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Water Conservation Science and Engineering
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  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 2366-3340 - ISSN (Online) 2364-5687
Published by Springer-Verlag Homepage  [2468 journals]
  • Evolution and Trends of Water Scarcity Indicators: Unveiling Gaps,
           Challenges, and Collaborative Opportunities

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      Abstract: Abstract Water scarcity indicators serve as tools for assessing the extent and nature of water scarcity within a region. The evolution of these indicators and assessment methodologies dates back to the 1980s. Employing a bibliometric approach, this study aims to delineate trends, research hotspots, influential studies, authors, institutions, and countries within the domain. Utilizing Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) extension and VosViewer software, 153 articles from Web of Science and 248 articles from Scopus up to the year 2020 were analyzed. The post-2000 era witnessed a notable surge in research endeavors, particularly directed at comprehensive water scarcity indicators. Key research domains included the integration of green and grey water, environmental flows, virtual water trade, water footprinting of food production, and exploration of adaptive capacity. Prominent research gaps encompassed the absence of climate change integration in water scarcity assessments, the omission of local contextual factors, challenges related to data availability, sociocultural considerations, and the influence of governance and policies. Geographic analysis highlighted a concentration of research output in regions such as China, the Americas, and Europe, underscoring comparatively tepid research activities in water scarcity hotspots including the Middle East, North Africa, and South Asia, coupled with an associated funding disparity. The study underscores the exigency for enhanced collaborative research endeavors rooted in holistic methodologies that inherently acknowledge local contextual nuances.
      PubDate: 2024-02-20
       
  • Utilization of Graphene Oxide-Chitosan Nanocomposite for the Removal of
           Heavy Metals: Kinetics, Isotherm, and Error Analysis

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      Abstract: Abstract In this study, the synthesis of nanocomposite using graphene oxide and chitosan and its application for the removal of Cr (VI) and Ni (II) ions from wastewater was explored. The characterization of the synthesized graphene oxide-chitosan nanocomposite (GO-CNC) has been investigated with XRD, FT-IR, and SEM. The effect of pH, adsorbent dosage, effluent concentration, and contact time on Cr(VI) and Ni(II) removal was studied. It was found that for Cr (VI) maximum of 90.74% removal was observed at pH 5, 105 min, initial metal ion concentration 10 mg L−1, and adsorbent dosage of 20 g L−1. Ni(II) removal of 58.56% occurred at pH of 8, 90 min, initial metal ion concentration of 10 mg L−1, and adsorbent dosage of 20 g L−1. Adsorption isotherms Langmuir, Freundlich, and Temkin were used. Best fit for Cr(VI) was Freundlich isotherm ions and Langmuir isotherm for Ni(II) with correlation coefficient values greater than 0.9. The Freundlich isotherm value 1/n less than 1 implies the favorability of the adsorption onto the GO-CNC. Our experimental data was described by the pseudo-second order kinetic model for both the metal ions. To forecast the best model, error functions, the sum of squared errors (SSE), the average relative error (ARE), the sum of absolute errors (EABS), and Marquardt’s percent standard deviation (MPSD) were used to predict the single parameters by using non-linear regression analysis to reduce the bias of linear correlation coefficient. The regeneration of GO-CNC nanocomposite showed significant removal efficiencies up to four cycles.
      PubDate: 2024-02-20
       
  • Delineation of Groundwater Potential Zones in Narmada District Gujarat
           (India) Using GIS and AHP Techniques

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      Abstract: Abstract A detailed study was conducted to identify groundwater potential zones in Gujarat’s Narmada district using the analytical hierarchy process (AHP) based on GIS and eleven thematic layers, including annual rainfall, slope, soil, curvature, drainage density, distance from river, lineament density, land use/land cover (LULC), geology, geomorphology, and topographic wetness index (TWI). The study’s findings demonstrate that a number of factors, including lithology, slope, and land use/land cover, have an influence on the potential for groundwater in the Narmada district. The total district was classified into low, moderate, and high potential zones; 31.79733 km2 (1.143461%) of the district falls in low groundwater potential zone, 2251.19 km2 (80.95484%) in moderate potential, and 497.81 km2 (17.9017%) in high potential zone. High groundwater potential zones are correlated with agricultural land use, moderate slopes, and favourable geomorphology, whereas low groundwater potential zones are associated with dense vegetation, steep slopes, and unfavourable geomorphology. Using groundwater level data, the ROC curve approach was used to evaluate the accuracy of the groundwater potential zones map. The generated maps of groundwater potential can be helpful in groundwater resource management and planning, helping to identify the best locations for digging new wells, maximising the usage of existing wells, and putting into practice effective groundwater management strategies.
      PubDate: 2024-02-14
       
  • Integration of Multivariate Adaptive Regression Splines and Weighted
           Arithmetic Water Quality Index Methods for Drinking Water Quality Analysis
           

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      Abstract: Abstract The water quality index (WQI) is a widely used tool for assessing water quality of various water bodies, but it has drawn criticism for being transferable globally and taking a more physical approach. The present study aimed to assess the water quality indices using weighted arithmetic method and investigate alternative approach to improve the prediction accuracy of WQI by applying machine learning algorithms. These include artificial neural networks, decision trees, random forest, gradient boosting machine, multivariate adaptive regression splines (MARS), Gaussian process with radial basic function, support vector machine with radial basic function, a hybrid of Bayesian and ridge regression, and K-nearest neighbor; the spatiotemporal assessment of the WQI revealed a considerable fluctuation that requires further research to determine the potential causes. The water quality dataset was split into training (70%) and testing (30%) datasets, and the tenfold cross-validation technique was utilized to compare models and optimize hyperparameters on various subsets of the dataset. The study result revealed that almost all of the deployed machine learning models performed well on the training dataset. The multivariate adaptive regression spline (MARS) model outperformed others during both the training and testing phases (RMSE = 0.044, R2 = 0.89, and MAE = 0.025; RMSE = 0.090, R2 = 0.87, and MAE = 0.061 respectively), with the normalized dataset. The worst prediction performance in the test dataset was attained by kernel-based models such as the Gaussian process and support vector machine, which was possibly the effect of overfitting during the model-building process. A MARS model equation, employing three strongly impacting water quality parameters, including E. coli, free residual chlorine, and turbidity, was finally suggested to predict the water quality index for drinking purposes.
      PubDate: 2024-02-02
       
  • Impact of Climate Change on Irrigation Case Study on Wonji Shoa Sugar
           Plantation Estate

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      Abstract: Abstract Irrigation is significant in increasing agriculture production and productivity for the sustainability of the country’s economy. Impacts on existing activities for irrigation design and management systems are obvious due to the rapid change of climate system. This paper’s future focus is to evaluate the influence of the changing climate on the crop yield and irrigation requirement for the Wonji Shoa sugarcane plantation estate. For future climate data, it used the results of projections of the CORDEX regional climate model (RCM) with bias correction for medium concentration representative pathway 4.5 rcp and high concentration representative pathway 8.5 rcp scenario. The down-scaled data were then used as input to the AquaCrop model. The time series indicates a significant increasing trend in maximum and minimum temperature values and a slight increasing trend in precipitation for both 4.5 rcp and 8.5 rcp scenarios. The evapotranspiration shows an increase in 20.34%, 20.12%, 23.59%, and 24.36% for 8.5 rcp in the period of 2020s, 2040s, 2060s, and 2080s, respectively. For 4.5 rcp scenario, the change is about 8.4%, 11.65%, 13.22%, and 15.85% for the period of 2020s, 2040s, 2060s, and 2080s, respectively. The model output shows that there is an annual increase in yield. For 8.5 rcp scenarios, the incensement is 6.2%, 7.84, 11.03%, and 14.48% in the 2020s, 2040s, 2060s, and 2080s, respectively. For 4.5 rcp scenarios, the increment is much lower compared to 8.5 rcp scenarios. But there is still an increase in yield for 4.5 rcp. The change is 0.3%, 1.8%, 7.02%, and 4.82% for the period of 2020s, 2040s, 2060s, and 2080s, respectively.
      PubDate: 2024-01-17
       
  • Estimation of Groundwater Evapotranspiration and Extinction Depth Using
           Diurnal Water Table Fluctuation and Remote Sensing Observations: A Case
           Study in Agriculture-Dominated Watershed of Eastern India

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      Abstract: Abstract Groundwater models meticulously considering the water balance components have paramount importance in sustainable decision-making on groundwater. Plant uptakes and transpires water from the groundwater, called groundwater evapotranspiration (ETG), ‛is one of the major contributions to the water balance. ETG needs to be quantified for shallow groundwater areas as they account for major depletion in groundwater. This study evaluated the White and modified White methods to estimate ETG for the agricultural-dominated Rana watershed with a tropical savanna climate in Eastern India. This modified method uses the sine function to capture the diurnal fluctuation of groundwater and estimates daily to seasonal ETG. Additionally, a physical-based modeling strategy was adopted to estimate the ETG over the study basin as a function of soil moisture change from the surface to the saturation depth and delineate the extinction depth of ETG. Additionally, this study compared the efficacy of both the empirical methods with the physical-based model to estimate ETG in agricultural land use. Results showed that ETG was nearly 50–70% of crop evapotranspiration and was higher in magnitude in the dry periods of the year due to less availability of topsoil moisture. The range of extinction depth was observed to be from 1 to 3 m for the hard rock area, whereas the same was from 5 to 9 m for other regions. When the comparison is made on a seven-day window, the modified White method produced an R2 of 0.88, whereas that of the White method was 0.40. Conclusively, the modified White method reliably estimates the ETG and can be applied successfully in shallow groundwater level regions for reducing uncertainty in groundwater head prediction due to oversimplification of water balance components.
      PubDate: 2024-01-12
       
  • Efficient Photocatalytic Decomposition of Acid Blue 25 Dye using Facilely
           Synthesized Magnesium Aluminate Nanoparticles

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      Abstract: Abstract The release of acid blue 25 dye from factories into water sources has been linked to various health issues, including cancer, skin irritation, redness, and allergic reactions. Also, the photocatalytic degradation process plays a vital role in addressing the global challenge of pollution by offering an environmentally friendly, versatile, and efficient method for removing contaminants from water. Therefore, this study focused on the low-cost and facile fabrication of MgAl2O4 nanoparticles by the Pechini sol–gel procedure. Subsequently, these nanoparticles were utilized for effective photocatalytic breakdown of acid blue 25 dye. Using tartaric acid in the Pechini sol–gel synthesis of MgAl2O4 nanoparticles introduces novel and significant aspects. Tartaric acid chelates with metal ions like magnesium and aluminum, ensuring a homogeneous ion distribution, enhanced precursor stability, reduced particle aggregation, and smaller crystal size in the final product. In addition, the fabricated MgAl2O4 nanoparticles were thoroughly characterized using different techniques, including Fourier-transform infrared spectroscopy (FT-IR), ultraviolet–visible spectrophotometry (UV–Vis), high-resolution transmission electron microscopy (HR-TEM), field emission scanning electron microscopy (FE-SEM), and X-ray powder diffraction (XRD). In addition, the XRD revealed that the mean crystal size of the fabricated MgAl2O4 nanoparticles was 14.25 nm, while their optical energy gap was 3.76 eV. FE-SEM analysis revealed a mixture of spherical and irregular forms with an average grain size of 0.34 µm. HR-TEM analysis revealed that the fabricated MgAl2O4 nanoparticles consisted of tiny spherical particles with an average diameter of 12.78 nm. The maximum photocatalytic breakdown of 50 mL of 100 mg/L acid blue 25 dye, reaching 99.86%, was achieved within 35 min at pH 3. Additionally, the results demonstrated consistent breakdown efficiency of the acid blue 25 dye even after four cycles, validating the efficacy and reusability of the developed MgAl2O4 nanoparticles.
      PubDate: 2024-01-12
       
  • Designing and Evaluating the Performance of Full-scale Bioretention Cells
           in Indian Conditions

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      Abstract: Abstract Urbanization leads to an increase in impervious area percentage and significantly alters the predevelopment hydrology. Bioretention cells are sustainable stormwater management techniques that mimic the natural soil system of an area and help in restoring the hydrological balance. Present study involved construction of full-scale bioretention cells and filling them with engineered filter media to assess the field performance. The filter media was prepared from coarse sand and topsoil mixed with rice straw–derived biochar and maize straw–derived compost. This study addresses the emerging need for effective stormwater management in urban areas by evaluating the performance of full-scale bioretention cells. The use of engineered filter media derived from rice and maize residues demonstrates innovation in stormwater management, and thus contributing to sustainable resource use. The bioretention cells were planted with plant varieties—Thumbergia erecta, Haemelia patens and Tabernaemontana divaricata. The bioretention cells were observed for pre- and post-plantation hydraulic conductivity and hydrologic performance. Full-scale bioretention cells reported a pre-plantation average hydraulic conductivity between 118.0 and 324.0 mm/hr. Post-plantation average hydraulic conductivity ranged between 341.6–562.0 mm/hr. The minimum and maximum pre-plantation hydraulic conductivity for bioretention cell 1 filled with compost were 112.5 and 136.5 mm/hr, respectively. The average hydraulic conductivity of 120.5, 211.1 and 241.4 mm/hr were observed for bioretention cells 1, 3 and 5 respectively. In the case of biochar-filled bioretention cells, the average hydraulic conductivity recorded for various rainfall events were 162.3, 175.5 and 190.3 mm/hr for bioretention cells 2, 4 and 6, respectively. Given the design parameters adopted for the field-scale bioretention cells, the time to empty based on minimum hydraulic conductivity values was 11 times faster than the recommended maximum time to empty for the bioretention cells. The volume and peak flow reduction of the full-scale bioretention cells ranged between 82.9–90.2% and 86.1–92.3%, respectively. The total contribution of 6 bioretention cells to the groundwater recharge in three recorded events was 18.2 m3.
      PubDate: 2024-01-10
       
  • Biosorption of Crystal Violet, a Cationic Dye onto Alkali Treated
           Rauvolfia tetraphylla Leaf: Kinetics, Isotherm and Thermodynamics

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      Abstract: Abstract The leaves of Rauvolfia tetraphylla (RTL), an abundantly grown woody shrub, have been modified with mild alkali and exercised for remarkable uptake of crystal violet dye from simulated and industrial wastewater. FESEM and FTIR characterize the material, whereas BET surface area indicates porosity. The stability of NRTL has been tested by TGA.FTIR proposes the presence of amine and polyphenolic functionalities which are capable of crystal violet binding through electrostatic and hydrogen bonding. As identified from FESEM images, surface texture displays well-defined channels with heterogeneous pore openings ideal for dye attachment. The NRTL’s zero-point charge (pHZPC) is 7.5, an ideal pH for dye removal from wastewater. The uptake process follows the Langmuir adsorption isotherm model (R2 = 0.998) and pseudo-second-order kinetic model (R2 = 0.999). Satisfactory regeneration (68%) has been achieved with 1:1 methanol/water solution and the material is capable of three-cycle use. Industrial effluent treatment was mapped to assess the field applicability of the present protocol. The activated leaves of Rauvolfia tetraphylla could be a future choice for small-scale dye removal from colored effluent with a maximum uptake competency of 109.99 mg/g.
      PubDate: 2024-01-09
       
  • Nitrogen- and Sulfur-Rich Activated Carbon Derived from Biomass Waste as
           Adsorption Probe for Pb2+ Ions

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      Abstract: Abstract In the present work, nitrogen (N)- and sulfur (S)-rich activated carbon were prepared from biomass waste pine needles through activation by conc. H2SO4 followed by its thermal annealing. The prepared activated carbon material was analyzed by HR-TEM, XRD, XPS, and FT-IR techniques. XPS and FT-IR analyses confirm different functionalities present in the sample along with their percentage. HR-TEM and XRD analysis confirmed that the sample is highly amorphous with small graphitic flakes embedded in it. The prepared material was designated as NS-PN-AC, exhibiting remarkable performance for extremely sensitive detection of Pb2+ ions by UV-Vis spectroscopy. The UV-Vis results show that the prepared material has a strong absorption peak at 0.2042 Å. However, the presence of Pb2+ significantly reduced the intensity of the absorption. A limit of detection (LOD) of 7.7 ppm was reached in the presence of Pb2+ concentration ranging from 0 to 10 ppm. These findings demonstrated the viability of developing sensors for detecting and removing lead (II) ions using inexpensive precursors.
      PubDate: 2023-12-14
       
  • Electrospun Polysulfone Hybrid Nanocomposite Fibers as Membrane for
           Separating Oil/Water Emulsion

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      Abstract: Abstract Commercial polymer membranes are largely utilized to separate oil/water mixtures; however, membrane fouling, flux decline, and short lifetime often inhibit their high performance. In order to resolve these drawbacks of the commercial membranes, we introduce a surface modification strategy following the electrospinning method. Electrospun fibers of polysulfone (PSf)/iron oxide (FeO)/halloysite nanotubes (HNT) nanocomposite are applied to modify the polyether sulfone (PES) standard membrane support surface for developing highly efficient oil/water emulsion separating membranes. This facile and simple spinning process for shorter periods ensures nanocomposite coatings on the standard PES membranes and allows a better oil/water separation. We analyze the structural and morphological characteristics of the modified membrane surface using scanning electron microscopy, Fourier transformation infrared spectroscopy, and X-ray diffraction studies and hydrophilicity from contact angle studies. FeO nanoparticles of 2–5 nm and HNTs of < 50 nm size mixed in PSf produce fibers of 531 ± 162 nm average diameter at a relatively lower applied electrical voltage of 14.5 kV, compared to PSf. Underwater and under-oil contact angle values are used to prove the surface characteristics of the membranes and total organic content (TOC) values for the emulsion separation performance. From PES support to PSf and PSf/HNT-FeO, the TOC values respectively change from 67 to 75 and 79%. We find moderately hydrophilic membranes (PSf/HNT-FeO) resulting in a higher permeate flux (28,447 Lm−2·h−1) and quicker separation performance. We believe this study provides a notable solution to modify the surface of commercial membranes for better emulsion separation performance.
      PubDate: 2023-12-13
       
  • Revealing Regime Shifts and Their Impact on Social-Ecological Systems: a
           Case Study on Iran

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      Abstract: Abstract This study examines the impact of human activities during the Anthropocene era on social-ecological systems globally, with specific focus on Iran. The investigation identifies regime shifts and their effects on ecosystem services, aiming to understand the causes and mechanisms behind these shifts. The key regime shifts observed in the studied provinces are the reduction of groundwater levels and river flows. Various factors, such as decreasing rainfall, increasing temperatures, unauthorized wells, and overexploitation of groundwater, contribute to these modifications. Network analysis reveals several drivers in the network, including non-implementation of land use planning, urbanization, poverty, dam construction and water transfer projects, inappropriate water allocation and distribution policies, and population increase. These regime shifts significantly impact multiple ecosystem services, such as climate regulation, water production, biodiversity, air quality regulation, food production, aesthetic and recreational values, and animal husbandry. Recognizing the ecosystem services at risk and understanding how they deteriorate in social-ecological systems inform managers about the main consequences of regime shifts in Iran. Thus, knowledge of regime shifts and their operation in different scales of social-ecological systems is crucial for future management planning. In conclusion, this study highlights the importance of recognizing regime shifts in social-ecological systems, understanding their drivers, and developing appropriate measures to adapt to the new state of the system. By doing so, effective management planning and adaptation to new social-ecological conditions can be achieved, ensuring the maintenance of ecosystem services for human well-being and environmental sustainability not only in Iran but also elsewhere.
      PubDate: 2023-12-07
       
  • Soil Loss Estimation Using RUSLE in Hard Rock Terrain: a Case Study of
           Bundelkhand, India

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      Abstract: Abstract The present study revealed the potential runoff estimation, soil erosion, and scope of groundwater recharge in the Bundelkhand region in the state of Uttar Pradesh, India. The estimation of runoff and soil erosion has provided a platform to evaluate the realistic potential for water conservation in the study area. Soil Conservation Services and Curve Number (SCS-CN) method has been used to calculate the runoff volume. The soil loss has been calculated using Revised Universal Soil Loss Equation (RUSLE). The estimated runoff varies from 5.5 to 28% of the total rainfall in the study area, while soil loss is estimated maximum (198.2 ton/ha/yr) in the watershed-I. The soil loss estimated has also been validated with a fair degree of accuracy using results of previous investigators. This finding provides the roadmap for the selection of suitable artificial recharge structures to augment the groundwater in the study area.
      PubDate: 2023-11-30
      DOI: 10.1007/s41101-023-00229-5
       
  • Assessment of Net Irrigation Requirements for Spring Wheat and Spring
           Maize in Shiyanghe Watershed, Northwestern China

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      Abstract: Abstract Evaluating net irrigation requirements could support water resources managements, especially in arid regions. Shiyanghe watershed was in the northwest of China, and its dominant grain crops were spring wheat and spring maize. Their net irrigation requirements rate would be assessed by subtracting effective rainfall from crop evapotranspiration rate at four meteorological stations in the study area in this study. Among which effective rainfall would be calculated by an empirical effective rainfall formula of Northern China and crop evapotranspiration rate would be estimated by FAO Penman–Monteith equation. Then, the estimated results of accumulated net irrigation requirements rate at different stations would be expanded to the entire watershed by using inverse distance weighted interpolation method. Results showed that the accumulated net irrigation requirements rate tended to be the biggest at Minqin station and smallest at Wushaoling station for both crops during different stages, which accord with the geography distribution in the watershed. And mid-season stage had the biggest net irrigation requirements rate, then development stage, last season stage, and initial stage. The zonal averaged accumulated net irrigation requirement rates of spring wheat and spring maize in the entire watershed except for Jingtai county were 353.20 mm/whole season and 432.62 mm/whole season, respectively. And comparison with local irrigation norms and irrigative efficiencies indicated insufficient local agricultural water supply. This study can help water resources and weather modification departments organizing arrangements and operations to mitigate with water shortage problems. The detailed data selection and processing methods are also referenceable for relevant researches.
      PubDate: 2023-11-08
      DOI: 10.1007/s41101-023-00228-6
       
  • Advancements in Water Desalination Through Artificial Intelligence: a
           Comprehensive Review of AI-Based Methods for Reverse Osmosis Membrane
           Processes

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      Abstract: Abstract This research paper focuses on the importance of water as a precious resource and the challenges associated with meeting the growing demand for clean, drinkable water, particularly in regions facing water scarcity. The paper emphasizes that desalination, which involves the removal of salt and other impurities from seawater, is a viable solution to address this challenge. The paper highlights the role of Artificial Intelligence (AI) in optimizing desalination processes, including predictive maintenance, predictive water quality, and predictive energy management. The paper reviews the latest research papers on AI-based water desalination systems, thoroughly analyzing the use of AI-based modeling tools for Reverse Osmosis (RO) membrane processes for water desalination. The study also gives current trends and future prospects, as well as analyzes the pros and cons of AI-based methodologies compared to conventional models. Overall, the article highlights how AI could improve RO-based membrane desalination operations and shortcomings and recommendations for future work.
      PubDate: 2023-10-13
      DOI: 10.1007/s41101-023-00227-7
       
  • Spatial Distribution, Exposure and Potential Ecotoxicological Health Risk
           Associated with Geogenic Contaminants in Groundwater Resources of Manipur
           Valley, India

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      Abstract: Abstract The concentration of selected geogenic contaminants were evaluated in the groundwater resources of Manipur Valley of India to assess their ecotoxicological human health impacts associated with long-term oral exposure to groundwater. The study focuses on and presents the regional distribution of exposure, concentration and potential ecotoxicological risks to human health among dependent adults and kids. According to the study, some geogenic pollutants, including Ni (24.28%), Co (2.85%), As (7.14%), F (37.14%) and Br (28.57%), have elevated concentrations that are higher than the WHO’s standard permitted thresholds. Approximately 94.6% of the groundwater samples are of acceptable quality, according to the heavy metal pollution index, with only 5.4% falling into the “unsuitable” category. The hazard quotients of As and F were found beyond the critical value (> 1) for non-carcinogenic health risk, whereas As and Cr exhibit very high values for carcinogenic health risk. The spatial distribution maps highlight the vulnerable zones concerning the concentration of the contaminants, oral exposure and potential human health risks associated with continuous long-term oral exposure. As a result, the study offers a thorough scenario of geogenic pollutants in the area’s groundwater resources and highlights likely spatially susceptible zones based on potential threats to human health. The groundwater management actions in the area and future uses of groundwater can both benefit from the baseline data provided by this study.
      PubDate: 2023-10-12
      DOI: 10.1007/s41101-023-00225-9
       
  • Quantifying Soil Erosion and Identifying Critical Source Areas Under
           Current Management in the Holeta Watershed, Awash Basin, Ethiopia

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      Abstract: Abstract Erosion is the most widespread form of soil degradation overall in the world. In the current study, soil erosion is quantified, and areas prone to high risk of soil erosion are identified under current management in the Holeta watershed, Awash Basin, Ethiopia, where lands are primarily cultivated. The Soil and Water Assessment Tool (SWAT) was applied to simulate the baseline hydrologic and soil erosion processes. The model used spatial (i.e., DEM, land use, and soil maps) and temporal (climate) data to simulate different biophysical processes. Moreover, streamflow and sediment data were acquired and analyzed for model calibration and validation. The performance of the model during calibration and validation with both streamflow and sediment loads was evaluated against the measured data by using statistical parameters (R2 = 0.64, 0.81, NSE = 0.61, 0.76, PBIAS = 12.6%, 9.8%, respectively) during calibration and validation with streamflow and (R2 = 0.78, 0.68, NSE = 0.74, 0.61, PBIAS = 16.1%, 18.2%, respectively) while calibration and validation by sediment. The annual sediment load in the Holeta watershed varies from 2 to 136.4 t/ha/year with an average of 18 t/ha/year. The annual severity of sediment load was prioritized under very low, low, moderate, high, very high, and severe. About 13.3% of the Holeta watershed’s sub-basin contributed a higher sediment yield than average under current management. The significant sediment yield is generated from cultivated areas whereas; the lowest magnitude is generated from forested areas. Overall, since the generated sediment is within the tolerated range, current conservation retains soil loss for sub-basin 2, 4–15, and effective management practices can be identified by further study and established for the erosion-affected areas (sub-basins 1 and 3).
      PubDate: 2023-09-27
      DOI: 10.1007/s41101-023-00226-8
       
  • Assessment of the Impact of Land Use and Land Cover Change on Hydrological
           Components of the Upper Watershed of Subarnarekha River Basin, Jharkhand,
           India Using SWAT Model

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      Abstract: Abstract This study investigated the impact of LULC changes on several hydrological components of the upper watershed of the Subarnarekha river basin, Jharkhand, India. Several hydrological components of the water balance were simulated using the Soil and Water Assessment Tool (SWAT). Three scenarios were generated using a combination of climatic data for the years (1997–2020) and LULC data for the years (2000, 2012, and 2020). The model was run successfully for the calibration and validation period using monthly stream flow data. Sixteen model parameters were applied for sensitivity analysis. RCHRG_DP and ALPHA_BF were found to be the most sensitive parameters. The components of the water balance were calculated accurately. The outcome of this study shows the decrease in evapotranspiration, recharge to deep aquifer and shallow aquifer, and the increase in surface runoff due to urban development and negative change in forest cover over the study area. A significant increase in surface runoff is viewed as a negative impact on watersheds or river basins that balances the hydrological process. In general, the increased surface runoff may intensify the environmental problem by accelerating erosion and sedimentation. The findings of this study will be beneficial to the hydrological community, water resource managers, and decision-makers active in agricultural water management and soil conservation as well as those working to mitigate increased surface runoff and floods from the perspective of LULC transformation and climate change.
      PubDate: 2023-09-27
      DOI: 10.1007/s41101-023-00224-w
       
  • Soil Erosion Assessment by RUSLE, Google Earth Engine, and Geospatial
           Techniques over Rel River Watershed, Gujarat, India

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      Abstract: Abstract The assessment of soil erosion holds paramount significance in sustainable land management and environmental conservation. In this context, the integration of advanced technologies such as the Revised Universal Soil Loss Equation (RUSLE), Google Earth Engine (GEE), and geospatial techniques presents a formidable approach for evaluating soil erosion dynamics. This integrated methodology proves particularly valuable when applied to the Rel River watershed, where factors such as terrain, land use, and precipitation patterns intricately influence erosion processes. The collective use of two methods, the quantitative method focused on RUSLE to assess soil under various circumstances of erosion and sediment yield, whereas the qualitative approach focused on spectral indices of soil erosion in GEE to generate degradation map. This study was aimed at evaluating soil erosion and land degradation across the Rel River watershed in the western region of Gujarat, India. Soil loss has been estimated using soil loss models, i.e., RUSLE and geoinformation datasets, which were extracted from GEE. The degraded area was prepared using GEE and mapped using geographical information system (GIS). The results demonstrate that estimated value for erosion due to rainfall is 37 to 40 MJ mm h−1 ha−1 year−1, soil erodibility is 0.01 to 0.05 ton h MJ−1 mm−1, topographic variables lies in a range from 0 to 20, and crop management factor is 0.001 to 1. The findings also demonstrate that the total annual soil loss for flood events in 2017 is 35.36 t/ha/year, which is categorized into the severe zone of degradation. According to the soil degradation map created using GEE, the majority of the study region falls into the low and medium degradation zones, while the northeastern part and river fall into the high degradation zone. The findings will be helpful in implementing soil management and conservation techniques to arrest soil erosion in the Rel River watershed.
      PubDate: 2023-09-26
      DOI: 10.1007/s41101-023-00223-x
       
  • Utilization of Pinus kesiya and Schima wallichii Biomass-Derived Activated
           Carbon for Methylene Blue Removal: Adsorption Performance and Mechanistic
           Insights

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      Abstract: Abstract Biomass material offers several advantages to synthesize activated carbon because of its economic viability, renewability, availability, and unique physicochemical properties. This piece of work reports activated carbon prepared from biomass of Pinus kesiya and Schima wallichii via ZnCl2 activation for potential application to remove methylene blue from water. The optimum adsorption parameters—pH, adsorbent dose, and agitation speed—were obtained using Taguchi design of experiment. Experimental equilibrium data of adsorption of methylene blue onto the adsorbents fitted well with Langmuir isotherm with maximum adsorption capacity of 116.28 mg g−1 and 95.24 mg g−1 for Pinus kesiya activated carbon and Schima wallichii activated carbon respectively. The kinetic experimental data followed a pseudo-second-order equation for both the adsorbents. The potential rate-controlling step in the adsorption of methylene blue onto the adsorbents was predominantly intraparticle diffusion with two stages of adsorption for Pinus kesiya activated carbon and three stages of adsorption for Schima wallichii activated carbon. Density functional study investigation suggested that methylene blue adsorption onto activated carbon is predominantly chemisorption, and the presence of a carboxylic acid functional group on the activated carbon surface has a higher methylene blue adsorption affinity with an adsorption energy of −171.85 kJ mol−1 compared to —CHO and —OH functionalized carbon, pristine activated carbon models. Our work indicates that activated carbon derived from Pinus kesiya and Schima wallichii biomass could be an efficient adsorbent to remove methylene blue from water.
      PubDate: 2023-09-15
      DOI: 10.1007/s41101-023-00220-0
       
 
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