Search results for: radar rainfall ensemble

Authors: Sudhir Kumar Singh, Debashish Chakravarty

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Slope stability analysis is an important aspect in the field of geotechnical engineering. It is also important from safety, and economic point of view as any slope failure leads to loss of valuable lives and damage to property worth millions. This paper aims at mitigating the risk of slope failure by studying the effect of different joint sets on the stability of mine pit slopes under the influence of various external factors, namely degree of saturation, rainfall intensity, and seismic coefficients. Supervised machine learning approach has been utilized for making accurate and reliable predictions regarding the stability of slopes based on the value of Factor of Safety. Numerous cases have been studied for analyzing the stability of slopes using the popular Finite Element Method, and the data thus obtained has been used as training data for the supervised machine learning models. The input data has been trained on different supervised machine learning models, namely Random Forest, Decision Tree, Support vector Machine, and XGBoost. Distinct test data that is not present in training data has been used for measuring the performance and accuracy of different models. Although all models have performed well on the test dataset but Random Forest stands out from others due to its high accuracy of greater than 95%, thus helping us by providing a valuable tool at our disposition which is neither computationally expensive nor time consuming and in good accordance with the numerical analysis result.

Keywords: finite element method, geotechnical engineering, machine learning, slope stability

Procedia PDF Downloads 88

Authors: Mustafa Salman, Nurcan Cetinkaya, Zehra Selcuk, Bugra Genc

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The objectives of the present study were to estimate the microbial-N flow to the small intestine and to predict the digestible organic matter intake (DOMI) in grazing Karayaka sheep based on urinary excretion of purine derivatives (xanthine, hypoxanthine, uric acid, and allantoin) by the use of spot urine sampling under field conditions. In the trial, 10 Karayaka sheep from 2 to 3 years of age were used. The animals were grazed in a pasture for ten months and fed with concentrate and vetch plus oat hay for the other two months (January and February) indoors. Highly significant linear and cubic relationships (P<0.001) were found among months for purine derivatives index, purine derivatives excretion, purine derivatives absorption, microbial-N and DOMI. Through urine sampling and the determination of levels of excreted urinary PD and Purine Derivatives / Creatinine ratio (PDC index), microbial-N values were estimated and they indicated that the protein nutrition of the sheep was insufficient. In conclusion, the prediction of protein nutrition of sheep under the field conditions may be possible with the use of spot urine sampling, urinary excreted PD and PDC index. The mean purine derivative levels in spot urine samples from sheep were highest in June, July and October. Protein nutrition of pastured sheep may be affected by weather changes, including rainfall. Spot urine sampling may useful in modeling the feed consumption of pasturing sheep. However, further studies are required under different field conditions with different breeds of sheep to develop spot urine sampling as a model.

Keywords: Karayaka sheep, spot sampling, urinary purine derivatives, PDC index, microbial-N, feed intake

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Authors: Muhammad Idnan, Arshad Javid, Muhammad Nadeem

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The present study was conducted from April 2013 to March 2014 to observe the behavioral parameters of Chinkara (Gazella bennettii) under captive conditions by comparing the captive-born and wild-caught animals for conservation strategies. Understanding the behavioral conformations plays a significant role in captive management. Due to human population explosion and mechanized hunting, the captive breeding seems to be the best way for sports hunting, bush meat, for leather industry and horns for traditional medicinal usage. Primarily, captive management has been used on trial and error basis due to deficiency of ethology of this least concerned species. Behavior of [(20 wild-caught (WC) and 10 captive-bred (CB)] adult Chinkara was observed at captive breeding facilities for ungulates at Ravi Campus, University of Veterinary and Animal Sciences at Kasur district which is situated on southeast side of Lahore. The average annual rainfall is about 650 mm, with frequent raining during monsoon. A focal sample was used to observe the various behavioral patterns for CB and WC chinkara. A similarity was observed in behavioral parameters in WC and CB animals, however, when the differences were considered, WC male deer showed a significantly higher degree of agonistic interaction as compared to the CB male chinkara. These findings suggest that there is no immediate impact of captivity on behavior of chinkara nevertheless 10 generations of captivity. It is suggested that the Chinkara is not suitable for domestication and for successful deer farming, a further study is recommended for ethology of chinkara.

Keywords: Chinkara (Gazella bennettii), domestication, deer farming, ex-situ conservation

Procedia PDF Downloads 147

Authors: Subbarao Pichuka, Amar Balakrishna Tej, Vikas Vemula

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In recent years, the frequency and intensity of urban floods have increased due to climate change all over the world provoking a significant loss in terms of human lives and property. This study investigates the effect of Land Use and Land Cover (LULC) changes and population growth on the urban environmental conditions in the Indian metropolitan city namely Hyderabad. The centennial built-up area data have been downloaded from the Global Human Settlement Layer (GHSL) web portal for various periods (1975 to 2014). The ArcGIS version 10.8 software is employed to convert the GHSL data into shape files and also to calculate the amount of built-up area in the study locations. The decadal population data are obtained from the Census from 1971 to 2011 and forecasted for the required years (1975 and 2014) utilizing the Geometric Increase Method. Next, the analysis has been carried out with respect to the increase in population and the corresponding rise in the built-up area. Further the effects of extreme rainfall events, which exacerbate urban flooding have also been reviewed. Results demonstrate that the population growth was the primary cause of the increase in impervious surfaces in the urban regions. It in turn leads to the intensification of surface runoff and thereby leads to Urban flooding. The built-up area has been doubled from 1975 to 2014 and the population growth has been observed between 109.24% to 400% for the past four decades (1971 to 2014) in the study area (Hyderabad). Overall, this study provides the hindsight on the current urban flooding scenarios, and the findings of this study can be used in the future planning of cities.

Keywords: urban LULC change, urban flooding, GHSL built-up data, climate change, ArcGIS

Procedia PDF Downloads 68

Authors: Ali Benali Djouher Leila

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Labiovelarization of velar consonants and labials is a very widespread phenomenon. It is attested in all the major northern Berber dialects. Only the Tuareg is totally unaware of it. But, even within the large Berber-speaking regions of the north, it is very unstable: it may be completely absent in certain dialects (such as the Bougie region in Kabylie), and its extension and frequency can vary appreciably between the dialects which know it. Some dialects of Great Kabylia or the Chleuh domain, for example, "labiovélarize" more than others from the same region. Thus, in Great Kabylia, the adjective "large" will be pronounced: amqqwran with the At Yiraten and amqqran with the At Yanni, a few kilometers away. One of the problems with them is deciding whether it is one or two phonemes. All the criteria used by linguists in this kind of case lead to the conclusion that they are unique phonemes (a phoneme and not a succession of two phonemes, / k + w /, for example). The phonetic and phonological criteria are moreover clearly confirmed by the morphological data since, in the system of verbal alternations, these complex segments are treated as single phonemes: agree, "to draw, to fetch water," akwer, "to fly," have exactly the same morphology as as "jealous," arem" taste," Ames, "dirty" or afeg, "steal" ... verbs with two radical consonants (type aCC). At the level of notation, both scientific and usual, it is, therefore, necessary to represent the labiovélarized by a single letter, possibly accompanied by a diacritic. In fact, actual practices are diverse. - The scientific representation of type does not seem adequate for current use because its realization is easy only on a microcomputer. The Berber Documentation File used a small ° (of n °) above the writing line: k °, g ° ... which has the advantage of being easy to achieve since it is part of general typographical conventions in Latin script and that it is present on a typewriter keyboard. Mouloud Mammeri, then the Berber Study Group of Vincennes (Tisuraf review), and a majority of Kabyle practitioners over the last twenty years have used the succession "consonant +" semi-vowel / w / "(CW) on the same line of writing; for all the reasons explained previously, this practice is not a good solution and should be abandoned, especially as it particularizes Kabyle in the Berber ensemble. In this study, we were interested in two velar consonants, / g / and / k /, labiovellarized: / gw / and the / kw / (we adopted the addition of the "w") for the representation for ease of writing in graphical mode. It is a question of trying to characterize these four consonants in order to see if they have different places of articulation and if they are distinct (if these velars are distinct from their labiovellarized counterpart). This characterization is done using locus equations.

Keywords: berber consonants;, labiovelarization, locus equations, acoustical caracterization, kabylian dialect, algerian language

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Authors: Zunaira Zaman, David Bohannon

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This study explores the application of machine learning (ML) for detecting security vulnerabilities in source code. The research aims to assist organizations with large application portfolios and limited security testing capabilities in prioritizing security activities. ML-based approaches offer benefits such as increased confidence scores, false positives and negatives tuning, and automated feedback. The initial approach using natural language processing techniques to extract features achieved 86% accuracy during the training phase but suffered from overfitting and performed poorly on unseen datasets during testing. To address these issues, the study proposes using the abstract syntax tree (AST) for Java and C++ codebases to capture code semantics and structure and generate path-context representations for each function. The Code2Vec model architecture is used to learn distributed representations of source code snippets for training a machine-learning classifier for vulnerability prediction. The study evaluates the performance of the proposed methodology using two datasets and compares the results with existing approaches. The Devign dataset yielded 60% accuracy in predicting vulnerable code snippets and helped resist overfitting, while the Juliet Test Suite predicted specific vulnerabilities such as OS-Command Injection, Cryptographic, and Cross-Site Scripting vulnerabilities. The Code2Vec model achieved 75% accuracy and a 98% recall rate in predicting OS-Command Injection vulnerabilities. The study concludes that even partial AST representations of source code can be useful for vulnerability prediction. The approach has the potential for automated intelligent analysis of source code, including vulnerability prediction on unseen source code. State-of-the-art models using natural language processing techniques and CNN models with ensemble modelling techniques did not generalize well on unseen data and faced overfitting issues. However, predicting vulnerabilities in source code using machine learning poses challenges such as high dimensionality and complexity of source code, imbalanced datasets, and identifying specific types of vulnerabilities. Future work will address these challenges and expand the scope of the research.

Keywords: code embeddings, neural networks, natural language processing, OS command injection, software security, code properties

Procedia PDF Downloads 92

Authors: Emmanuel Iyamuremye, Edouard Singirankabo, Alexis Habineza, Yunvirusaba Nelson

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Temperature is one of the most important climatic factors for crop production. However, severe temperatures cause drought, feverish and cold spells that have various consequences for human life, agriculture, and the environment in general. It is necessary to provide reliable information related to the incidents and the probability of such extreme events occurring. In the 21st century, the world faces a huge number of threats, especially from climate change, due to global warming and environmental degradation. The rise in temperature has a direct effect on the decrease in rainfall. This has an impact on crop growth and development, which in turn decreases crop yield and quality. Countries that are heavily dependent on agriculture use to suffer a lot and need to take preventive steps to overcome these challenges. The main objective of this study is to model the statistical behaviour of extreme maximum temperature values in Rwanda. To achieve such an objective, the daily temperature data spanned the period from January 2000 to December 2017 recorded at nine weather stations collected from the Rwanda Meteorological Agency were used. The two methods, namely the block maxima (BM) method and the Peaks Over Threshold (POT), were applied to model and analyse extreme temperature. Model parameters were estimated, while the extreme temperature return periods and confidence intervals were predicted. The model fit suggests Gumbel and Beta distributions to be the most appropriate models for the annual maximum of daily temperature. The results show that the temperature will continue to increase, as shown by estimated return levels.

Keywords: climate change, global warming, extreme value theory, rwanda, temperature, generalised extreme value distribution, generalised pareto distribution

Procedia PDF Downloads 157

Authors: Ana C. V. Freitas, Luciana B. M. Pires, Joao P. Martins

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In recent years, fire dynamics in deforestation areas of tropical forests have received considerable attention because of their relationship to climate change. Climate models project great increases in the frequency and area of drought in the Amazon region, which may increase the occurrence of fires. This study analyzes the historical record number of fire outbreaks in 2017 using satellite-derived data sets of active fire detections, burned area, precipitation, and data of the Fire Program from the Center for Weather Forecasting and Climate Studies (CPTEC/INPE). A downward trend in the number of fire outbreaks occurred in the first half of 2017, in relation to the previous year. This decrease can be related to the fact that 2017 was not an El Niño year and, therefore, the observed rainfall and temperature in the Amazon region was close to normal conditions. Meanwhile, the worst period in history for fire outbreaks began with the subsequent arrival of the dry season. September of 2017 exceeded all monthly records for number of fire outbreaks per month in the entire series. This increase was mainly concentrated in Bolivia and in the states of Amazonas, northeastern Pará, northern Rondônia and Acre, regions with high densities of rural settlements, which strongly suggests that human action is the predominant factor, aggravated by the lack of precipitation during the dry season allowing the fires to spread and reach larger areas. Thus, deforestation in the Amazon is primarily a human-driven process: climate trends may be providing additional influences.

Keywords: Amazon forest, climate change, deforestation, human-driven process, fire outbreaks

Procedia PDF Downloads 113

Authors: Ian N. Robertson

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Alkali Silica Reaction (ASR) occurs in concrete when the alkali hydroxides (Na, K and OH) from the cement react with unstable silica, SiO2, in some types of aggregate. The gel that forms during this reaction will expand when it absorbs water, potentially leading to cracking and overall expansion of the concrete. ASR has resulted in accelerated deterioration of concrete highways, dams and other structures that are exposed to moisture during their service life. Concrete aggregates available in Hawaii have not demonstrated a history of ASR, however, accelerated laboratory tests using ASTM 1260 indicated a potential for ASR with some aggregates. Certain clients are now requiring import of aggregates from the US mainland at great expense. In order to assess the accuracy of the laboratory test results, a long-term field study of the potential for ASR in concretes made with Hawaiian aggregates was initiated in 2011 with funding from the US Federal Highway Administration and Hawaii Department of Transportation. Thirty concrete specimens were constructed of various concrete mixtures using aggregates from all Hawaiian aggregate sources, and some US mainland aggregates known to exhibit ASR expansion. The specimens are located in an open field site in Manoa valley on the Hawaiian Island of Oahu, exposed to relatively high humidity and frequent rainfall. A weather station at the site records the ambient conditions on a continual basis. After two years of monitoring, only one of the Hawaiian aggregates showed any sign of expansion. Ten additional specimens were fabricated with this aggregate to confirm the earlier observations. Admixtures known to mitigate ASR, such as fly ash and lithium, were included in some specimens to evaluate their effect on the concrete expansion. This paper describes the field evaluation program and presents the results for all forty specimens after four years of monitoring.

Keywords: aggregate, alkali silica reaction, concrete durability, field exposure

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Authors: Lule Basha, Eralda Gjika

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This study is focused on analyzing climate change in Albania and its potential effects on cereal yields. Initially, monthly temperature and rainfalls in Albania were studied for the period 1960-2021. Climacteric variables are important variables when trying to model cereal yield behavior, especially when significant changes in weather conditions are observed. For this purpose, in the second part of the study, linear and nonlinear models explaining cereal yield are constructed for the same period, 1960-2021. The multiple linear regression analysis and lasso regression method are applied to the data between cereal yield and each independent variable: average temperature, average rainfall, fertilizer consumption, arable land, land under cereal production, and nitrous oxide emissions. In our regression model, heteroscedasticity is not observed, data follow a normal distribution, and there is a low correlation between factors, so we do not have the problem of multicollinearity. Machine-learning methods, such as random forest, are used to predict cereal yield responses to climacteric and other variables. Random Forest showed high accuracy compared to the other statistical models in the prediction of cereal yield. We found that changes in average temperature negatively affect cereal yield. The coefficients of fertilizer consumption, arable land, and land under cereal production are positively affecting production. Our results show that the Random Forest method is an effective and versatile machine-learning method for cereal yield prediction compared to the other two methods.

Keywords: cereal yield, climate change, machine learning, multiple regression model, random forest

Procedia PDF Downloads 74

Authors: Alireza Nikbakht Shahbazi

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There are various factors that affect climate changes; drought is one of those factors. Investigation of efficient methods for estimating climate change impacts on drought should be assumed. The aim of this paper is to investigate climate change impacts on drought in Karoon3 watershed located south-western Iran in the future periods. The atmospheric general circulation models (GCM) data under Intergovernmental Panel on Climate Change (IPCC) scenarios should be used for this purpose. In this study, watershed drought under climate change impacts will be simulated in future periods (2011 to 2099). Standard precipitation index (SPI) as a drought index was selected and calculated using mean monthly precipitation data in Karoon3 watershed. SPI was calculated in 6, 12 and 24 months periods. Statistical analysis on daily precipitation and minimum and maximum daily temperature was performed. LRAS-WG5 was used to determine the feasibility of future period's meteorological data production. Model calibration and verification was performed for the base year (1980-2007). Meteorological data simulation for future periods under General Circulation Models and climate change IPCC scenarios was performed and then the drought status using SPI under climate change effects analyzed. Results showed that differences between monthly maximum and minimum temperature will decrease under climate change and spring precipitation shall increase while summer and autumn rainfall shall decrease. The precipitation occurs mainly between January and May in future periods and summer or autumn precipitation decline and lead up to short term drought in the study region. Normal and wet SPI category is more frequent in B1 and A2 emissions scenarios than A1B.

Keywords: climate change impact, drought severity, drought frequency, Karoon3 watershed

Procedia PDF Downloads 224

Authors: K. Shimola, M. Krishnaveni

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This paper examines vulnerability assessment of water resources in a semi-arid basin using the 4-step approach. The vulnerability assessment framework is developed to study the water resources vulnerability which includes the creation of GIS-based vulnerability maps. These maps represent the spatial variability of the vulnerability index. This paper introduces the 4-step approach to assess vulnerability that incorporates a new set of indicators. The approach is demonstrated using a framework composed of a precipitation data for (1975–2010) period, temperature data for (1965–2010) period, hydrological model outputs and the water resources GIS data base. The vulnerability assessment is a function of three components such as exposure, sensitivity and adaptive capacity. The current water resources vulnerability is assessed using GIS based spatio-temporal information. Rainfall Coefficient of Variation, monsoon onset and end date, rainy days, seasonality indices, temperature are selected for the criterion ‘exposure’. Water yield, ground water recharge, evapotranspiration (ET) are selected for the criterion ‘sensitivity’. Type of irrigation and storage structures are selected for the criterion ‘Adaptive capacity’. These indicators were mapped and integrated in GIS environment using overlay analysis. The five sub-basins, namely Arjunanadhi, Kousiganadhi, Sindapalli-Uppodai and Vallampatti Odai, fall under medium vulnerability profile, which indicates that the basin is under moderate stress of water resources. The paper also explores prioritization of sub-basinwise adaptation strategies to climate change based on the vulnerability indices.

Keywords: adaptive capacity, exposure, overlay analysis, sensitivity, vulnerability

Procedia PDF Downloads 300

Authors: Malik Abid Hussain Khokhar, Muhammad Adnan Tahir, Hisham Bin Hafeez Awan

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Continuous environmental determinism and climatic change in the entire globe due to increasing land surface temperature (LST) has become a vital phenomenon nowadays. LST is accelerating because of increasing greenhouse gases in the environment which results of melting down ice caps, ice sheets and glaciers. It has not only worse effects on vegetation and water bodies of the region but has also severe impacts on monsoon areas in the form of capricious rainfall and monsoon failure extensive precipitation. Environment can be monitored with the help of various geographic information systems (GIS) based algorithms i.e. SC (Single), DA (Dual Angle), Mao, Sobrino and SW (Split Window). Estimation of LST is very much possible from digital image processing of satellite imagery. This paper will encompass extraction of LST of Abbottabad using SW technique of GIS and Remote Sensing over last ten years by means of Landsat 7 ETM+ (Environmental Thematic Mapper) and Landsat 8 vide their Thermal Infrared (TIR Sensor) and Optical Land Imager (OLI sensor less Landsat 7 ETM+) having 100 m TIR resolution and 30 m Spectral Resolutions. These sensors have two TIR bands each; their emissivity and spectral radiance will be used as input statistics in SW algorithm for LST extraction. Emissivity will be derived from Normalized Difference Vegetation Index (NDVI) threshold methods using 2-5 bands of OLI with the help of e-cognition software, and spectral radiance will be extracted TIR Bands (Band 10-11 and Band 6 of Landsat 7 ETM+). Accuracy of results will be evaluated by weather data as well. The successive research will have a significant role for all tires of governing bodies related to climate change departments.

Keywords: environment, Landsat 8, SW Algorithm, TIR

Procedia PDF Downloads 346

Authors: Takashi Yamaguchi, Ichio Asanuma, Jong G. Park, Kenneth J. Mackin, John Mittleman

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In this paper, vessel detection using the artificial neural network is proposed in order to automatically construct the vessel detection model from the satellite imagery of day/night band (DNB) in visible infrared in the products of Imaging Radiometer Suite (VIIRS) on Suomi National Polar-orbiting Partnership (Suomi-NPP).The goal of our research is the establishment of vessel detection method using the satellite imagery of DNB in order to monitor the change of vessel activity over the wide region. The temporal vessel monitoring is very important to detect the events and understand the circumstances within the maritime environment. For the vessel locating and detection techniques, Automatic Identification System (AIS) and remote sensing using Synthetic aperture radar (SAR) imagery have been researched. However, each data has some lack of information due to uncertain operation or limitation of continuous observation. Therefore, the fusion of effective data and methods is important to monitor the maritime environment for the future. DNB is one of the effective data to detect the small vessels such as fishery ships that is difficult to observe in AIS. DNB is the satellite sensor data of VIIRS on Suomi-NPP. In contrast to SAR images, DNB images are moderate resolution and gave influence to the cloud but can observe the same regions in each day. DNB sensor can observe the lights produced from various artifact such as vehicles and buildings in the night and can detect the small vessels from the fishing light on the open water. However, the modeling of vessel detection using DNB is very difficult since complex atmosphere and lunar condition should be considered due to the strong influence of lunar reflection from cloud on DNB. Therefore, artificial neural network was applied to learn the vessel detection model. For the feature of vessel detection, Brightness Temperature at the 3.7 μm (BT3.7) was additionally used because BT3.7 can be used for the parameter of atmospheric conditions.

Keywords: artificial neural network, day/night band, remote sensing, Suomi National Polar-orbiting Partnership, vessel detection, Visible Infrared Imaging Radiometer Suite

Procedia PDF Downloads 221

Authors: Ramin Mansouri

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Due to the contrast of rivers discharge regime with water demands, one of the best ways to use water resources is to regulate the natural flow of the rivers and supplying water needs to construct dams. Optimal utilization of reservoirs, consideration of multiple important goals together at the same is of very high importance. To study about analyzing this method, statistical data of Bakhtiari and Roudbar dam over 46 years (1955 until 2001) is used. Initially an appropriate objective function was specified and using DE algorithm, the rule curve was developed. In continue, operation policy using rule curves was compared to standard comparative operation policy. The proposed method distributed the lack to the whole year and lowest damage was inflicted to the system. The standard deviation of monthly shortfall of each year with the proposed algorithm was less deviated than the other two methods. The Results show that median values for the coefficients of F and Cr provide the optimum situation and cause DE algorithm not to be trapped in local optimum. The most optimal answer for coefficients are 0.6 and 0.5 for F and Cr coefficients, respectively. After finding the best combination of coefficients values F and CR, algorithms for solving the independent populations were examined. For this purpose, the population of 4, 25, 50, 100, 500 and 1000 members were studied in two generations (G=50 and 100). result indicates that the generation number 200 is suitable for optimizing. The increase in time per the number of population has almost a linear trend, which indicates the effect of population in the runtime algorithm. Hence specifying suitable population to obtain an optimal results is very important. Standard operation policy had better reversibility percentage, but inflicts severe vulnerability to the system. The results obtained in years of low rainfall had very good results compared to other comparative methods.

Keywords: reservoirs, differential evolution, dam, Optimal operation

Procedia PDF Downloads 63

Authors: Md. Kumruzzaman, Anutosh Das, Md. Mosharraf Hossain

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Historically, rapid urban growth activities are considered one of the main culprits behind urban floods or waterlogging. The increased unplanned urbanization of many areas of Dhaka has resulted in waterlogging, urban floods, and increasing groundwater depth. To determine potential groundwater recharge from precipitation, the study is being conducted to examine the changes in land use/land cover (LULC) and urban runoff extent based on the NRCS-CN from 2005–2021. Four kinds of land use are used to examine the LULC change: built-up, bare land, vegetation, and water body. These categories are used for the years 2005, 2010, 2015, and 2021. The built-up area is growing at a relatively fast rate: 7.43%, 17.4%, and 5.21%, respectively, between the years 2005 and 2010, 2010 and 2015, and 2015 and 2021. As the amount of impervious surface rose in Dhaka city, stormwater discharge increased from 2005 to 2021. In 2005, 2010, 2015, and 2021, heavy stormwater runoff regions made up around 24.873%, 32.616%, 49.118%, and 55.986% of the entire Dhaka city. Stormwater runoff accounted for around 53.738%, 55.092%, 63.472%, and 67.061% of the total rainfall in 2005, 2010, 2015, and 2021, respectively. Between 2005 and 2021, a significant portion of the natural land cover was altered because of the expanding impervious surface, which also harmed the natural drainage system. Due to careless growth, the potential for stormwater runoff and groundwater recharge in Dhaka city worsens every year. Concerning this situation, a sustainable urban drainage system (SUDS) can be the best possible solution for minimizing the stormwater runoff and groundwater recharge problem.

Keywords: LULC, impervious surface, stormwater runoff, groundwater recharge, SUDS

Procedia PDF Downloads 62

Authors: N. Y. H. Konagano

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Riverside population of Brazilian amazon suffers drinking water scarcity, seeking alternative water resources such as well and rivers, ordinary polluted. Although Amazon Region holds high annual river inflow and enough available of underground water, human activities have compromised the conservation of water resources. In addition, decentralized rural households make difficult to access of potable water. Main objective is to analyze quantitatively the potential of rainwater harvesting to human consumption at Marupaúba community, located in northeast of Amazon region, Brazil. Methods such as historical rainfall data series of municipality of Tomé-Açu at Pará state were obtained from Hydrological Information System of National Water Agency (ANA). Besides, Rippl method was used to calculate, mainly, volume of the reservoir based on difference of water demand and volume available through rainwater using as references two houses (CA I and CA II) as model of rainwater catchment and supply. Results presented that, from years 1984 to 2017, average annual precipitation was 2.607 mm, average maximum precipitation peak was 474 mm on March and average minimum peak on September was 44 mm. All months, of a year, surplus volume of water have presented in relation to demand, considering catchment area (CA) I = 134.4m² and demand volume =0.72 m³/month; and, CA II = 81.84 m² and demand volume = 0.48 m³/month. Based on results, it is concluded that it is feasible to use rainwater for the supply of the rural community Marupaúba, since the access of drinking water is a human right and the lack of this resource compromises health and daily life of human beings.

Keywords: Amazon Region, rainwater harvesting, rainwater resource, rural community

Procedia PDF Downloads 138

Authors: Marine Kobalava

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The article analyzes the level of Georgia's tourism potential usage during the pandemic. The conclusion is drawnthat Georgia, as a tourism brand, is in a significant crisis at this stage, revenues from this sector have been substantially reduced, communication with potential customers is interrupted, no international marketing and PR communication strategies have been developed for the post-pandemic period. In order to rehabilitate the tourism industry of Georgia, it is considered vital to take measures using international marketing and PR communication strategies adjusted to the needs of the sectorthat will improve the use of tourism potential and stimulate the development of the sector. The goal of the research is to identify the factors hindering the use of tourism potential in the direction of international marketing and PR communication strategies in the post-pandemic period and to develop recommendations on ways to solve them. Research methods. The paper uses various theoretical and methodological tools of research, including Bibliographic research has been conducted on the main research issues; Analysis, synthesis, induction, and other methods are used to select and group data, identify similarities and differences, and identify trends; Endogenous and exogenous factors affecting the field of tourism have been studied by means of SWOT and PESTEL analyzes. A comparison model is used to analyze the strategy documents. Primary accounting materials are obtained from the National Statistics Office and the relevant ministries. Based on the results of the research, the directions of correct positioning of tourism products and marketing communication in the post-pandemic period have been developed. It is substantiated that a short-term international marketing strategy should include: probable goals of communication, maintaining a position on a potential traveler's “radar,” focusing communication on key motivating factors (gastronomy, winemaking, folklore, protected areas, mountainous regions). From a marketing point of view, it is important: holding international marketing events, compiling a list of target countries, formation of stimulus mechanisms, development of incentive programs for international tour operators, etc. The paper draws conclusions about the problems of using the tourism potential, recommendations on ways to solve this problems through international marketing and PR communication strategies are offered

Keywords: PR communication, international marketing strategy, tourism potential, post-pandemic period

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Authors: Ajit Kumar Behera, Saranya P., Sudhir Kumar, Krishnakumar A

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The stable isotope (δ¹⁸ O and δ²H) composition of groundwater of the coastal areas of Periyar and Mahanadi basins falling along East and West coast of India during North-East (NE) monsoon season have been studied. The east and west coast regions are surrounded by the Bay of Bengal and the Arabian Sea respectively, which are considered to be the primary sources for precipitation over India. The major difference between the Bay of Bengal and the Arabian Sea is that a number of large rivers feed the Bay of Bengal, whereas the Arabian Sea is fed by very few small rivers, resulting in enriched stable isotopic composition of the Arabian Sea than the Bay of Bengal. Previous studies have reported depleted ratios of stable isotopes during Northeast monsoon along East and West coasts due to the influence of the Bay of Bengal moisture source. The isotopic composition of groundwater of the Mahanadi delta in the east coast region varies from -6.87 ‰ to -3.40 ‰ for δ¹⁸ O and -45.42 ‰ to -22.43‰ for δ²H. However, the groundwater of the Periyar basin in the west coast has enriched stable isotope value varying from -4.3‰ to -2.5 ‰ for δ¹⁸ O and for δ²H from -23.7 to -6.4 ‰ which is a characteristic of South-West monsoon season. This suggests the groundwater system of the Mahanadi delta and the Periyar basins are influenced by dissimilar moisture sources. The δ¹⁸ O and δ² H relationship (δ²H= 6.513 δ¹⁸ O - 1.39) and d-excess value (< 10) in the east coast region indicates the influence of NE monsoon implying the quick groundwater recharge after precipitation with significant amount of evaporation. In contrast, the δ¹⁸ O and δ²H regression line (δ²H= 8.408 δ¹⁸ O + 11.71) with high d-excess value (>10) in the west coast region implies delayed recharge due to SW monsoon. The observed isotopic enrichment in west coast suggests that NE winter monsoon rainfall does not replenish groundwater quick enough to produce isotopic depletion during the season.

Keywords: Arabian sea, bay of Bengal, groundwater, monsoon, stable isotope

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Authors: Olalekan Sunday Alabi, Titus Adeyemi Alonge, Olumuyiwa Idowu Ojo

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Agricultural land suitability analysis and mapping play an imperative role for sustainable utilization of scarce physical land resources. The objective of this study was to prepare spatial database of physical land resources for irrigated agriculture and to assess land suitability for irrigation and developing suitable area map of the study area. The study was conducted at Kampe-Omi irrigation scheme located at Yagba West Local Government Area of Kogi State, Nigeria. Temperature and rainfall data of the study area were collected for 10 consecutive years (2005-2014). Geographic Information System (GIS) techniques were used to develop irrigation land suitability map of the study area. Attribute parameters such as the slope, soil properties, topography of the study area were used for the analysis. The available data were arranged, proximity analysis of Arc-GIS was made, and this resulted into five mapping units. The final agricultural land suitability map of the study area was derived after overlay analysis. Based on soil composition, slope, soil properties and topography, it was concluded that; Kampe-Omi has rich sandy loam soil, which is viable for agricultural purpose, the soil composition is made up of 60% sand and 40% loam. The land-use pattern map of Kampe-Omi has vegetal area and water-bodies covering 55.6% and 19.3% of the total assessed area respectively. The landform of Kampe-Omi is made up of 41.2% lowlands, 37.5% normal lands and 21.3% highlands. Kampe-Omi is adequately suitable for agricultural purpose while an extra of 20.2% of the area is highly suitable for agricultural purpose making 72.6% while 18.7% of the area is slightly suitable.

Keywords: remote sensing, GIS, Kampe–Omi, land suitability, mapping

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Authors: Chen Zhi-Wei, Hsieh Wei-Fang

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Taiwan annual rainfall is global average of 2.5 times, plus city excessive development, green constantly to reduced, instead of is big area of artificial base disc, makes Taiwan rainy season during occurred of storm cannot timely of emissions, led to flood constantly, and rain also cannot was retained again using, led to city hydrological balance suffered damage, and to Regulation city of by brings of negative effect, increased green covered rate became most effective of method, and city land limited, so roof green gradually became a alternative program. Green roofs have become one of the Central and local government policy initiatives for urban development, in foreign countries, such as the United States, and Japan, and Singapore etc. Development of roof greening as an important policy, has become a trend of the times. In recent years, many experts and scholars are also on the roof greening all aspects of research, mostly for green roof for the environmental impact of benefits, such as: carbon reduction, cooling, thermostat, but research on the benefits of green roofs under water cut but it is rare. Therefore, this research literature from green roof in to view and analyze what kind of medium suitable for roof greening and use of green base plate combination simulated green roof structure, via different proportions of the medium with water retention plate and drainage board, experiment with different planting base plate combination of water conservation performance. Research will want to test the effect of roof planting base mix, promotion of relevant departments and agencies in future implementation of green roofs, prompted the development of green roofs, which in the end Taiwan achieve sustainable development of the urban environment help.

Keywords: thin-layer roof greening and planting medium, water efficiency

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Authors: Dagem Alemayehu, Samson Gebersilassie, Jan Frank

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Climate change is impacting nutrition through reducing food quantity and access, limiting dietary diversity, and decreased nutritional food content as well as strongly affecting seasonal rainfall in Ethiopia. Nevertheless, only a few data is available on the impacts of seasonality in Infant, and Young Child Feeding (IYCF) practices undernutrition among 6-23 months old children in different agro-ecological zones of poor resource settings of Ethiopia. Methods: Socio-demographic, anthropometry, and IYCF indicators were assessed in the harvest and lean seasons among children aged 6–23 months of age randomly selected from rural villages of lowland and midland agro-ecological zones. Results: Child stunting and underweight increased from prevalence of 32.8 % and 23.9 % (lowland &midland respectively) in the lean season to 36.1% and 33.8 % harvest seasons, respectively. The biggest increase in the prevalence of stunting and underweight between harvest and lean seasons was noted in the lowland zone. Wasting decreased from 11.6% lean to 8.5% harvest, with the biggest decline recorded in the midland zone. Minimum meal frequency, minimum acceptable diet, and poor dietary diversity increased considerably in harvest compared to a lean season in the lowland zone. Feeding practices and maternal age were predictors of wasting, while women's dietary diversity and children's age was a predictor of child dietary diversity in both seasons. Conclusion: There is seasonal variation in undernutrition and IYCF practices among children 6-23 months of age with more pronounced effect lowland agro-ecological zone.

Keywords: agroecology, seasonality, stunting, wasting

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Authors: Gopika Rajagopal, Sudheesh Thiyyakkandi

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Back-to-back reinforced earth (RE) walls are extensively used in these days as bridge abutments and highway ramps, owing to their cost efficiency and ease of construction. High quality select fill is the most suitable backfill material due to its excellent engineering properties and constructability. However, industries are compelled to use low quality, locally available soil because of its ample availability on site. However, several failure cases of such walls are reported, especially subsequent to rainfall events. The stiffness of reinforcement is one of the major factors affecting the performance of RE walls. The present study focused on analyzing the effect of reinforcement stiffness on the performance of complete select fill, complete marginal fill, and hybrid-fill (i.e., combination of select and marginal fills) back-to-back RE walls, immediately after construction and upon rainwater infiltration through finite element modelling. A constant width to height (W/H) ratio of 3 and height (H) of 6 m was considered for the numerical analysis and the stiffness of reinforcement layers was varied from 500 kN/m to 10000 kN/m. Results showed that reinforcement stiffness had a noticeable influence on the response of RE wall, subsequent to construction as well as rainwater infiltration. Facing displacement was found to decrease and maximum reinforcement tension and factor of safety were observed to increase with increasing the stiffness of reinforcement. However, beyond a stiffness of 5000 kN/m, no significant reduction in facing displacement was observed. The behavior of fully marginal fill wall considered in this study was found to be reasonable even after rainwater infiltration when the high stiffness reinforcement layers are used.

Keywords: back-to-back reinforced earth wall, finite element modelling, rainwater infiltration, reinforcement stiffness

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Authors: Joshua Buli, David Pietrowski, Samuel Britton

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Processing SAR data usually requires constraints in extent in the Fourier domain as well as approximations and interpolations onto a planar surface to form an exploitable image. This results in a potential loss of data requires several interpolative techniques, and restricts visualization to two-dimensional plane imagery. The data can be interpolated into a ground plane projection, with or without terrain as a component, all to better view SAR data in an image domain comparable to what a human would view, to ease interpretation. An alternate but computationally heavy method to make use of more of the data is the basis of this research. Pre-processing of the SAR data is completed first (matched-filtering, motion compensation, etc.), the data is then range compressed, and lastly, the contribution from each pulse is determined for each specific point in space by searching the time history data for the reflectivity values for each pulse summed over the entire collection. This results in a per-3D-point reflectivity using the entire collection domain. New advances in GPU processing have finally allowed this rapid projection of acquired SAR data onto any desired reference surface (called backprojection). Mathematically, the computations are fast and easy to implement, despite limitations in SAR phase history data size and 3D-point cloud size. Backprojection processing algorithms are embarrassingly parallel since each 3D point in the scene has the same reflectivity calculation applied for all pulses, independent of all other 3D points and pulse data under consideration. Therefore, given the simplicity of the single backprojection calculation, the work can be spread across thousands of GPU threads allowing for accurate reflectivity representation of a scene. Furthermore, because reflectivity values are associated with individual three-dimensional points, a plane is no longer the sole permissible mapping base; a digital elevation model or even a cloud of points (collected from any sensor capable of measuring ground topography) can be used as a basis for the backprojection technique. This technique minimizes any interpolations and modifications of the raw data, maintaining maximum data integrity. This innovative processing will allow for SAR data to be rapidly brought into a common reference frame for immediate exploitation and data fusion with other three-dimensional data and representations.

Keywords: backprojection, data fusion, exploitation, three-dimensional, visualization

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Authors: Joo-Heon Lee, Seo-Yeon Park, Chanyang Sur, Ho-Won Jang

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Satellite-based remote sensing technique has been widely used in the area of drought and environmental monitoring to overcome the weakness of in-situ based monitoring. There are many advantages of remote sensing for drought watch in terms of data accessibility, monitoring resolution and types of available hydro-meteorological data including environmental areas. This study was focused on the applicability of drought monitoring based on satellite imageries by applying to the historical drought events, which had a huge impact on meteorological, agricultural, and hydrological drought. Satellite-based drought indices, the Standardized Precipitation Index (SPI) using Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Mission (GPM); Vegetation Health Index (VHI) using MODIS based Land Surface Temperature (LST), and Normalized Difference Vegetation Index (NDVI); and Scaled Drought Condition Index (SDCI) were evaluated to assess its capability to analyze the complex topography of the Korean peninsula. While the VHI was accurate when capturing moderate drought conditions in agricultural drought-damaged areas, the SDCI was relatively well monitored in hydrological drought-damaged areas. In addition, this study found correlations among various drought indices and applicability using Receiver Operating Characteristic (ROC) method, which will expand our understanding of the relationships between hydro-meteorological variables and drought events at global scale. The results of this research are expected to assist decision makers in taking timely and appropriate action in order to save millions of lives in drought-damaged areas.

Keywords: drought monitoring, moderate resolution imaging spectroradiometer (MODIS), remote sensing, receiver operating characteristic (ROC)

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Authors: Raoudane Bouziyan, Kawser Mohammad Tawhid

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Microstrip antennas are low in profile, light in weight, conformable in structure and are now developed for many applications. The main difficulty of the microstrip antenna is its narrow bandwidth. Several modern applications like satellite communications, remote sensing, and multi-function radar systems will find it useful if there is dual-band antenna operating from a single aperture. Some applications require covering both transmitting and receiving frequency bands which are spaced apart. Providing multiple antennas to handle multiple frequencies and polarizations becomes especially difficult if the available space is limited as with airborne platforms and submarine periscopes. Dual band operation can be realized from a single feed using slot loaded or stacked microstrip antenna or two separately fed antennas sharing a common aperture. The former design, when used in arrays, has certain limitations like complicated beam forming or diplexing network and difficulty to realize good radiation patterns at both the bands. The second technique provides more flexibility with separate feed system as beams in each frequency band can be controlled independently. Another desirable feature of a dual band antenna is easy adjustability of upper and lower frequency bands. This thesis presents investigation of a new dual-band antenna, which is a hybrid of microstrip and waveguide radiating elements. The low band radiator is a Shorted Annular Ring (SAR) microstrip antenna and the high band radiator is an aperture antenna. The hybrid antenna is realized by forming a waveguide radiator in the shorted region of the SAR microstrip antenna. It is shown that the upper to lower frequency ratio can be controlled by the proper choice of various dimensions and dielectric material. Operation in both linear and circular polarization is possible in either band. Moreover, both broadside and conical beams can be generated in either band from this antenna element. Finite Element Method based software, HFSS and Method of Moments based software, FEKO were employed to perform parametric studies of the proposed dual-band antenna. The antenna was not tested physically. Therefore, in most cases, both HFSS and FEKO were employed to corroborate the simulation results.

Keywords: FEKO, HFSS, dual band, shorted annular ring patch

Procedia PDF Downloads 387

Authors: Vaidehi Murarka, Sneha Mehta, Dishant Upadhyay

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Our project topic is “Alphabet Recognition using pixel probability distribution”. The project uses techniques of Image Processing and Machine Learning in Computer Vision. Alphabet recognition is the mechanical or electronic translation of scanned images of handwritten, typewritten or printed text into machine-encoded text. It is widely used to convert books and documents into electronic files etc. Alphabet Recognition based OCR application is sometimes used in signature recognition which is used in bank and other high security buildings. One of the popular mobile applications includes reading a visiting card and directly storing it to the contacts. OCR's are known to be used in radar systems for reading speeders license plates and lots of other things. The implementation of our project has been done using Visual Studio and Open CV (Open Source Computer Vision). Our algorithm is based on Neural Networks (machine learning). The project was implemented in three modules: (1) Training: This module aims “Database Generation”. Database was generated using two methods: (a) Run-time generation included database generation at compilation time using inbuilt fonts of OpenCV library. Human intervention is not necessary for generating this database. (b) Contour–detection: ‘jpeg’ template containing different fonts of an alphabet is converted to the weighted matrix using specialized functions (contour detection and blob detection) of OpenCV. The main advantage of this type of database generation is that the algorithm becomes self-learning and the final database requires little memory to be stored (119kb precisely). (2) Preprocessing: Input image is pre-processed using image processing concepts such as adaptive thresholding, binarizing, dilating etc. and is made ready for segmentation. “Segmentation” includes extraction of lines, words, and letters from the processed text image. (3) Testing and prediction: The extracted letters are classified and predicted using the neural networks algorithm. The algorithm recognizes an alphabet based on certain mathematical parameters calculated using the database and weight matrix of the segmented image.

Keywords: contour-detection, neural networks, pre-processing, recognition coefficient, runtime-template generation, segmentation, weight matrix

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Authors: Henok Hailemariam, Frank Wuttke

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Collapsible soils are weak soils that appear to be stable in their natural state, normally dry condition, but rapidly deform under saturation (wetting), thus generating large and unexpected settlements which often yield disastrous consequences for structures unwittingly built on such deposits. In this study, a prediction model for the relative subsidence of stressed collapsible soils based on dielectric permittivity measurement is presented. Unlike most existing methods for soil subsidence prediction, this model does not require moisture content as an input parameter, thus providing the opportunity to obtain accurate estimation of the relative subsidence of collapsible soils using dielectric measurement only. The prediction model is developed based on an existing relative subsidence prediction model (which is dependent on soil moisture condition) and an advanced theoretical frequency and temperature-dependent electromagnetic mixing equation (which effectively removes the moisture content dependence of the original relative subsidence prediction model). For large scale sub-surface soil exploration purposes, the spatial sub-surface soil dielectric data over wide areas and high depths of weak (collapsible) soil deposits can be obtained using non-destructive high frequency electromagnetic (HF-EM) measurement techniques such as ground penetrating radar (GPR). For laboratory or small scale in-situ measurements, techniques such as an open-ended coaxial line with widely applicable time domain reflectometry (TDR) or vector network analysers (VNAs) are usually employed to obtain the soil dielectric data. By using soil dielectric data obtained from small or large scale non-destructive HF-EM investigations, the new model can effectively predict the relative subsidence of weak soils without the need to extract samples for moisture content measurement. Some of the resulting benefits are the preservation of the undisturbed nature of the soil as well as a reduction in the investigation costs and analysis time in the identification of weak (problematic) soils. The accuracy of prediction of the presented model is assessed by conducting relative subsidence tests on a collapsible soil at various initial soil conditions and a good match between the model prediction and experimental results is obtained.

Keywords: collapsible soil, dielectric permittivity, moisture content, relative subsidence

Procedia PDF Downloads 339

Authors: Bei Zhang, Zhaoxin Zhang, Lidong Zhao

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Green infrastructures (GIs) for rainwater management can directly meet the multiple purposes of urban greening and non-point source pollution control. To reveal the overall layout law of GIs dominated by typical woody plants and their impact on urban environmental effects, we constructed a HYDRUS-1D and Stormwater management (SWMM) coupling model to simulate the response of typical root woody plant planting methods on urban hydrological. The results showed that the coupling model had high adaptability to the simulation of urban surface runoff control effect under different woody plant planting methods (NSE ≥0.64 and R² ≥ 0.71). The regulation effect on surface runoff showed that the average runoff reduction rate of GIs increased from 60 % to 71 % with the increase of planting area (5% to 25%) under the design rainfall event of the 2-year recurrence interval. Sophora japonica with tap roots was slightly higher than that of without plants (control) and Malus baccata (M. baccata) with fibrous roots. The comprehensive benefit evaluation system of rainwater utilization technology was constructed by using an analytic hierarchy process. The coupling model was used to evaluate the comprehensive benefits of woody plants with different planting areas in the study area in terms of environment, economy, and society. The comprehensive benefit value of planting 15% M. baccata was the highest, which was the first choice for the planting of woody plants in the study area. This study can provide a scientific basis for the decision-making of green facility layouts of woody plants.

Keywords: green infrastructure, comprehensive benefits, runoff regulation, woody plant layout, coupling model

Procedia PDF Downloads 47

Authors: Luvindran Sugumaran, Mohd Nashrul Mohd Zubir, Kazi Md Salim Newaz, Tuan Zaharinie Tuan Zahari, Suazlan Mt Aznam, Aiman Mohd Halil

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With the fast growth of integrated circuits and the trend towards making electronic devices smaller, the heat dissipation load of electronic devices has continued to go over the limit. The high heat flux element would not only harm the operation and lifetime of the equipment but would also impede the performance upgrade brought about by the iteration of technological updates, which would have a direct negative impact on the economic and production cost benefits of rising industries. Hence, in high-tech industries like radar, information and communication, electromagnetic power, and aerospace, the development and implementation of effective heat dissipation technologies were urgently required. Pool boiling is favored over other cooling methods because of its capacity to dissipate a high heat flux at a low wall superheat without the usage of mechanical components. Enhancing the pool boiling performance by increasing the heat transfer coefficient via surface modification techniques has received a lot of attention. There are several surface modification methods feasible today, but the stability and durability of surface modification are the greatest priority. Thus, laser machining is an interesting choice for surface modification due to its low production cost, high scalability, and repeatability. In this study, different patterns of laser-processed copper surfaces are fabricated to investigate the nucleate pool boiling heat transfer performance of distilled water. The investigation showed that there is a significant enhancement in the pool boiling heat transfer performance of the laser-processed surface compared to the reference surface due to the notable increase in nucleation frequency and nucleation site density. It was discovered that the heat transfer coefficients increased when both the surface area ratio and the ratio of peak-to-valley height of the microstructure were raised. It is believed that the development of microstructures on the surface as a result of laser processing is the primary factor in the enhancement of heat transfer performance.

Keywords: heat transfer coefficient, laser processing, micro structured surface, pool boiling

Procedia PDF Downloads 69