Search results for: artificial recharge of groundwater

Authors: Olu Ale, Olugbenga Aribisala, Sanmi Awopetu

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Groundwater (Wells) is obtained from several well-defined and different water-bearing geological layers or strata. The physical, chemical and bacteriological quality of the water contributed from each of these water-bearing formations and resultant effects of indiscriminate wastes disposal will be dependent on the dissolution of material within the formation. Therefore, water withdrawn from any ground water source will be a composite of these individual aquifers. The water quality was determined by actual sampling and analysis of the completed wells. This study attempted to examine the physicochemical and bacteriological water quality of twenty five selected wells comprising twenty boreholes (deep wells) and five hand dug wells (shallow wells). The twenty five wells cut across the entire Ado Ekiti Metropolitan area. The water samples collected using standard method was promptly taken to water laboratory at the Federal Polytechnic Ado-Ekiti for analysis, physical, chemical and bacteriological tests were carried out. Quality characteristics tested were found to meet WHO’s standard and generally acceptable, making it potable for drinking in most situations, thus encouraging the use of groundwater. Possible improvement strategies to groundwater exploitation were highlighted while remedies to poor quality water were suggested.

Keywords: bacteriological, physicochemical, quality, wells, Ado Ekiti

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Authors: Sneha Thakur, Sanjeev Karmakar

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This paper proposed hybrid Particle Swarm Optimization (PSO) – Long-Short Term Memory (LSTM) model for groundwater level prediction. The evaluation of the performance is realized using the parameters: root mean square error (RMSE) and mean absolute error (MAE). Ground water level forecasting will be very effective for planning water harvesting. Proper calculation of water level forecasting can overcome the problem of drought and flood to some extent. The objective of this work is to develop a ground water level forecasting model using deep learning technique integrated with optimization technique PSO by applying 29 years data of Chhattisgarh state, In-dia. It is important to find the precise forecasting in case of ground water level so that various water resource planning and water harvesting can be managed effectively.

Keywords: long short-term memory, particle swarm optimization, prediction, deep learning, groundwater level

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Authors: Zainab Abbas Soharwardi, Chunli Su, Harold Wilson Tumwitike Mapoma, Syed Zahid Aziz, Mahmut Ince

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This study investigated the spatial variations of groundwater chemistry used by communities in Lahore city with emphasis on arsenic (As) and fluoride (F) levels. A total of 472 tubewell samples were collected from 7 towns and analyzed for physical and chemical parameters, including pH, turbidity, electrical conductivity (EC), total dissolved solids (TDS), total hardness, HCO3, Ca2+, Mg2+, Na+, K+, SO42-, Cl-, NO3-, NO2-, F- and As. There were significant spatial variations observed for total hardness, TDS, HCO3, NO3 and As. In general, the south-east of the city displayed higher TH and HCO3 while the north-east showed significantly higher As concentrations attributed to the heterogeneity of the aquifer and industrial activities. In most cases, As was higher than WHO limit value. Indiscriminate disposal of domestic and commercial wastewater into River Ravi is the cause of elevated NO3 observed in the north-west compared to other places in the area. Investigation of the groundwater type revealed facies in the order: Ca-Mg-HCO3-SO4 > Mg-Ca-HCO3-SO4 > Ca-Mg-HCO3-SO4-Cl > Mg-Ca-HCO3-SO4 > Ca-HCO3-SO4 > Ca-Mg-SO4-HCO3. The plausible mineralization control mechanism seems to be that of carbonate weathering, although silicate weathering is probable. Moreover, PHREEQC model results showed that the groundwater was under saturated with respect to evaporites (anhydrite, fluorite, gypsum and halite) while generally equilibrium to saturated with respect to aragonite, calcite and dolomite. The Hierarchical Cluster Analysis (HCA) showed that pH significantly affected As, F, NO3 and NO2 while HCO3 contributing most to the observed TDS values in Lahore. It is concluded that inherent mineral dissolution/ precipitation, pH, oxic conditions, anthropogenic activities, atmospheric transport/ wet deposition, microbial activities and surface soil characteristics play their significant roles in elevating both As and F in the city's groundwater.

Keywords: Lahore, arsenic, fluoride, groundwater

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Authors: Cansu Bozer, Saadet İrem Turgut

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Artificial intelligence (AI) has become one of the most important technologies of the digital age and is transforming many sectors, including education. The advantages offered by AI, such as automation, personalised learning, and data analytics, create new opportunities for both teachers and students in education systems. Preschool education plays a fundamental role in the cognitive, social, and emotional development of children. In this period, the foundations of children's creative thinking, problem-solving, and critical thinking skills are laid. Educational technologies, especially artificial intelligence-based applications, are thought to contribute to the development of these skills. For example, artificial intelligence-supported digital learning tools can support learning processes by offering activities that can be customised according to the individual needs of each child. However, the successful use of artificial intelligence-based applications in preschool education can be realised under the guidance of teachers who have the right knowledge about this technology. Therefore, it is of great importance to measure preschool teachers' awareness levels of artificial intelligence and to understand which variables affect this awareness. The aim of this study is to measure preschool teachers' awareness levels of artificial intelligence and to determine which factors are related to this awareness. In line with this purpose, teachers' level of knowledge about artificial intelligence, their thoughts about the role of artificial intelligence in education, and their attitudes towards artificial intelligence will be evaluated. The study will be conducted with 100 teachers working in Turkey using a descriptive survey model. In this context, ‘Artificial Intelligence Awareness Level Scale for Teachers’ developed by Ferikoğlu and Akgün (2022) will be used. The collected data will be analysed using SPSS (Statistical Package for the Social Sciences) software. Descriptive statistics (frequency, percentage, mean, standard deviation) and relationship analyses (correlation and regression analyses) will be used in data analysis. As a result of the study, the level of artificial intelligence awareness of preschool teachers will be determined, and the factors affecting this awareness will be identified. The findings obtained will contribute to the determination of studies that can be done to increase artificial intelligence awareness in preschool education.

Keywords: education, child development, artificial intelligence, preschool teachers

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Authors: N. Balaban, A. Buernstein, F. Gelman, Z. Ronen

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Brominated flame retardants are widespread pollutants, and are known to be toxic, carcinogenic, endocrinic disrupting as well as recalcitrant. The industrial complex Neot Hovav, in the Northern Negev, Israel, is situated above a fractured chalk aquitard, which is polluted by a wide variety of halogenated organic compounds. Two of the abundant pollutants found in the site are Dibromoneopentyl-glycol (DBNPG) and tribromoneopentyl-alcohol (TBNPA). Due to the elusive nature of the groundwater flow, it is difficult to connect between the spatial changes in contaminant concentrations to degradation. In this study, we attempt to determine whether these compounds are biodegraded in the groundwater, and to gain a better understanding concerning the bacterial community in the groundwater. This was achieved through the application of compound-specific isotope analysis (CSIA) of carbon (13^C/12^C) and bromine (81^Br/79^Br), and new-generation MiSeq pyrosequencing. The sampled boreholes were distributed among three main areas of the industrial complex: around the production plant of TBNPA and DBNPG; along the Hovav Wadi (small ephemeral stream) which crosses and drains the industrial complex; and downstream to the industrial area. TBNPA and DBNPG are found in all three areas, with no clear connection to the proximity of the borehole to the production plant. Initial isotopic data of TBNPA from boreholes in the area surrounding the production plant, reveal no changes in the carbon and bromine isotopic values. When observing the microbial groundwater community, the dominant phylum is Proteobacteria. Known anaerobic dehalogenating bacteria such as Dehalococcoides from the Chloroflexi phylum have also been detected. A statistical comparison of the groundwater microbial diversity using a multi-variant ordination of non-metric multidimensional scaling (NMDS) reveals three main clusters in accordance to spatial location in the industrial complex: all the boreholes sampled adjacent to the production plant cluster together and separately from the Wadi Hovav boreholes cluster and the downstream to the industrial area borehole cluster. This work provides the basis for the development and implication of an isotopic fractionation based tool for assessing the biodegradation of brominated organic compounds in contaminated environments, and a novel attempt to characterize the spatial microbial diversity in the contaminated site.

Keywords: biodegradation, brominated flame retardants, groundwater, isotopic fractionation, microbial diversity

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Authors: Imran Aziz Tunio

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Islamkot is an underdeveloped sub-district (Taluka) in the Tharparkar district Sindh province of Pakistan located between latitude 24°25'19.79"N to 24°47'59.92"N and longitude 70° 1'13.95"E to 70°32'15.11"E. The Islamkot has an arid desert climate and the region is generally devoid of perennial rivers, canals, and streams. It is highly dependent on rainfall which is not considered a reliable surface water source and groundwater is the only key source of water for many centuries. To assess groundwater’s potential, an electrical resistivity survey (ERS) was conducted in Islamkot Taluka. Groundwater investigations for 128 Vertical Electrical Sounding (VES) were collected to determine the groundwater potential and obtain qualitatively and quantitatively layered resistivity parameters. The PASI Model 16 GL-N Resistivity Meter was used by employing a Schlumberger electrode configuration, with half current electrode spacing (AB/2) ranging from 1.5 to 100 m and the potential electrode spacing (MN/2) from 0.5 to 10 m. The data was acquired with a maximum current electrode spacing of 200 m. The data processing for the delineation of dune sand aquifers involved the technique of data inversion, and the interpretation of the inversion results was aided by the use of forward modeling. The measured geo-electrical parameters were examined by Interpex IX1D software, and apparent resistivity curves and synthetic model layered parameters were mapped in the ArcGIS environment using the inverse Distance Weighting (IDW) interpolation technique. Qualitative interpretation of vertical electrical sounding (VES) data shows the number of geo-electrical layers in the area varies from three to four with different resistivity values detected. Out of 128 VES model curves, 42 nos. are 3 layered, and 86 nos. are 4 layered. The resistivity of the first subsurface layers (Loose surface sand) varied from 16.13 Ωm to 3353.3 Ωm and thickness varied from 0.046 m to 17.52m. The resistivity of the second subsurface layer (Semi-consolidated sand) varied from 1.10 Ωm to 7442.8 Ωm and thickness varied from 0.30 m to 56.27 m. The resistivity of the third subsurface layer (Consolidated sand) varied from 0.00001 Ωm to 3190.8 Ωm and thickness varied from 3.26 m to 86.66 m. The resistivity of the fourth subsurface layer (Silt and Clay) varied from 0.0013 Ωm to 16264 Ωm and thickness varied from 13.50 m to 87.68 m. The Dar Zarrouk parameters, i.e. longitudinal unit conductance S is from 0.00024 to 19.91 mho; transverse unit resistance T from 7.34 to 40080.63 Ωm2; longitudinal resistance RS is from 1.22 to 3137.10 Ωm and transverse resistivity RT from 5.84 to 3138.54 Ωm. ERS data and Dar Zarrouk parameters were mapped which revealed that the study area has groundwater potential in the subsurface.

Keywords: electrical resistivity survey, GIS & RS, groundwater potential, environmental assessment, VES

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Authors: Joseph Omeiza Alao

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The wobbly state of waste management and the high level of environmental irresponsibility is a threat to environmental security, which invariably endangered public health, regional groundwater systems and atmospheric condition. The dumping of waste materials in water bodies and gutters and the frequent burning of waste materials heaped at dumpsites as well depict the highest level of environmental indiscipline. These unruly human factors have compelled this study to apply four different techniques for environmental impact assessment and the possible public health risks of poor waste management in Nigeria. The techniques include a geophysical survey (resistivity data acquisition), dispatched questionnaire surveys, physiochemical water analysis and a physical survey of several dumpsites. While the resistivity data indicates high-level dumpsite leachate invading the ground soil down to the water table, the physiochemical water analysis depicts high content of BOD (401 – 711) mg/l, COD (731 – 1312) mg/l, TDS (419 – 1871) mg/l and heavy metals (0.014 – 1.971) mg/l present in the regional groundwater systems, which have altered the chemistry of the regional groundwater. The resistivity data shows that the overburdened soil layer overlaying the regional groundwater systems was very low (4.5 Ωm – 151 Ωm) as against the existing data (180 Ωm – 3500 Ωm). However, the physical surveys and the dispatched questionnaire surveys explore the depth of environmental irresponsibility among the citizen. While the imprints of gross environmental indiscipline may be absolutely irreversible, adequate knowledge of the environmental implications of careless waste disposal. After a critical examination of the current waste management strategies in Nigeria, the study suggests a future direction for environmental security and sustainability. Several influential regional factors, such as geology, climatic conditions, and hydrology, were also discussed.

Keywords: groundwater, environmental indiscipline, waste management, water analysis, leachate plumes, public health

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Authors: Mayank Sharma

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Groundwater has been a matter of great concern in the past years due to the depletion in the water table. This has resulted from the over-exploitation of groundwater resources. Sub-surface exploration of groundwater is a great way to identify the groundwater potential of an area. Thus, in order to meet the water needs for irrigation in the study area, there was a need for a tube well to be installed. Therefore, a Geophysical investigation was carried out to find the most suitable point of drilling and sinking of tube well that encounters an aquifer. Hence, an electrical resistivity survey of geophysical exploration was used to know the aquifer zones of the area. The Vertical Electrical Sounding (VES) method was employed to know the subsurface geology of the area. Seven vertical electrical soundings using Schlumberger electrode array were carried out, having the maximum AB electrode separation of 700m at selected points in Ayma, Kharagpur-1 block of Paschim Midnapore district, West Bengal. The VES was done using an IGIS DDR3 Resistivity meter up to an approximate depth of 160-180m. The data was interpreted, processed and analyzed. Based on all the interpretations using the direct method, the geology of the area at the points of sounding was interpreted. It was established that two deeper clay-sand sections exist in the area at a depth of 50-70m (having resistivity range of 40-60ohm-m) and 70-160m (having resistivity range of 25-35ohm-m). These aquifers will provide a high yield of water which would be sufficient for the desired irrigation in the study area.

Keywords: VES method, Schlumberger method, electrical resistivity survey, geophysical exploration

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Authors: Josua Sihotang

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Jakarta Capital Special Region is the province that densely populated with rapidly growing infrastructure but less attention for the environmental condition. This makes some social problem happened like lack of clean water supply. Shallow groundwater and river water condition that has contaminated make the layer of deep water carrier (aquifer) should be done. This research aims to provide the people insight about deep groundwater potential and to determine the depth, location, and quality where the aquifer can be found in Jakarta’s area, particularly Kapuk-Cengkareng’s people. This research was conducted by geophysical method namely Well Logging Analysis. Well Logging is the geophysical method to know the subsurface lithology with the physical characteristic. The observation in this research area was conducted with several well devices that is Spontaneous Potential Log (SP Log), Resistivity Log, and Gamma Ray Log (GR Log). The first devices well is SP log which is work by comprising the electrical potential difference between the electrodes on the surface with the electrodes that is contained in the borehole and rock formations. The second is Resistivity Log, used to determine both the hydrocarbon and water zone based on their porosity and permeability properties. The last is GR Log, work by identifying radioactivity levels of rocks which is containing elements of thorium, uranium, or potassium. The observation result is curve-shaped which describes the type of lithological coating in subsurface. The result from the research can be interpreted that there are four of the deep groundwater layer zone with different quality. The good groundwater layer can be found in layers with good porosity and permeability. By analyzing the curves, it can be known that most of the layers which were found in this wellbore are clay stone with low resistivity and high gamma radiation. The resistivity value of the clay stone layers is about 2-4 ohm-meter with 65-80 Cps gamma radiation. There are several layers with high resistivity value and low gamma radiation (sand stone) that can be potential for being an aquifer. This is reinforced by the sand layer with a right-leaning SP log curve proving that this layer is permeable. These layers have 4-9 ohm-meter resistivity value with 40-65 Cps gamma radiation. These are mostly found as fresh water aquifer.

Keywords: aquifer, deep groundwater potential, well devices, well logging analysis

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Authors: Dib Imane, Chettah Wahid, Khedidja Abdelhamid

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The plain of Gadaïne - Ain Yaghout, located in the wilaya of Batna (Eastern Algeria), experiences intensive human activities, particularly in agricultural practices which are accompanied by an increasing use of chemical fertilizers and manure. These activities lead to a degradation of the quality of water resources. In order to protect the quality of groundwater in this plain and formulate effective strategies to mitigate or avoid any contamination of groundwater, a risk assessment using the European method known as “COSTE Action 620” was applied to the mio-. plio-quaternary aquifer of this plain. Risk assessment requires the identification of existing dangers and their potential impact on groundwater by using a system of evaluation and weighting. In addition, it also requires the integration of the hydrogeological factors that influence the movement of contaminants by means of the intrinsic vulnerability maps of groundwater, which were produced according to the modified DRASTIC method. The overall danger on the plain ranges from very low to high. Farms containing stables, houses detached from the public sewer system, and sometimes manure piles were assigned a weighting factor expressing the highest degree of harmfulness; this created a medium to high danger index. Large areas for agricultural practice and grazing are characterized, successively, by low to very low danger. Therefore, the risks present at the study site are classified according to a range from medium to very high-risk intensity. These classes successively represent 3%, 49%, and 0.2% of the surface of the plain. Cultivated land and farms present a high to very high level of risk successively. In addition, with the exception of the salt mine, which presents a very high level of risk, the gas stations and cemeteries, as well as the railway line, represent a high level of risk.

Keywords: semi-arid, quality of water resources, risk assessment, vulnerability, contaminants

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Authors: Siamak Feizi, Gunvor Baardvik

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Soil erosion has special consequences for landfills that are more serious than those found at conventional construction sites. Different potential heads between two sides of a landfill and the subsequent movement of water through pores within the soil body could trigger the soil erosion and construction instability. Such a condition was encountered in a landfill project in the southern part of Norway. To check the risk of internal erosion due to changes in the groundwater level (because of seasonal flooding in the river), a series of numerical simulations by means of Geo-Seep software was conducted. Output of this study provides a total picture of the landfill stability, possibilities of erosions, and necessary measures to prevent or reduce the risk for the landfill operator.

Keywords: erosion, seepage, landfill, stability

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Authors: Rama Bhattacharyya, S. N. Ojha, Umesh K. Singh

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Anthropogenic control on groundwater chemistry has emerged as a critical concern now-a-days, especially in the industrial areas. In view of this, a comprehensive study on the distribution of the heavy metal in the groundwater was conducted to investigate the impact of urbanization in the aquatic media. Water samples either from well or borehole from Fourty different sites in and around, Durgapur, West Bengal were collected for this purpose. The samples were analyzed using Inductively Coupled Plasma Mass Spectrometry (ICP-MS) for Calcium (Ca), Cobalt (Co), Chromium (Cr), Copper (Cu), Iron (Fe), Potassium (K), Magnesium (Mg), Manganese (Mn), Sodium (Na), Nickel (Ni), Lead (Pb), Zinc (Zn) content and the levels were compared with WHO specified maximum contaminant level as well as permissible limits given by the Bureau of Indian Standards (BIS). The result obtained from the present study indicates a significant risk to the population of this important emerging ‘smart city’ of eastern India. Because of the toxicity of these metals and the fact that for many tube-wells, dug-wells and bore-wells are the only sources of the water supply for a major fraction of the population in this environment. In this study, an attempt has been made to develop metal contamination risk map.

Keywords: heavy metals, ground water, maximum contamination level, ICP-MS

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Authors: O. P. Oladipo, O. A. Falode

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The determination of Recovery Factor is of great importance to the reservoir engineer since it relates reserves to the initial oil in place. Reserves are the producible portion of reservoirs and give an indication of the profitability of a field Development. The core objective of this project is to develop an artificial neural network model using selected reservoir data to predict Recovery Factors (RF) of hydrocarbon reservoirs and compare the model with a couple of the existing correlations. The type of Artificial Neural Network model developed was the Single Layer Feed Forward Network. MATLAB was used as the network simulator and the network was trained using the supervised learning method, Afterwards, the network was tested with input data never seen by the network. The results of the predicted values of the recovery factors of the Artificial Neural Network Model, API Correlation for water drive reservoirs (Sands and Sandstones) and Guthrie and Greenberger Correlation Equation were obtained and compared. It was noted that the coefficient of correlation of the Artificial Neural Network Model was higher than the coefficient of correlations of the other two correlation equations, thus making it a more accurate prediction tool. The Artificial Neural Network, because of its accurate prediction ability is helpful in the correct prediction of hydrocarbon reservoir factors. Artificial Neural Network could be applied in the prediction of other Petroleum Engineering parameters because it is able to recognise complex patterns of data set and establish a relationship between them.

Keywords: recovery factor, reservoir, reserves, artificial neural network, hydrocarbon, MATLAB, API, Guthrie, Greenberger

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Authors: Victorita Radulescu

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Introduction: The optimum exploitation of agricultural land in the presence of an aquifer polluted by the surface sources requires close monitoring of groundwater level in both periods of intense irrigation and in absence of the irrigations, in times of drought. Currently in Romania, in the south part of the country, the Baragan area, many agricultural lands are confronted with the risk of groundwater pollution in the absence of systematic irrigation, correlated with the climate changes. Basic Methods: The non-steady flow of the groundwater from an aquifer can be described by the Bousinesq’s partial differential equation. The finite element method was used, applied to the porous media needed for the water mass balance equation. By the proper structure of the initial and boundary conditions may be modeled the flow in drainage or injection systems of wells, according to the period of irrigation or prolonged drought. The boundary conditions consist of the groundwater levels required at margins of the analyzed area, in conformity to the reality of the pollutant emissaries, following the method of the double steps. Major Findings/Results: The drainage condition is equivalent to operating regimes on the two or three rows of wells, negative, as to assure the pollutant transport, modeled with the variable flow in groups of two adjacent nodes. In order to obtain the level of the water table, in accordance with the real constraints, are needed, for example, to be restricted its top level below of an imposed value, required in each node. The objective function consists of a sum of the absolute values of differences of the infiltration flow rates, increased by a large penalty factor when there are positive values of pollutant. In these conditions, a balanced structure of the pollutant concentration is maintained in the groundwater. The spatial coordinates represent the modified parameters during the process of optimization and the drainage flows through wells. Conclusions: The presented calculation scheme was applied to an area having a cross-section of 50 km between two emissaries with various levels of altitude and different values of pollution. The input data were correlated with the measurements made in-situ, such as the level of the bedrock, the grain size of the field, the slope, etc. This method of calculation can also be extended to determine the variation of the groundwater in the aquifer following the flood wave propagation in envoys.

Keywords: environmental protection, infiltrations, numerical modeling, pollutant transport through soils

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Authors: Reza Dinarvand, Mahdi Sadeghian, Somaye Sadeghian

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Prediction of the ultimate bearing capacity of piles (Qu) is one of the basic issues in geotechnical engineering. So far, several methods have been used to estimate Qu, including the recently developed artificial intelligence methods. In recent years, optimization algorithms have been used to minimize artificial network errors, such as colony algorithms, genetic algorithms, imperialist competitive algorithms, and so on. In the present research, artificial neural networks based on colonial competition algorithm (ANN-ICA) were used, and their results were compared with other methods. The results of laboratory tests of short piles in clayey soils with parameters such as pile diameter, pile buried length, eccentricity of load and undrained shear resistance of soil were used for modeling and evaluation. The results showed that ICA-based artificial neural networks predicted lateral bearing capacity of short piles with a correlation coefficient of 0.9865 for training data and 0.975 for test data. Furthermore, the results of the model indicated the superiority of ICA-based artificial neural networks compared to back-propagation artificial neural networks as well as the Broms and Hansen methods.

Keywords: artificial neural network, clayey soil, imperialist competition algorithm, lateral bearing capacity, short pile

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Authors: Hafiz Arbab Sakandar, Sabahat Yaqub, Ayesha Sameen, Muhammad Imran, Sarfraz Ahmad

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Yoghurt is one of the famous nutritious fermented milk products which have myriad of positive health effects on human beings and curable against different intestinal diseases. This research was conducted to observe effects of different artificial sweeteners on the quality parameters of yoghurt with relation to storage. Some people are allergic to natural sweeteners so artificial sweetener will be helpful for them. Physical-chemical, Microbiology and various sensory evaluation tests were carried out with the interval of 7, 14, 21, and 28 days. It was outcome from this study that addition of artificial sweeteners in yoghurt has shown much harmful effects on the yoghurt microorganisms and other physicochemical parameters from quality point of view. Best results for acceptance were obtained when aspartame was added in yoghurt at level of 0.022 percent. In addition, growth of beneficial microorganisms in yoghurt was also improved as well as other sensory attributes were enhanced by the addition of aspartame.

Keywords: yoghurt, artificial sweetener, storage, quality parameters

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Authors: A. J. Olatunji, Adebolu Temitope Johnson

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Groundwater samples were collected randomly from hand-dug wells and boreholes in parts of the Ado Ekiti metropolis and were subjected to quality assessment and characterization. Physicochemical analyses, which include the in-situ parameters (pH units, Turbidity, and Electrical Conductivity) and laboratory analysis of selected ionic concentrations, were carried out following standard methods. Hydrochemistry of the present study revealed relative mean concentrations of cations in the order Ca2+ > Na+ > Mg2+ > Cu2+> Fe > Mn2+ and that of anions: Cl- > NO3- > SO42- > F - respectively considering World Health Organisation Standard (WHO) range of values for potable water. The result shows that values of certain parameters (Total Dissolved Solid (TDS), Manganese, Calcium, Magnesium, Fluoride, and Sulphate) were below the Highest Desirable Level of the Standards, while values of some other parameters (pH Units, Electrical Conductivity, Turbidity, Alkalinity, Sodium, Copper, Chloride, and Total Hardness) were within the range of figures between Highest Desirable Level (HDL) and Maximum Permissible Level (MPL) of World Health Organization (WHO) drinking water Standards. The reduction in the mean concentration value of Total Dissolved Solids (TDS) of most borehole samples follows the fact that water had been allowed to settle in the overhead tanks before usage; we discussed and brainstormed in the course of sampling and agreed to take a sample that way because that represents what the people consume, it also shows an indication while there was slightly concentration increase of these soluble ions in hand-dug wells samples than borehole samples only with the exception of borehole sample seven BH7 because BH7 uses the mono-pumping system. These in-situ parameters and ionic concentrations were further displayed and or represented on bar charts along with the WHO standards for better pictorial clarifications. Deductions from field observation indices revealed the imprints of natural weathering, ion-exchange processes, and anthropogenic activities influencing groundwater quality. A strong degree of association was found to exist between sodium and chlorine ions in both hand-dug well and borehole groundwater samples through the use of Pearson’s correlation coefficient; this association can further be supported by the chemistry of the parent bedrock associated with the study area because the chemistry of groundwater is a replica of its host rock. The correlation of those two ions must have begun from the period of mountain building, indicating an identical source from which they were released to the groundwater. Moreover, considering the comparison of ionic species concentrations of all samples with the (WHO) standards, there were no anomalous increases or decreases in the laboratory analysis results; this simply reveals an insignificant state of pollution of the groundwater. The study and its sampling techniques were not set to target the likely area and extent of groundwater pollution but its portability. It could be said that the samples were safe for human consumption.

Keywords: groundwater, physicochemical, parameters ionic, concentrations, WHO standards

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Authors: Khaled M. Alhawiti

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This research study aims to present a retrospective study about speech recognition systems and artificial intelligence. Speech recognition has become one of the widely used technologies, as it offers great opportunity to interact and communicate with automated machines. Precisely, it can be affirmed that speech recognition facilitates its users and helps them to perform their daily routine tasks, in a more convenient and effective manner. This research intends to present the illustration of recent technological advancements, which are associated with artificial intelligence. Recent researches have revealed the fact that speech recognition is found to be the utmost issue, which affects the decoding of speech. In order to overcome these issues, different statistical models were developed by the researchers. Some of the most prominent statistical models include acoustic model (AM), language model (LM), lexicon model, and hidden Markov models (HMM). The research will help in understanding all of these statistical models of speech recognition. Researchers have also formulated different decoding methods, which are being utilized for realistic decoding tasks and constrained artificial languages. These decoding methods include pattern recognition, acoustic phonetic, and artificial intelligence. It has been recognized that artificial intelligence is the most efficient and reliable methods, which are being used in speech recognition.

Keywords: speech recognition, acoustic phonetic, artificial intelligence, hidden markov models (HMM), statistical models of speech recognition, human machine performance

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Authors: Joel Podgorski, Manouchehr Amini, Annette Johnson, Michael Berg

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One-third of the world’s population relies on groundwater for its drinking water. Natural geogenic arsenic and fluoride contaminate ~10% of wells. Prolonged exposure to high levels of arsenic can result in various internal cancers, while high levels of fluoride are responsible for the development of dental and crippling skeletal fluorosis. In poor urban and rural settings, the provision of drinking water free of geogenic contamination can be a major challenge. In order to efficiently apply limited resources in the testing of wells, water resource managers need to know where geogenically contaminated groundwater is likely to occur. The Groundwater Assessment Platform (GAP) fulfills this need by providing state-of-the-art global arsenic and fluoride contamination hazard maps as well as enabling users to create their own groundwater quality models. The global risk models were produced by logistic regression of arsenic and fluoride measurements using predictor variables of various soil, geological and climate parameters. The maps display the probability of encountering concentrations of arsenic or fluoride exceeding the World Health Organization’s (WHO) stipulated concentration limits of 10 µg/L or 1.5 mg/L, respectively. In addition to a reconsideration of the relevant geochemical settings, these second-generation maps represent a great improvement over the previous risk maps due to a significant increase in data quantity and resolution. For example, there is a 10-fold increase in the number of measured data points, and the resolution of predictor variables is generally 60 times greater. These same predictor variable datasets are available on the GAP platform for visualization as well as for use with a modeling tool. The latter requires that users upload their own concentration measurements and select the predictor variables that they wish to incorporate in their models. In addition, users can upload additional predictor variable datasets either as features or coverages. Such models can represent an improvement over the global models already supplied, since (a) users may be able to use their own, more detailed datasets of measured concentrations and (b) the various processes leading to arsenic and fluoride groundwater contamination can be isolated more effectively on a smaller scale, thereby resulting in a more accurate model. All maps, including user-created risk models, can be downloaded as PDFs. There is also the option to share data in a secure environment as well as the possibility to collaborate in a secure environment through the creation of communities. In summary, GAP provides users with the means to reliably and efficiently produce models specific to their region of interest by making available the latest datasets of predictor variables along with the necessary modeling infrastructure.

Keywords: arsenic, fluoride, groundwater contamination, logistic regression

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Authors: Siti Aslamyah, Yushinta Fujaya, Okto Rimaldi

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One of the problems faced in the crab hatchery operations is the reliance on the use of natural feed. This study aims to analyze the response of larval development and determine the initial stages crab larvae begin to fully able to accept artificial feeding predigest with the help of probiotic Bacillus sp. The experiment was conducted in June 2014 through July 2014 at the location of the scale backyard hatcheries, Bojo village Mallusettasi sub-district, district Barru. This study was conducted in two stages larval rearing. The first stage is designed in a completely randomized design with 5 treatments and each with 3 repetitions, ie, without the use of artificial feeding; predigest feed given from zoea 1 - megalopa; predigest feed given since zoea 2 - megalopa; predigest feed given from zoea 3 - megalopa; and feed predigest given since zoea 4 - megalopa. The second stage of the two treatments, i.e. comparing artificial feeding without and with predigest. The results showed that the artificial feeding predigest able to replace the use of natural feed started zoea 3 generated based on the survival rate. Artificial feeding predigest provide a higher survival rate (16%) compared to artificial diets without predigest only 10.8%. However, feed predigest not give a different effect on the rate of development of stadia. Cell activity in larvae that received artificial feed predigest higher with RNA-DNA ratio of 8.88 compared with no predigest only 5:36. This research is very valuable information for crab hatchery hatchery scale households have limitations in preparing natural food.

Keywords: artificial feeding, development of stadia, larvae Portunus pelagicus, predigest

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Authors: Amina Ramadni, Safia Taleb, André Dératani

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The present study presents, firstly, to characterize the physicochemical quality of brackish groundwater of the Terminal Complex (TC) from the region of Eloued-souf and to investigate the presence of fluoride, and secondly, to study the comparison of adsorbing power of three materials, such as (activated alumina AA, sodium clay SC and hydroxyapatite HAP) against the groundwater in the region of Eloued-souf. To do this, a sampling campaign over 16 wells and consumer taps was undertaken. The results show that the groundwater can be characterized by very high fluoride content and excessive mineralization that require in some cases, specific treatment before supply. The study of adsorption revealed removal efficiencies fluoride by three adsorbents, maximum adsorption is achieved after 45 minutes at 90%, 83.4% and 73.95%, and with an adsorbed fluoride content of 0.22 mg/L, 0.318 mg/L and 0.52 mg/L for AA, HAP and SC, respectively. The acidity of the medium significantly affects the removal fluoride. Results deducted from the adsorption isotherms also showed that the retention follows the Langmuir model. The adsorption tests by adsorbent materials show that the physicochemical characteristics of brackish water are changed after treatment. The adsorption mechanism is an exchange between the OH^- ions and fluoride ions. Three materials are proving to be effective adsorbents for fluoride removal that could be developed into a viable technology to help reduce the salinity of the Saharan hyper-fluorinated waters. Finally, a comparison between the results obtained from the different adsorbents allowed us to conclude that the defluoridation by AA is the process of choice for many waters of the region of Eloued-souf, because it was shown to be a very interesting and promising technique.

Keywords: fluoride removal, hydrochemical characterization of groundwater, natural materials, nanofiltration

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Authors: Nouf Nasser, Nada Alotaibi, Jazzal Kandiel

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This research study is about the use of artificial intelligence in PhotoRoom. When an individual selects a photo, PhotoRoom automagically removes or separates the background from other parts of the photo through the use of artificial intelligence. This will allow an individual to select their desired background and edit it as they wish. The methodology used was an observation, where various reviews and parts of the app were observed. The review section's findings showed that many people actually like the app, and some even rated it five stars. The conclusion was that PhotoRoom is one of the best photo editing apps due to its speed and accuracy in removing backgrounds.

Keywords: removing background, app, artificial intelligence, machine learning

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Authors: K. A. Laptinskiy, S. A. Burikov, A. M. Vervald, S. A. Dolenko, T. A. Dolenko

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The article presents the results of the application of artificial neural networks to separate the fluorescent contribution of nanodiamonds used as biomarkers, adsorbents and carriers of drugs in biomedicine, from a fluorescent background of own biological fluorophores. The principal possibility of solving this problem is shown. Use of neural network architecture let to detect fluorescence of nanodiamonds against the background autofluorescence of egg white with high accuracy - better than 3 ug/ml.

Keywords: artificial neural networks, fluorescence, data aggregation, biomarkers

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Authors: Albatool Al Abdulwahid, Bayan Shakally, Mariam Mohamed, Wed Almokri

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Artificial intelligence has infiltrated every part of our life and every field we can think of. With technical developments, artificial intelligence applications are becoming more prevalent. We chose ELSA speak because it is a magnificent example of Artificial intelligent applications, ELSA speak is a smartphone application that is free to download on both IOS and Android smartphones. ELSA speak utilizes artificial intelligence to help non-native English speakers pronounce words and phrases similar to a native speaker, as well as enhance their English skills. It employs speech-recognition technology that aids the application to excel the pronunciation of its users. This remarkable feature distinguishes ELSA from other voice recognition algorithms and increase the efficiency of the application. This study focused on evaluating ELSA speak application, by testing the degree of effectiveness based on survey questions. The results of the questionnaire were variable. The generality of the participants strongly agreed that ELSA has helped them enhance their pronunciation skills. However, a few participants were unconfident about the application’s ability to assist them in their learning journey.

Keywords: ELSA speak application, artificial intelligence, speech-recognition technology, language learning, english pronunciation

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Authors: Syed Muzyan Shahzad, Liu Jianxin, Asim Shahzad, Muhammad Sharjeel Raza, Sun Ya, Fanidi Meryem

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Electrical resistivity investigation was conducted in vicinity of Tarbela Ghazi, in order to study the subsurface layer with a view of determining the depth to the aquifer and thickness of groundwater potential zones. Vertical Electrical Sounding (VES) using Schlumberger array was carried out at 16 VES stations. Well logging data at four tube wells have been used to mark the super saturated zones with great discharge rate. The present paper shows a geoelectrical identification of the lithology and an estimate of the relationship between the resistivity and Dar Zarrouk parameters (transverse unit resistance and longitudinal unit conductance). The VES results revealed both homogeneous and heterogeneous nature of the subsurface strata. Aquifer is unconfined to confine in nature, and at few locations though perched aquifer has been identified, groundwater potential zones are developed in unconsolidated deposits layers and more than seven geo-electric layers are observed at some VES locations. Saturated zones thickness ranges from 5 m to 150 m, whereas at few area aquifer is beyond 150 m thick. The average anisotropy, transvers resistance and longitudinal conductance values are 0.86 %, 35750.9821 Ω.m², 0.729 Siemens, respectively. The transverse unit resistance values fluctuate all over the aquifer system, whereas below at particular depth high values are observed, that significantly associated with the high transmissivity zones. The groundwater quality in all analyzed samples is below permissible limit according to World Health Standard (WHO).

Keywords: aquifer, Dar Zarrouk parameters, geoelectric layers, Tarbela Ghazi

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Authors: Meshandren Naidoo

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An artificial intelligence (AI) system named DABUS 2021 made headlines when it became the very first AI system to be listed in a patent which was then granted by the South African patent office. This grant raised much criticism. The question that this research intends to answer is (1) whether, in South African patent law, an AI can be an inventor. This research finds that despite South African law not recognizing an AI as a legal person and despite the legislation not explicitly allowing AI to be inventors, a legal interpretative exercise would allow AI inventorship.

Keywords: artificial intelligence, creativity, innovation, law

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Authors: Oluwatosin Olofintoye, Josiah Adeyemo, Gbemileke Shomade

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The relationship between rainfall and runoff is an important issue in surface water hydrology therefore the understanding and development of accurate rainfall-runoff models and their applications in water resources planning, management and operation are of paramount importance in hydrological studies. This paper reviews some of the previous works on the rainfall-runoff process modeling. The hydrologic applications of conceptual models and artificial neural networks (ANNs) for the precipitation-runoff process modeling were studied. Gradient training methods such as error back-propagation (BP) and evolutionary algorithms (EAs) are discussed in relation to the training of artificial neural networks and it is shown that application of EAs to artificial neural networks training could be an alternative to other training methods. Therefore, further research interest to exploit the abundant expert knowledge in the area of artificial intelligence for the solution of hydrologic and water resources planning and management problems is needed.

Keywords: artificial intelligence, artificial neural networks, evolutionary algorithms, gradient training method, rainfall-runoff model

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Authors: Rajkumar Ghosh

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The present study focuses on conducting a socio-economic assessment of groundwater contamination by arsenic and iron and explores the feasibility of rainwater harvesting (RWH) as an alternative water source in the Amdanga Block of North 24 Parganas, West Bengal, India. The region is plagued by severe groundwater contamination, primarily due to excessive concentrations of arsenic and iron, which pose significant health risks to the local population. The study utilizes a mixed-methods approach, combining quantitative analysis of water samples collected from different locations within the Amdanga Block and socio-economic surveys conducted among the affected communities. The results reveal alarmingly high levels of arsenic and iron contamination in the groundwater, surpassing the World Health Organization (WHO) and Indian government's permissible limits. This contamination significantly impacts the health and well-being of the local population, leading to a range of health issues such as skin The water samples are analyzed for arsenic and iron levels, while the surveys gather data on water usage patterns, health conditions, and socio-economic factors. lesions, respiratory disorders, and gastrointestinal problems. Furthermore, the socio-economic assessment highlights the vulnerability of the affected communities due to limited access to safe drinking water. The findings reveal the adverse socio-economic implications, including increased medical expenditures, reduced productivity, and compromised educational opportunities. To address these challenges, the study explores the feasibility of rainwater harvesting as an alternative source of clean water. RWH systems have the potential to mitigate groundwater contamination by providing a sustainable and independent water supply. The assessment includes evaluating the rainwater availability, analyzing the infrastructure requirements, and estimating the potential benefits and challenges associated with RWH implementation in the study area. The findings of this study contribute to a comprehensive understanding of the socio-economic impact of groundwater contamination by arsenic and iron, emphasizing the urgency to address this critical issue in the Amdanga Block. The feasibility assessment of rainwater harvesting serves as a practical solution to ensure a safe and sustainable water supply, reducing the dependency on contaminated groundwater sources. The study's results can inform policymakers, researchers, and local stakeholders in implementing effective mitigation measures and promoting the adoption of rainwater harvesting as a viable alternative in similar arsenic and iron-contaminated regions.

Keywords: contamination, rainwater harvesting, groundwater, sustainable water supply

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Authors: Benhamza Moussa, Aissaoui Marwa, Touati Mounira, Chaoui Widad

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The Guelma-Bouchegouf irrigated area is located in the northeast of Algeria, and it extends about 80 km. It was commissioned in 1996, with an irrigable area of 9250 ha, it spreads on both banks of the Seybouse Wadi and it is subdivided into five autonomous distribution sectors. In order to assess the state of groundwater quality, the results of the chemical analyzes were plotted on the Piper diagram, which shows that the chemical facies are sulfate-calcium chloride and sulfate-calcium with a slight tendency to migrate to chlorinated sulphate - sodium. The predominance of sulphates in the waters of the region is geologically explained by the existence in the Guelma Basin of evaporitic deposits, which are mainly represented by rock salt and gypsum. In addition to this natural origin, we can mention the anthropogenic origin, following the use of chemical fertilizers in the Guelma-Bouchegouf irrigated area. Na⁺ and Mg²⁺ show moderate to significant mineralization of water, closely correlated with very high conductivities. The values of the recorded conductivities vary from 1360 μs / cm (P3) to 4610 μs / cm (P10). These important values are due to dissolved salts on the one hand and the leaching of fertilizers by irrigation water on the other hand. NO₃⁻ and NH₄⁺ show little to significant pollution throughout the study area. Phosphate represents significant pollution, with excessive values far exceeding the allowable standard. With respect to ammonium, 87% of the sampling points present little pollution and 13 % significant pollution. Regarding phosphates, in the form of PO₄³⁻, groundwater in the study area represents significant pollution; all values far exceed the allowable standard.

Keywords: groundwater, organic parameters, standards, Pollution

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Authors: Newton Muhury, Armando A. Apan, Tek Maraseni

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This study modelled the relationships between vegetation response and available water below the soil surface using the Terra’s Moderate Resolution Imaging Spectroradiometer (MODIS) generated Normalised Difference Vegetation Index (NDVI) and soil water content (SWC) data. The Soil & Water Assessment Tool (SWAT) interface known as ArcSWAT was used in ArcGIS for the groundwater analysis. The SWAT model was calibrated and validated in SWAT-CUP software using 10 years (2001-2010) of monthly streamflow data. The average Nash-Sutcliffe Efficiency during the calibration and validation was 0.54 and 0.51, respectively, indicating that the model performances were good. Twenty years (2001-2020) of monthly MODIS NDVI data for three different types of vegetation (forest, shrub, and grass) and soil water content for 43 sub-basins were analysed using the WEKA, machine learning tool with a selection of two supervised machine learning algorithms, i.e., support vector machine (SVM) and random forest (RF). The modelling results show that different types of vegetation response and soil water content vary in the dry and wet season. For example, the model generated high positive relationships (r=0.76, 0.73, and 0.81) between the measured and predicted NDVI values of all vegetation in the study area against the groundwater flow (GW), soil water content (SWC), and the combination of these two variables, respectively, during the dry season. However, these relationships were reduced by 36.8% (r=0.48) and 13.6% (r=0.63) against GW and SWC, respectively, in the wet season. On the other hand, the model predicted a moderate positive relationship (r=0.63) between shrub vegetation type and soil water content during the dry season, which was reduced by 31.7% (r=0.43) during the wet season. Our models also predicted that vegetation in the top location (upper part) of the sub-basin is highly responsive to GW and SWC (r=0.78, and 0.70) during the dry season. The results of this study indicate the study region is suitable for seasonal crop production in dry season. Moreover, the results predicted that the growth of vegetation in the top-point location is highly dependent on groundwater flow in both dry and wet seasons, and any instability or long-term drought can negatively affect these floodplain vegetation communities. This study has enriched our knowledge of vegetation responses to groundwater in each season, which will facilitate better floodplain vegetation management.

Keywords: ArcSWAT, machine learning, floodplain vegetation, MODIS NDVI, groundwater

Procedia PDF Downloads 119