Game-theoretic optimization of landslide susceptibility mapping: a comparative study between Bayesian-optimized basic neural network and new generation neural network models.

Landslide susceptibility mapping is essential for reducing the risk of landslides and ensuring the safety of people and infrastructure in landslide-prone areas. However, little research has been done on the development of well-optimized Elman neural networks (ENN), deep neural networks (DNN), and artificial neural networks (ANN) for robust landslide susceptibility mapping (LSM). Additionally, there is a research gap regarding the use of Bayesian optimization and the derivation of SHapley Additive exPlanations (SHAP) values from optimized models. Therefore, this study aims to optimize DNN, ENN, and ANN models using Bayesian optimization for landslide susceptibility mapping and derive SHAP values from these optimized models. The LSM models have been validated using the receiver operating characteristics curve, confusion matrix, and other twelve error matrices. The study used six machine learning-based feature selection techniques to identify the most important variables for predicting landslide susceptibility. The decision tree, random forest, and bagging feature selection models showed that slope, elevation, DFR, annual rainfall, LD, DD, RD, and LULC are influential variables, while geology and soil texture have less influence. The DNN model outperformed the other two models, covering 7839.54 km2 under the very low landslide susceptibility zone and 3613.44 km2 under the very high landslide susceptibility zone. The DNN model is better suited for generating landslide susceptibility maps, as it can classify areas with higher accuracy. The model identified several key factors that contribute to the initiation of landslides, including high elevation, built-up and agricultural land use, less vegetation, aspect (north and northwest), soil depth less than 140 cm, high rainfall, high lineament density, and a low distance from roads. The study's findings can help stakeholders make informed decisions to reduce the risk of landslides and ensure the safety of people and infrastructure in landslide-prone areas.

Identification of Playa Lakes and tracking their evolution pathways using geochemical models in the Great Indian Thar desert.

Playa Lakes of the great Indian Thar desert are unique and intricate systems with pronounced scientific and ecological significance. In this study, the combined use of geospatial and field data assisted in depicting and understanding the changes within these natural systems. The purpose of this study is to provide a comprehensive dataset of Playa Lakes, which can help with an overall understanding of playas from a geochemical, ecological, and economic perspective. The 1163 surface depressions were accounted for as possible playas considering the threshold area of >5 km2. A total of 42 representative surface water samples were collected from the selected playas (Sambhar, Didwana, Pachpadra, and Pokhran) and hydrochemical analysis was carried out to identify the geochemical evolution of these playas. The major water types were Na-Cl and Na-Cl-SO4 type. Hardie and Eugster's model was used to explain the possible sequence of evolutionary pathways and brine shifts in the selected playas. Simulated evaporation modeling suggests precipitation of major evaporites (chlorides, carbonates, and sulphates) during progressive evaporation. Surface sediment analysis (X-ray diffraction) confirmed the presence of calcite, halite, and dolomite minerals in the playa sediments. The greatest economic value of these playas may be mineral production and providing food and habitat for migratory birds, though conservation and policy intervention is required for their sustainable utilization.

Groundwater fluoride across the Punjab plains of Pakistan and India: Distribution and underlying mechanisms.

Chronic exposure from drinking well-water with naturally high concentrations of fluoride (F-) has serious health consequences in several regions across the world including South Asia, where the rural population is particularly dependent on untreated groundwater pumped from private wells. An extensive campaign to test 28,648 wells was conducted across the Punjab plains of Pakistan and India by relying primarily on field kits to document the scale of the problem and shed light on the underlying mechanisms. Groundwater samples were collected from a subset of 712 wells for laboratory analysis of F- and other constituents. A handful of sites showing contrasting levels of F- in groundwater were also drilled to determine if the composition of aquifer sediment differed between these sites. The laboratory data show that the field kits correctly classified 91% of the samples relative to the World Health Organization guideline for drinking water of 1.5 mg/L F-. The kit data indicate that 9% of wells across a region extending from the Indus to the Sutlej rivers were elevated in F- relative to this guideline. Field data indicate an association between the proportion of well-water samples with F- > 1.5 mg/L and electric conductivity (EC) > 1.5 mS/cm across six floodplains and six intervening doabs. Low Ca2+ concentrations and elevated bicarbonate (HCO3- > 500 mg/L) and sodium (Na+ > 200 mg/L) in high F- groundwater suggest regulation by fluorite. This could be through either the lack of precipitation or the dissolution of fluorite regulated by the loss of Ca2+ from groundwater due to precipitation of calcite and/or ion exchange with clay minerals. Widespread salinization of Punjab aquifers attributed to irrigation may have contributed to higher F- levels in groundwater of the region. Historical conductivity data suggest salinization has yet to be reversed in spite of changes in water resources management.

Regulation of groundwater arsenic concentrations in the Ravi, Beas, and Sutlej floodplains of Punjab, India.

Recent testing has shown that shallow aquifers of the Ravi River floodplain are more frequently affected by groundwater arsenic (As) contamination than other floodplains of the upper Indus River basin. In this study, we explore the geochemical origin of this contrast by comparing groundwater and aquifer sand composition in the 10-30 m depth range in 11 villages along the Ravi and adjacent Beas and Sutlej rivers. The drilling was preceded by testing wells in the same villages with field kits not only for As but also for nitrate (NO3 -), iron (Fe), and sulfate (SO4 2-). Concentrations of NO3 - were ≥20 mg/L in a third of the wells throughout the study area, although conditions were also sufficiently reducing to maintain >1 mg/L dissolved Fe in half of all the wells. The grey to grey-brown color of sand cuttings quantified with reflectance measurements confirms extensive reduction of Fe oxides in aquifers of the affected villages. Remarkably high levels of leachable As in the sand cuttings determined with the field kit and As concentration up to 40 mg/kg measured by X-ray fluorescence correspond to depth intervals of high As in groundwater. Anion-exchange separation in the field and synchrotron-based X-ray spectroscopy of sand cuttings preserved in glycerol indicate speciation in both groundwater and aquifer sands that is dominated by As(V) in the most enriched depth intervals. These findings and SO4 2- concentrations ≥20 mg/L in three-quarters of the sampled wells suggest that high levels of NO3 -, presumably from extensive fertilizer application, may have triggered the release of As by oxidizing sulfide-bound As supplied by erosion of black shale and slate in the Himalayas. Radiocarbon dating of sub-surface clay cuttings indicates that multiple episodes of inferred As-sulfide input reached the Ravi floodplain over the past 30 kyr. Why the other river basins apparently did not receive similar inputs of As-sulfide remains unclear. High NO3 - in groundwater may at the same time limit concentrations of As in groundwater to levels lower than they could have been by oxidizing both Fe(II) and As(III). In this particular setting, a kit can be used to analyze sand cuttings for As while drilling in order to target As-safe depths for installing domestic wells by avoiding intervals with high concentrations of As in aquifer sands with the well screen.

Arsenic enrichment in groundwater and associated health risk in Bari doab region of Indus basin, Punjab, India.

Contaminated groundwater is considered as one of the most important pathways of human exposure to the geogenic contaminants. Present study has been conducted in a part of Indus basin to investigate the presence and spatial distribution of arsenic (As) and other trace metals in groundwater. The As concentration varies from bdl-255.6 µg/L and 24.6% of the 73 collected groundwater samples have As above world health organization (WHO) guideline of 10 µg/L. High concentration of As is found along the newer alluvium of Ravi River. As is found with high bicarbonate (HCO3-) and Iron (Fe) and low nitrate (NO3-) indicating reductive dissolution of Fe bearing minerals. However, silicate weathering along with high sulphate (SO42) and positive oxidation-reduction potential (ORP) indicates mixed redox conditions. Weathering of minerals along with other major hydrogeochemical process are responsible for composition of groundwater. With 31.5% of the samples, sodium bicarbonate (Na-HCO3) is the major water facies followed by magnesium bicarbonate (Mg-HCO3) in 30% of samples. As, Fe and other trace metals including copper (Cu), cadmium (Cd), chromium (Cr), zinc (Zn) were used to calculate the health risk for children and adults in the region. Out of 73 samples, 58% has high Fe, 32.8% has high Zn, and 4.1% has high Cd which are above the prescribed limits of WHO guidelines. Health risk of the population has been assessed using chronic dose index (CDI), hazardous quotients (HQ) and hazardous index (HI) for children and adults. The mean CDI values follows the order as Fe > Zn > Cu > As > Cr > Cd, while the HQ values indicates high As hazards for both children and adults. 43.8% of the groundwater samples have high HI for adults, however, 49.3% has high HI for children indicating higher risk for children compared to adults. A large-scale testing should be prioritized to test the wells for As and other trace metals in the study region to reduce health risks.

Predicting groundwater arsenic contamination: Regions at risk in highest populated state of India.

Arsenic (As) contamination of groundwater is a public health concern, impacting the lives of approximately 100 million people in India. Chronic exposure to As significantly increases mortality due to the occurrence of several types of cancer, respiratory and cardiac diseases. Uttar Pradesh is a part of the middle Indo-Gangetic plains and has been found to be severely affected by As contamination of groundwater, as established by several small-scale studies. The current study incorporates a hybrid method based on a random forest ensemble algorithm and univariate feature selection using 1473 data points for predicting As in the region. Twenty direct/proxy predictor variables were considered to describe the geochemical environment, aquifer conditions and topography that are responsible for As enrichment in groundwater. The map of As predicted through the hybrid random forest ensemble model shows an overall accuracy of 84.67%. The hybrid random forest model performs better than the univariate, logistic, fuzzy, adaptive fuzzy and adaptive neuro fuzzy inference systems, which have been widely used for As prediction. The projected number of rural populations at risk due to high As exposure is 12% of the total population of the region, which accounts for 23.48 million people who are at risk. The predictive map provides insight for the regions where future testing campaigns and interventions for mitigation should be prioritized by policymakers.

Field testing of over 30,000 wells for arsenic across 400 villages of the Punjab plains of Pakistan and India: Implications for prioritizing mitigation.

Most of the rural population of 90 million in Punjab province in Pakistan and Punjab state in India drinks, and cooks with, untreated water drawn from shallow wells. Limited laboratory testing has shown that groundwater in the region can contain toxic levels of arsenic. To refine this assessment, a total of 30,567 wells from 383 villages were tested with a field kit in northern Punjab province of Pakistan and western Punjab state of India. A subset of 431 samples also tested in the laboratory show that 85% of wells were correctly classified by the kit relative to the World Health Organization guideline of 10 µg/L for arsenic in drinking water. The kit data show that 23% of the tested wells did not meet the WHO guideline for arsenic but also that 87% of households with a well high in arsenic live within 100 m of a well that meets the WHO guideline. The implication is that many households could rapidly lower their exposure if the subset of safe wells could be shared. In a follow-up conducted one year later in five villages where 59% of wells were elevated in arsenic, two-thirds of households indicated that they had switched to a neighboring well in response to the testing. The blanket testing of millions of wells for arsenic in the region should therefore be prioritized over much costlier water treatment and piped water supply projects that will take much longer to have a comparable impact.

Quantitative analysis of the methane gas emissions from municipal solid waste in India.

Increased emissions of greenhouse gases have altered the global ambient temperature and adversely affected global climatic conditions. The municipal solid waste (MSW) generated by households is considered the third largest anthropogenic source of methane (CH4) emissions, constituting 11% of all global CH4 emissions. The current study derived total MSW CH4 emission estimates using the IPCC default method (DM), modified triangular method (MTM) and first order decay method (FOD). The estimated CH4 emission was higher for the DM than the other methods, and was comparable to estimates from other studies. This study observed that the net annual emission of CH4 from landfills in India increased from 404 Gg in 1999-2000 to 990 Gg and 1084 Gg in 2011 and 2015, respectively. We also found that CH4 emissions were highly correlated (R2 = 0.8) with the gross state domestic product (GSDP) of states and the gross domestic product (GDP) of the country, which is an indicator of human well-being. The MSW management policy of India needs to be reviewed in a current policy context, as the management and efficient utilization of MSW technologies might help increase the use of CH4 as an energy source and thereby improve its sustainable and cost-effective management.

Aqueous geochemistry of fluoride enriched groundwater in arid part of Western India.

Fluoride-enriched water has become a major public health issue in India. The present study tries to evaluate the geochemical mechanism of fluoride enrichment in groundwater of western India. Total 100 groundwater samples were collected for the study spreading across the entire study area. The results of the analyzed parameters formed the attribute database for geographical information system (GIS) analysis and final output maps. A preliminary field survey was conducted and fluoride testing was done using Hach make field kits. The fluoride concentration ranges from 0.08 to 6.6 mg/L (mean 2.4 mg/L), with 63 % of the samples containing fluoride concentrations that exceed the World Health Organization (WHO) drinking water guideline value of 1.5 mg/L and 85 % samples exceeding the Bureau of Indian Standards (BIS) guidelines of 1 mg/L. The study also reveals high concentration of nitrate that is found to be above WHO standrads. The dominant geochemical facies present in water are Na-Cl-HCO3 (26 samples), Na-Ca-Cl-HCO3 (20 samples), Na-Cl (14 samples), and Na-Ca-Mg-Cl-HCO3 (11 samples); however, sodium and bicarbonate being the major component in all the water types of 100 samples, which in fact has a tendency to increase fluoride concentration in water by dissolving fluoride from fluorite. The thermodynamic considerations between the activities of calcium, fluoride, and bicarbonate suggest that fluoride concentration is being governed by activity of calcium ion. X-ray diffraction analysis of sediments reveals calcite and fluorite are the main solubility-control minerals controlling the aqueous geochemistry of high fluoride groundwater. The results indicate that the fluoride concentration in groundwater is mainly governed by geochemical composition of rocks, such as metamorphic granites and sedimentary rocks, alkaline hydrogeological environment, climatic conditions, high temperature and lesser rainfall, and geochemical processes such as weathering, evaporation, dissolution, and ion exchange.

Identification of erosional and inundation hazard zones in Ken-Betwa river linking area, India, using remote sensing and GIS.

Ken-Betwa river link is one of the pilot projects of the Inter Linking of Rivers program of Government of India in Bundelkhand Region. It will connect the Ken and Betwa rivers through a system of dams, reservoirs, and canals to provide storage for excess rainfall during the monsoon season and avoid floods. The main objective of this study is to identify erosional and inundation prone zones of Ken-Betwa river linking site in India using remote sensing and geographic information system tools. In this study, Landsat Thematic Mapper data of year 2005, digital elevation model from the Shuttle Radar Topographic Mission, and other ancillary data were analyzed to create various thematic maps viz. geomorphology, land use/land cover, NDVI, geology, soil, drainage density, elevation, slope, and rainfall. The integrated thematic maps were used for hazard zonation. This is based on categorizing the different hydrological and geomorphological processes influencing the inundation and erosion intensity. Result shows that the southern part of the study area which lies in Panna district of Madhya Pradesh, India, is more vulnerable than the other areas.

Geochemical modeling of high fluoride concentration in groundwater of Pokhran area of Rajasthan, India.

The groundwater is the only major source of drinking water in western part of Rajasthan, India. The study was carried out to locate and decipher hydrogeochemical reactions responsible for elevated concentration of fluoride. The concentration of fluoride ranged from 0.6 to 4.74 ppm in groundwater of study area. Since the area is a desertic terrain and no industries are present thus possibility of anthropogenic input of fluoride is all most negligible thus the enrichment of fluoride in groundwater is only possible due to rock-water interaction. The highly alkaline conditions indicated fluorite dissolution as major process responsible for high concentration of fluoride in Pokhran.