Applied Water Science最新文献

Vegetation density extraction is influenced by the characteristics of satellite images, vegetation type, classification algorithm, and region, but there is little information about multispectral imaging (MSI). Studying the compatibility of the information content of sensors to replace sensors in areas where there is no easy access to their data is necessary for remote sensing (RS) studies. This study aims to assess the suitability of MSI from Sentinel-2 and Spot-5 satellites for generating pasture density maps. The Middle Kashkan watershed in the Lorestan Province of Iran was the study area. Geometric correction of the images was performed using ground control points (GCP) and the area's digital elevation model, achieving an accuracy of 0.21 pixels or better. Supervised classification techniques including parallelogram, minimal distance, maximum likelihood, and artificial neural network (ANN) algorithms were applied to the primary MSI of each satellite, as well as the integrated image of Spot-5 and the resulting pasture density map. Three density categories were considered: 5–25%, 25–50%, and over 50%. To validate the accuracy of the classification, a ground truth map of the region was created by interpreting a referenced official digital orthophotomosaic image at a scale of 1:40,000. Comparative analysis of the classified images revealed that the Sentinel-2 image with PCA-2-8 band composition and ANN classification algorithm yielded superior results, with an overall accuracy of 65.72% and a kappa coefficient of 0.08, compared to the Spot-5 image with PCA-3-1 band composition and the ANN classification algorithm. Spot-5 satellite images demonstrated greater effectiveness in generating pasture cover maps across the three density categories. These findings suggest that satellite images with suitable spatial and spectral resolution can be effectively utilized for generating accurate pasture density maps and monitoring long-term pasture preservation, particularly in regions characterized by high aerial photography altitudes in pasture areas. This approach holds the potential for effective pasture management and conservation efforts on a global scale.

Noble metal-free nickel manganese oxysulfide (NiMnOS) catalysts were successfully prepared via a facile and eco-friendly approach at a low synthesis temperature of 90 °C in a water bath. The catalysts were synthesized by varying Ni: Mn molar ratios such as 25:75, 50:50, 75:25 and abbreviated as NiMnOS-25, NiMnOS-50, and NiMnOS-75, respectively. The bare NiOS and MnOS were also prepared for comparison purposes. The characterizations of the prepared samples were conducted with different techniques, and the catalytic activity was investigated through the reduction of methylene blue (MB) dye in the presence of NaBH₄ in an aqueous solution. Among the prepared catalysts, NiMnOS-25 exhibited excellent performance and reduced 98.46% of MB within 5 min. However, NiOS, NiMnOS-50, NiMnOS-75, and MnOS were reduced 9.6%, 98.41%, 97.04%, and 6.40% of MB dye, respectively, within 7 min. The catalytic reduction activity could be mainly attributed to the synergistic effects of the metals (Ni and Mn), more exposed active sites. Therefore, the bimetal NiMnOS catalyst could be a promising candidate for the reduction of organic dyes in wastewater treatment technologies.

Jakarta is the center of Indonesia’s economy and development. However, the city of Jakarta suffers from many problems related to groundwater, and good groundwater governance is needed to realize groundwater sustainability. Groundwater management can be initiated by undertaking conceptual and numerical groundwater modeling. This paper reviews several previous studies related to groundwater modeling of the Jakarta groundwater basin that have provided information about the groundwater system and groundwater quantity. However, improvements are required for any further studies. The critical challenges to providing a complete picture of the groundwater conditions in the Jakarta groundwater basin are the availability of reliable data and improved groundwater flow models.

Dam breach floods pose significant threats to downstream areas, necessitating accurate prediction of inundation scenarios to mitigate potential damage. This paper presents a novel methodology for hydrodynamic modeling of dam breach floods, leveraging a comprehensive approach that integrates satellite imagery, unmanned aerial vehicles (UAVs), and Google Earth Engine (GEE) to forecast downstream inundation scenarios. Specifically, UAVs were utilized to generate high-resolution Digital Elevation Models (DEMs) of the flood-affected areas, ensuring precise representation of topography in the model. The approach incorporates Cartosat DEM data for catchment modeling, while NASA's Global Precipitation Measurement mission data, integrated with GEE, facilitated accurate estimation of rainfall in ungagged catchment areas. Furthermore, the Hydrological Engineering Center-Hydrological Modeling System was employed for rainfall-runoff simulation and flood hydrograph derivation, followed by application of the HEC River Analysis System (RAS) for hydrodynamic modeling under dam breach conditions. This integrated modeling approach was applied as a case study of Banaskantha district, Gujarat, India. The outcome was the generation of scenario maps based on HEC-RAS results, which include flood extent, water depth, and flow velocity, highlighting downstream areas affected by flooding. Validation of the hydrodynamic dam breach model performance was conducted using actual field measurements and simulated results, employing statistical analysis methods including Support Vector Regression (SVR) and linear regression to determine coefficient of determination (R²), Root-Mean-Square Error, and Mean Absolute Error of observed and simulated data. The coefficient of determination (R²) values for measured and simulated flow (0.91) and water level (0.86) calculated using SVR demonstrate strong correlation between observed and simulated values. This integrated study of hydrodynamic modeling in data-scarce areas aids in accurate estimation of future probable flooding in downstream areas in the event of a dam break, underscoring the potential of advanced surveying and modeling techniques in flood assessment and management. Ultimately, this integration of technologies aims to enhance community resilience and mitigate socioeconomic costs associated with dam breach floods.

The effective removal of dye pollutants from water and wastewater is a key environmental challenge. The present study is developed to investigate alizarin (ALI) dye and its derivations, including Alizarin blue (ABL), Alizarin purpurin (APU), Quinalizarin (AQU), Alizarin cyanin (ACY), and Alizarin Red S (ARS) removal process from water and wastewater sources, using covalent organic frameworks (COFs) nanoadsorbents. Herein, we explore the process of how dye molecules are absorbed onto COFs with precise supramolecular structures. The molecular dynamics (MD) and well-tempered metadynamics (WTMtD) simulations are used to investigate this process in aqueous solution. From the results obtained, it is clear that the intermolecular van der Waals (vdw) and π-π interactions have a significant role on accelerating the interaction between dye molecules and the COF nanostructures. This ultimately leads to the creation of a stable dye-COF complex. The dye-adsorbent average interaction energy value reaches around APU-COF1=−604.34, AQU-COF1=-515.25, ABL-COF1=−504.74, ALI-COF1=−489.48, ARS-COF1=−475.81, ACY-COF1=−273.82, AQU-COF2=−459.76, ALI-COF2=−451.46, ABL-COF2=−405.90, APU-COF2=−367.55, ACY-COF2=−287.89, ARS-COF2=−210.63 kJ/mol for dye/COF1 and dye/COF2 complexes, respectively. The primary interaction between dye and COFs is attributed to the Lennard-Jones term, resulting from the formation of a strong π-π interaction between the dye molecules and the surface of the adsorbent. Overall, our simulations confirmed that the COF1 nanostructure is more effective than the COF2 nanostructure in removing alizarin dye and its derivatives. In this study, not only the performance of two COFs in removing alizarin dye and its derivatives has been compared, but also the possibility of removing alizarin dye and its derivatives with both COFs has been examined.

Groundwater aquifers constitute the primary water supply for populations in arid regions, exemplified by the Goharkooh Plain in Iran's driest drainage basin, where conditions of high evapotranspiration and low precipitation prevail. With the escalating demand for water resources, driven mainly by agricultural expansion, the strategic management of groundwater assets has become increasingly critical. This study focuses on delineating groundwater potential zones (GWPZs) through an integrated approach combining multi-criteria decision analysis and geospatial tools. Based on an extensive literature review, nine thematic layers were selected and developed: lithology, geology, drainage density, slope gradient, elevation, vegetation cover, lineament density, land use, and precipitation. These criteria were initially weighted using the analytical hierarchical process (AHP) and subsequently integrated via weighted overlay analysis. In this research, the strategic selection of thematic layers for assessing groundwater potential in arid regions has been identified as an innovative approach that could significantly advance studies in similar settings. The analysis revealed that approximately 60% of the study area, primarily in the southwestern parts, exhibited moderate to very high groundwater potential. This potential is primarily attributed to the presence of alluvial deposits, low drainage density, and favorable slope and elevation conditions. Applying the receiver operating characteristic (ROC) curve yields an area under the curve (AUC) of 81.5%, indicating a relatively high level of predictive accuracy. These findings demonstrate the efficacy of this integrated approach, suggesting its broader applicability in regions with analogous groundwater challenges and management needs.

Perfluoroalkyl acids (PFAAs) are widespread in the aquatic environment and also measurable in ground and drinking water. Because of the insufficient PFAA elimination in conventional water treatment processes, e. g. active carbon based methods, consumers in areas with contaminated water supplies are exposed to an elevated health hazard. For this purpose, the applicability of five differentially fluorinated silica-based adsorbents (HSU00107954-958) to remove the potentially human toxic perfluoroalkyl sulfonic acids(PFSAs) perfluorooctane sulfonic acid (PFOS), perfluorohexane sulfonic acid (PFHxS), and perfluorobutane sulfonic acid (PFBS) from water was investigated with regard to removal efficiencies (REs) and equilibrium loadings. During the adsorbent screening at nanomolar concentrations (20.0–33.4 nmol L⁻¹) maximum REs of 46.9% for PFBS (HSU00107954), 79.4% for PFHxS (HSU00107954), and between 86.5 to 96.7% for PFOS (HSU00107956, and HSU00107954, respectively) have been achieved. Even at picomolar concentrations (< 400 pmol L⁻¹) HSU00107954 was still able to eliminate PFBS and PFHxS with an efficiency of 46.3–51.2% and 79.1–88.2%, respectively. Analyses of the equilibrium loadings of the functionalized adsorbents in the concentration range 40.1 pmol to 3.34 nmol L⁻¹ resulted in appropriate linearized Freundlich isotherms for all investigated PFSA. Compared to literature-based Freundlich adsorption coefficients (K_F) for granular activated carbon (GAC), the determined K_F values (nmol⁽¹⁻ⁿ⁾ Lⁿ m⁻²) of the most efficient adsorbents HSU00107956 and HSU00107954 for each PFSA were significantly 8–10 and 50–60 times higher, respectively. These proven increased adsorption capacities relative to activated carbon possibly indicate specific PFSA selectivities of the functionalized macroporous silica adsorbents.

In arid climates, conventional water resources are severely limited and stressed in the face of rapid population growth and future climate change. So, it is necessary to find alternative non-conventional water resources for use in drought situations. Additionally, the non-conventional water resources in these areas are not sufficient to meet future water demand. Therefore, non-conventional water resources can be adopted as a strategic reserve to bridge the gap between water supply and demand in case of emergency and drought events. These resources might include rainwater harvesting, treated wastewater, and desalinated seawater. Managed aquifer recharge (MAR) can be applied to store these resources in the hydrogeological system using Geo information System—Multi Criteria Decision Analysis (GIS-MCDA) approach for determining the suitable MAR location for storage. North-west Kingdom of Saudi Arabia area was chosen for this study because it is extremely arid, has high potential for social and economic development, and it has newly constructed non-conventional water infrastructures distributed throughout the area including water desalination plants, Tertiary Sewage Effluent (TSE) waste water plants, and flash-flood storage dams. To identify the suitable MAR site location and structure, different data related to aquifer hydrogeology, surface hydrology, hydrometeorology, and water quality were applied. Then, GIS-MCDA holistic approach was applied with aid of ordered weighting average (OWA) technique. Finally, two maps were created to show the MAR location and structure type. Potential map indicates that ~ 18.85% of the area is suitable for MAR installations. About 0.17% of the total area exhibited very high potential, where infiltration ponds can be applied, 1.86% had high potential for construction of check dams with diversion channels, and 16.82% had moderate potential for installation of recharge wells. Additionally, 56 MAR structures were proposed and a map showing their locations has been created. Thus, results indicated that the study area is promising for MAR installation. These maps could aid the decision makers to propose a sustainable development plan for the future water resources of the area.

Rising population strains food resources; reusing wastewater increases but brings microbial and heavy metal pollution, impacting nature and human health. Among environmental pollutants, heavy metals in wastewater are a major concern. Using magnetized water is a method to improve water and soil quality. The aim of this research is to investigate the effect of using treated magnetized wastewater on the chemical properties and tracking of heavy metals in the soil, performance and yield components, water efficiency, and absorption of heavy metals by maize plant. Irrigation treatments consisted of various water and wastewater blending ratios under both magnetic and non-magnetic field application conditions. The results showed that the effect of irrigation water and mixing of water and wastewater on electrical conductivity, soil salts and heavy metals in different depths were significant at 1% probability level. On average, irrigation with magnetized wastewater caused a significant increase in grain yield (9.8%) and biological yield of maize (10.63%) compared to non-magnetized wastewater treatment. Irrigation with magnetized wastewater caused a significant increase in biological (10.92%) and physical (10.13%) productivities compared to non-magnetized wastewater treatment. With applying a magnetic field resulted in a reduction of 17.99%, 23.25%, 17.86%, and 17.12% in the concentration of lead, cadmium, zinc, and nickel in the aerial parts of the plant, respectively, compared to the non-magnetized water treatment. Magnetized water increases the water use efficiency of maize and irrigation management with this technology can be useful in more effective and economical use of limited water resources.

The currently used standardised precipitation index (SPI) does not allow for a reliable assessment of the impact of drought due to the small and unevenly distributed network of meteorological stations. Hopes for developing methods to assess the impact of droughts are pinned on remote data acquisition and the use of analysis of aerial photographs and satellite scenes. The aim of this study is to assess the occurrence of drought based on the normalised difference vegetation index (NDVI) and SPI at multiple time scales (1-, 3-, and 6-, 9- and 12-month). NDVI values do not simply reflect meteorological drought. However, the spatial co-occurrence of meteorological drought with drought defined on the basis of the NDVI index was demonstrated. The study presents a new approach to identifying drought characterized by SPI and NDVI based on the bivariate choropleth map method, which can indicate the actual places of drought occurrence. The study was carried out for the upper Noteć catchment located in Central Poland.