Quality Index Map Research Articles

Integrating GEE and IWQI for sustainable irrigation: A geospatial water quality assessment

The surface and sub-surface water quality is one of the decisive parameters for sustainable agriculture and water resources management. Deteriorating water quality impacts the irrigation, crop production, and human health. Therefore, the present work made an attempt to identify the water suitability for irrigation using the contemporary approach i.e. Irrigation Water Quality Index (IWQI) and Zone mapping using GIS techniques, and demonstrated for case of Wadhwan, Gujarat India. Three indices i.e., NDVI, NDWI, and LSWI were mapped using Landsat satellite imagery, whereas, Watermask index was mapped using Sentinel II satellite imagery for the assessment of the availability of water in different forms. The IWQI has applied to categorize the water quality as severe, high, moderate, low, and no restriction. The IWQI in the study area ranges from 6.4 to 62.5. The overall the water quality of study area shows that the 13.64 % of the region in severe restriction range, 56.82% in high restriction range, and 29.54% in moderate restriction range, which is in alarming for farmers and policy makers. The GIS zoning map effectively visualized the spatial distribution of IWQI, helping decision-makers to identify severity zones. Furthermore, the Piper diagram analysis has been performed, which shows that the water quality of the study area falls under mixed Ca2+-Mg2+-Cl-, mixed Ca2+-Na+-HCO3-, and Na-HCO3 types. The results revealed that major areas are in moderate to severe restriction zones, lying under deteriorated water quality, and need immediate attention for improvement before use. The IWQI advances SDG 2 (Zero Hunger) by optimizing water quality for crop production and SDG 6 (Clean Water and Sanitation) by ensuring sustainable water resource management, while indirectly supporting SDG 15 (Life on Land) through improved soil health and land management practices.

Assessing the Groundwater Quality in Urban Areas Using the DEMATEL Method

The Dhanbad area in Jharkhand, India, is a significant coal mining region located in the middle of the Damodar River basin. The geological composition of the area ranges in age from to Recent, encompassing, granites, pegmatite, and gneisses. These rocks are accompanied by bands of s and amphibolites. In this particular region, groundwater occurrence and movement are primarily restricted to semi weathered/weathered and fractured rocks. The movement of groundwater depends on various factors, including the thickness, size, extent, and openness of the weathered zone, as well as the interconnections of fractures within the rocks. Due to the dynamic nature of groundwater resources, it is susceptible to various factors that can impact its availability and quality. The expansion of irrigation activities, industrialization, and urbanization in the area can have significant implications for the groundwater resources. These activities can lead to increased water demand, contamination risks, and changes in the hydrological balance. Given the importance of groundwater as a vital resource, it becomes crucial to monitor and conserve it effectively. Monitoring techniques, such as hydrological studies, geophysical surveys, and groundwater level measurements, can provide valuable information about the status and behavior of groundwater resources. Conservation efforts may involve implementing sustainable water management practices, promoting water-use efficiency, and controlling pollution sources. By utilizing GIS and available physic-chemical data, the study seeks to generate a comprehensive water quality index map that can assist in making informed decisions regarding water resource management and protection in the Dhanbad area. This understanding can help in developing sustainable strategies to ensure the availability and quality of groundwater in areas like, where natural resources are intricately linked to human activities and industrial development. The variations in the resistivity of water-bearing weathered/fractured rocks in the Dhanbad area depend on the specific geological characteristics of the rocks and their water content. The resistivity refers to the rock's ability to resist the flow of electric current and can provide insights into the rock's porosity and permeability, which are crucial factors for groundwater movement. The depth to groundwater in the area can vary and is typically measured from below ground level. This depth is influenced by factors such as local topography, rainfall patterns, and geological conditions. The presence of active and abandoned coal mines, waste dumps, coal washeries, coking coal plants, and thermal power plants can introduce pollutants into the environment. These pollutants have the potential to contaminate groundwater, affecting its quality and usability. It is important to address these environmental concerns and prioritize the implementation of effective measures to mitigate the impact of coal mining and related activities on groundwater resources. Alternative parameters taken as Total dissolved solid, total hardness, Nitrate, ammonia nitrogen, Fluoride, Fluoride. the first ranking training is obtained with the lowest quality of compensation.

Quantitative and qualitative assessment of groundwater resources for drinking water supply in the peri-urban area of Dhaka, Bangladesh

Groundwater is the primary source of freshwater for drinking, industrial, and agricultural water in many nations worldwide. This vital resource is deteriorating due to rapidly growing urbanization, pollution, overexploitation, and climate change. However, it is unclear how much this specific resource deteriorates over time. Therefore, this study aimed to investigate groundwater resources qualitatively and quantitatively in the peri-urban area of Dhaka, Bangladesh. The study used the modified Mann-Kendall trend test, hotspot analysis, groundwater recharge estimation, multivariate statistical analysis, and the water quality index (WQI) mapping. The trend analysis of groundwater levels indicates that in the most recent year, groundwater levels close to industrial areas have declined at a maximum rate of 1.18 m/year. The estimated groundwater recharge reveals that it is highest (480 mm/year) on rural agricultural land and lowest (220 mm/year) in urban areas. With a 99% confidence level, the groundwater water trend cluster analysis indicates the hotspots of groundwater level depletion near the industrial area. The results showed that Mn, Fe, and As exceeded the World Health Organization's (WHO) recommended limit for drinking water by 76.92%, 61.53%, and 23.07%, respectively. The principal component analysis and hierarchical clustering results indicate that groundwater quality is influenced by rock-water interaction and human interventions. The WQI results suggest that 47.05% of the samples were excellent, 7.69% were good, 9.96% were poor, 17.65% were very poor, and the remaining 17.65% were unfit for drinking purposes. The depletion of groundwater hotspots was identified in northeast region of the study area. Overall, an integrated framework was proposed that offers a holistic approach to sustainable groundwater resource management amid urbanization and industrialization. These findings will provide an essential guideline for groundwater resource management in the peri-urban area of Dhaka city.

Spatial evaluation of groundwater vulnerability using the DRASTIC-L model with the analytic hierarchy process (AHP) and GIS approaches in Edo State, Nigeria

The drinking of contaminated water is potentially hazardous to the well-being of humanity. Effective groundwater management depends on detecting groundwater contamination before it hits a critical point. The DRASTIC framework, modified globally to include land use (L), is utilized to evaluate groundwater vulnerability in various regions. In this study, an assessment of groundwater's susceptibility to contamination and a water quality index map to determine its fitness for Edo State have been done using the DRASTIC, DRASTIC-AHP, and DRASTIC-L-AHP models. The distinction of potential-risk water zones in Edo State, Nigeria, was made possible by the GIS that was used to create and combine several attribute maps. Results established that in the study area, very low (1,741.683 km2; 45%), low (1,741.683 km2; 10%), moderate (3,483.366 km2; 20%), and high (4,354.2075 km2; 25%) risk zones of groundwater contamination were identified on the overall DRASTIC-L-AHP map. The study found a significant pollution risk in one-fourth of the area, primarily in the Edo north and south regions of the study area. The significance of each factor for groundwater susceptibility and contamination risk was evaluated through a sensitivity analysis (SA). The SA indicated that the impact of the vadose zone is the most efficient variable in the DRASTIC-L-AHP model, with an effective weight value of 33.45% that is much larger than the theoretical value of 21.51%. The DRASTIC-L-AHP model, validated through hydrochemical analysis, is the least inaccurate and suitable for the current study area, serving as a useful pre-decisional tool for managing and preserving groundwater.

Land suitability assessment for wheat-barley cultivation in a semi-arid region of Eastern Anatolia in Turkey.

The efficient use and sustainability of agricultural lands depend heavily on the characteristics of soil resources in a given area, as different soil properties can significantly impact crop growth and yield. Therefore, land suitability studies play a crucial role in determining the appropriate crops for a given area and ensuring sustainable agricultural practices. This study, conducted in Tusba District-Van, Turkey, represents a significant advancement in land suitability studies for wheat-barley cultivation. Using geographic information systems, the analytical hierarchical process method, and the standard scoring function, lands were determined based on the examined criteria for the suitability of wheat-barley cultivation. One of this study's main findings is identifying critical factors that influence the suitability of land for wheat-barley cultivation. These factors include slope, organic matter content, available water capacity, soil depth, cation exchange capacity, pH level, and clay content. It is important to note that slope is the most influential factor, followed by organic matter content and available water capacity. A Soil Quality Index map was produced, and the suitability of wheat-barley production in the studied area was demonstrated. More than 28% of the study area was very suitable for wheat-barley production (S2), and more than was 39% moderately suitable (S3). A positive regression (R2=0.67) was found between soil quality index values and crop yield. The relationship between soil quality index values and crop yield is above acceptable limits. Land suitability assessment can minimize labor and cost losses in the planning and implementation of sustainable ecological and economic agriculture. Furthermore, land suitability classes play an active role in the selection of the product pattern of the area by presenting a spatial decision support system.

Development of overall quality index and overall quality map according to tensile mechanical properties and artificial aging heat treatment conditions for cast aluminum alloy using multi-criteria decision-making and multiple regression model

Development of overall quality index and overall quality map according to tensile mechanical properties and artificial aging heat treatment conditions for cast aluminum alloy using multi-criteria decision-making and multiple regression model

A multivariate approach for mapping a soil quality index and its uncertainty in southern France

AbstractPedometricians have spent a lot of effort on mapping soil types and basic soil properties. However, end‐users typically need a more elaborate soil quality index for land management. Soil quality indices are typically derived from multiple individual soil properties by evaluating whether specific criteria are met. If this is based on individually mapped soil properties, then an important consequence is that cross‐correlations between soil properties are ignored. This makes it impossible to quantify the uncertainties associated with the mapped indices. The objective of this study was to map a soil potential multifunctionality index for agriculture (Agri‐SPMI) over a 12,125 km2 study region located along the French Mediterranean coast to help urban planners preserve soils of the highest quality. The index considered the ability of soils to fulfil four functions under five land use scenarios. A binary map represented each soil function fulfilment for a given scenario. The final soil quality index map was the sum of the 20 binary maps. A regression cokriging model was developed to map the basic soil properties first individually from legacy soil data and spatial soil covariates using a random forest algorithm, and next, interpolate the residuals using cokriging and the linear model of coregionalisation. The mapping uncertainties of soil properties were propagated by calculating the soil quality index over 300 stochastic simulations of soil properties derived from the linear models of coregionalisation. Results showed a poor prediction accuracy of the quality index, mainly because some soil properties were poorly predicted (notably available water capacity and coarse fragments) and used in combination with extreme thresholds that defined land suitability. Overall, the uncertainty was correctly quantified because the stochastic simulations reproduced the width of the observed distribution well, but the shapes of the distributions differed considerably from those of the observations. We envisage some ways for improvement, such as creating probability maps instead of the mean from simulations, and changing the prediction support from point to area.Highlights The study mapped a soil quality index (Agri‐SPMI) to help preserve soils of highest quality along the French Mediterranean coast. The Agri‐SPMI considered the ability of soils to fulfill four functions under five land use scenarios, derived from multiple individual soil properties. A regression cokriging model was developed to map the basic soil properties, followed by interpolating the residuals using cokriging and the linear model of coregionalisation. The study accurately quantified mapping uncertainties using stochastic simulations, but the soil quality index prediction accuracy was poor, with suggestions for improvement.

Hydrochemical Characterization and Quality Assessment of Groundwater in Hatiya Island, Southeastern Coastal Region of Bangladesh

Groundwater is a vital source of fresh water for drinking and agricultural purposes in the region of Hatiya Island, Bangladesh, yet it is subject to contamination by natural and anthropogenic activities. Over time, the contamination has resulted in a variety of negative effects on human health. This research aims to examine groundwater hydrogeochemical characterization and suitability for irrigation and drinking purposes on different indices utilizing a combined geochemical method, multivariate statistical approaches, and geospatial analysis. Results of hydrogeochemical analyses of 15 groundwater samples from the intermediate aquifer (60–90 m depth) represent the order of cations, anions, and metal concentrations as Na+ > Mg2+ > Ca2+ > K+, Cl− > SO42− > HCO3− > NO3−, and Fe > I > Br > Mn > As, respectively. Saltwater intrusion has been determined to be the most important hydrogeochemical process influencing the chemistry of groundwater. Principal component analysis, Pearson’s correlation matrix, and hierarchical cluster analysis indicate that groundwater quality is highly governed by geogenic influences. This information has been evaluated using a drinking water quality index map, which found that six (40%) of the groundwater samples are suitable for human consumption, whereas the other nine (60%) are unfit for drinking. The analysis of irrigation quality parameters revealed that eight (54%) of the groundwater samples are in excellent or good condition for agricultural uses; however, the other seven (46%) samples are unsuitable.

Multiple Quadratic Polynomial Regression Models and Quality Maps for Tensile Mechanical Properties and Quality Indices of Cast Aluminum Alloys according to Artificial Aging Heat Treatment Condition

To evaluate the quality of cast aluminum alloys quantitatively and intuitively, quality index and quality map have been used. Quality index and quality map are to quantitatively evaluate the quality of cast aluminum alloys according to yield strength (YS), ultimate tensile strength (UTS), elongation to fracture (Ef), and strain energy density (W). There are some quality indices such as Q, QR, QC, and Q0. The quality maps are generated to intuitively evaluate the quality level based on the quality indices. These quality indices and quality maps show the quality levels according to the pairs of tensile mechanical properties such as UTS and Ef, or YS and Ef, or YS and W. By using these quality maps, it is impossible to directly evaluate the quality levels according to the artificial aging heat treatment condition. We develop multiple quadratic polynomial regression models and quality maps for tensile mechanical properties and quality indices of the cast aluminum alloys according to artificial aging heat treatment condition. The performances of the regression models are evaluated using the mean absolute errors, mean relative errors, and coefficients of determination. The regression models and quality maps could be widely used to evaluate the quality of the cast aluminum alloys according to the aging heat treatment conditions and determine the rational aging heat treatment condition.

Characteristics of Dissolved Organic Matter and Its Relationship with Water Quality along the Downstream of the Kaidu River in China

The variability in the quality of water that runs along the course of a river, flowing out of a mountain pass, through an agricultural oasis and into a lake, has been a key topic of research in recent years. In this study, the characteristics of dissolved organic matter (DOM) along the river flow, and its relationship with water quality, were analyzed using the Canadian water quality index (CWQI), parallel factor (PARAFAC) and self-organizing map (SOM). The study results include: (1) The conclusion of field sampling along the lower reaches of the Kaidu River and laboratory measurements of water quality parameters, using CWQI to determine the water quality index of the lower Kaidu River, ranging between 59.58 and 93.47. The water quality of the lower reaches of the Kaidu River generally ranges between moderate and good, and can meet the water use requirements of Class II water function standards. (2) The DOM composition of the river predominantly contained three fluorescence components, while the three fluorescence indices of the water body varied less in different river sections. Based on the SOM training model, the fluorescence intensity of the C1 component was larger among the three fluorescence components, followed by the C2 component, and the smallest fluorescence intensity of the C3, which was dominated by humic-like substances, with a high authigenic origin and humification degree. (3) The fluorescence index and fluorescence components were correlated with water quality parameters, and it was found that C1, C2 and C3 were negative and correlated significantly with SO42- and Total-dissolved solids (TDS) concentrations; FI, HIX and BIX showed strong positive correlations with SAL and Cu and negative correlations with dissolved oxygen (DO). This study provides a scientific basis for surface water quality monitoring and water quality pollution management in the Kaidu River.

Correlation, Regression Analysis, and Spatial Distribution Mapping of WQI for an Urban Lake in Noyyal River Basin in the Textile Capital of India

Nowadays, the major threat to humans occurs due to water quality deterioration. The quality of water creates a new sign for the public to prevent them from waterborne diseases. This study uses sensitive water quality parameters obtained from the northeast monsoon season, October 2021, at different locations in Mooli Kulam lake (11°07′17.6″ N, 77°22′59.9″ E) of Tiruppur District, Tamil Nadu, India. The parameters considered for the analysis of lake water quality are closely included with drinking and irrigation parameters. The northeast monsoon samples collected from the lake were analysed and the Water Quality Indexing was applied to the dataset using three methods, namely, the Weight Arithmetic method, the Canadian Council of Ministers of the Environment, and Horton’s method. The parameters are divided into drinking water variables and irrigation water variables. This study includes water quality index mapping using Inverse Distance Weighting interpolation of the spatial distribution method using ArcMap 10.8. The dataset was subjected to correlation and regression analysis in order to determine the most significant pollutant. A total of 10 sampling stations and 23 water quality parameters have been analysed. The results obtained show that the lake has high eutrophication with compounds of potassium, iron, and nitrates.

Groundwater Quality Index Mapping for Irrigation Purposes in the El Hezma‐El Hmila Aquifer (Medenine, Tunisia)

AbstractIn the El Hezma‐El Hmila region (Southeastern Tunisia), the Mio‐Plio‐quaternary aquifer is subject to excessive extraction of groundwater, leading to drops in potentiometric surfaces and a subsequent degradation of groundwater quality. Therefore, surveys have been conducted to provide some basic information on groundwater suitability. The assessment of the water quality for agricultural purposes is the principal aim of this study. To achieve this objective, an integrated approach to processing hydrogeological and geochemical data is used. The analytical physicochemical data from wells in the study area are processed with the geographic information system (GIS) using a multi‐criteria decision analysis (MCDA), simulationsgraphics, and an irrigation water quality index (IWQI). The two obtained IWQI maps based on GIS‐MCDA show different quality classes. In fact, using the weighted linear combination (WLC), only two classes (medium and low suitability with 11.5 and 88.5% of the study area, respectively) are displayed, whereas the Boolean logic model reveals four classes (good, permissible, doubtful, and unsuitable) for irrigation purposes. In this regard, the obtained results areconsidered an appropriate tool for agricultural planning as well as a guide for decision makers to identify areas where irrigation can be suitable without affecting both soil and water quality.

Application of GIS Technique to Assess the Habbaniya Lake Water for Human Consumption

Geographic Information System (GIS) technique was used in this study to produce a Water Quality Index (WQI) map to assess the water of Habbaniya Lake for drinking purposes. Sixteen samples of fresh surface water were collected and analyzed to verify the physiochemical parameters of the WQI. These parameters include Total Dissolved Solids, pH, Calcium, Magnesium, Sodium, Potassium, Chloride, Sulfate, and Nitrates. The result of these parameters has been transferred to the GIS platform to construct a water quality database and map of spatial distribution for each parameter using the inverse distance weight (IDW technique). The results of these parameters were also used to calculate irrigation water quality index values, and transferred to the GIS platform for the production of the water quality index map. The spatial distribution index of drinking water in Habbaniya Lake is depicted on this map. It shows that WQI for all water samples is within the second category (50-100) except (S 5 and S 8) below the second category (<50). The short-scope of WQI indicates that the water quality of Habbaniya Lake has been considered as convergent water quality that fluctuated from excellent water to good water for human drinking. It shows also that the northwestern part of Habbaniya Lake waters is more appropriate for drinking since the Al-Warar Canal drains in this part, which takes its water mainly from the Euphrates River.

Hydrogeochemical characterization and quality assessment of groundwater resource in Savar - an industrialized zone of Bangladesh.

Savar Upazila in the Dhaka District is a rapidly expanding city with a diverse range of industries and agricultural activities. This expansion poses environmental challenges including the threat to groundwater contamination. Based on these considerations, the objective of this research is to carry out ashallowgroundwater hydrogeochemical characterization and an assessment of the suitablity of the groundwaterfor drinking and irrigational purposes using a geochemical approach, multivariate statistical techniques, and some indices ofgroundwater quality. Thehydrogeochemical analyses of 42 groundwater samples from shallow depths (18 - 76m) showed that the order of concentrations of cations, anions, and metals was Ca2+ > Na+ > Mg2+ > K+, HCO3- > Cl- > SO42- > NO3-, and Cr > As > Pb > Mn > Fe, respectively. Weathering of silicates was found to be the most significant hydrogeochemical process governing the chemistry of groundwater. Cation exchange also plays a significant role in the evolution of thegroundwater chemistry. Principal component analysis and hierarchical cluster analysis suggested that anthropogenic activities are influencing groundwater quality. A drinkingwater quality index map showed that about 91% of the groundwater samples were in the excellent category and suitable for human consumption, with only a few samples exceeding the standards of theWHO and Bangladesh for concentrations ofCa2+, Mg2+, HCO3-, Fe, Mn, and As. An analysis of irrigation quality parameters found that most of the groundwater samples were eitherexcellent or good for agricultural uses, except for one samplein the Tetuljhora Union that was unsuitable based on residual sodium carbonate. This finding may be useful to local governments in understanding the current status of groundwater quality, tracking potential threats of contamination, and initiating appropriate measures for long-term groundwater resource management.

Effect of shifting cultivation and fallow on soil quality index in Mokokchung district, Nagaland, India

BackgroundShifting cultivation is a major agriculture practice in the Nagaland state of India. This study examines the effect of shifting cultivation and the length of the fallow period on soil quality index (SQI). Four sites were selected for the study, viz., a shifting cultivation site (SCS), a 3-year-old fallow land (FL-3), a 7-year-old fallow land (FL-7), and a 12-year-old fallow land (FL-12). Soil parameters were recorded seasonally and SQI was calculated from the minimum data set.ResultsWith the increase in the fallow period, the values of conductivity, soil organic carbon, available nitrogen, available phosphorus, exchangeable potassium, moisture, clay, and cation exchange capacity of soil increased. Meanwhile, soil pH and bulk density decreased with fallow duration. The additive SQIa values were in the order SCS < FL-3 < FL-12 < FL-7; meanwhile, the weighted SQIw values were in the order SCS < FL-3 < FL-7 < FL-12. It is also observed that the SQI value decreases with the increase in soil depth under both the weighted and additive indexes. SCS with the lowest SQI value reflects the reduced soil organic carbon (SOC) and macronutrients. Increased SOC levels in site FL-12 (2.88–3.94%) may be one reason for its higher SQI value.ConclusionsOur study highlights that unsustainable practices of shifting cultivation and reduction in the fallow period negatively affect soil quality. Furthermore, the study also recommends the use of the weighted method of SQI as it agrees with the reports of land use causing alteration in the soil quality. Our findings may be utilized to quickly access and disseminate information to the stakeholders and aid in constructing local soil quality index maps of the region. There is an urgent need for a rapid, cost and resource-efficient soil quality assessment and SQI may be one tool that achieves this goal.

Multi-Indicator and Geospatial Based Approaches for Assessing Variation of Land Quality in Arid Agroecosystems

Novel spatial models for appraising arable land resources using data processing techniques can increase insight into agroecosystem services. Hence, the principal component analysis (PCA), hierarchal cluster analysis (HCA), analytical hierarchy process (AHP), fuzzy logic, and geographic information system (GIS) were integrated to zone and map agricultural land quality in an arid desert area (Matrouh Governorate, Egypt). Satellite imageries, field surveys, and soil analyses were employed to define eighteen indicators for terrain, soil, and vegetation qualities, which were then reduced through PCA to a minimum data set (MDS). The original and MDS were weighted by AHP through experts’ opinions. Within GIS, the raster layers were generated, standardized using fuzzy membership functions (linear and non-linear), and assembled using arithmetic mean and weighted sum algorithms to produce eight land quality index maps. The soil properties (pH, salinity, organic matter, and sand), slope, surface roughness, and vegetation could adequately express the land quality. Accordingly, the HCA could classify the area into eight spatial zones with significant heterogeneity. Selecting salt-tolerant crops, applying leaching fraction, adopting sulfur and organic applications, performing land leveling, and using micro-irrigation are the most recommended practices. Highly significant (p &lt; 0.01) positive correlations occurred among all the developed indices. Nevertheless, the coefficient of variation (CV) and sensitivity index (SI) confirmed the better performance of the index developed from the non-linearly scored MDS and weighted sum model. It could achieve the highest discrimination in land qualities (CV &gt; 35%) and was the most sensitive (SI = 3.88) to potential changes. The MDS within this index could sufficiently represent TDS (R2 = 0.88 and Kappa statistics = 0.62), reducing time, effort, and cost for estimating the land performance. The proposed approach would provide guidelines for sustainable land-use planning in the studied area and similar regions.

Clinical and laboratory characterization of patients with localized scleroderma and response to UVA-1 phototherapy: In vivo and in vitro skin models.

Localized scleroderma (LS) is a rare disease leading to progressive hardening and induration of the skin and subcutaneous tissues. LS is responsive to UVA-1 phototherapy, though its exact mechanism of action dermal fibrosis is yet to be fully elucidated. We aimed to investigate the molecular changes induced by UVA-1 rays in human primary fibroblasts cultures. A total of 16 LS patients were treated with medium-dose UVA-1 phototherapy. At baseline, during and after therapy, Localized Scleroderma Assessment Tool, Dermatology Life Quality Index and lesions' staging and mapping were performed along with high-frequency ultrasound (HFUS) examination for dermal thickness assessment. Gene expression analysis for 23 mRNA transcripts, in vitro UVA-1 irradiation and viability tests were realized on lesional fibroblasts' primary cultures, before and 3 months after therapy. The dermal thickness, the LoSCAT and the DLQI progressively decreased starting from the last phototherapy session up to the 6 and 9 month follow-ups (-57% and -60%, respectively). Molecular gene analysis (rt-PCR) revealed that UVA-1 phototherapy exerts multiple effects: the activation of specific anti-fibrotic pathways (e.g., overexpression of CTHRC1 and metalloproteases 1, 2, 7, 8, 9, 12, suppression of TIMP-1), the downregulation of peculiar pro-fibrotic pathways (e.g., downregulation of TGF-ß, TGF-ßrII, Grb2, SMAD 2/3, TNRSF12A, CTGF) through a significant overexpression of IL-1ß; the stabilization of collagen synthesis acting on genes COL1A1, COL3A1, COL8A1, COL10A1, COL12A1. UVA-1 phototherapy adds significant benefits in local tissue remodeling, rebalancing the alteration between pro-fibrotic and anti-fibrotic pathways; these changes can be well monitored by HFUS.

An integrated approach to explore the suitability of nitrate-contaminated groundwater for drinking purposes in a semiarid region of India

The main objective of the present study is to perform risk assessment of groundwater contaminated by nitrate (NO3−) and evaluate the suitability of groundwater for domestic purposes in the Palani region of South India. Thirty groundwater samples were collected in the study area. Various groundwater quality analysis parameters such as the pH, electrical conductivity, total dissolved solids, total hardness, major cations (Ca2+, Mg2+, Na+, and K+), and major anions (Cl−, SO42−, F−, CO32−, and HCO3−) were adopted in this study to evaluate the drinking water suitability according to 2011 World Health Organization (WHO) standards. Piper and Gibbs’s diagrams for the tested groundwater indicated that, due to the influence of rock–water interactions, evaporation, and reverse ion exchange, the chemical composition of groundwater varied. According to water quality index (WQI) mapping results, 46.67% of the sample locations was identified as contaminated zones via GIS spatial analysis. Multivariate statistical analysis methods, such as principal component analysis, cluster analysis, and the Pearson correlation matrix, were applied to better understand the relationship between water quality parameters. The results demonstrated that 40% of the samples could be identified as highly affected zones in the study region due to a high nitrate concentration. The noncarcinogenic health risks among men, women, and children reached 40, 50, and 53%, respectively. The results illustrated that children and women occurred at a higher risk than did men in the study region. The major sources of contamination included discharge from households, uncovered septic tanks, leachate from waste dump sites, and excess utilization of fertilizers in the agricultural sector. Furthermore, using the nitrate health hazard integrated method with the conventional indexing approach ensures that groundwater reliability can be guaranteed, contamination can be explored, and appropriate remedial measures can be implemented.

Groundwater Quality Index Assessment using the Entropy Method on the Nineveh Plain in Northern Iraq

Human health is greatly and directly affected by the quality of groundwater and the extent of its pollution. This research evaluated the quality of groundwater in the Nineveh plain in northern Iraq and determined the suitability of groundwater for drinking purposes. Sixty-nine groundwater samples were taken and the major physical and chemical constituents, including pH, TDS, EC, Ca2+, Mg2+, Na+, K+, Cl−, So42-, HCO3-, and NO3-. were analyzed to use in calculating groundwater quality index for drinking purpose based on the World Health Organization standards for the year 2017. To prevent subjectively assigning weights in the calculation groundwater quality index, the entropy information theory was used. The estimated groundwater quality index values were loaded into ArcGIS 10.8 as a point, shapefile and interpolated using Empirical Bayesian Kriging techniques to produce the final groundwater quality index map of the study area. Results indicated that the entropy groundwater quality index for 2.9% of the samples were within the excellent range, 33% were in the good range, 14.5% were within the moderate range. The groundwater quality index values range between (48-581.8). These values were manually classified into five categories: &gt;200 (very poor), 200-150 (poor), 150-100 (moderate), 100-50 (good), and &lt;50 (excellent). The study discovered that the excellent class occupies 0.2 % (50.9 km2) of the study area, while the good class occupies 23.4% (596 km2), the medium class occupies 18.6 % (473.7 km2), and the poor and extremely poor classes occupy 26.1 % (664.8 km2) and 31.7% (807 km2), respectively.

Assessment of water quality index using Analytic Hierarchy Process (AHP) and GIS: a case study of a struggling Asan River

ABSTRACT India has abundant water resources, including rivers and snow-covered mountains in the Himalayas, which can supply the country’s water needs. In many areas, however, accessible water supplies are depleting due to fast population growth and the need to fulfill rising demands for irrigation, human and industrial consumption. Physico-chemical and microbiological characteristics were stuided of the Asan river water in Doon valley of Uttarakhand, India, that sampled were collected a fourteen water quality parameters at seven locations from October 2018 to March 2019. The water quality index and water quality maps was prepared in the Arc GIS software 10.7 using Inverse distance weighted (IDW) method. The sampled datasets were used to prepare a spatial water quality index map based on Analytical Hierarchy Process. Based on the results the weightage of the pH was found to the maximum (24%), BOD (17%), DO (13.7%), TDS (11.1%), EC (7.8%), TH (4.8%), CH (4.6%), MH (4.5%), WT (3.4%), AT (2.4%), Na (1.9%), K (1.7%), NO3(1.5%) and PO4 (1.3%). The result demonstrates that the water is heavily polluted towards station three caused due to the extensive anthropogenic activities. Thus, there is a need for combined government and non-government measures to enable the Asan rivers to slow their decline and return to their natural, pollutant-free state, which is crucial for the health of their environment.