectivity, emphasized structural differentiation within the range of variability. The nearest neighbor method was more accurate in showing the actual structure of fluctuation of parameters with higher fluctuation in the water column. Its advantage is a detailed recognition of the vertical variability of selected parameters in the water column. The method may be used regardless of the lake depth, its location in climatic zone, and/or region.

Assessment of hydro-geochemical properties of groundwater under the effect of desalination wastewater discharge in an arid area

Desalination to increase irrigation water supply for agricultural production is becoming important in water-scarce regions. While desalination has positive effects on the potential irrigation water quantity and quality, the technique may also be a considered potential source of groundwater pollution. The present study investigated the effects of desalination wastewater discharge on groundwater quality in an arid area in southern Iran for the 2012-2017 period. The chemical composition of the groundwater samples was evaluated considering pH, EC, Na⁺, Ca²⁺, Mg²⁺, SO₄²⁺, Cl^-, and HCO₃^-. The suitability of groundwater for drinking and irrigation purposes as well as spatial pattern of groundwater pollution was analyzed. The results showed that mean concentration of Na⁺, Ca²⁺, Mg²⁺, SO₄^2-, and Cl^- in all investigated wells increased from 148, 94, 46, 247, and 257 mg/L in 2012 to 282, 146, 71, 319, and 582 mg/L in 2017, respectively. Using Gibb's diagram, it was shown that the groundwater quality is slightly alkaline and primarily controlled by evaporation. Based on our findings, about 78% of the study aquifer displayed groundwater with good to excellent water quality that can be used for drinking and irrigation purposes. However, the eastern part of the aquifer was classified as unsuitable for use due to the disposal of desalination plant wastewater. The spatial distribution of WQI and other indices such as SAR, TDS, and TH showed that groundwater in the eastern part of the aquifer has deteriorated since the establishment of the desalination plants. To reverse this trend, it is important to implement regulations against wastewater discharge from desalination plants.

The Integration of Multivariate Statistical Approaches, Hyperspectral Reflectance, and Data-Driven Modeling for Assessing the Quality and Suitability of Groundwater for Irrigation

Sustainable agriculture in arid regions necessitates that the quality of groundwater be carefully monitored; otherwise, low-quality irrigation water may cause soil degradation and negatively impact crop productivity. This study aimed to evaluate the quality of groundwater samples collected from the wells in the quaternary aquifer, which are located in the Western Desert (WD) and the Central Nile Delta (CND), by integrating a multivariate analysis, proximal remote sensing data, and data-driven modeling (adaptive neuro-fuzzy inference system (ANFIS) and support vector machine regression (SVMR)). Data on the physiochemical parameters were subjected to multivariate analysis to ease the interpretation of groundwater quality. Then, six irrigation water quality indices (IWQIs) were calculated, and the original spectral reflectance (OSR) of groundwater samples were collected in the 302–1148 nm range, with the optimal spectral wavelength intervals corresponding to each of the six IWQIs determined through correlation coefficients (r). Finally, the performance of both the ANFIS and SVMR models for evaluating the IWQIs was investigated based on effective spectral reflectance bands. From the multivariate analysis, it was concluded that the combination of factor analysis and principal component analysis was found to be advantageous to examining and interpreting the behavior of groundwater quality in both regions, as well as predicting the variables that may impact groundwater quality by illuminating the relationship between physiochemical parameters and the factors or components of both analyses. The analysis of the six IWQIs revealed that the majority of groundwater samples from the CND were highly suitable for irrigation purposes, whereas most of the groundwater from the WD can be used with some limitations to avoid salinity and alkalinity issues in the long term. The high r values between the six IWQIs and OSR were located at wavelength intervals of 302–318, 358–900, and 1074–1148 nm, and the peak value of r for these was relatively flat. Finally, the ANFIS and SVMR both obtained satisfactory degrees of model accuracy for evaluating the IWQIs, but the ANFIS model (R2 = 0.74–1.0) was superior to the SVMR (R2 = 0.01–0.88) in both the training and testing series. Finally, the multivariate analysis was able to easily interpret groundwater quality and ground-based remote sensing on the basis of spectral reflectance bands via the ANFIS model, which could be used as a fast and low-cost onsite tool to estimate the IWQIs of groundwater.

A Multivariate Geomorphometric Approach to Prioritize Erosion-Prone Watersheds

Soil erosion is considered one of the main degradation processes in ecosystems located in developing countries. In northern Mexico, one of the most important hydrological regions is the Conchos River Basin (CRB) due to its utilization as a runoff source. However, the CRB is subjected to significant erosion processes due to natural and anthropogenic causes. Thus, classifying the CRB’s watersheds based on their erosion susceptibility is of great importance. This study classified and then prioritized the 31 watersheds composing the CRB. For that, multivariate techniques such as principal component analysis (PCA), group analysis (GA), and the ranking methodology known as compound parameter (Cp) were used. After a correlation analysis, the values of 26 from 33 geomorphometric parameters estimated from each watershed served for the evaluation. The PCA defined linear-type parameters as the main source of variability among the watersheds. The GA and the Cp were effective for grouping the watersheds in five groups, and provided the information for the spatial analysis. The GA methodology best classified the watersheds based on the variance of their parameters. The group with the highest prioritization and erosion susceptibility included watersheds RH24Lf, RH24Lb, RH24Nc, and RH24Jb. These watersheds are potential candidates for the implementation of soil conservation practices.

Groundwater Contamination, Subsurface Processes, and Remediation Methods: Overview of the Special Issue of Water on Groundwater Contamination and Remediation

This special issue of Water brings together ten studies on groundwater contamination and remediation. Common themes include practical techniques for plume identification and delineation, the central role of subsurface processes, the pervasiveness of non-Fickian transport, and the importance of bacterial communities in the broader context of biogeochemistry.