Search results for: flood forecasting

Authors: L. Nahimana

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The eastern edge of the East African Rift in Burundi shows many mass movement phenomena corresponding to landslides, mudflow, debris flow, spectacular erosion (mega-gully), flash floods and alluvial deposits. These phenomena usually occur during the rainy season. Their extent and consecutive damages vary widely. To manage these phenomena, it is necessary to adopt a methodological approach of their mapping with a structured database. The elements for this database are: three-dimensional extent of the phenomenon, natural causes and conditions (geological lithology, slope, weathering depth and products, rainfall patterns, natural environment) and the anthropogenic factors corresponding to the various human activities. The extent of the area provides information about the possibilities and opportunities for mitigation technique. The lithological nature allows understanding the influence of the nature of the rock and its structure on the intensity of the weathering of rocks, as well as the geotechnical properties of the weathering products. The slope influences the land stability. The intensity of annual, monthly and daily rainfall helps to understand the conditions of water saturation of the terrains. Certain natural circumstances such as the presence of streams and rivers promote foot slope erosion and thus the occurrence and activity of mass movements. The construction of some infrastructures such as new roads and agglomerations deeply modify the flow of surface and underground water followed by mass movements. Using geospatial data selected on the East African Rift in Burundi, it is presented case of mass movements illustrating the nature, importance, various factors and the extent of the damages. An analysis of these elements for each hazard can guide the options for mitigation of the phenomenon and its consequences.

Keywords: mass movement, landslide, mudflow, debris flow, spectacular erosion, mega-gully, flash flood, alluvial deposit, East African rift, Burundi

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Authors: Adebola Adedugbe

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The challenge of post-harvest losses poses serious threats for food security in Nigeria and the north-eastern part with the country losing about $9billion annually due to postharvest losses in the sector. Post-harvest loss (PHL) is the quantitative and qualitative loss of food in various post-harvest operations. In Nigeria, post-harvest losses (PHL) have been a major challenge to food security and improved farmer’s income. In 2022, the Nigerian government had said over 30 percent of food produced by Nigerian farmers perish during post-harvest. For many in northeast Nigeria, agriculture is the predominant source of livelihood and income. The persistent communal conflicts, flood, decade-old attacks by boko haram and insurgency in this region have disrupted farming activities drastically, with farmlands becoming insecure and inaccessible as communities are forced to abandon ancestral homes, The impact of climate change is also affecting agricultural and fishing activities, leading to shortage of food supplies, acute hunger and loss of livelihood. This has continued to impact negatively on the region and country’s food production and availability making it loose billions of US dollars annually in income in this sector. The root cause of postharvest losses among others in crops, livestock and fisheries are lack of modern post-harvest equipment, chemical and lack of technologies used for combating losses. The 2019 Global Hunger Index showed Nigeria’s case was progressing from a ‘serious to alarming level’. As part of measures to address the problem of post-harvest losses experienced by farmers, the federal government of Nigeria concessioned 17 silos with 6000 metric tonne storage space to private sector to enable farmers to have access to storage facilities. This paper discusses the causes, effects and solutions in handling post-harvest losses and optimize returns on food security in northeast Nigeria.

Keywords: farmers, food security, northeast Nigeria, postharvest loss

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Authors: Anand Malik

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The Himalayas with high tectonic activities poses a great threat to human life and property. Climate change is another reason which triggering extreme events multiple fold effect on high mountain glacial environment, rock falls, landslides, debris flows, flash flood and snow avalanches. One such extreme event of cloud burst along with breach of moraine dammed Chorabri Lake occurred from June 14 to June 17, 2013, triggered flooding of Saraswati and Mandakini rivers in the Kedarnath Valley of Rudraprayag district of Uttrakhand state of India. As a result, huge volume of water with its high velocity created a catastrophe of the century, which resulted into loss of large number of human/animals, pilgrimage, tourism, agriculture and property. Thus a comprehensive assessment of debris flow hazards requires GIS-based modeling using numerical methods. The aim of present study is to focus on analysis and mapping of debris flow movements using geospatial data with flow-r (developed by team at IGAR, University of Lausanne). The model is based on combined probabilistic and energetic algorithms for the assessment of spreading of flow with maximum run out distances. Aster Digital Elevation Model (DEM) with 30m x 30m cell size (resolution) is used as main geospatial data for preparing the run out assessment, while Landsat data is used to analyze land use land cover change in the study area. The results of the study area show that model can be applied with great accuracy as the model is very useful in determining debris flow areas. The results are compared with existing available landslides/debris flow maps. ArcGIS software is used in preparing run out susceptibility maps which can be used in debris flow mitigation and future land use planning.

Keywords: debris flow, geospatial data, GIS based modeling, flow-R

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Authors: Akbar Khodavirdizadeh, Ali Nemati Babaylou, Hassan Moomivand

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The history of human access to water technique has been one of the factors in the formation of human civilizations in the ancient world. The technique that makes surface water and groundwater accessible to humans on the ground has been a clever technique in human life to reach the water. In this study, while examining the water technique of ancient Iran using the Qanats technique, the water supply system of different regions of the ancient world were also studied and compared. Six groups of the ancient region of ancient Greece (Archaic 480-750 BC and Classical 223-480 BC), Urartu in Tuspa (600-850 BC), Petra (106-168 BC), Ancient Rome (265 BC), and the ancient United States (1450 BC) and ancient Iranian water technologies were studied under water supply systems. Past water technologies in these areas: water transmission systems in primary urban centers, use of water structures in water control, use of bridges in water transfer, construction of waterways for water transfer, storage of rainfall, construction of various types of pottery- ceramic, lead, wood and stone pipes have been used in water transfer, flood control, water reservoirs, dams, channel, wells, and Qanat. The central plateau of Iran is one of the arid and desert regions. Archaeological, geomorphological, and paleontological studies of the central region of the Iranian plateau showed that without the use of Qanats, the possibility of urban civilization in this region was difficult and even impossible. Zarch aqueduct is the most important aqueduct in Yazd region. Qanat of Zarch is a plain Qanat with a gallery length of 80 km; its mother well is 85 m deep and has 2115 well shafts. The main purpose of building the Qanat of Zārch was to access the groundwater source and transfer it to the surface of the ground. Regarding the structure of the aqueduct and the technique of transferring water from the groundwater source to the surface, it has a great impact on being different from other water techniques in the ancient world. The results show that the use of water technologies in ancient is very important to understand the history of humanity in the use of hydraulic techniques.

Keywords: ancient water technologies, groundwaters, qanat, human history, Ancient Iran

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Authors: H. H. Elewa, E. M. Ramadan, A. M. Nosair

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Rainfall water harvesting is considered as an important tool for overcoming water scarcity in arid and semi-arid region. Wadi Watir in the southeastern part of Sinai Peninsula is considered as one of the main and active basins in the Gulf of Aqaba drainage system. It is characterized by steep hills mainly consist of impermeable rocks, whereas the streambeds are covered by a highly permeable mixture of gravel and sand. A comprehensive approach involving the integration of geographic information systems, remote sensing and watershed modeling was followed to identify the RWH capability in this area. Eight thematic layers, viz volume of annual flood, overland flow distance, maximum flow distance, rock or soil infiltration, drainage frequency density, basin area, basin slope and basin length were used as a multi-parametric decision support system for conducting weighted spatial probability models (WSPMs) to determine the potential areas for the RWH. The WSPMs maps classified the area into five RWH potentiality classes ranging from the very low to very high. Three performed WSPMs' scenarios for W. Watir reflected identical results among their maps for the high and very high RWH potentiality classes, which are the most suitable ones for conducting surface water harvesting techniques. There is also a reasonable match with respect to the potentiality of runoff harvesting areas with a probability of moderate, low and very low among the three scenarios. WSPM results have shown that the high and very high classes, which are the most suitable for the RWH are representing approximately 40.23% of the total area of the basin. Accordingly, several locations were decided for the establishment of water harvesting dams and cisterns to improve the water conditions and living environment in the study area.

Keywords: Sinai, Wadi Watir, remote sensing, geographic information systems, watershed modeling, runoff water harvesting

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Authors: Xiyue Wang, Shaoning Yan

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Cities in China today is faced with an increasingly serious river ecological crisis accompanying with the development of urbanization: waterlogging on account of the fragmented urban natural hydrological system; the limited ecological function of the hydrological system caused by a destruction of water system and waterfront ecological environment. Additionally, the eco-hydrological processes of rivers are affected by various environmental factors, which are more complex in the context of urban environment. Therefore, efficient hydrological monitoring and analysis tools, accurate and visual hydrological and hydraulic models are becoming more important basis for decision-makers and an important way for landscape architects to solve urban hydrological problems, formulating sustainable and forward-looking schemes. The study mainly introduces the river and flood analysis model based on the platform of Autodesk Civil 3D. Taking the Luanhe River in Qian'an City of Hebei Province as an example, the 3D models of the landform, river, embankment, shoal, pond, underground stream and other land features were initially built, with which the water transfer simulation analysis, river floodplain analysis, and river ecology analysis were carried out, ultimately the real-time visualized simulation and analysis of rivers in various hypothetical scenarios were realized. Through the establishment of digital hydrological and hydraulic model, the hydraulic data can be accurately and intuitively simulated, which provides basis for rational water system and benign urban ecological system design. Though, the hydrological and hydraulic model based on Autodesk Civil3D own its boundedness: the interaction between the model and other data and software is unfavorable; the huge amount of 3D data and the lack of basic data restrict the accuracy and application range. The hydrological and hydraulic model based on Autodesk Civil3D platform provides more possibility to access convenient and intelligent tool for urban planning and monitoring, a solid basis for further urban research and design.

Keywords: visualization, hydrological and hydraulic model, Autodesk Civil 3D, urban river

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Authors: Badli Shah Mohd Yusoff, Khairur Rijal Jamaludin, Rozetta Dollah

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The emerging of reverse logistics and product recovery management is an important concept in reconciling economic and environmental objectives through recapturing values of the end of life product returns. End of life products contains valuable modules, parts, residues and materials that can create value if recovered efficiently. The main objective of this study is to explore and develop a model to recover as much of the economic value as reasonably possible to find the optimality of return acquisition and sorting to meet demand and maximize profits over time. In this study, the benefits that can be obtained for remanufacturer is to develop demand forecasting of used products in the future with uncertainty of returns and quality of products. Formulated based on a generic disassembly tree, the proposed model focused on three reverse logistics activity, namely refurbish, remanufacture and disposal incorporating all plausible means quality levels of the returns. While stricter sorting policy, constitute to the decrease amount of products to be refurbished or remanufactured and increases the level of discarded products. Numerical experiments carried out to investigate the characteristics and behaviour of the proposed model with mathematical programming model using Lingo 16.0 for medium-term planning of return acquisition, disassembly (refurbish or remanufacture) and disposal activities. Moreover, the model seeks an analysis a number of decisions relating to trade off management system to maximize revenue from the collection of use products reverse logistics services through refurbish and remanufacture recovery options. The results showed that full utilization in the sorting process leads the system to obtain less quantity from acquisition with minimal overall cost. Further, sensitivity analysis provides a range of possible scenarios to consider in optimizing the overall cost of refurbished and remanufactured products.

Keywords: core acquisition, end of life, reverse logistics, quality uncertainty

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Authors: Xue Wang, Liwei Fan

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Renewable energy technology innovation is an important way to realize the energy transformation. Our government has issued a series of policies to guide and support the development of renewable energy. The implementation of these policies will affect the further development, utilization and technological innovation of renewable energy. In this context, it is of great significance to systematically sort out and evaluate the renewable energy technology innovation policy for improving the existing policy system. Taking the 190 renewable energy technology innovation policies issued during 2005-2021 as a sample, from the perspectives of policy issuing departments and policy keywords, it uses text mining and content analysis methods to analyze the current situation of the policies and conduct a semantic network analysis to identify the core issuing departments and core policy topic words; A PMC (Policy Modeling Consistency) index model is built to quantitatively evaluate the selected policies, analyze the overall pros and cons of the policy through its PMC index, and reflect the PMC value of the model's secondary index The core departments publish policies and the performance of each dimension of the policies related to the core topic headings. The research results show that Renewable energy technology innovation policies focus on synergy between multiple departments, while the distribution of the issuers is uneven in terms of promulgation time; policies related to different topics have their own emphasis in terms of policy types, fields, functions, and support measures, but It still needs to be improved, such as the lack of policy forecasting and supervision functions, the lack of attention to product promotion, and the relatively single support measures. Finally, this research puts forward policy optimization suggestions in terms of promoting joint policy release, strengthening policy coherence and timeliness, enhancing the comprehensiveness of policy functions, and enriching incentive measures for renewable energy technology innovation.

Keywords: renewable energy technology innovation, content analysis, policy evaluation, PMC index model

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Authors: Rohini Hariharan, Yazhini R, Bhamidipati Naga Shrikarti

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In the realm of cricket, particularly within the context of the Indian Premier League (IPL), the ability to predict team scores accurately holds significant importance for both cricket enthusiasts and stakeholders alike. This paper presents a comprehensive study on IPL score prediction utilizing various machine learning algorithms, including Support Vector Machines (SVM), XGBoost, Multiple Regression, Linear Regression, K-nearest neighbors (KNN), and Random Forest. Through meticulous data preprocessing, feature engineering, and model selection, we aimed to develop a robust predictive framework capable of forecasting team scores with high precision. Our experimentation involved the analysis of historical IPL match data encompassing diverse match and player statistics. Leveraging this data, we employed state-of-the-art machine learning techniques to train and evaluate the performance of each model. Notably, Multiple Regression emerged as the top-performing algorithm, achieving an impressive accuracy of 77.19% and a precision of 54.05% (within a threshold of +/- 10 runs). This research contributes to the advancement of sports analytics by demonstrating the efficacy of machine learning in predicting IPL team scores. The findings underscore the potential of advanced predictive modeling techniques to provide valuable insights for cricket enthusiasts, team management, and betting agencies. Additionally, this study serves as a benchmark for future research endeavors aimed at enhancing the accuracy and interpretability of IPL score prediction models.

Keywords: indian premier league (IPL), cricket, score prediction, machine learning, support vector machines (SVM), xgboost, multiple regression, linear regression, k-nearest neighbors (KNN), random forest, sports analytics

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Authors: Ahmed A. Lugard, Mohammed A. Aliyu

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This paper studied the influence of urban development and its accompanied land surface transformation on sediment concentration of a natural flowing Ginzo river across the city of Katsina. An opposite twin river known as Tille river, which is less urbanized, was used to compare the result of the sediment concentration of the Ginzo River in order to ascertain the consequences of the urban area on impacting the sediment concentration. An instrument called USP 61 point integrating cable way sampler described by Gregory and walling (1973), was used to collect the suspended sediment samples in the wet season months of June, July, August and September. The result obtained in the study shows that only the sample collected at the peripheral site of the city, which is mostly farmland areas resembles the results in the four sites of Tille river, which is the reference stream in the study. It was found to be only + 10% different from one another, while at the other three sites of the Ginzo which are highly urbanized the disparity ranges from 35-45% less than what are obtained at the four sites of Tille River. In the generalized assessment, the t-distribution result applied to the two set of data shows that there is a significant difference between the sediment concentration of urbanized River Ginzo and that of less urbanized River Tille. The study further discovered that the less sediment concentration found in urbanized River Ginzo is attributed to concretization of surfaced, tarred roads, concretized channeling of segments of the river including the river bed and reserved open grassland areas, all within the catchments. The study therefore concludes that urbanization affect not only the hydrology of an urbanized river basin, but also the sediment concentration which is a significant aspect of its geomorphology. This world certainly affects the flood plain of the basin at a certain point which might be a suitable land for cultivation. It is recommended here that further studies on the impact of urbanization on River Basins should focus on all elements of geomorphology as it has been on hydrology. This would make the work rather complete as the two disciplines are inseparable from each other. The authorities concern should also trigger a more proper environmental and land use management policies to arrest the menace of land degradation and related episodic events.

Keywords: environment, infiltration, river, urbanization

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Authors: James Ladzekpo

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Background: The urgent need to identify new pharmacological targets for diabetes treatment and prevention has been amplified by the disease's extensive impact on individuals and healthcare systems. A deeper insight into the biological underpinnings of diabetes is crucial for the creation of therapeutic strategies aimed at these biological processes. Current predictive models based on genetic variations fall short of accurately forecasting diabetes. Objectives: Our study aims to pinpoint key epigenetic factors that predispose individuals to diabetes. These factors will inform the development of an advanced predictive model that estimates diabetes risk from genetic profiles, utilizing state-of-the-art statistical and data mining methods. Methodology: We have implemented a recursive feature elimination with cross-validation using the support vector machine (SVM) approach for refined feature selection. Building on this, we developed six machine learning models, including logistic regression, k-Nearest Neighbors (k-NN), Naive Bayes, Random Forest, Gradient Boosting, and Multilayer Perceptron Neural Network, to evaluate their performance. Findings: The Gradient Boosting Classifier excelled, achieving a median recall of 92.17% and outstanding metrics such as area under the receiver operating characteristics curve (AUC) with a median of 68%, alongside median accuracy and precision scores of 76%. Through our machine learning analysis, we identified 31 genes significantly associated with diabetes traits, highlighting their potential as biomarkers and targets for diabetes management strategies. Conclusion: Particularly noteworthy were the Gradient Boosting Classifier and Multilayer Perceptron Neural Network, which demonstrated potential in diabetes outcome prediction. We recommend future investigations to incorporate larger cohorts and a wider array of predictive variables to enhance the models' predictive capabilities.

Keywords: diabetes, machine learning, prediction, biomarkers

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Authors: A. Terfous, Y. Liu, A. Ghenaim, P. A. Garambois

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With increasing urbanization worldwide, it is crucial to sustainably manage sediment flows in urban networks and especially in stormwater detention basins. One key aspect is to propose optimized designs for detention tanks in order to best reduce flood peak flows and in the meantime settle particles. It is, therefore, necessary to understand complex flows patterns and sediment deposition conditions in stormwater detention basins. The aim of this paper is to study flow structure and particle deposition pattern for a given tank geometry in view to control and maximize sediment deposition. Both numerical simulation and experimental works were done to investigate the flow and sediment distribution in a storm tank with a cavity. As it can be indicated, the settle distribution of the particle in a rectangular tank is mainly determined by the flow patterns and the bed shear stress. The flow patterns in a rectangular tank differ with different geometry, entrance flow rate and the water depth. With the changing of flow patterns, the bed shear stress will change respectively, which also play an influence on the particle settling. The accumulation of the particle in the bed changes the conditions at the bottom, which is ignored in the investigations, however it worth much more attention, the influence of the accumulation of the particle on the sedimentation should be important. The approach presented here is based on the resolution of the Reynolds averaged Navier-Stokes equations to account for turbulent effects and also a passive particle transport model. An analysis of particle deposition conditions is presented in this paper in terms of flow velocities and turbulence patterns. Then sediment deposition zones are presented thanks to the modeling with particle tracking method. It is shown that two recirculation zones seem to significantly influence sediment deposition. Due to the possible overestimation of particle trap efficiency with standard wall functions and stick conditions, further investigations seem required for basal boundary conditions based on turbulent kinetic energy and shear stress. These observations are confirmed by experimental investigations processed in the laboratory.

Keywords: storm sewers, sediment deposition, numerical simulation, experimental investigation

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Authors: Muhammad Nouman, Fahad Tiwana, Muhammad Irfan, Mohsin Tiwana

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Traffic congestion has been increasing significantly in major metropolitan areas as a result of increased motorization, urbanization, population growth and changes in the urban density. Traffic congestion compromises efficiency of transport infrastructure and causes multiple traffic concerns; including but not limited to increase of travel time, safety hazards, air pollution, and fuel consumption. Traffic management has become a serious challenge for federal and provincial governments, as well as exasperated commuters. Effective, flexible, efficient and user-friendly traffic information/database management systems characterize traffic conditions by making use of traffic counts for storage, processing, and visualization. While, the emerging data collection technologies continue to proliferate, its accuracy can be guaranteed through the comparison of observed data with the manual handheld counters. This paper presents the design of tablet based manual traffic counting application and framework for development of traffic database management system for Pakistan. The database management system comprises of three components including traffic counting android application; establishing online database and its visualization using Google maps. Oracle relational database was chosen to develop the data structure whereas structured query language (SQL) was adopted to program the system architecture. The GIS application links the data from the database and projects it onto a dynamic map for traffic conditions visualization. The traffic counting device and example of a database application in the real-world problem provided a creative outlet to visualize the uses and advantages of a database management system in real time. Also, traffic data counts by means of handheld tablet/ mobile application can be used for transportation planning and forecasting.

Keywords: manual count, emerging data sources, traffic information quality, traffic surveillance, traffic counting device, android; data visualization, traffic management

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Authors: Mohammed Seyam, Faridah Othman, Ahmed El-Shafie

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The early warning of high stream flow events (HSF) and floods is an important aspect in the management of surface water and rivers systems. This process can be performed using either process-based models or data driven-based models such as artificial intelligence (AI) techniques. The main goal of this study is to develop efficient AI-based model for predicting the real-time hourly stream flow (Q) and apply it as early warning tool of HSF and floods in the downstream area of the Selangor River basin, taken here as a paradigm of humid tropical rivers in Southeast Asia. The performance of AI-based models has been improved through the integration of the lag time (Lt) estimation in the modelling process. A total of 8753 patterns of Q, water level, and rainfall hourly records representing one-year period (2011) were utilized in the modelling process. Six hydrological scenarios have been arranged through hypothetical cases of input variables to investigate how the changes in RF intensity in upstream stations can lead formation of floods. The initial SF was changed for each scenario in order to include wide range of hydrological situations in this study. The performance evaluation of the developed AI-based model shows that high correlation coefficient (R) between the observed and predicted Q is achieved. The AI-based model has been successfully employed in early warning throughout the advance detection of the hydrological conditions that could lead to formations of floods and HSF, where represented by three levels of severity (i.e., alert, warning, and danger). Based on the results of the scenarios, reaching the danger level in the downstream area required high RF intensity in at least two upstream areas. According to results of applications, it can be concluded that AI-based models are beneficial tools to the local authorities for flood control and awareness.

Keywords: floods, stream flow, hydrological modelling, hydrology, artificial intelligence

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Authors: Emily Injete Amondo, Alisher Mirzabaev, Emmanuel Rukundo

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Children in rural farming households are often vulnerable to a multitude of risks, including health risks associated with climate change and variability. Cognizant of this, this study empirically traced the relationship between climate variability and nutritional health outcomes in rural children while identifying the cause-and-effect transmission mechanisms. We combined four waves of the rich Uganda National Panel Survey (UNPS), part of the World Bank Living Standards Measurement Studies (LSMS) for the period 2009-2014, with long-term and high-frequency rainfall and temperature datasets. Self-reported drought and flood shock variables were further used in separate regressions for triangulation purposes and robustness checks. Panel fixed effects regressions were applied in the empirical analysis, accounting for a variety of causal identification issues. The results showed significant negative outcomes for children’s anthropometric measurements due to the impacts of moderate and extreme droughts, extreme wet spells, and heatwaves. On the contrary, moderate wet spells were positively linked with nutritional measures. Agricultural production and child diarrhea were the main transmission channels, with heatwaves, droughts, and high rainfall variability negatively affecting crop output. The probability of diarrhea was positively related to increases in temperature and dry spells. Results further revealed that children in households who engaged in ex-ante or anticipatory risk-reducing strategies such as savings had better health outcomes as opposed to those engaged in ex-post coping such as involuntary change of diet. These results highlight the importance of adaptation in smoothing the harmful effects of climate variability on the health of rural households and children in Uganda.

Keywords: extreme weather events, undernutrition, diarrhea, agricultural production, gridded weather data

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Authors: Md Y. Reja, Samuel D. Brody, Wesley E. Highfield, Galen D. Newman

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Historically, wetlands in the United States have been lost due to agriculture, anthropogenic activities, and rapid urbanization along the coast. Such losses of wetlands have resulted in high flooding risk for coastal communities over the period of time. In addition, alteration of wetlands via the Section 404 Clean Water Act permits can increase the flooding risk to future hurricane events, as the cumulative impact of this program is poorly understood and under-accounted. Further, recovery after hurricane events is acting as an encouragement for new development and reconstruction activities by converting wetlands under the wetland alteration permitting program. This study investigates the degree to which hurricane recovery activities in coastal communities are undermining the ability of these places to absorb the impacts of future storm events. Specifically, this work explores how and to what extent wetlands are being affected by the federal permitting program post-Hurricane Ike in 2008. Wetland alteration patterns are examined across three counties (Harris, Galveston, and Chambers County) along the Texas Gulf Coast over a 10-year time period, from 2004-2013 (five years before and after Hurricane Ike) by conducting descriptive spatial analyses. Results indicate that after Hurricane Ike, the number of permits substantially increased in Harris and Chambers County. The vast majority of individual and nationwide type permits were issued within the 100-year floodplain, storm surge zones, and areas damaged by Ike flooding, suggesting that recovery after the hurricane is compromising the ecological resiliency on which coastal communities depend. The authors expect that the findings of this study can increase awareness to policy makers and hazard mitigation planners regarding how to manage wetlands during a long-term recovery process to maintain their natural functions for future flood mitigation.

Keywords: ecological resiliency, Hurricane Ike, recovery, Section 404 Permitting, wetland alteration

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Authors: M. Varin, A. M. Dubois, R. Gadbois-Langevin, B. Chalghaf

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Good knowledge of the physical environment is essential for an integrated forest planning. This information enables better forecasting of operating costs, determination of cutting volumes, and preservation of ecologically sensitive areas. The use of satellite images in stereoscopic pairs gives the capacity to generate high precision 3D models, which are scale-adapted for harvesting operations. These models could represent an alternative to 3D LiDAR data, thanks to their advantageous cost of acquisition. The objective of the study was to assess the quality of stereo-derived canopy height models (CHM) in comparison to a traditional LiDAR CHM and ground tree-height samples. Two study sites harboring two different forest stand types (broadleaf and conifer) were analyzed using stereo pairs and tri-stereo images from the WorldView-3 satellite to calculate CHM. Acquisition of multispectral images from an Unmanned Aerial Vehicle (UAV) was also realized on a smaller part of the broadleaf study site. Different algorithms using two softwares (PCI Geomatica and Correlator3D) with various spatial resolutions and band selections were tested to select the 3D modeling technique, which offered the best performance when compared with LiDAR. In the conifer study site, the CHM produced with Corelator3D using only the 50-cm resolution panchromatic band was the one with the smallest Root-mean-square deviation (RMSE: 1.31 m). In the broadleaf study site, the tri-stereo model provided slightly better performance, with an RMSE of 1.2 m. The tri-stereo model was also compared to the UAV, which resulted in an RMSE of 1.3 m. At individual tree level, when ground samples were compared to satellite, lidar, and UAV CHM, RMSE were 2.8, 2.0, and 2.0 m, respectively. Advanced analysis was done for all of these cases, and it has been noted that RMSE is reduced when the canopy cover is higher when shadow and slopes are lower and when clouds are distant from the analyzed site.

Keywords: very high spatial resolution, satellite imagery, WorlView-3, canopy height models, CHM, LiDAR, unmanned aerial vehicle, UAV

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Authors: Zhuo Feng, Ying Gao

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Public-private partnership (PPP), as an innovative way to provide infrastructures by the private sector, is being widely used throughout the world. Compared with the traditional mode, PPP emerges largely for merits of relieving public budget constraint and improving infrastructure supply efficiency by involving private funds. However, PPP projects are characterized by large scale, high investment, long payback period, and long concession period. These characteristics make PPP projects full of risks. One of the most important risks faced by the private sector is demand risk because many factors affect the real demand. If the real demand is far lower than the forecasting demand, the private sector will be got into big trouble because operating revenue is the main means for the private sector to recoup the investment and obtain profit. Therefore, it is important to study how the government compensates the private sector when the demand risk occurs in order to achieve Pareto-improvement. This research focuses on price compensation mechanism, an ex-post compensation mechanism, and analyzes, by mathematical modeling, the impact of price compensation mechanism on payoff of the private sector and consumer surplus for PPP toll road projects. This research first investigates whether or not price compensation mechanisms can obtain Pareto-improvement and, if so, then explores boundary conditions for this mechanism. The research results show that price compensation mechanism can realize Pareto-improvement under certain conditions. Especially, to make the price compensation mechanism accomplish Pareto-improvement, renegotiation costs of the government and the private sector should be lower than a certain threshold which is determined by marginal operating cost and distortionary cost of the tax. In addition, the compensation percentage should match with the price cut of the private investor when demand drops. This research aims to provide theoretical support for the government when determining compensation scope under the price compensation mechanism. Moreover, some policy implications can also be drawn from the analysis for better risk-sharing and sustainability of PPP projects.

Keywords: infrastructure, price compensation mechanism, public-private partnership, renegotiation

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Authors: Taha Benarbia

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The advent of automated and connected vehicles has revolutionized the transportation industry, presenting new opportunities for enhancing the efficiency, safety, and sustainability of our transportation networks. This paper explores the integration of automated and connected vehicles into a smart transportation framework, leveraging the power of deep learning techniques to optimize the overall network performance. The first aspect addressed in this paper is the deployment of automated vehicles (AVs) within the transportation system. AVs offer numerous advantages, such as reduced congestion, improved fuel efficiency, and increased safety through advanced sensing and decisionmaking capabilities. The paper delves into the technical aspects of AVs, including their perception, planning, and control systems, highlighting the role of deep learning algorithms in enabling intelligent and reliable AV operations. Furthermore, the paper investigates the potential of connected vehicles (CVs) in creating a seamless communication network between vehicles, infrastructure, and traffic management systems. By harnessing real-time data exchange, CVs enable proactive traffic management, adaptive signal control, and effective route planning. Deep learning techniques play a pivotal role in extracting meaningful insights from the vast amount of data generated by CVs, empowering transportation authorities to make informed decisions for optimizing network performance. The integration of deep learning with automated and connected vehicles paves the way for advanced transportation network optimization. Deep learning algorithms can analyze complex transportation data, including traffic patterns, demand forecasting, and dynamic congestion scenarios, to optimize routing, reduce travel times, and enhance overall system efficiency. The paper presents case studies and simulations demonstrating the effectiveness of deep learning-based approaches in achieving significant improvements in network performance metrics

Keywords: automated vehicles, connected vehicles, deep learning, smart transportation network

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Authors: Renee Yi-Mond Yuan

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The fast development of tourism industries around the world, has largely contributed to many cities, and countries economical and social progress. Past year Taiwan in particular was ranked among one of fastest raise growth country. Thanks to the prominent importance of this phenomenon; seasonal mobility or multipurpose trips have reached more than 1 Billion tourists crossing International borders and more than 4 billion intramural travelers that have nourished the economy and employment in the service sector in most attractive regions, representing about one tenth of World GDP amount, including trade, research, cultural or journalistic purposes. Then the increased activities are giving pressure to the consumption of energy, water, resources, and Greenhouse Gas emissions. The further concentration of tourists in most beautiful sites of the World with consistent supply and reduced pollutions and means for waste control and risks management are challenging the preservation and protection of the natural original environment, including species and their ecosystems, ethnics and their cultures or languages, protection of inherited landscapes and monuments for the future generations to come. In this article, few projects will be analyzed, methods and directions in the EU sustainable development scheme giving way to economical and social activities and preserve rural areas and remote countryside as well as smarter cities development. EU ETS forecasting escalation in the next few decades for road and air, and will reconsider investments and reliance on Biobased alternatives that may turn out solutions and contributions to sustain popularization of tourism development. Study of Examples of Stakeholders practices and Governments efforts, consumer’s attitude to bring new forms of more responsible holidays models: ecotourism, eco-certification, partnerships, investment in technologies and facilities, and possibly create greener perceptions and less impacting demands for the longer term through association, organizations and awards.

Keywords: tourism, sustainability, protection, risks management, change in rural/urban environment

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Authors: Simone Tedeschi, Francesco Crespi, Paolo Liberati, Massimo Paradiso, Antonio Sciala

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This paper aims at contributing to the understanding of smokers’ responses to cigarette prices increases with a focus on heterogeneity, both across individuals and price levels. To do this, a stated preference quasi-experimental design grounded in a random utility framework is proposed to evaluate the effect on smokers’ utility of the price level and variation, along with social conditioning and health impact perception. The analysis is based on individual-level data drawn from a unique survey gathering very detailed information on Italian smokers’ habits. In particular, qualitative information on the individual reactions triggered by changes in prices of different magnitude and composition are exploited. The main findings stemming from the analysis are the following; the average price elasticity of cigarette consumption is comparable with previous estimates for advanced economies (-.32). However, the decomposition of this result across five latent-classes of smokers, reveals extreme heterogeneity in terms of price responsiveness, implying a potential price elasticity that ranges between 0.05 to almost 1. Such heterogeneity is in part explained by observable characteristics such as age, income, gender, education as well as (current and lagged) smoking intensity. Moreover, price responsiveness is far from being independent from the size of the prospected price increase. Finally, by comparing even and uneven price variations, it is shown that uniform across-brand price increases are able to limit the scope of product substitutions and downgrade. Estimated price-response heterogeneity has significant implications for tax policy. Among them, first, it provides evidence and a rationale for why the aggregate price elasticity is likely to follow a strictly increasing pattern as a function of the experienced price variation. This information is crucial for forecasting the effect of a given tax-driven price change on tax revenue. Second, it provides some guidance on how to design excise tax reforms to balance public health and revenue goals.

Keywords: smoking behaviour, preference heterogeneity, price responsiveness, cigarette taxation, random utility models

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Authors: Mostafa Zandi, Ramin Mansouri

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Spillways are one of the most important hydraulic structures of dams that provide the stability of the dam and downstream areas at the time of flood. Morning-Glory spillway is one of the common spillways for discharging the overflow water behind dams, these kinds of spillways are constructed in dams with small reservoirs. In this research, the hydraulic flow characteristics of a morning-glory spillways are investigated with CFD model. Two dimensional unsteady RANS equations were solved numerically using Finite Volume Method. The PISO scheme was applied for the velocity-pressure coupling. The mostly used two-equation turbulence models, k- and k-, were chosen to model Reynolds shear stress term. The power law scheme was used for discretization of momentum, k , and  equations. The VOF method (geometrically reconstruction algorithm) was adopted for interface simulation. The results show that the fine computational grid, the input speed condition for the flow input boundary, and the output pressure for the boundaries that are in contact with the air provide the best possible results. Also, the standard wall function is chosen for the effect of the wall function, and the turbulent model k -ε (Standard) has the most consistent results with experimental results. When the jet is getting closer to end of basin, the computational results increase with the numerical results of their differences. The lower profile of the water jet has less sensitivity to the hydraulic jet profile than the hydraulic jet profile. In the pressure test, it was also found that the results show that the numerical values of the pressure in the lower landing number differ greatly in experimental results. The characteristics of the complex flows over a Morning-Glory spillway were studied numerically using a RANS solver. Grid study showed that numerical results of a 57512-node grid had the best agreement with the experimental values. The desired downstream channel length was preferred to be 1.5 meter, and the standard k-ε turbulence model produced the best results in Morning-Glory spillway. The numerical free-surface profiles followed the theoretical equations very well.

Keywords: morning-glory spillway, CFD model, hydraulic characteristics, wall function

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Authors: Bharat Sapkota

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Nepal is the one of the victim country of climate change. Decreasing snow line, sometimes higher and sometime non-rain fall are common phenomena in hill area. Natural flood disaster and drought is also common every year in certain place of the country. So this paper analyze the effect of climate and natural water sources for sustainability of water sanitation and hygiene of Tanahun district. It is one of the Rural Water Supply and Sanitation Project Western Nepal Phase-II (RWSSP-WN Phase-II) project district out of 14 project districts of western and mid-western Nepal. RWSSP-WN II is a bilateral development cooperation of governments of Nepal and Finland. Big investment is still going on in water sanitation and hygiene sector but sustainability is still a challenge throughout the country. So RWSSP-WN has started the strengthen of the capacity of local Governments to deliver services in water supply, sanitation and hygiene and its sustainability through the implementation of cross cutting approach of climate change and disaster risk reduction. The study shows that the average yield in 685 natural point sources were around 0.045 l/s in 2014 but it was twice as high in 2004 i.e. 0.09 l/s. The maximum measured yield in 2014 was 1.87 l/s, whereas, the maximum yield was 3 l/s in 2004. Likewise, spring source mean and maximum yield measured in 2014 were 0.16 l/s and 3.33 l/s respectively, whereas, mean and maximum yields in 2004 were 0.204 l/s and 3 l/s respectively. Small streams average yield measured in 2014 was 0.32 l/s with the maximum of around 4.99 l/s. In 2004, mean and maximum yields of streams were 0.485 l/s and 5 l/s respectively. The overall climate between years 2002 to 2013 and measured yield data between 2004 and 2014 shows climate as one of the causes of water source decline. The temperature is rising with pace of 0.041°C per year and rainfall is decreased by 16.8 mm/year. The Khosla’s empirical formula shows decrease of 1.7 cm/year in runoff. At present sustainability of water, sanitation and hygiene is more challenge due to sources decreasing in the district. Sanitation and hygiene total behavior change and watershed conservation as well as design and implementation of recharge pound construction are the way forward of sustainability of water, sanitation and hygiene.

Keywords: water sanitation, hygiene, sustainability, climate change

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Authors: Zeynep Yazicioglu

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Project development is a complex process where many stakeholders work together. Employers and main contractors are the base stakeholders, whereas designers, engineers, sub-contractors, suppliers, supervisors, and consultants are other stakeholders. A combination of the complexity of the building process with a large number of stakeholders often leads to time and cost overruns and irregular resource utilization. Failure to comply with the work schedule and inefficient use of resources in the construction processes indicate that it is necessary to accelerate production and increase productivity. The development of computer software called Building Information Modeling, abbreviated as BIM, is a major technological breakthrough in this area. The use of BIM enables architectural, structural, mechanical, and electrical projects to be drawn in coordination. BIM is a tool that should be considered by every stakeholder with the opportunities it offers, such as minimizing construction errors, reducing construction time, forecasting, and determination of the final construction cost. It is a process spreading over the years, enabling all stakeholders associated with the project and construction to use it. The main goal of this paper is to explore the problems associated with the adoption of BIM in multi-stakeholder projects. The paper is a conceptual study, summarizing the author’s practical experience with design offices and construction firms working with BIM. In the transition period to BIM, three of the challenges will be examined in this paper: 1. The compatibility of supplier companies with BIM, 2. The need for two-dimensional drawings, 3. Contractual issues related to BIM. The paper reviews the literature on BIM usage and reviews the challenges in the transition stage to BIM. Even on an international scale, the supplier that can work in harmony with BIM is not very common, which means that BIM's transition is continuing. In parallel, employers, local approval authorities, and material suppliers still need a 2-D drawing. In the BIM environment, different stakeholders can work on the same project simultaneously, giving rise to design ownership issues. Practical applications and problems encountered are also discussed, providing a number of suggestions for the future.

Keywords: BIM opportunities, collaboration, contract issues about BIM, stakeholders of project

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Authors: Ziaullah, Shah Wahab Ali

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Micro-grid equipped with heterogeneous energy resources present the idea of small scale distributed energy management (DEM). DEM helps in minimizing the transmission and operation costs, power management and peak load demands. Micro-grids are collections of small, independent controllable power-generating units and renewable energy resources. Micro-grids also motivate to enable active customer participation by giving accessibility of real-time information and control to the customer. The capability of fast restoration against faulty situation, integration of renewable energy resources and Information and Communication Technologies (ICT) make micro-grid as an ideal system for distributed power systems. Micro-grids can have a bank of energy storage devices. The energy management system of micro-grid can perform real-time energy forecasting of renewable resources, energy storage elements and controllable loads in making proper short-term scheduling to minimize total operating costs. We present a review of existing micro-grids optimization objectives/goals, constraints, solution approaches and tools used in micro-grids for energy management. Cost-benefit analysis of micro-grid reveals that cooperation among different micro-grids can play a vital role in the reduction of import energy cost and system stability. Cooperative micro-grids energy trading is an approach to electrical distribution energy resources that allows local energy demands more control over the optimization of power resources and uses. Cooperation among different micro-grids brings the interconnectivity and power trading issues. According to the literature, it shows that open area of research is available for cooperative micro-grids energy trading. In this paper, we proposed and formulated the efficient energy management/trading module for interconnected micro-grids. It is believed that this research will open new directions in future for energy trading in cooperative micro-grids/interconnected micro-grids.

Keywords: distributed energy management, information and communication technologies, microgrid, energy management

Procedia PDF Downloads 357

Authors: Frederico Fialho Teixeira, Islam Mashaly, Maryam Shafiei, Jurij Karlovsek

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The ubiquity of data gathering and smart technologies, advancements in virtual technologies, and the development of the internet of things (IoT) have created urgent demands for the development of frameworks and efficient workflows for data collection, visualisation, and analysis. Digital twin, in different scales of the city into the building, allows for bringing together data from different sources to generate fundamental and illuminating insights for the management of current facilities and the lifecycle of amenities as well as improvement of the performance of current and future designs. Over the past two decades, there has been growing interest in the topic of digital twin and their applications in city and building scales. Most such studies look at the urban environment through a homogeneous or generalist lens and lack specificity in particular characteristics or identities, which define an urban university campus. Bridging this knowledge gap, this paper offers a framework for developing a digital twin for a university campus that, with some modifications, could provide insights for any large-scale digital twin settings like towns and cities. It showcases how currently unused data could be purposefully combined, interpolated and visualised for producing analysis-ready data (such as flood or energy simulations or functional and occupancy maps), highlighting the potential applications of such a framework for campus planning and policymaking. The research integrates campus-level data layers into one spatial information repository and casts light on critical data clusters for the digital twin at the campus level. The paper also seeks to raise insightful and directive questions on how digital twin for campus can be extrapolated to city-scale digital twin. The outcomes of the paper, thus, inform future projects for the development of large-scale digital twin as well as urban and architectural researchers on potential applications of digital twin in future design, management, and sustainable planning, to predict problems, calculate risks, decrease management costs, and improve performance.

Keywords: digital twin, smart campus, framework, data collection, point cloud

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Authors: Flavia Cordeiro, Fabio Silva, Alvaro Eiras, Jose Luiz Acebal

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Aedes aegypti is present in the tropical and subtropical regions of the world and is a vector of several diseases such as dengue fever, yellow fever, chikungunya, zika etc. The growth in the number of arboviruses cases in the last decades became a matter of great concern worldwide. Meteorological factors like mean temperature and precipitation are known to influence the infestation by the species through effects on physiology and ecology, altering the fecundity, mortality, lifespan, dispersion behaviour and abundance of the vector. Models able to describe the dynamics of the vector population size should then take into account the meteorological variables. The relationship between meteorological factors and the population dynamics of Ae. aegypti adult females are studied to provide a good set of predictors to model the dynamics of the mosquito population size. The time-series data of capture of adult females of a public health surveillance program from the city of Lavras, MG, Brazil had its association with precipitation, humidity and temperature analysed through a set of statistical methods for time series analysis commonly adopted in Signal Processing, Information Theory and Neuroscience. Cross-correlation, multicollinearity test and whitened cross-correlation were applied to determine in which time lags would occur the influence of meteorological variables on the dynamics of the mosquito abundance. Among the findings, the studied case indicated strong collinearity between humidity and precipitation, and precipitation was selected to form a pair of descriptors together with temperature. In the techniques used, there were observed significant associations between infestation indicators and both temperature and precipitation in short, mid and long terms, evincing that those variables should be considered in entomological models and as public health indicators. A descriptive model used to test the results exhibits a strong correlation to data.

Keywords: Aedes aegypti, cross-correlation, multicollinearity, meteorological variables

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Authors: Bhawesh Kumar, A. P. Krishna

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There are continuous changes upon earth’s surface by a variety of natural and anthropogenic agents cut, carry away and depositing of minerals from land. Running water has higher capacity of erosion than other geomorphologic agents. This research work has been carried out on Ganga River, whose channel is continuously changing under the influence of geomorphic agents and human activities in the surrounding regions. The main focus is to study morphological characteristics and sand dynamics of Ganga River with particular emphasis on bank lines and width changes using remote sensing and GIS techniques. The advance remote sensing data and topographical data were interpreted for obtaining 52 years of changes. For this, remote sensing data of different years (LANDSAT TM 1975, 1988, 1993, ETM 2005 and ETM 2012) and toposheet of SOI for the year 1960 were used as base maps for this study. Sinuosity ratio, braiding index and migratory activity index were also established. It was found to be 1.16 in 1975 and in 1988, 1993, 2005 and 2005 it was 1.09, 1.11, 1.1, 1.09 respectively. The analysis also shows that the minimum value found in 1960 was in reach 1 and maximum value is 4.8806 in 2012 found in reach 4 which suggests creation of number of islands in reach 4 for the year 2012. Migratory activity index (MAI), which is a standardized function of both length and time, was computed for the 8 representative reaches. MAI shows that maximum migration was in 1975-1988 in reach 6 and 7 and minimum migration was in 1993-2005. From the channel change analysis, it was found that the shifting of bank line was cyclic and the river Ganges showed a trend of southward maximum values. The advanced remote sensing data and topographical data helped in obtaining 52 years changes in the river due to various natural and manmade activities like flood, water velocity and excavation, removal of vegetation cover and fertile soil excavation for the various purposes of surrounding regions.

Keywords: braided index, migratory activity index (MAI), Ganga river, river morphology

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Authors: Sulaiman Al-Hinai, Setyawan Widyarto

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The aim of this study is to identify the critically dominating factors on the delays of road constructions in the GCC countries and their effects on project delivery in Arab countries. Towards the achieved of the objectives the study used the empirical literature from the all relevant online sources and database as many as possible. The findings of this study have summarized and short listed of the success factors in the two categories such as internal and external factors have caused to be influenced to delay of road constructions in the Arab regions. However, in the category of internal factors, there are 63 factors short listed from seven group of factors which has revealed to effects on the delay of road constructions especially, the consultant related factors, the contractor related factors, designed related factors, client related factors, labor related factors, material related issues, equipment related issues respectively. Moreover, for external related factors are also considered to summarized especially natural disaster (flood, hurricanes and cyclone etc.), conflict, war, global financial crisis, compensation delay to affected property owner, price fluctuated, unexpected ground conditions (soil and high-water level), changing of government regulations and laws, delays in obtaining permission from municipality, loss of time by traffic control and restrictions at job site, problem with inhabitant of community, delays in providing service from utilities (water and electricity’s) and accident during constructions accordingly. The present study also concluded the effects of above factors which has delay road constructions through increasing of cost and overrun it, taken overtime, creating of disputes, going for lawsuits, finally happening of abandon of projects. Thus, the present study has given the following recommendations to overcome of above problems by increasing of detailed site investigations, ensure careful monitoring and regular meetings, effective site management, collaborative working and effective coordination’s, proper and comprehensive planning and scheduling and ensure full and intensive commitment from all parties accordingly.

Keywords: Arab GCC countries, critical success factors, road constructions delay, project management

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Authors: Ouabo Emmanuel Romaric, Amougou Armathe

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Background and aim: The study of impacts of floods and landslides at a small scale, specifically in the urban areas of developing countries is done to provide tools and actors for a better management of risks in such areas, which are now being affected by climate change. The main objective of this study is to assess the hydrometeorological vulnerabilities associated with flooding and urban landslides to propose adaptation measures. Methods: Climatic data analyses were done by calculation of indices of climate change within 50 years (1960-2012). Analyses of field data to determine causes, the level of risk and its consequences on the area of study was carried out using SPSS 18 software. The cartographic analysis and GIS were used to refine the work in space. Then, spatial and terrain analyses were carried out to determine the morphology of field in relation with floods and landslide, and the diffusion on the field. Results: The interannual changes in precipitation has highlighted the surplus years (21), the deficit years (24) and normal years (7). Barakat method bring out evolution of precipitation by jerks and jumps. Floods and landslides are correlated to high precipitation during surplus and normal years. Data field analyses show that populations are conscious (78%) of the risks with 74% of them exposed, but their capacities of adaptation is very low (51%). Floods are the main risk. The soils are classed as feralitic (80%), hydromorphic (15%) and raw mineral (5%). Slope variation (5% to 15%) of small hills and deep valley with anarchic construction favor flood and landslide during heavy precipitation. Mismanagement of waste produce blocks free circulation of river and accentuate floods. Conclusion: Vulnerability of population to hydrometeorological risks in Yaoundé VI is the combination of variation of parameters like precipitation, temperature due to climate change, and the bad planning of construction in urban areas. Because of lack of channels for water to circulate due to saturation of soils, the increase of heavy precipitation and mismanagement of waste, the result are floods and landslides which causes many damages on goods and people.

Keywords: climate change, floods, hydrometeorological, vulnerability

Procedia PDF Downloads 447