Impact of land use/land cover changes on water quality and human health in district Peshawar Pakistan

Assessment of hydrochemical characteristics, health risks and quality of groundwater for drinking and irrigation purposes in a mountainous region of Pakistan

Renowned for its agriculture, livestock, and mining, Zhob district, Pakistan, faces the urgent problem of declining groundwater quality due to natural and human-induced factors. This deterioration poses significant challenges for residents who rely on groundwater for drinking, domestic, and irrigation purposes. Therefore, this novel study aimed to carry out a comprehensive assessment of groundwater quality in Zhob district, considering various aspects such as hydrochemical characteristics, human health risks, and suitability for drinking and irrigation purposes. While previous studies may have focused on one or a few of these aspects, this study integrates multiple analyses to provide a holistic understanding of the groundwater quality situation in the region. Additionally, the study applies a range of common hydrochemical analysis methods (acid-base titration, flame atomic absorption spectrometry, and ion chromatography), drinking water quality index (WQI), irrigation indices, and health risk assessment models, using 19 water quality parameters. This multi-method approach enhances the robustness and accuracy of the assessment, providing valuable insights for decision-makers and stakeholders. The results revealed that means of the majority of water quality parameters, such as pH (7.64), electrical conductivity (830.13 μScm-1), total dissolved solids (562.83 mgL-1), as well as various anions, and cations, were in line with drinking water norms. However, the water quality index (WQI) predominantly indicated poor drinking water quality (range = 51-75) at 50% sites, followed by good quality (range = 26-50) at 37% of the sites, with 10% of the sites exhibiting very poor quality (range = 76-100). For irrigation purposes, indices such as sodium percent (mean = 31.37%), sodium adsorption ratio (mean = 0.98 meqL-1), residual sodium carbonate (- 3.15 meqL-1), Kelley's index (mean = 0.49), and permeability (mean = 49.11%) indicated suitability without immediate treatment. However, the magnesium hazard (mean = 46.11%) and potential salinity (mean = 3.93) demonstrated that prolonged application of groundwater for irrigation needs soil management to avoid soil compaction and salinity. Water samples exhibit characteristics of medium salinity and low alkalinity (C2S1) as well as high salinity and low alkalinity (C3S1) categories. The Gibbs diagram results revealed that rock weathering, including silicate weathering and cation exchange, is the primary factor governing the hydrochemistry of groundwater. The hydrochemical composition is dominated by mixed Ca-Mg-Cl, followed by Na-Cl and Mg-Cl types. Furthermore, the human health risk assessment highlighted that fluoride (F-) posed a higher risk compared with nitrate (NO3-). Additionally, ingestion was found to pose a higher risk to health compared to dermal contact, with children being particularly vulnerable. The average hazard index (HI) for children was 1.24, surpassing the allowable limit of 1, indicating detrimental health effects on this subpopulation. Conversely, average HI values for adult females (0.59) and adult males (0.44) were within safe levels, suggesting minimal concerns for these demographic groups. Overall, the study's interdisciplinary approach and depth of analysis make a significant contribution to understanding groundwater quality dynamics and associated risks in Zhob district, potentially informing future management and mitigation strategies.

Assessment of landcover impacts on the groundwater quality using hydrogeochemical and geospatial techniques

Groundwater quality is influenced by urbanization and land use land cover (LULC) changes. This study investigated their impact on groundwater quality in Quetta City, Pakistan, from 2015 to 2021. About 58 groundwater samples from monitoring wells were analyzed using hydrogeochemical and statistical methods. The water quality index (WQI), Wilcox, USSL, and various agricultural indices were employed to assess water quality trends. LULC analysis and NDVI using Sentinel-2 imagery revealed increased urban and agricultural areas and decreased barren land. Rapid urbanization was evident, with the buildup class expanding by 7.50% during this period. NDVI findings emphasized monitoring vegetation health and water quality for environmental assessments. The groundwater in Quetta was primarily classified as Cl-Ca·Mg, Cl-Ca, and Cl-Na according to the Piper diagram, with water-rock interactions and rock weathering evident. Most groundwater samples were suitable for irrigation according to the Wilcox and USSL diagrams. The WQI demonstrated overall safety for human consumption, but declining WQI values in northern parts due to urbanization are concerning. The results also revealed a moderate positive relationship between landcover classes and WQI values. It can be concluded that urbanization and excessive use of pesticides contributed to declining agricultural land quality. The spatial overlay of agricultural indices with landcover class suggested that barren land was most suitable, followed by build-up and agriculture were suitable for drinking and agriculture purposes. Moreover, agricultural indices moderately declined due to excessive fertilizers and pesticides in the agriculture landcover class. Thus, effective water resource management is crucial to address challenges. This comprehensive study serves as a baseline for future research and recommends larger-scale studies to implement efficient management strategies, urbanization planning, and safe irrigation and drinking water practices to prevent groundwater pollution.

Assessment of groundwater quality for human consumption and its health risks in the Middle Magdalena Valley, Colombia

Groundwater is the primary source of water for people living in rural areas, especially during seasons when surface water is contaminated or unavailable. In Colombia, people use groundwater as drinking water without additional treatment. In addition, there is no infrastructure for wastewater collection and sewage treatment in the region of the Middle Magdalena Valley. The current study aims to evaluate the quality of groundwater in this region to determine any potential health hazards associated with its consumption. To reach the objective, three (3) physicochemical and microbiological sampling campaigns were carried out during different hydrological periods. A total of 428 groundwater samples were analyzed for over 28 parameters. The results were compared with the water quality standards proposed by the US EPA and Colombian regulations for human consumption. The analysis revealed the presence of total and fecal coliforms in 89% and 58% of the analyzed samples, respectively, identifying them as the main contaminants in groundwater. Furthermore, the pH levels did not meet the standards set by the US EPA in 33.8% of the cases and by Colombian regulations in 31.02%. Additionally, 32.8%, 17.6%, 14.3%, and 10.9% of the samples failed to meet the established thresholds for apparent color, magnesium, iron, and nitrates, respectively, under both standards. Moreover, only the analyses of selenium, mercury, and zinc complied with the quality standards under both regulatory frameworks. Based on the Colombian Drinking-Water Quality Risk Index (CDWQRI-IRCA), the risk associated with water quality meant for human consumption was assessed. The results showed that over 84% of the samples analyzed posed a high risk to human health, 4.6% posed a medium risk, 5.5% posed a low risk, and only 5.7% posed no risk at all. Additionally, official mortality statistics for children under four years old were reviewed, which revealed two deaths in 2019 due to Acute Diarrheal Disease (ADD) caused by consumption of contaminated water. Therefore, it is crucial to implement water treatment systems, establish aqueducts in rural areas, and conduct rigorous and systematic monitoring of drinking water to ensure it is safe for human consumption. It is also important to track morbidity and mortality rates associated with water consumption.

Effects of landscape pattern on water quality at multi-spatial scales in Wuding River Basin, China

Urbanization and agricultural land use have led to water quality deterioration. Studies have been conducted on the relationship between landscape patterns and river water quality; however, the Wuding River Basin (WDRB), which is a complex ecosystem structure, is facing resource problems in river basins. Thus, the multi-scale effects of landscape patterns on river water quality in the WDRB must be quantified. This study explored the spatial and seasonal effects of land use distribution on river water quality. Using the data of 22 samples and land use images from the WDRB for 2022, we quantitatively described the correlation between river water quality and land use at spatial and seasonal scales. Stepwise multiple linear regression (SMLR) and redundancy analyses (RDA) were used to quantitatively screen and compare the relationships between land use structure, landscape patterns, and water quality at different spatial scales. The results showed that the sub-watershed scale is the best spatial scale model that explains the relationship between land use and water quality. With the gradual narrowing of the spatial scale range, cultivated land, grassland, and construction land had strong water quality interpretation abilities. The influence of land use type on water quality parameter variables was more distinct in rainy season than in the dry season. Therefore, in the layout of watershed management, reasonably adjusting the proportion relationship of vegetation and artificial building land in the sub-basin scale and basin scope can realize the effective control of water quality optimization.

The multiscale nexus among land use-land cover changes and water quality in the Suquía River Basin, a semi-arid region of Argentina

Agricultural intensification and urban sprawl have led to significant alterations in riverscapes, and one of the critical consequences is the deterioration of water quality with significant implications for public health. Therefore, the objectives of this study were the assessment of the water quality of the Suquía River, the assessment of LULC change at different spatial scales, and the analysis of the potential seasonal correlation among LULC change and Water Quality Index (WQI). The Sample Sites (SS) 1 and 2 before Cordoba city had the highest WQI values while from SS3 the WQI decreased, with the lowest WQI close to the wastewater treatment plant (SS7) after Cordoba city. From SS8 in a agricultural context, the WQI increases but does not reach the original values. In light of analysis carried out, the correlation between water quality variables and the different LULC classes at the local and regional scales demonstrated that WQI is negatively affected by agricultural and urban activities, while natural classes impacted positively. The spatialization of the results can help strongly in assessing and managing the diffusion of point and non-point pollution along the riverscape. The knowledge gained from this research can play a crucial role in water resources management, which supports the provision of river ecosystem services essential for the well-being of local populations.

"Urban-Satellite" estimates in the ABCD Study: Linking Neuroimaging and Mental Health to Satellite Imagery Measurements of Macro Environmental Factors

While numerous studies over the last decade have highlighted the important influence of environmental factors on mental health, globally applicable data on physical surroundings are still limited. Access to such data and the possibility to link them to epidemiological studies is critical to unlocking the relationship of environment, brain and behaviour and promoting positive future mental health outcomes. The Adolescent Brain Cognitive Development (ABCD) Study is the largest ongoing longitudinal and observational study exploring brain development and child health among children from 21 sites across the United States. Here we describe the linking of the ABCD study data with satellite-based "Urban-Satellite" (UrbanSat) variables consisting of 11 satellite-data derived environmental indicators associated with each subject's residential address at their baseline visit, including land cover and land use, nighttime lights, and population characteristics. We present these UrbanSat variables and provide a review of the current literature that links environmental indicators with mental health, as well as key aspects that must be considered when using satellite data for mental health research. We also highlight and discuss significant links of the satellite data variables to the default mode network clustering coefficient and cognition. This comprehensive dataset provides the foundation for large-scale environmental epidemiology research.

Reconnaissance Survey of Organic Contaminants of Emerging Concern in the Kabul and Swat Rivers of Pakistan

The Swat and Kabul rivers of northern Pakistan are within an important regional watershed that supports river-based livelihoods and is impacted by untreated effluent discharges and municipal solid waste. Evidence indicates that fish populations are decreasing in these rivers. One potential cause of poor aquatic health is pollution; therefore, we investigated the presence of contaminants of emerging concern (CECs) in the river systems. Water samples were collected in the Kabul River (n = 9) and Swat River (n = 10) during seasons of high (summer 2018) and low (winter 2019) river flow. Agrochemicals, pharmaceuticals, plasticizers, chemicals in personal care products, and hormones were quantified via liquid chromatography high-resolution mass spectrometry. In the Swat River, caffeine (18-8452 ng/L), N,N-diethyl-meta-toluamide (DEET; 16-56 ng/L), and plasticizers (13-7379 ng/L) were detected at all sites during both seasons, while butachlor (16-98 ng/L) was detected only during high flow. In the Kabul River, caffeine (12-2081 ng/L) and several plasticizers (91-722 ng/L) were detected at all sites during both seasons, while DEET (up to 97 ng/L) was detected only during high flow. During low flow, pharmaceuticals (analgesics and nonsteroidal anti-inflammatory drugs) were quantified in both rivers (up to 823 ng/L), with detection frequencies from 70% to 100% and 0% to 78% in the Swat and Kabul Rivers, respectively. Intermittent-use and natural seasonal processes (increased runoff and dilution from rainfall and snowmelt) yielded higher agrochemical concentrations and lower concentrations of continuous-use compounds (e.g., caffeine) during high flow. The present study provides the first insight into CEC concentrations in the Swat River, additional insight into the Kabul River stressors, and, overall, contaminant risks to aquatic life. Environ Toxicol Chem 2023;42:2599-2613. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Multi-spatial-scale land/use land cover influences on seasonally dominant water quality along Middle Ganga Basin

Studying spatiotemporal water quality characteristics and their correlation with land use/land cover (LULC) patterns is essential for discerning the origins of various pollution sources and for informing strategic land use planning, which, in turn, requires a comprehensive analysis of spatiotemporal water quality data to comprehend how surface water quality evolves across different time and space dimensions. In this study, we compared catchment, riparian, and reach scale models to assess the effect of LULC on WQ. Using various multivariate techniques, a 14-year dataset of 20 WQ variables from 20 monitoring stations (67,200 observations) is studied along the Middle Ganga Basin (MGB). Based on the similarity and dissimilarity of WQPs, the K-means clustering algorithm classified the 20 monitoring stations into four clusters. Seasonally, the three PCs chosen explained 75.69% and 75% of the variance in the data. With PCs > 0.70, the variables EC, pH, Temp, TDS, NO2 + NO3, P-Tot, BOD, COD, and DO have been identified as dominant pollution sources. The applied RDA analysis revealed that LULC has a moderate to strong contribution to WQPs during the wet season but not during the dry season. Furthermore, dense vegetation is critical for keeping water clean, whereas agriculture, barren land, and built-up area degrade WQ. Besides that, the findings suggest that the relationship between WQPs and LULC differs at different scales. The stacked ensemble regression (SER) model is applied to understand the model's predictive power across different clusters and scales. Overall, the results indicate that the riparian scale is more predictive than the watershed and reach scales.

Performance Evaluation of UF Membranes Derived from Recycled RO Membrane, a Step towards Circular Economy in Desalination

Reverse osmosis (RO) spiral wound membrane generation reached 93.5% in 2020, resulting in 14,000 tons of used RO membranes being discarded annually into landfills, which is unprecedented. The current study aims to chemically convert the end-of-life RO membrane, followed by its performance evaluation and microbial removal efficiency on three different sources of water, i.e., tap water (TW), integrated constructed wetland permeate (ICW-P), and membrane bio-rector permeate (MBR-P), respectively. This was accomplished by selecting 6 years of spent Filmtech (LC-LE-4040) thin film composite type brackish water reverse osmosis (BWRO) membrane, followed by alkaline and acidic cleaning for 2 h. Finally, the conversion was carried out by 6% sodium hypochlorite (NaOCl) with 300,000 ppm/h exposure by active system (AS) using the clean in place CIP pump at 2 bars for 10 h duration. The membrane demonstrated 67% water recovery and 1% saltwater rejection, which means RO membrane now converted into recycled RO (R-RO) or (UF) by removal of the polyamide (PA) layer. Water recovery was 67% for TW, 68% for ICW-P, and 74% for MBR-P, respectively, with the consistent saltwater rejection rate of 1% being observed, while R-RO exhibited an effective COD removal of 65.79%, 62.96%, and 67.72% in TW, ICW-P, and MBR-P, respectively. The highest turbidity removal of 96% in the ICW-P was also recorded for R-RO. For morphological properties, SEM analysis of the R-RO membrane revealed a likewise appearance as a UF membrane, while pore size is also comparable with the UF membrane. The most probable number (MPN) also showed complete removal of total coliforms after passing through the R-RO membrane. These features made the R-RO membrane an excellent choice for drinking water treatment and wastewater treatment polishing steps. This solution can help developing nations to be efficient in resource recovery and contribute to the circular economy.

Potential risk assessment due to groundwater quality deterioration and quantifying the major influencing factors using geographical detectors in the Gunabay watershed of Ethiopia

Groundwater quality has become deteriorated due to natural and anthropogenic activities. Poor water quality has a potential risk to human health and the environment. Therefore, the study aimed to assess the potential risk of groundwater quality contamination levels and public health risks in the Gunabay watershed. For this task, seventy-eight groundwater samples were collected from thirty-nine locations in the dry and wet seasons during 2022. The groundwater contamination index was applied to assess the overall quality of groundwater. Six major driving forces (temperature, population density, soil, land cover, recharge, and geology) and their quantitative impact of each factor on groundwater quality deterioration were demonstrated using Geodetector. The results showed that low groundwater quality was detected in urban and agricultural land. Especially nitrate contamination was highly linked to groundwater quality deterioration and public health risks, and a medium contamination level was observed in the area. This indicates that the inappropriate application of fertilizer on agricultural land and wastewater from urban areas has a great impact on shallow aquifers in the study area. Furthermore, the major influencing factors are ranked as soil type (0.33-0.31) > recharge (0.17-0.15) > temperature (0.13-0.08) > population density (0.1-0.08) > land cover types (0.07-0.04) > lithology (0.05-0.04). The interaction detector revealed that the interaction between soil ∩ recharge, soil ∩ temperature, and soil ∩ land cover, temperature ∩ recharge is more influential to deteriorate groundwater quality in both seasons. Identification and quantification of the major influencing factors may provide new insight into groundwater resource management.

Assessment and validation of groundwater vulnerability to nitrate and TDS using based on a modified DRASTIC model: a case study in the Erbil Central Sub-Basin, Iraq

In recent years, groundwater vulnerability assessment has become a crucial step in effectively protecting groundwater resources against increasing groundwater pollution in recent years. Sustainable effectual management of groundwater sources in terms of quality has become a critical factor in the development of unplanned urbanization areas, especially in regions with intensive agricultural and industrial activities in the land use/land cover (LULC) models. In this study, the GIS-based DRASTIC model was used by modified to estimate the groundwater vulnerability of porous aquifers to nitrate and total dissolved solids (TDS). The DRASTIC and the modified DRASTIC models generate four different groundwater vulnerability zones: high (33.6, 37.8%), moderate (45.9, 42.3%), low (18.7, 18.3%), and very low (1.8,1.6%). DRASTIC_LULC index map provides four different vulnerability zones: low, moderate, high, and very high, covering 0.1%, 7.6%, 83.6%, and 8.7% of the Erbil Central Sub-Basin, respectively. The most important hydrogeological factors determining the DRASTIC vulnerability obtained from sensitivity analyses are depth to the water table and impact of vadose zone parameters with average effective weight values of 23.7% and 22.6%. For validating the DRASTIC_LULC model, the water quality parameters, nitrate and TDS, have been used with an accuracy of 68% and 79%, which indicates that the validation accuracy for this model is quite high. Maps obtained as a result of this study can be used to create a baseline map for the sustainable management of groundwater quality in vulnerable areas of the Erbil Central Sub-Basin and its planning.

Identification and selection of suitable landfill sites using GIS-based multi-criteria decision analysis in the Peshawar District, Pakistan

Managing municipal solid waste (MSW) is indispensable for public health and quality living standards in urban and rural environments. Suitable landfill site selection (LSS) requires the consideration of many diverse criteria. This study uses various environmental, social and economic criteria in a sophisticated multi-criteria decision analysis (MCDA) within the geographical information system (GIS) and aims to provide a scientific basis for the identification of suitable landfill sites which can efficiently be used for MSW in one of the most urbanized cities (Peshawar district) in Pakistan. The methodology involves pairwise comparisons of the selected and ranked criteria using the analytical hierarchy process (AHP). A weighted linear combination (WLC) was applied to generate the most suitable landfill site for MSW disposal within the study area. The results show that approximately 11.4% (14,485.15 ha) and 16.6% (21,211.95 ha) of the total study area are either very highly suitable or highly suitable, 20.8% (26,525.56 ha) area is unsuitable and the remaining areas are either low (27.3%; 34,834.84 ha) or moderately suitable (23.8%; 30,356.84 ha) for the construction of landfill sites. It is recommended that using the proposed landfill sites would have the least consequences of public health risks and environmental degradation.

Impact of land use/land cover on groundwater resources in tropical unconfined aquifers of south-western India

Groundwater quality assessment is essential to understand land use impacts and implement water management plans. The present study aims to assess the impact of land use/land cover (LULC) on the groundwater table, and its quality in the tropical unconfined aquifers. Two hundred groundwater samples were collected from 100 sampling wells during monsoon and post-monsoon seasons. The drinking water quality index and irrigation quality indices were estimated based on the various parameters obtained from the laboratory analysis. Human health risk concerning nitrate contamination was evaluated based on the USEPA method. The land-use/land-cover map prepared using ArcGIS showed that the study area consists dominantly of croplands. Drinking water quality index results suggested that the groundwater samples were excellent to moderately suitable for drinking purposes. Only one sample was unsuitable for drinking. The different irrigation quality indices revealed various degrees of groundwater suitability for irrigation purposes. The spatial distribution of the corrosivity ratio suggests avoiding the metal pipe, for transportation of groundwater supply in the northern part of the study area. Fertilizers used in agriculture and soak pit leakages have contributed to high nitrate concentration in a few parts of the study area. Human health risk assessment showed that infants are vulnerable to non-carcinogenic health risks. The impact of the LULC assessment revealed that groundwater quality was moderately suitable for drinking in urban land. The study suggests implementing proper sewage treatment measures to avoid groundwater contamination. Overall, the findings are important in adopting site-specific, groundwater management strategies in the study area. Polluted and unpolluted areas demarcated in the study are beneficial for decision-makers to develop suitable groundwater management plans. The study recommends informed LULC development in the study area to improve groundwater quality and reduce human health risks.

Comprehensive assessment of the impact of land use and hydrogeological properties on the groundwater quality in Taiwan using factor and cluster analyses

This study aims at making a comprehensive assessment of the impact of land use and the hydrogeological properties on groundwater quality. First, factor analysis (FA) is applied to reveal the main pollutant sources and hydrogeological processes controlling the groundwater quality. FA identifies the four most important factors. Factor 1 (seawater salinization) is characterized by a medium loading of land use type of aquaculture. It is recognized that the high scores for factor 1 in coastal areas are due to over-pumping from aquafarms. Focused land use management is required to prevent saline-water intrusion in coastal aquifers. Factor 3 (nitrate pollution) shows high correlations with the land use type of fruit farming and the gravel thickness in unsaturated layers. High scores for factor 3 are also found in the proximal area of the Chuoshui River Alluvial Fan and the northeastern mountain area in the Pingtung Plain. Fruit farmers should be educated to reduce the application of fertilizers and promote the organic fruit farming. The impacts of land use and the hydrogeological properties on both Factor 2 (arsenic enrichment) and Factor 4 (reductive dissolution of Fe²⁺ and Mn²⁺) are negligible. Second, cluster analysis (CA) is performed on computed scores of the four main factors to separates 123 monitoring wells into cluster 1 (low polluted zone), cluster 2 (nitrate polluted zone) and cluster 3 (hybrid polluted zone). The results obtained from CA provide practical applications such as reduce agrichemical use in the areas of cluster 2 and enforce intensive monitoring in the prioritizing areas of cluster 3. This study successively uses the FA and CA to extract the meaningful information present by geographical visualization of scores for 4 main factors and 3 distinct clusters zones. The results are essential for formulating sound groundwater resource and land use management policies to ensure groundwater sustainability.

Spatio-temporal assessment of land use dynamics and urbanization: linking with environmental aspects and DPSIR framework approach

Urbanization is the main force of the global environmental as well as land use land cover changes (LULC). Urbanization is caused by prompt increase in population growth, migration, and urge for employment. In this study, Geographic Information System (GIS) was applied for the analysis and representation of spatio-temporal changes in LULC in Peshawar district and these results were linked with environmental aspects and Driver-Pressure-State-Impact-Response (DPSIR) framework approaches. For LULC classification, the Landsat freely available satellite imageries were used. The analysis revealed that the vegetation cover has increased from 37.8% of the total area to 71.3% during 1990-2020 and this change in vegetation is attributed to the government initiatives of Billion Tree Tsunami afforestation project after 2014 which has substantially decreased the barren land (from 66% in 1990 to 19% in 2020) in southeastern part of Peshawar district. Although, there was reduction in the vegetation cover in the past but due to extensive plantation between 2014 and 2020 resulted rapid increase in vegetation cover in the study area. The results of the present study detected a remarkable increase in built-up area which has increased almost 224.6% from 1990 to 2020. The study area population has increased from 2.12 million during 1998 to 4.26 million in 2017. The DPSIR results revealed that drivers and pressure have adverse effects on the carrying capacity of natural resources which have resulted deterioration of ecosystem. The resulted reduced capacity leading towards land degradation, loss of agricultural land, decline the groundwater level and resulted in pluvial flooding in Peshawar district. Government and environmental protection agency should implement the land use bylaws to reduce the rapid and unplanned urban growth and its negative impacts on natural environment.

Analysing Effects on Ground Water Levels Due to Conversion of Rural to Urban Landscapes

Greater NOIDA evolved from 1991 with 101 villages to 2020 with 293 villages. This is an ideal case of rural to urban transformation in the immediate past. This transformation led to a decrease in recharging natural surfaces and an increase in impermeable surfaces. Along with the reduction in recharge areas, an increase in population has necessitated more and more extraction of groundwater resulting in an imbalance of water extraction and recharge. The result is depletion of groundwater levels in this area. The area is part of the wide Indo-Gangetic alluvium with sand, silt and clay layers resting on quartzite’s of Delhi Super Group. Geomorphological map prepared using digital elevation models of the area shows older and younger alluvial plains and active flood plains of the river Hindan. Time series analysis of key land use land cover classes shows that recharge areas were reduced from 77 % to 30 % from 2005 to 2019 and impervious surfaces have increased from 19 % to 65 % for the same period. Aquifers of the area are both phreatic and semi-confined. The aquifer parameters estimated through step drawdown test and long duration aquifer performance test indicates that the average coefficient of transmissivity of the area is 1752 m2/day and the average coefficient of storage is 4.84 x 10-4. Discharge of the wells shows a yield of 8 to 16 lps for a drawdown of 3 to 6 m. An attempt has been made to know the behaviour of groundwater levels during the same period as that of land use land cover. The results indicate a 74 % depletion in groundwater levels with an average annual depletion of 21 %. An interrelationship between urban growth and groundwater levels has been established in this study. This analysis indicates that as agriculture declined water levels also depleted and have a positive correlation of 0.852. On the contrary, as the built-up increased water level has depleted hence have a negative relationship with a correlation coefficient of -0.851. To make it a sustainable resource, these overexploited aquifers need careful participatory management by communities, Scientists, and policymakers.

Groundwater quality assessment and its vulnerability to pollution: a study of district Nowshera, Khyber Pakhtunkhwa, Pakistan

Groundwater is the drinking water source for the majority of rural settlements of district Nowshera, Khyber Pakhtunkhwa, Pakistan. The study aimed to analyze the groundwater quality and its vulnerability to pollution and to develop its spatial distribution mapping. For this purpose, forty-eight groundwater samples were collected from dug wells, tube wells, and hand pumps of sixteen villages and analyzed for physicochemical parameters. The XY coordinates of the sample's sources were marked by Magellan Triton 1500 handheld global positioning system (GPS). The results were compared with WHO and Pak-EPA guidelines. The results of the majority of selected parameters were found within the WHO and Pak-EPA guidelines; however, in certain areas the concentration of total dissolved solids (TDS), chlorides (Cl^-), and alkalinity were higher than the guideline limits. Based on cumulative water quality the excellent water quality prevails over an area of 376 km² (21% of district area), good water quality 726 km² (42%), poor 424 km² (24%), very poor 116 km² (6%), and unfit for drinking 84 km² (4%). The water of the Nizampur and Rashaki areas were categorized unfit for drinking. The groundwater quality of nearly one-half of the district varies from poor to very poor, and the soil type and vadose zone sediment/material was found the key reason for groundwater contamination. Based on the infiltration capacity of vadose zone material, the study area was divided into four water pollution vulnerable zones. The low vulnerable zone covers an area of 104 km², moderate 862 km², high 667 km², and very high 93 km². The most important factor which determines the vulnerability of the groundwater to contamination is the vadose zone material/sediment which in turn determines the soil infiltration capacity. The generated groundwater susceptibility and water quality maps provide critical information for identifying optimal locations for supply wells.

Non-Carcinogenic Health Risk Evaluation of Elevated Fluoride in Groundwater and Its Suitability Assessment for Drinking Purposes Based on Water Quality Index

Fluoride (F^-) contamination in drinking groundwater is a significant human health risk in Pakistan. Moreover, high fluoride pollution in drinking water causes a variety of disorders, including dental, neurological, and skeletal fluorosis. The aim of this research was to evaluate the health risk of elevated fluoride in groundwater and its suitability assessment for drinking purposes. The total of (n = 37) samples were collected from community tube wells of Quetta Valley, Balochistan, Pakistan. The results show a mean pH value of 7.7, TDS of 404.6 mg/L, EC of 500 µs/cm, depth of 96.8 feet, and turbidity of 1.7 nephelometric turbidity units. The mean values of HCO₃^-, Ca²⁺, Mg²⁺, and Na⁺, were 289.5, 47.5, 30.6, and 283.3 mg/L, respectively. The mean values of SO₄^2-, NO₃^-, K⁺, Cl^-, and Fe²⁺, were 34.9, 1.0, 1.6, 25.6, and 0.01 mg/L, respectively. The F^- concentration in the groundwater varied between 0.19 and 6.21, with a mean value of 1.8 mg/L, and 18 samples out of 37 were beyond the WHO recommended limit of 1.5 mg/L. The hydrochemical analysis results indicated that among the groundwater samples of the study area, 54% samples were Na-HCO₃ type and 46% were mixed CaNaHCO₃ type. The saturation indices of the mineral phases reveal that the groundwater sources of the study area were saturated with CaCO₃ and halide minerals due to their positive (SI) values. Such minerals include calcite, dolomite, gypsum, and fluorite. The principal component analysis results reveal that the groundwater sources of the study area are contaminated due to geological and anthropogenic actions. The health risk assessment results of the F^- concentrations show the ranges of ADD_ingestion for children, females, and males in the Quetta Valley, and their mean values were observed to be 0.093052, 0.068825, and 0.065071, respectively. The HQ_ingestion mean values were 1.55086, 1.147089, and 1.084521 for children, females, and males, respectively. It was noticed that children had the highest maximum and average values of ADD_ingestion and HQ_ingestion in the research area, indicating that groundwater fluoride intake poses the greatest health risk to children. The water quality index (WQI) analyses show that 44% of the samples belong to the poor-quality category, 49% were of good quality, and 8% of the samples of the study area belong to the excellent category.

A Geographically Weighted Random Forest Approach to Predict Corn Yield in the US Corn Belt

Crop yield prediction before the harvest is crucial for food security, grain trade, and policy making. Previously, several machine learning methods have been applied to predict crop yield using different types of variables. In this study, we propose using the Geographically Weighted Random Forest Regression (GWRFR) approach to improve crop yield prediction at the county level in the US Corn Belt. We trained the GWRFR and five other popular machine learning algorithms (Multiple Linear Regression (MLR), Partial Least Square Regression (PLSR), Support Vector Regression (SVR), Decision Tree Regression (DTR), and Random Forest Regression (RFR)) with the following different sets of features: (1) full length features; (2) vegetation indices; (3) gross primary production (GPP); (4) climate data; and (5) soil data. We compared the results of the GWRFR with those of the other five models. The results show that the GWRFR with full length features (R2 = 0.90 and RMSE = 0.764 MT/ha) outperforms other machine learning algorithms. For individual categories of features such as GPP, vegetation indices, climate, and soil features, the GWRFR also outperforms other models. The Moran’s I value of the residuals generated by GWRFR is smaller than that of other models, which shows that GWRFR can better address the spatial non-stationarity issue. The proposed method in this article can also be potentially used to improve yield prediction for other types of crops in other regions.

Estimation of groundwater pollution levels and specific ionic sources in the groundwater, using a comprehensive approach of geochemical ratios, pollution index of groundwater, unmix model and land use/land cover - A case study

This study aimed to evaluate the degree of groundwater pollution and to assess the contribution of specific ionic sources to groundwater, thereby helping to identify the changes in groundwater chemistry and also in groundwater quality from a rural part of Telangana, India, using the comprehensive understanding of geochemical ratios (GR), pollution index of groundwater (PIG), unmix model (UM), and land use/land cover. Groundwater samples collected (22) from the study area were analysed for pH, EC, TDS, Ca²⁺, Mg²⁺, Na⁺, K⁺, HCO₃^-, Cl^-, SO₄^2-, NO₃^-, and F^-_. The hydrogeochemical diagram showed the dominant groundwater type of Ca²⁺- Mg²⁺- HCO₃^- due to the water-soil-rock interactions. GR, chloro-alkaline indices, and saturation indices revealed the groundwater chemistry that explains the mineral weathering and dissolution, ion exchange, and evaporation processes as the chief geogenic origin, and also the contamination of surface water due to the influence of household wastewater, septic tank leaks, irrigation-return-flows, chemical composts, etc. as the secondary anthropogenic sources on the aquifer system. Changes in groundwater quality from the recharge area to the discharge area and the correlation coefficient of chemical variables further supported the sources of geogenic and anthropogenic origins. According to PIG's calculations, the present study area was classified as the insignificant pollution zone (5.89%), which shows all chemical variables within their drinking water quality limits, and the low pollution zone (43.34%), medium pollution zone (27.48%), high pollution zone (17.34%), and very high pollution zone (5.95%), which exhibit the TDS, Mg²⁺, Na⁺, K⁺, HCO₃^-, Cl^-, NO₃^-, SO₄^2-, and F^-contents above the drinking water quality standards. This indicates the gradual increase in the intensity of pollution activity. UM also classified the contribution of specific ions (>50%) into three sources: Source I (K⁺) measures the poor sewage conditions and potash fertilizers; Source II (SO₄^2-, Mg²⁺, NO₃^-, Na⁺, and Ca²⁺) specifies the poor sewage conditions, irrigation-return-flows, and chemical fertilizers (gypsum and nitrate); and Source III (F^- and HCO₃^-) represents the dissolution of fluoride minerals as a major contributor to groundwater chemistry. Furthermore, the land use/land cover observations had also supported the assessment of groundwater pollution levels and the contribution of specific ionic sources made by PIG and UM. As a result, the present study clearly indicated that groundwater quality of a geogenic origin is primarily overcome the impact of anthropogenic sources. Therefore, the present study suggested strategic measures to control groundwater pollution and improve groundwater quality.

Health and Human Wellbeing in China: Do Environmental Issues and Social Change Matter?

How to mitigate greenhouse gas emission and achieve human development remain major sustainability issues, particularly in China. Empirical research on the effects of climate warming and social change on human health and wellbeing is quite fragmented. This study examines the impact of environmental issues and social changes on health and human wellbeing using a time series data of China from 1991 to 2020. Findings show that environmental issues have a negative impact on health and human wellbeing in long run. While the internet is a form of social change that tends to improve health and human wellbeing in the long run. FDI exerts a positive effect on human health, but it does not improve wellbeing in the long run. In contrast, financial development does not improve human health but it has a significant positive impact on wellbeing in the long run. Our empirical insights have important implications for achieving human wellbeing through the pursuit of environmental sustainability and social change.

Characterizing Spatiotemporal Variations in the Urban Thermal Environment Related to Land Cover Changes in Karachi, Pakistan, from 2000 to 2020

Understanding the spatiotemporal patterns of urban heat islands and the factors that influence this phenomenon can help to alleviate the heat stress exacerbated by urban warming and strengthen heat-related urban resilience, thereby contributing to the achievement of the United Nations Sustainable Development Goals. The association between surface urban heat island (SUHI) effects and land use/land cover features has been studied extensively, but the situation in tropical cities is not well-understood due to the lack of consistent data. This study aimed to explore land use/land cover (LULC) changes and their impact on the urban thermal environment in a tropical megacity—Karachi, Pakistan. Land cover maps were produced, and the land surface temperature (LST) was estimated using Landsat images from five different years over the period 2000–2020. The surface urban heat island intensity (SUHII) was then quantified based on the LST data. Statistical analyses, including geographically weighted regression (GWR) and correlation analyses, were performed in order to analyze the relationship between the land cover composition and LST. The results indicated that the built-up area of Karachi increased from 97.6 km² to 325.33 km² during the period 2000–2020. Among the different land cover types, the areas classified as built-up or bare land exhibited the highest LST, and a change from vegetation to bare land led to an increase in LST. The correlation analysis indicated that the correlation coefficients between the normalized difference built-up index (NDBI) and LST ranged from 0.14 to 0.18 between 2000 and 2020 and that NDBI plays a dominant role in influencing the LST. The GWR analysis revealed the spatial variation in the association between the land cover composition and the SUHII. Parks with large areas of medium- and high-density vegetation play a significant role in regulating the thermal environment, whereas the scattered vegetation patches in the urban core do not have a significant relationship with the LST. These findings can be used to inform adaptive land use planning that aims to mitigate the effects of the UHI and aid efforts to achieve sustainable urban growth.