Search results for: flood mitigation

Authors: Hadjer Didouh, Mohammed Hadj Melliani, Izzeddine Sameut Bouhaik

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Corrosion is a serious problem in industrial installations or metallic transport pipes. Corrosion is an interfacial process controlled by several parameters. The presence of microorganisms affects the kinetics of corrosion. This type of corrosion is often referred to as bio-corrosion or corrosion influenced by microorganisms (MIC). The action of a microorganism or a bacterium is carried out by the formation of biofilm following its attachment to the metal surface. The formation of biofilm isolates the metal surface from its environment and allows the bacteria to control the parameters of the metal/bacteria interface. Biofilm formation by sulfate-reducing bacteria (SRB) X52 steel poses substantial challenges in the oil and gas industry SONATRACH of Algeria. This research delves into the complex attachment mechanisms employed by SRB biofilm on X52 carbon steel and investigates innovative strategies for effective mitigation using biocides. The exploration commences by elucidating the underlying mechanisms facilitating SRB biofilm adhesion to X52 carbon steel, considering factors such as surface morphology, electrostatic interactions, and microbial extracellular substances. Advanced microscopy and spectroscopic techniques provide support to the attachment processes, laying the foundation for targeted mitigation strategies. The use of 100 ppm of Moringa Oleifera extract biocide as a promising approach to control and prevent SRB biofilm formation on X52 carbon steel surfaces. Green extracts undergo evaluation for their effectiveness in disrupting biofilm development while ensuring the integrity of the steel substrate. Systematic analysis is conducted on the biocide's impact on the biofilm's structural integrity, microbial viability, and overall attachment strength. This two-pronged investigation aims to deepen our comprehension of SRB biofilm dynamics and contribute to the development of effective strategies for mitigating its impact on X52 carbon steel.

Keywords: attachment, bio-corrosion, biofilm, metal/bacteria interface

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Authors: Manish Khanra, Shashank Prabhu

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The decarbonization of hard-to-abate sectors is currently high on the agenda in the EU and its member states, as these sectors have substantial shares in overall GHG emissions while it is facing serious challenges to decarbonize. In particular, the aviation sector accounts for 2.8% of global anthropogenic CO₂ emissions. These emissions are anticipated to grow dramatically unless immediate mitigating efforts are implemented. Hydrogen and its derivatives based on renewable electricity can have a key role in the transition towards CO₂-neutral flights. The substantial shares of energy carriers in the form of drop-in fuel, direct combustion and Hydrogen-to-Electric are promising in most scenarios towards 2050. For creating appropriate policies to ramp up the production and utilisation of hydrogen commodities in the German aviation sector, a detailed analysis of the spatial distribution of supply-demand sites is essential. The objective of this research work is to assess the demand for hydrogen-based alternative fuels in the German aviation sector to achieve the perceived goal of the ‘Net Zero’ scenario by 2050. Here, the analysis of the technological pathways for the production and utilisation of these fuels in various aircraft options is conducted for reaching mitigation targets. Our method is based on data-driven bottom-up assessment, considering production and demand sites and their spatial distribution. The resulting energy demand and its spatial distribution with consideration of technology diffusion lead to a possible transition pathway of the aviation sector to meet short-term and long-term mitigation targets. Additionally, to achieve mitigation targets in this sector, costs and policy aspects are discussed, which would support decision-makers from airline industries, policymakers and the producers of energy commodities.

Keywords: the aviation sector, hard-to-abate sectors, hydrogen demand, alternative fuels, technological pathways, data-driven approach

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Authors: Sakshi Yadav, Sushila Shekhawat

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This study addresses different types of points of view as seen in nature documentary films with the help of three eco documentaries, and it would be significant in understanding the role of the narrative point of view as a tool for showing and telling in documentaries. Narrative analysis of a film forms an essential aspect of the discourse of scholarship in film studies. Narration is the chain of events occurring in time and space. The notion of narrative provides the idea of coherence and wholeness to the story. There are various components that the narration carries, one of which is the perspective or point of view. The narrator plays the role of a mediator between the film and the audience; thus, his perspective influences the way the audience interprets the film. Feature films have been analyzed through narrative points of view; however, this research intends to conduct it from the angle of a nature documentary film. The study will examine narrative viewpoints unique to nature documentary films using three ecological documentary films-The Cove (2009), Tale of a forest (2012), and Before the flood (2016). This research will apply the framework of narrative theory and will investigate the impact of the different types of narrative points of view, as each portrays the human-nature relationship from a different standpoint, and it will also study the effect that the narrative point of view has on the mode of these eco documentaries.

Keywords: ecodocumentary, narrative, human-nature relationship, point of view

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Authors: Mohammad Saber Eslamlou, Manouchehr Tabibian, Mahta Mirmoghtadaei

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The history of urban development and the increasing complexities of urban life have long been intertwined with different natural and man-made disasters. Sometimes, these unpleasant events have destroyed the cities forever. The growth of the urban population and the increase of social and economic resources in the cities increased the importance of developing a holistic approach to dealing with unknown urban disasters. As a result, the interest in resilience has increased in most of the scientific fields, and the urban planning literature has been enriched with the studies of the social, economic, infrastructural, and physical abilities of the cities. In this regard, different conceptual frameworks and patterns have been developed focusing on dimensions of resilience and different kinds of disasters. As the most frequent and likely natural disaster in Iran is flooding, the present study aims to develop a cause-effect model of urban resilience against flood in Karaj City. In this theoretical study, desk research and documentary studies were used to find the elements and dimensions of urban resilience. In this regard, 6 dimensions and 32 elements were found for urban resilience and a questionnaire was made by considering the requirements of TOPSIS techniques (pairwise comparison). The sample of the research consisted of 10 participants who were faculty members, academicians, board members of research centers, managers of the Ministry of Road and Urban Development, board members of New Towns Development Company, experts, and practitioners of consulting companies who had scientific and research backgrounds. The gathered data in this survey were analyzed using TOPSIS and Shannon Entropy techniques. The results show that Infrastructure/Physical, Social, Organizational/ Institutional, Structural/Physical, Economic, and Environmental dimensions are the most effective factors in urban resilience against floods in Karaj, respectively. Finally, a comprehensive model and a systematic framework of factors that affect the urban resilience of Karaj against floods was developed. This cause – effect model shows how different factors are related and influence each other, based on their connected structure and preferences.

Keywords: urban resilience, TOPSIS, Shannon entropy, cause-effect model of resilience, flood

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Authors: Ahmed A. D. Sarhan, Hong Wan Ping, M. Sayuti

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In this current era of competitive machinery productions, the industries are designed to place more emphasis on the product quality and reduction of cost whilst abiding by the pollution-preventing policy. In attempting to delve into the concerns, the industries are aware that the effectiveness of existing lubrication systems must be improved to achieve power-efficient and pollution-preventing machining processes. As such, this research is targeted to study on a plausible solution to the issue in grinding titanium alloy (Ti-6Al-4V) by using nanolubrication, as an alternative to flood grinding. The aim of this research is to evaluate the optimum condition of grinding force and surface roughness using MQL lubricating system to deliver nano-oil at different level of weight concentration of Silicon Dioxide (SiO2) mixed normal mineral oil. Taguchi Design of Experiment (DoE) method is carried out using a standard Taguchi orthogonal array of L16(43) to find the optimized combination of weight concentration mixture of SiO2, nozzle orientation and pressure of MQL. Surface roughness and grinding force are also analyzed using signal-to-noise(S/N) ratio to determine the best level of each factor that are tested. Consequently, the best combination of parameters is tested for a period of time and the results are compared with conventional grinding method of dry and flood condition. The results show a positive performance of MQL nanolubrication.

Keywords: grinding, MQL, precision grinding, Taguchi optimization, titanium alloy

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Authors: Wisdom Robert Duruji, Moses Kanayochukwu Ifoh, Efeoghene Edward Esiemunobo

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This study examines the impact of natural and artificial disasters, lackadaisical and semantic approach in risk management, and mitigation implication for sustainable development goals in Nigeria, from 2009 to 2022. The study utilizes a range of research methods to achieve its objectives. These include literature review, website knowledge, Google search, news media information, academic journals, field-work and on-site observations. These diverse methods allow for a comprehensive analysis on the impact and the implications being study. The study finds that paradigm shift from remediating seismic, flooding, environmental pollution and degradation natural disasters by Nigeria Emergency Management Agency (NEMA), to political and charity organization; has plunged risk reduction strategies to embezzling opportunities. However, this lackadaisical and semantic approach in natural disaster mitigation, invariably replicates artificial disasters in Nigeria through: Boko Haram terrorist organization, Fulani herdsmen and farmers conflicts, political violence, kidnapping for ransom, ethnic conflicts, Religious dichotomy, insurgency, secession protagonists, unknown-gun-men, and banditry. This study also, finds that some Africans still engage in self-imposed slavery through human trafficking, by nefariously stow-away to Europe; through Libya, Sahara desert and Mediterranean sea; in search for job opportunities, due to ineptitude in governance by their leaders; a perilous journey that enhanced artificial disasters in Nigeria. That artificial disaster fatality in Nigeria increased from about 5,655 in 2009 to 114,318 in 2018; and to 157,643 in 2022. However, financial and material loss of about $9.29 billion was incurred in Nigeria due to natural disaster, while about $70.59 billion was accrued due to artificial disaster; from 2009 to 2018. Although disaster risk mitigation and politics can synergistically support sustainable development goals; however, they are different entities, and need for distinct separations in Nigeria, as in reality and perception. This study concluded that referendum should be conducted in Nigeria, to ascertain its current status as a nation. Therefore it is recommended that Nigerian governments should refine its naturally endowed crude oil locally; to end fuel subsidy scam, corruption and poverty in Nigeria!

Keywords: corruption, crude oil, environmental risk analysis, Nigeria, referendum, terrorism

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Authors: George R. Puno, Eric N. Bruno

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The natural landscape of the Philippine archipelago plus the current realities of climate change make the country vulnerable to flood hazards. Flooding becomes the recurring natural disaster in the country resulting to lose of lives and properties. Musimusi is among the rivers which exhibited inundation particularly at the inhabited floodplain portion of its watershed. During the event, rescue operations and distribution of relief goods become a problem due to lack of high resolution flood maps to aid local government unit identify the most affected areas. In the attempt of minimizing impact of flooding, hydrologic modelling with high resolution mapping is becoming more challenging and important. This study focused on the analysis of flood extent as a function of different geomorphologic characteristics of Musimusi watershed. The methods include the delineation of morphometric parameters in the Musimusi watershed using Geographic Information System (GIS) and geometric calculations tools. Digital Terrain Model (DTM) as one of the derivatives of Light Detection and Ranging (LiDAR) technology was used to determine the extent of river inundation involving the application of Hydrologic Engineering Center-River Analysis System (HEC-RAS) and Hydrology Modelling System (HEC-HMS) models. The digital elevation model (DEM) from synthetic Aperture Radar (SAR) was used to delineate watershed boundary and river network. Datasets like mean sea level, river cross section, river stage, discharge and rainfall were also used as input parameters. Curve number (CN), vegetation, and soil properties were calibrated based on the existing condition of the site. Results showed that the drainage density value of the watershed is low which indicates that the basin is highly permeable subsoil and thick vegetative cover. The watershed’s elongation ratio value of 0.9 implies that the floodplain portion of the watershed is susceptible to flooding. The bifurcation ratio value of 2.1 indicates higher risk of flooding in localized areas of the watershed. The circularity ratio value (1.20) indicates that the basin is circular in shape, high discharge of runoff and low permeability of the subsoil condition. The heavy rainfall of 167 mm brought by Typhoon Seniang last December 29, 2014 was characterized as high intensity and long duration, with a return period of 100 years produced 316 m3s-1 outflows. Portion of the floodplain zone (1.52%) suffered inundation with 2.76 m depth at the maximum. The information generated in this study is helpful to the local disaster risk reduction management council in monitoring the affected sites for more appropriate decisions so that cost of rescue operations and relief goods distribution is minimized.

Keywords: flooding, geomorphology, mapping, watershed

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Authors: Massimiliano Condotta, Giovanni Borga, Chiara Scanagatta

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Urban systems are places where the various actors involved interact and enter in conflict, in particular with reference to topics such as traffic congestion and security. But topics of discussion, and often clash because of their strong complexity, are air and noise pollution. For air pollution, the complexity stems from the fact that atmospheric pollution is due to many factors, but above all, the observation and measurement of the amount of pollution of a transparent, mobile and ethereal element like air is very difficult. Often the perceived condition of the inhabitants does not coincide with the real conditions, because it is conditioned - sometimes in positive ways other in negative ways - from many other factors such as the presence, or absence, of natural elements such as trees or rivers. These problems are seen with noise pollution as well, which is also less considered as an issue even if it’s problematic just as much as air quality. Starting from these opposite positions, it is difficult to identify and implement valid, and at the same time shared, mitigation solutions for the problem of urban pollution (air and noise pollution). The LOOPER (Learning Loops in the Public Realm) project –described in this paper – wants to build and test a methodology and a platform for participatory co-design, planning, and construction process inside a learning loop process. Novelties in this approach are various; the most relevant are three. The first is that citizens participation starts since from the research of problems and air quality analysis through a participatory data collection, and that continues in all process steps (design and construction). The second is that the methodology is characterized by a learning loop process. It means that after the first cycle of (1) problems identification, (2) planning and definition of design solution and (3) construction and implementation of mitigation measures, the effectiveness of implemented solutions is measured and verified through a new participatory data collection campaign. In this way, it is possible to understand if the policies and design solution had a positive impact on the territory. As a result of the learning process produced by the first loop, it will be possible to improve the design of the mitigation measures and start the second loop with new and more effective measures. The third relevant aspect is that the citizens' participation is carried out via Urban Living Labs that involve all stakeholder of the city (citizens, public administrators, associations of all urban stakeholders,…) and that the Urban Living Labs last for all the cycling of the design, planning and construction process. The paper will describe in detail the LOOPER methodology and the technical solution adopted for the participatory data collection and design and construction phases.

Keywords: air quality, co-design, learning loops, noise pollution, urban living labs

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Authors: Cristina S. Decano, Vitaliana U. Malamug, Melissa E. Agulto, Helen F. Gavino

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This study aimed to introduce new natural fiber to be used in the production of geotextile net for mitigation of soil erosion. Fiber extraction from the stalks was the main challenge faced during the processing of stalks to ropes. Thus, an investigation on the extraction procedures of corn (Zea mays L.) stalk under biological and chemical retting was undertaken. Results indicated significant differences among percent fiber yield as affected by the retting methods used with values of 15.07%, 12.97%, 11.60%, and 9.01%, for dew, water, chemical (1 day after harvest and15 days after harvest), respectively, with the corresponding average extracting duration of 70, 82, 89, and 94 minutes. Physical characterization of the developed corn stalk geotextile net resulted to average mass per unit area of 806.25 g/m² and 241% water absorbing capacity. The effect of corn stalk geotextile net in mitigating soil erosion was evaluated in a laboratory experiment for 30^o and 60^o inclinations with three treatments: bare soil (A₁), corn stalk geotextile net (A₂) and combined cornstalk geotextile net and vegetation cover (A₃). Results revealed that treatment A₂ and A₃ significantly decreased sediment yield and an increase in terms of soil loss reduction efficiency. The cost of corn stalk geotextile net is Php 62.41 per square meter.

Keywords: corn stalk, natural geotextile, retting, soil erosion

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Authors: Kim Anema, Matthias Max, Chris Zevenbergen

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For any flood risk manager the 'safety paradox' has to be a familiar concept: low probability leads to a sense of safety, which leads to more investments in the area, which leads to higher potential consequences: keeping the aggregated risk (probability*consequences) at the same level. Therefore, it is important to mitigate potential consequences apart from probability. However, when the (perceived) probability is so low that there is no recognizable trend for society to adapt to, addressing the potential consequences will always be the lagging point on the agenda. Preparedness programs fail because of lack of interest and urgency, policy makers are distracted by their day to day business and there's always a more urgent issue to spend the taxpayer's money on. The leading question in this study was how to address the social consequences of flooding in a context of (perceived) low probability. Disruptions of everyday urban life, large or small, can be caused by a variety of (un)expected things - of which flooding is only one possibility. Variability like this is typically addressed with resilience - and we used the concept of Community Resilience as the framework for this study. Drawing on face to face interviews, an extensive questionnaire and publicly available statistical data we explored the 'whole society response' to two recent urban flood events; the Brisbane Floods (AUS) in 2011 and the Dresden Floods (GE) in 2013. In Brisbane, we studied how the societal impacts of the floods were counteracted by both authorities and the public, and in Dresden we were able to validate our findings. A large part of the reactions, both public as institutional, to these two urban flood events were not fuelled by preparedness or proper planning. Instead, more important success factors in counteracting social impacts like demographic changes in neighborhoods and (non-)economic losses were dynamics like community action, flexibility and creativity from authorities, leadership, informal connections and a shared narrative. These proved to be the determining factors for the quality and speed of recovery in both cities. The resilience of the community in Brisbane was good, due to (i) the approachability of (local) authorities, (ii) a big group of ‘secondary victims’ and (iii) clear leadership. All three of these elements were amplified by the use of social media and/ or web 2.0 by both the communities and the authorities involved. The numerous contacts and social connections made through the web were fast, need driven and, in their own way, orderly. Similarly in Dresden large groups of 'unprepared', ad hoc organized citizens managed to work together with authorities in a way that was effective and speeded up recovery. The concept of community resilience is better fitted than 'social adaptation' to deal with the potential consequences of an (im)probable flood. Community resilience is built on capacities and dynamics that are part of everyday life and which can be invested in pre-event to minimize the social impact of urban flooding. Investing in these might even have beneficial trade-offs in other policy fields.

Keywords: community resilience, disaster response, social consequences, preparedness

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Authors: Michael Bellas, George Voulgaridis

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This paper refers to the world known mega - landslide induced at the community of Ropoto, belonging to the Municipality of Trikala, in the Central part of Greece. The landslide affected the debris as well as the colluvium mantle of the flysch, and makes up a special case of study in engineering geology and geotechnical engineering not only because of the size of the domain affected by the landslide (approximately 750m long), but also because of the geostructure’s global behavior. Due to the landslide, the whole community’s infrastructure massively collapsed and human lives were put in danger. After the complete simulation of the coupled Seepage - Deformation phenomenon due to the extreme rainfall, and by closely examining the slope’s global behavior, both the mitigation of the landslide, as well as, an advanced surveillance method (Fiber Bragg Grating) using fiber optics were further studied, in order both to retain the geostructure and to monitor its health by creating an early warning system, which would serve as a complete safety net for saving both the community’s infrastructure as well as the lives of its habitats.

Keywords: landslide, remediation measures, the finite element method (FEM), Fiber Bragg Grating (FBG) sensing method

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Authors: Mohsen Sheikholeslami, Zahra Khalili, Ladan Momayez

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Impacts of environmental parameters and dust deposition on the efficiency of solar panel have been scrutinized in this article. To gain thermal output, trapezoidal cooling channel has been attached in the bottom of the panel incorporating ternary nanofluid. To produce working fluid, water has been mixed with Fe₃O₄-TiO₂-GO nanoparticles. Also, the arrangement of fins has been considered to grow the cooling rate of the silicon layer. The existence of a thermoelectric layer above the cooling channel leads to higher electrical output. Efficacy of ambient temperature (Ta), speed of wind (V𝓌ᵢₙ𝒹) and inlet temperature (Tᵢₙ) and velocity (Vin) of ternary nanofluid on performance of PVT has been assessed. As Tin increases, electrical efficiency declines about 3.63%. Increase of ambient temperature makes thermal performance enhance about 33.46%. The PVT efficiency decreases about 13.14% and 16.6% with augment of wind speed and dust deposition. CO₂ mitigation has been reduced about 15.49% in presence of dust while it increases about 17.38% with growth of ambient temperature.

Keywords: photovoltaic system, CO₂ mitigation, ternary nanofluid, thermoelectric generator, environmental parameters, trapezoidal cooling channel

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Authors: Osung Im, Neha Yadav, Eui Hoon Lee, Joong Hoon Kim

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Artificial Neural Network (ANN) approach is commonly used in lots of fields for forecasting. In water resources engineering, forecast of water level or inflow of reservoir is useful for various kind of purposes. Due to advantages of ANN, many papers were written for inflow prediction in river networks, but in this study, ANN is used in urban sewer networks. The growth of severe rain storm in Korea has increased flood damage severely, and the precipitation distribution is getting more erratic. Therefore, effective pump operation in pump station is an essential task for the reduction in urban area. If real time inflow of pump station reservoir can be predicted, it is possible to operate pump effectively for reducing the flood damage. This study used ANN model for pump station reservoir inflow prediction using upstream sewer depth data. For this study, rainfall events, sewer depth, and inflow into Banpo pump station reservoir between years of 2013-2014 were considered. Feed – Forward Back Propagation (FFBF), Cascade – Forward Back Propagation (CFBP), Elman Back Propagation (EBP) and Nonlinear Autoregressive Exogenous (NARX) were used as ANN model for prediction. A comparison of results with ANN model suggests that ANN is a powerful tool for inflow prediction using the sewer depth data.

Keywords: artificial neural network, forecasting, reservoir inflow, sewer depth

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Authors: Marzieh Karimihaghighi, Carlos Castillo

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This work studies how Machine Learning (ML) may be used to increase the effectiveness of a criminal recidivism risk assessment tool, RisCanvi. The two key dimensions of this analysis are predictive accuracy and algorithmic fairness. ML-based prediction models obtained in this study are more accurate at predicting criminal recidivism than the manually-created formula used in RisCanvi, achieving an AUC of 0.76 and 0.73 in predicting violent and general recidivism respectively. However, the improvements are small, and it is noticed that algorithmic discrimination can easily be introduced between groups such as national vs foreigner, or young vs old. It is described how effectiveness and algorithmic fairness objectives can be balanced, applying a method in which a single error disparity in terms of generalized false positive rate is minimized, while calibration is maintained across groups. Obtained results show that this bias mitigation procedure can substantially reduce generalized false positive rate disparities across multiple groups. Based on these results, it is proposed that ML-based criminal recidivism risk prediction should not be introduced without applying algorithmic bias mitigation procedures.

Keywords: algorithmic fairness, criminal risk assessment, equalized odds, recidivism

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Authors: Rahma Al Maawali, Hameed Sulaiman

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Air pollution both from point and non-point sources is difficult to control once released in to the atmosphere. There is no engineering method known available to ameliorate the dispersed pollutants. The only suitable approach is the ecological method of constructing green belts in and around the pollution sources. Air pollution in Muscat, Oman is a serious concern due to ever increasing vehicles on roads. Identifying the air pollution tolerance levels of species is important for implementing pollution control strategies in the urban areas of Muscat. Hence, in the present study, Air Pollution Tolerance Index (APTI) for ten avenue tree species was evaluated by analyzing four bio-chemical parameters, plus their Anticipated Performance Index (API) in field conditions. Based on the two indices, Ficus benghalensis was the most suitable one with the highest performance score. Conocarpus erectuse, Phoenix dactylifera, and Pithcellobium dulce were found to be good performers and are recommended for extensive planting. Azadirachta indica which is preferred for its dense canopy is qualified in the moderate category. The rest of the tree species expressed lower API score of less than 51, hence cannot be considered as suitable species for pollution mitigation plantation projects.

Keywords: air pollution tolerance index (APTI), avenue tree species, bio-chemical parameters, muscat

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Authors: Christopher B. Obida, George A. Blackburn, James D. Whyatt, Kirk T. Semple

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In many regions of the world, especially in developing countries, river network data are outdated or completely absent, yet such information is critical for supporting important functions such as flood mitigation efforts, land use and transportation planning, and the management of water resources. In this study, a method was developed for delineating river networks using Sentinel 1 imagery. Unsupervised classification was applied to multi-temporal Sentinel 1 data to discriminate water bodies from other land covers then the outputs were combined to generate a single persistent water bodies product. A thinning algorithm was then used to delineate river centre lines, which were converted into vector features and built into a topologically structured geometric network. The complex river system of the Niger Delta was used to compare the performance of the Sentinel-based method against alternative freely available water body products from United States Geological Survey, European Space Agency and OpenStreetMap and a river network derived from a Shuttle Rader Topography Mission Digital Elevation Model. From both raster-based and vector-based accuracy assessments, it was found that the Sentinel-based river network products were superior to the comparator data sets by a substantial margin. The geometric river network that was constructed permitted a flow routing analysis which is important for a variety of environmental management and planning applications. The extracted network will potentially be applied for modelling dispersion of hydrocarbon pollutants in Ogoniland, a part of the Niger Delta. The approach developed in this study holds considerable potential for generating up to date, detailed river network data for the many countries where such data are deficient.

Keywords: Sentinel 1, image processing, river delineation, large scale mapping, data comparison, geometric network

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Authors: Mani Venkatesh, Catarina Delgado, Purvishkumar Patel

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The sustainable supply chain is gaining popularity among practitioners because of increased environmental degradation and stakeholder awareness. On the other hand supply chain, risk management is very crucial for the practitioners as it potentially disrupts supply chain operations. Prediction and addressing the risk caused by social issues in the supply chain is paramount importance to the sustainable enterprise. More recently, the usage of Big data analytics for forecasting business trends has been gaining momentum among professionals. The aim of the research is to explore the application of big data, predictive analytics in successfully mitigating supply chain social risk and demonstrate how such mitigation can help in achieving sustainability (environmental, economic & social). The method involves the identification and validation of social issues in the supply chain by an expert panel and survey. Later, we used a case study to illustrate the application of big data in the successful identification and mitigation of social issues in the supply chain. Our result shows that the company can predict various social issues through big data, predictive analytics and mitigate the social risk. We also discuss the implication of this research to the body of knowledge and practice.

Keywords: big data, sustainability, supply chain social sustainability, social risk, case study

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Authors: Aiman Mazhar Qureshi, Ahmed Rachid

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Extreme heat events are emerging human environmental health concerns in dense urban areas due to anthropogenic activities. High spatial and temporal resolution heat maps are important for urban heat adaptation and mitigation, helping to indicate hotspots that are required for the attention of city planners. The Heat Vulnerability Index (HVI) is the important approach used by decision-makers and urban planners to identify heat-vulnerable communities and areas that require heat stress mitigation strategies. Amiens is a medium-sized French city, where the average temperature has been increasing since the year 2000 by +1°C. Extreme heat events are recorded in the month of July for the last three consecutive years, 2018, 2019 and 2020. Poor air quality, especially ground-level ozone, has been observed mainly during the same hot period. In this study, we evaluated the HVI in Amiens during extreme heat days recorded last three years (2018,2019,2020). The Principal Component Analysis (PCA) technique is used for fine-scale vulnerability mapping. The main data we considered for this study to develop the HVI model are (a) socio-economic and demographic data; (b) Air pollution; (c) Land use and cover; (d) Elderly heat-illness; (e) socially vulnerable; (f) Remote sensing data (Land surface temperature (LST), mean elevation, NDVI and NDWI). The output maps identified the hot zones through comprehensive GIS analysis. The resultant map shows that high HVI exists in three typical areas: (1) where the population density is quite high and the vegetation cover is small (2) the artificial surfaces (built-in areas) (3) industrial zones that release thermal energy and ground-level ozone while those with low HVI are located in natural landscapes such as rivers and grasslands. The study also illustrates the system theory with a causal diagram after data analysis where anthropogenic activities and air pollution appear in correspondence with extreme heat events in the city. Our suggested index can be a useful tool to guide urban planners and municipalities, decision-makers and public health professionals in targeting areas at high risk of extreme heat and air pollution for future interventions adaptation and mitigation measures.

Keywords: heat vulnerability index, heat mapping, heat health-illness, remote sensing, urban heat mitigation

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Authors: Raphaël Weuts, Mykyta Petik, Anton Vedder

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Artificial Intelligence has the potential to create and already creates enormous value in healthcare. Prescriptive systems might be able to make the use of healthcare capacity more efficient. Such systems might entail interpretations that exclude the effect of confounders that brings risks with it. Those risks might be mitigated by regulation that prevents systems entailing such risks to come to market. One modality of regulation is that of legislation, and the European AI Act is an example of such a regulatory instrument that might mitigate these risks. To assess the risk mitigation potential of the AI Act for those risks, this research focusses on a case study of a hypothetical application of medical device software that entails the aforementioned risks. The AI Act refers to the harmonised norms for already existing legislation, here being the European medical device regulation. The issue at hand is a causal link between a confounder and the value the algorithm optimises for by proxy. The research identifies where the AI Act already looks at confounders (i.a. feedback loops in systems that continue to learn after being placed on the market). The research identifies where the current proposal by parliament leaves legal uncertainty on the necessity to check for confounders that do not influence the input of the system, when the system does not continue to learn after being placed on the market. The authors propose an amendment to article 15 of the AI Act that would require high-risk systems to be developed in such a way as to mitigate risks from those aforementioned confounders.

Keywords: AI Act, healthcare, confounders, risks

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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: Mohamed Alzarug Aburugba, Rashid Mohamed Eltanashi

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Rainwater is considered an essential water resource, as it contributes to filling the deficit in water resources, especially in countries that suffer from a scarcity of natural water sources. One of the important issues facing the Water and Gas Services Department at the Libyan Iron and Steel Company is the large loss of quantities of industrial water, both direct and indirect cooling water (DCW, ICW), produced within the company due to leaks in the cooling systems of the factories of the Libyan Iron and Steel Company. These amounts of polluted industrial water leakage are mixed with rainwater collected by stormwater stations (6 stations) in LISCO, which is pumped to the sea through pumps with a very high flow rate, and thus, this will carry a lot of waste, heavy metals, and oils to the sea, which negatively affects marine environmental resources. This paper assesses the environmental impact of the quantities of rainwater and mixed industrial water in stormwater stations in the Libyan Iron and Steel Company and methods of mitigation, treating pollutants and reusing them as industrial water in the production processes of the steel industry.

Keywords: rainwater, mitigation, impact, sewage, heavy metals, assessment, pollution, environment, natural resources, industrial water.

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Authors: Stephen Adeniyi Adefegha, Vitor Mostardeiro, Vera Maria Morsch, Ademir F. Morel, Ivana Beatrice Manica Da Cruz, Sabrina Somacal Maria Rosa Chitolina Schetinger

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Moringa stenopetala is often consumed as food and used in folkloric medicine for the management of several diseases. Purpose: This study was set up in order to assess the effect of aqueous extract of Moringa stenopetala on cell viability and oxidative stress biomarkers in BV-2 microglial cells. Aqueous extracts of M. stenopetala were prepared, lyophilized and reconstituted in 0.5% dimethylsulphoxide (DMSO). Cells were treated with M. stenopetala extracts (0.1 - 100 µg/ml) for cell viability and nitric oxide (NO) production tests. However, M. stenopetala extract (50 µg/ml) was used in the treatment of cells for the determination of protein carbonyl content and reactive oxygen species (ROS) level. Incubation of BV-2 microglia cell with M. stenopetala extract maintained cell viability, diminished NO and ROS levels, and reduced protein carbonyl contents Chlorogenic acid, rutin, kaempferol and quercetin derivatives were the main phenolic compounds identified in M. stenopetala leaf extract. These phenolic compounds present in M. stenopetala may be responsible for the mitigation of oxidative stress in BV-2 microglial cells.

Keywords: oxidative stress, BV-2 microglial cell, Moringa stenopetala, cell viability, antioxidant

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Authors: Ajibola O. Akinrinde, Andrew Swanson, Remy Tiako

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There exist significant losses on transmission lines due to distance, as power generating stations could be located far from some isolated settlements. Standalone wind farms could be a good choice of alternative power generation for such settlements that are far from the grid due to factors of long distance or socio-economic problems. However, uncompensated wind farms consume reactive power since wind turbines are induction generators. Therefore, capacitor banks are used to compensate reactive power, which in turn improves the voltage profile of the network. Although capacitor banks help improving voltage profile, they also undergo switching actions due to its compensating response to the variation of various types of load at the consumer’s end. These switching activities could cause transient overvoltage on the network, jeopardizing the end-life of other equipment on the system. In this paper, the overvoltage caused by these switching activities is investigated using the IEEE bus 14-network to represent a standalone wind farm, and the simulation is done using ATP/EMTP software. Scenarios involving the use of pre-insertion resistor and pre-insertion inductor, as well as controlled switching was also carried out in order to decide the best mitigation option to reduce the overvoltage.

Keywords: capacitor banks, IEEE bus 14-network, pre-insertion resistor, standalone wind farm

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Authors: D. Bianco, A. Sollazzo, M. Barbarino, G. Elia, A. Smoraldi, N. Favaloro

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The activities, described in the present paper, have been conducted in the framework of the HYPROB-New Program, carried out by the Italian Aerospace Research Centre (CIRA) promoted and funded by the Italian Ministry of University and Research (MIUR) in order to improve the National background on rocket engine systems for space applications. The Program has the strategic objective to improve National system and technology capabilities in the field of liquid rocket engines (LRE) for future Space Propulsion Systems applications, with specific regard to LOX/LCH4 technology. The main purpose of the HYPROB program is to design and build a Propulsion Test Facility (HIMP) allowing test activities on Liquid Thrusters. The development of skills in liquid rocket propulsion can only pass through extensive test campaign. Following its mission, CIRA has planned the development of new testing facilities and infrastructures for space propulsion characterized by adequate sizes and instrumentation. The IMP test cell is devoted to testing articles representative of small combustion chambers, fed with oxygen and methane, both in liquid and gaseous phase. This article describes the activities that have been carried out for the evaluation of the acoustic impact, and its consequent mitigation. The impact of the simulated acoustic disturbance has been evaluated, first, using an approximated method based on experimental data by Baumann and Coney, included in “Noise and Vibration Control Engineering” edited by Vér and Beranek. This methodology, used to evaluate the free-field radiation of jet in ideal acoustical medium, analyzes in details the jet noise and assumes sources acting at the same time. It considers as principal radiation sources the jet mixing noise, caused by the turbulent mixing of jet gas and the ambient medium. Empirical models, allowing a direct calculation of the Sound Pressure Level, are commonly used for rocket noise simulation. The model named after K. Eldred is probably one of the most exploited in this area. In this paper, an improvement of the Eldred Standard model has been used for a detailed investigation of the acoustical impact of the Hyprob facility. This new formulation contains an explicit expression for the acoustic pressure of each equivalent noise source, in terms of amplitude and phase, allowing the investigation of the sources correlation effects and their propagation through wave equations. In order to enhance the evaluation of the facility acoustic impact, including an assessment of the mitigation strategies to be set in place, a more advanced simulation campaign has been conducted using both an in-house code for noise propagation and scattering, and a commercial code for industrial noise environmental impact, CadnaA. The noise prediction obtained with the revised Eldred-based model has then been used for formulating an empirical/BEM (Boundary Element Method) hybrid approach allowing the evaluation of the barrier mitigation effect, at the design. This approach has been compared with the analogous empirical/ray-acoustics approach, implemented within CadnaA using a customized definition of sources and directivity factor. The resulting impact evaluation study is reported here, along with the design-level barrier optimization for noise mitigation.

Keywords: acoustic impact, industrial noise, mitigation, rocket noise

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Authors: Xuguo Zhang, Jimmy Fung, Kenneth Leung, Alexis Lau

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Fine particulate matter concentrations have been decreasing in the past few years while the ozone concentrations are posing an increasing trend in the Greater Bay Area (GBA) of China. A series of control policies have been released to mitigate the country-wide air pollution, however, how to effectively evaluate the exercised control measures and efficiently reveal potential projected mitigation pathways are still limited. By refining an enhanced air-quality-modeling system, this study provides an account of the air quality assessments from 2019 to 2025 to appraise the air quality results and improvement under designed scenarios for assessing the optimum scope for tightening the Air Quality Objectives (AQOs). The results show that it is doable to tighten the 24-hour AQO for SO2 from the World Health Objective air quality guidelines Interim Targets Level-1 (IT-1) (125μg/m3) to IT-2 level (50μg/m3) with the current number of exceedance allowed (three) remains unchanged. It is also possible to tighten the annual AQO for PM2.5 from IT-1 (35 μg/m3) to IT 2 (25 μg/m3), and its 24-hr AQO from IT-1 (75 μg/m3) to IT 2 (50 μg/m3) with the number of exceedances allowed increased from current nine to 35. Regional cooperation under the development of the GBA cooperation are still needed to be focused and strengthen due to the cross-boundary transport characteristics of the air pollution.

Keywords: air quality attainment, Hong Kong, mitigation policy, chemical transport modeling, sensitivity analysis

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Authors: Olubisi Friday Oluduro

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The Paris Agreement 2015, the result of negotiations under the United Nations Framework Convention on Climate Change (UNFCCC), after Kyoto Protocol expiration, sets a long-term goal of limiting the increase in the global average temperature to well below 2 degrees Celsius above pre-industrial levels, and of pursuing efforts to limiting this temperature increase to 1.5 degrees Celsius. An advancement on the erstwhile Kyoto Protocol which sets commitments to only a limited number of Parties to reduce their greenhouse gas (GHGs) emissions, it includes the goal to increase the ability to adapt to the adverse impacts of climate change and to make finance flows consistent with a pathway towards low GHGs emissions. For it achieve these goals, the Agreement requires all Parties to undertake efforts towards reaching global peaking of GHG emissions as soon as possible and towards achieving a balance between anthropogenic emissions by sources and removals by sinks in the second half of the twenty-first century. In addition to climate change mitigation, the Agreement aims at enhancing adaptive capacity, strengthening resilience and reducing the vulnerability to climate change in different parts of the world. It acknowledges the importance of addressing loss and damage associated with the adverse of climate change. The Agreement also contains comprehensive provisions on support to be provided to developing countries, which includes finance, technology transfer and capacity building. To ensure that such supports and actions are transparent, the Agreement contains a number reporting provisions, requiring parties to choose the efforts and measures that mostly suit them (Nationally Determined Contributions), providing for a mechanism of assessing progress and increasing global ambition over time by a regular global stocktake. Despite the somewhat global look of the Agreement, it has been fraught with manifold limitations threatening its very existential capability to produce any meaningful result. Considering these obvious limitations some of which were the very cause of the failure of its predecessor—the Kyoto Protocol—such as the non-participation of the United States, non-payment of funds into the various coffers for appropriate strategic purposes, among others. These have left the developing countries largely threatened eve the more, being more vulnerable than the developed countries, which are really responsible for the climate change scourge. The paper seeks to examine the mitigation and adaptation measures under the Paris Agreement 2015, appraise the present situation since the Agreement was concluded and ascertain whether the developing countries have been better or worse off since the Agreement was concluded, and examine why and how, while projecting a way forward in the present circumstance. It would conclude with recommendations towards ameliorating the situation.

Keywords: mitigation, adaptation, climate change, Paris agreement 2015, framework

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Authors: Jayson Cheyne, David Butler, Iain Bomphray

Abstract:

In recent years, lithium-ion batteries have been used increasingly for electric vehicles and large energy storage systems due to their high-power density and long lifespan. Despite this, thermal runaway remains a significant safety problem because of its uncontrollable and irreversible nature - which can lead to fires and explosions. In large-scale lithium-ion packs and modules, thermal runaway propagation between cells can escalate fire hazards and cause significant damage. Thus, safety measures are required to mitigate thermal runaway propagation. The current research explores composite phase change materials (PCM) containing expanded graphite (EG) for thermal runaway mitigation. PCMs are an area of significant interest for battery thermal management due to their ability to absorb substantial quantities of heat during phase change. Moreover, the introduction of EG can support heat transfer from the cells to the PCM (owing to its high thermal conductivity) and provide shape stability to the PCM during phase change. During the research, a thermal model was established for an array of 16 cylindrical cells to simulate heat dissipation with and without the composite PCM. Two conditions were modeled, including the behavior during charge/discharge cycles (i.e., throughout regular operation) and thermal runaway. Furthermore, parameters including cell spacing, composite PCM thickness, and EG weight percentage (WT%) were varied to establish the optimal material parameters for enabling thermal runaway mitigation and effective thermal management. Although numerical modeling is still ongoing, initial findings suggest that a 3mm PCM containing 15WT% EG can effectively suppress thermal runaway propagation while maintaining shape stability. The next step in the research is to validate the model through controlled experimental tests. Additionally, with the perceived fire safety concerns relating to PCM materials, fire safety tests, including UL-94 and Limiting Oxygen Index (LOI), shall be conducted to explore the flammability risk.

Keywords: battery safety, electric vehicles, phase change materials, thermal management, thermal runaway

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Authors: Ruhizal Roosli, Julaihi Wahid, Abu Hassan Abu Bakar, Faizal Baharum

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This paper reports on the progress of a study on the reconstruction project after the ‘Yellow Flood’ disaster in Kelantan, Malaysia. Malaysia still does not have guidelines to build housing after a disaster especially in disaster-prone areas. At the international level, many guidelines have been prepared that is found suitable for post-disaster housing. Which guidelines can be adapted that best describes the situation in Malaysia? It was reported that the houses should be built on stilts, which can withstand certain level of impact during flooding. Unfortunately, until today no specific guideline was available to assist homeowners to rebuild their homes after disaster. In addition, there is also no clear operational procedure to monitor the progress of this construction work. This research is an effort to promoting resilient housing; safety and security; and secure tenure in a prone area. At the end of this study, key lessons will be emerged from the review process and data analysis. These inputs will then have influenced to the content that will be developed and presented as guidelines. An overall objective is to support humanitarian responses to disaster and conflicts for resilience house construction to flood prone area. Interviews with the field based staff were from recent post-disaster housing workforce (disaster management mechanism in Malaysia especially in Kelantan). The respondents were selected based on their experiences in disaster response particularly related to housing provision. These key lessons are perhaps the best practical (operational and technical) guidelines comparing to other International cases to be adapted to the national situations.

Keywords: disaster, guideline, housing, Malaysia, reconstruction

Procedia PDF Downloads 496

Authors: Mara Getachew Zenebe, Luuk Fleskens, Abdu Obieda Ahmed

Abstract:

This paper seeks to advance our scientific understanding of optimizing flood utilization in regions impacted by climate change, with a focus on enhancing agricultural productivity through effective irrigation management. The study was conducted as part of a three-year (2021 to 2023) USAID-supported initiative aimed at promoting Economic Growth and Peace in the Gash Agricultural Scheme (GAS), situated in Sudan's water-stressed Eastern region. GAS is the country's largest flood-irrigated scheme, covering 100,800 hectares of cultivable land, with a potential to provide the food security needs of over a quarter of a million agro-pastoral community members. GAS relies on the Gash River, which sources its water from high-intensity rainfall events in the highlands of Ethiopia and Eritrea. However, climate change and variations in these highlands have led to increased variability in the Gash River's flow. The study conducted water balance analyses based on a ten-year dataset of the annual Gash River flow, irrigated area; as well as the evapotranspiration demand of the major sorghum crop. Data collection methods included field measurements, surveys, remote sensing, and CropWat modelling. The water balance assessment revealed that the existing three-year rotation-based irrigation system management, capping cultivated land at 33,000 hectares annually, is excessively risk-averse. While this system reduced conflicts among the agro-pastoral communities by consistently delivering on the land promised to be annually cultivated, it also increased GAS's vulnerability to flood damage due to several reasons. The irrigation efficiency over the past decade was approximately 30%, leaving significant unharnessed floodwater that caused damage to infrastructure and agricultural land. The three-year rotation resulted in inadequate infrastructural maintenance, given the destructive nature of floods. Additionally, it led to infrequent land tillage, allowing the encroachment of mesquite trees hindering major sorghum crop growth. Remote sensing data confirmed that mesquite trees have overtaken 70,000 hectares in the past two decades, rendering them unavailable for agriculture. The water balance analyses suggest shifting to a two-year rotation, covering approximately 50,000 hectares annually while maintaining risk aversion. This shift could boost GAS's annual sorghum production by two-thirds, exceeding 850,000 tons. The scheme's efficiency can be further enhanced through low-cost on-farm interventions. Currently, large irrigation plots that range from 420 to 756 hectares are irrigated with limited water distribution guidance, leading to uneven irrigation. As demonstrated through field trials, implementing internal longitudinal bunds and horizontal deflector bunds can increase adequately irrigated parts of the irrigation plots from 50% to 80% and thus nearly double the sorghum yield to 2 tons per hectare while reducing the irrigation duration from 30 days to a maximum of 17 days. Flow measurements in 2021 and 2022 confirmed that these changes sufficiently meet the sorghum crop's water requirements, even with a conservative 60% field application efficiency assumption. These insights and lessons from the GAS on enhancing agricultural resilience and sustainability in the face of climate change are relevant to flood-based livelihood systems globally.

Keywords: climate change, irrigation management and productivity, variable flood flows, water balance analysis

Procedia PDF Downloads 56

Authors: Vimala Rani P, Narasimha Malikarjunan, Mercy Shalinie S

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Data Networking was brought forth as an instantiation of information-centric networking. The attackers can send a colossal number of spoofs to take hold of the Pending Interest Table (PIT) named an Interest Flooding attack (IFA) since the in- interests are recorded in the PITs of the intermediate routers until they receive corresponding Data Packets are go beyond the time limit. These attacks can be detrimental to network performance. PIT expiration rate or the Interest satisfaction rate, which cannot differentiate the IFA from attacks, is the criterion Traditional IFA detection techniques are concerned with. Threshold values can casually affect Threshold-based traditional methods. This article proposes an accurate IFA detection mechanism based on a Multiple Feature-based Extreme Learning Machine (MF-ELM). Accuracy of the attack detection can be increased by presenting the entropy of Internet names, Interest satisfaction rate and PIT usage as features extracted in the MF-ELM classifier. Furthermore, we deploy a queue-based hostile Interest prefix mitigation mechanism. The inference of this real-time test bed is that the mechanism can help the network to resist IFA with higher accuracy and efficiency.

Keywords: information-centric network, pending interest table, interest flooding attack, MF-ELM classifier, queue-based mitigation strategy

Procedia PDF Downloads 191