Search results for: water prediction

Authors: Abdelrahman Elsehsah, Abdelazim Negm, Eid Ashour, Mohamed Elsahabi

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Water resources management is a critical field that encompasses the planning, development, conservation, and allocation of water resources to meet societal needs while ensuring environmental sustainability. This paper reviews the key concepts and challenges in water resources management, emphasizing the significance of a holistic approach that integrates social, economic, and environmental factors. Traditional water management practices, characterized by supply-oriented strategies and centralized control, are increasingly inadequate in addressing contemporary challenges such as water scarcity, climate change impacts, and ecosystem degradation. Emerging technologies, particularly machine learning and remote sensing, offer innovative solutions to enhance decision-making processes in water management. Machine learning algorithms facilitate accurate water demand forecasting, quality monitoring, and leak detection, while remote sensing technologies provide vital data for assessing water availability and quality. This review highlights the need for integrated water management strategies that leverage these technologies to promote sustainable practices and foster resilience in water systems. Future research should focus on improving data quality, accessibility, and the integration of diverse datasets to optimize the benefits of these technological advancements.

Keywords: water resources management, water scarcity, climate change, machine learning, remote sensing, water quality, water governance, sustainable practices, ecosystem management

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Authors: Elizabeth Spink

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The United Nations' Sustainable Development Goal 6 sets a target for safe and affordable drinking water for all. Developing country governments aiming to achieve this goal often face significant challenges when trying to service last mile customers, particularly those in peri-urban and rural areas. Expansion of water networks often requires high connection fees from households, and demand for connections may be low if there are cheaper substitute sources of water available. This research studies the effect of the availability of substitute sources of water on demand for individual water connections in Livingstone, Zambia, using an event study analysis of metering campaigns. Metering campaigns reduce the share of a household's neighbors that can provide free water to the household if their water connection becomes disconnected due to nonpayment. The results show that household payments in newly metered regions increase by 10 percentage points in the months following metering events, with a decrease in disconnections of 6 percentage points for low-income households. To isolate the effect of changes in a household's substitution possibilities, a similar analysis is conducted among households that neighbor the metered region. These results show mixed evidence of the impact of substitutes on payment behavior and disconnections. The results suggest that metering may be effective in increasing household demand for individual water connections primarily through a lower monthly cost burden for newly metered households.

Keywords: piped-water access, water demand, water utilities, water sharing

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Authors: Samaneh Abolli, Mahmood Alimohammadi

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The survey analyzed 71 bottled water brands in Tehran, Iran, examining 10 physicochemical parameters and 16 heavy metals. The water quality index (WQI) approach was used to assess water quality, and methods such as carcinogen risk (CR) and hazard index (HI) were employed to evaluate health risks. The results indicated that the bottled water had good quality overall, but some brands were of poor or very poor quality. The study also revealed significant human health risks, especially for children, due to the presence of minerals and heavy metals in bottled water. Correlation analyses and risk assessments for various substances were conducted, providing valuable insights into the potential health impacts of the analyzed bottled water.

Keywords: bottled wate, rwater quality index, health risk assessment, contamination degree, heavy metal evaluation index

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Authors: Hooman Fallah

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Seawater injection and produced water re-injection are presently the most commonly used approach to enhanced recovery. The dominant factors for total oil recovery are the reservoir temperature, reservoir pressure, crude oil and water composition. In this study, the production under water injection in Soroosh, one of the southern Iranian heavy oil field has been simulated (the fluid properties are focused). In order to reveal the dominant factors in this production process, the sensitivity analysis has been done for the following effective factors, fluid viscosity, initial water saturation, gravity force and injection well strategy. It is crystal clear that the study of the dominant factors in production processes will help the engineers to design the best production mechanisms in our numerous hydrocarbon reservoirs.

Keywords: water injection, initial water saturation, oil viscosity, gravity force, injection well strategy

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Authors: T. Tahri, H. Zahloul, K. E. Meddah, H. Lazergue

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This paper presents a theoretical study that leads to the design of a photovoltaic pumping system to irrigate six hectares of oranges in the valley of Chlef using the software "PVSYST". It was shown that the site of Chlef presents a favorable climate to this type of energy with an irradiation of over 5 kWh/m2/day, and significant resources underground water. Another very important coincidence still promotes the use of this type of energy for pumping water in Chlef is that the demand for water, especially in agriculture, peaked in hot and dry where it is precisely when one has access to the maximum of solar energy.

Keywords: solar energy, irradiation, water pumping, design, Valley of Chlef

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Authors: Tarek S. Jamil, Ahmed M. Shaban, Eman S. Mansor, Ahmed A. Karim, Azza M. Abdel Aty

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In this manuscript, 35 m³/d NF unit was designed and applied for surface water treatment of river Nile water. Intake of Embaba drinking water treatment plant was selected to install that unit at since; it has the lowest water quality index value through the examined 6 sites in greater Cairo area. The optimized operating conditions were feed and permeate flow, 40 and 7 m³/d, feed pressure 2.68 bar and flux rate 37.7 l/m2.h. The permeate water was drinkable according to Egyptian Ministerial decree 458/2007 for the tested parameters (physic-chemical, heavy metals, organic, algal, bacteriological and parasitological). Single and double sand filters were used as pretreatment for NF membranes, but continuous clogging for sand filters moved us to use UF membrane as pretreatment for NF membrane.

Keywords: River Nile, NF membrane, pretreatment, UF membrane, water quality

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Authors: Khalid S. Hashim, Andy Shaw, Rafid Alkhaddar, Montserrat Ortoneda Pedrola

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A flow column has been innovatively used in the design of a new electrocoagulation reactor (ECR1) that will reduce the temperature of water being treated; where the flow columns work as a radiator for the water being treated. In order to investigate the performance of ECR1 and compare it to that of traditional reactors; 600 mL water samples with an initial temperature of 35 0C were pumped continuously through these reactors for 30 min at current density of 1 mA/cm2. The temperature of water being treated was measured at 5 minutes intervals over a 30 minutes period using a thermometer. Additional experiments were commenced to investigate the effects of initial temperature (15-35 0C), water conductivity (0.15 – 1.2 S) and current density (0.5 -3 mA/cm2) on the performance of ECR1. The results obtained demonstrated that the ECR1, at a current density of 1 mA/cm2 and continuous flow model, reduced water temperature from 35 0C to the vicinity of 28 0C during the first 15 minutes and kept the same level till the end of the treatment time. While, the temperature increased from 28.1 to 29.8 0C and from 29.8 to 31.9 0C in the batch and the traditional continuous flow models respectively. In term of initial temperature, ECR1 maintained the temperature of water being treated within the range of 22 to 28 0C without the need for external cooling system even when the initial temperatures varied over a wide range (15 to 35 0C). The influent water conductivity was found to be a significant variable that affect the temperature. The desirable value of water conductivity is 0.6 S. However, it was found that the water temperature increased rapidly with a higher current density.

Keywords: water temperature, flow column, electrocoagulation

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Authors: Farnaz Farhangi

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Many people in New Zealand believe that the access to water is inexhaustible, and it comes from a history of virtually unrestricted access to it. For the region like Hamilton which is one of New Zealand’s fastest growing cities, it is crucial for policy makers to know about the future water consumption and implementation of rules and regulation such as universal water metering. Hamilton residents use water freely and they do not have any idea about how much water they use. Hence, one of proposed objectives of this research is focusing on forecasting water consumption using different methods. Residential water consumption time series exhibits seasonal and trend variations. Seasonality is the pattern caused by repeating events such as weather conditions in summer and winter, public holidays, etc. The problem with this seasonal fluctuation is that, it dominates other time series components and makes difficulties in determining other variations (such as educational campaign’s effect, regulation, etc.) in time series. Apart from seasonality, a stochastic trend is also combined with seasonality and makes different effects on results of forecasting. According to the forecasting literature, preprocessing (de-trending and de-seasonalization) is essential to have more performed forecasting results, while some other researchers mention that seasonally non-adjusted data should be used. Hence, I answer the question that is pre-processing essential? A wide range of forecasting methods exists with different pros and cons. In this research, I apply double seasonal ARIMA and Artificial Neural Network (ANN), considering diverse elements such as seasonality and calendar effects (public and school holidays) and combine their results to find the best predicted values. My hypothesis is the examination the results of combined method (hybrid model) and individual methods and comparing the accuracy and robustness. In order to use ARIMA, the data should be stationary. Also, ANN has successful forecasting applications in terms of forecasting seasonal and trend time series. Using a hybrid model is a way to improve the accuracy of the methods. Due to the fact that water demand is dominated by different seasonality, in order to find their sensitivity to weather conditions or calendar effects or other seasonal patterns, I combine different methods. The advantage of this combination is reduction of errors by averaging of each individual model. It is also useful when we are not sure about the accuracy of each forecasting model and it can ease the problem of model selection. Using daily residential water consumption data from January 2000 to July 2015 in Hamilton, I indicate how prediction by different methods varies. ANN has more accurate forecasting results than other method and preprocessing is essential when we use seasonal time series. Using hybrid model reduces forecasting average errors and increases the performance.

Keywords: artificial neural network (ANN), double seasonal ARIMA, forecasting, hybrid model

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Authors: Ali Montazar

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California and the Colorado River Basin are facing increasing uncertainty concerning water supplies. The Colorado River is the main source of irrigation water in the low desert of California. Currently, due to an increasing water-use competition and long-term drought at the Colorado River Basin, efficient use of irrigation water is one of the highest conservation priorities in the region. This study aims to present some of current irrigation technologies and management approaches in the low desert and assess the viability and potential of these water management practices. The results of several field experiments are used to assess five water conservation practices of sub-surface drip irrigation, automated surface irrigation, sprinkler irrigation, tail-water recovery system, and deficit irrigation strategy. The preliminary results of several ongoing studies at commercial fields are presented, particularly researches in alfalfa, sugar beets, kliengrass, sunflower, and spinach fields. The findings indicate that all these practices have significant potential to conserve water (an average of 1 ac-ft/ac) and enhance the efficiency of water use (15-25%). Further work is needed to better understand the feasibility of each of these applications and to help maintain profitable and sustainable agricultural production system in the low desert as water and labor costs, and environmental issues increase.

Keywords: automated surface irrigation, deficit irrigation, low desert of California, sprinkler irrigation, sub-surface drip irrigation, tail-water recovery system

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Authors: Cecilia Kunseh Betek

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Managing rural water supply systems effectively and efficiently is a challenge in the O R Tambo District Municipality due to the long distances between consumers and municipal centres. This is a couple with the low income of most residents and the government's policy of free basic water which is making rural water provision very difficult. With regard to cartage, the results reveal that the majority (84.4%) of the population covers distances of about 1kilometre to fetch water, and 15.6% travel up kilometer to access water facilities. This means that the water sources are located very far from households, outside the officially legislated array of 200metres. These are many reasons to account for this situation. Firstly, this implies that there are inadequate stand pipes to cater for all the homesteads scattered across the rugged terrain of OR Tambo District municipality. Secondly, and following from the first explanation, it would be seen that funding that is made available is not adequate, or is not efficiently spent on the targeted projects. The situation in the rural areas of South Africa is fraught with cumbersome complexity when it comes to service delivery.

Keywords: water, management, government, rural

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Authors: Luyao Liu, Dekui Yuan, Xu Li

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As one of the most important bays of China, the water exchange capacity of Bohai Bay can influence the economic development and urbanization of surrounding cities. However, the rapid reclamation has influenced the weak water exchange capacity of this semi-enclosed bay in recent years. This paper sets two hydrodynamic models of Bohai Bay with two shorelines before and after reclamation. The mean value and distribution of Turn-over Time, the distribution of residual current, and the feature of the tracer path are compared. After comparison, it is found that Bohai Bay keeps these characteristics; the spending time of water exchange in the northern is longer than southern, and inshore is longer than offshore. However, the mean water exchange time becomes longer after reclamation. In addition, the material spreading is blocked because of the inwardly extending shorelines, and the direction changed from along the shoreline to towards the center after reclamation.

Keywords: Bohai Bay, water exchange, reclamation, turn-over time

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Authors: S. A. Che Osmi, W. M. F. W. Ishak, S. F. Che Osmi

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Nowadays the issues of water quality and water pollution have been a major problem across the country. A lot of management attempt to develop their own TMDL database in order to control the river pollution. Over the past decade, the mathematical modeling has been used as the tool for the development of TMDL. This paper presents the application of water quality modeling to develop the total maximum daily load (TMDL) information. To obtain the reliable database of TMDL, the appropriate water quality modeling should choose based on the available data provided. This paper will discuss on the use of several water quality modeling such as QUAL2E, QUAL2K, and EFDC to develop TMDL. The attempts to integrate several modeling are also being discussed in this paper. Based on this paper, the differences in the application of water quality modeling based on their properties such as one, two or three dimensional are showing their ability to develop the modeling of TMDL database.

Keywords: TMDL, water quality modeling, QUAL2E, EFDC

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Authors: Emery Jr. Coppola

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Water resources are being depleted and degraded at an alarming and non-sustainable rate worldwide. In some areas, it is progressing more slowly. In other areas, irreversible damage has already occurred, rendering regions largely unsuitable for human existence with destruction of the environment and the economy. Today, 2.5 billion people or 36 percent of the world population live in water-stressed areas. The convergence of factors that created this global water crisis includes local, regional, and global failures. In this paper, a survey of some of these factors is presented. They include abuse of political power and regulatory acquiescence, improper planning and design, ignoring good science and models, systemic failures, and division between the powerful and the powerless. Increasing water demand imposed by exploding human populations and growing economies with short-falls exacerbated by climate change and continuing water quality degradation will accelerate this growing water crisis in many areas. Without regional measures to improve water efficiencies and protect dwindling and vulnerable water resources, environmental and economic displacement of populations and conflict over water resources will only grow. Perhaps more challenging, a global commitment is necessary to curtail if not reverse the devastating effects of climate change. Factors will be illustrated by real-world examples, followed by some partial solutions offered by water experts for helping to mitigate the growing water crisis. These solutions include more water efficient technologies, education and incentivization for water conservation, wastewater treatment for reuse, and improved data collection and utilization.

Keywords: climate change, water conservation, water crisis, water technologies

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Authors: Oseni Taiwo Amoo, Bloodless Dzwairo

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In this paper, we extend the versatility and usefulness of GIS as a methodology for any river basin hydrologic characteristics analysis (HCA). The Gurara River basin located in North-Central Nigeria is presented in this study. It is an on-going research using spatial Digital Elevation Model (DEM) and Arc-Hydro tools to take inventory of the basin characteristics in order to predict water abstraction quantification on streamflow regime. One of the main concerns of hydrological modelling is the quantification of runoff from rainstorm events. In practice, the soil conservation service curve (SCS) method and the Conventional procedure called rational technique are still generally used these traditional hydrological lumped models convert statistical properties of rainfall in river basin to observed runoff and hydrograph. However, the models give little or no information about spatially dispersed information on rainfall and basin physical characteristics. Therefore, this paper synthesizes morphometric parameters in generating runoff. The expected results of the basin characteristics such as size, area, shape, slope of the watershed and stream distribution network analysis could be useful in estimating streamflow discharge. Water resources managers and irrigation farmers could utilize the tool for determining net return from available scarce water resources, where past data records are sparse for the aspect of land and climate.

Keywords: hydrological characteristic, stream flow, runoff discharge, land and climate

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Authors: Zeinab Syed Abdel Rehim

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Water shortage is considered as one of the huge problems the world encounter now. Water desalination is considered as one of the more suitable methods governments can use to substitute the increased need for potable water. The humidification-dehumidification process for water desalination is viewed as a promising technique for small capacity production plants. The process has several attraction features which include the use of sustainable energy sources, low technology, and low-temperature dehumidification. A pilot experimental set-up plant was constructed with the conventional HVAC components such as air blower that supplies air to an air duct inside which air preheater, steam injector and cooling coil of a small refrigeration unit are placed. The present work evaluates the characteristics of humidification-dehumidification process for water desalination as a function of air flow rate, total power input and air inlet temperature in order to study the optimum conditions required to produce distilled water.

Keywords: condensation, dehumidification, evaporation, humidification, water desalination

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Authors: V. Sobotková, B. Šarapatka, M. Dumbrovský, J. Uhrová, M. Bednář

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The paper deals with the influence of implemented conservation measures on the quality of surface water resources. Recently, a new process of complex land consolidation in the Czech Republic has provided a unique opportunity to improve the quality of the environment and sustainability of crop production by means of better soil and water conservation. The most important degradation factor in our study area in the Hubenov drinking water reservoir catchment basin was water erosion together with loss of organic matter. Hubenov Reservoir water resources were monitored for twenty years (1990–2010) to collect water quality data for nitrate nitrogen (N-NO3-), total P, and undissolved substances. Results obtained from measurements taken before and after land consolidation indicated a decrease in the linear trend of N-NO3- and total P concentrations, this was achieved through implementation of conservation measures limiting soil degradation in the Hubenov reservoir catchment area.

Keywords: complex land consolidation, degradation, land use, soil and water conservation, surface water resources

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Authors: Abdullah Ay, Şehnaz Şener

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It is of great importance to reveal their current status and conduct research in this direction for the sustainable use and protection of lakes, which are among the most important water resources for meeting water needs and ensuring ecological balance. In this context, the purpose of this study is to determine the hydrogeochemical properties, as well as water quality and usability characteristics of Işıklı Lake within the Lakes Region of Turkey. Işıklı Lake is a tectonic lake located in the Aegean Region of Turkey. The lake has a surface area of approximately 36 km². Temperature (T), electrical conductivity (EC) and hydrogen ion concentration (pH), dissolved oxygen (%, mg/l), Oxidation Reduction Potential (ORP; mV), and amount of dissolved solids in water (TDS; mg/l) of water samples taken from the lake values were determined by in situ analysis. Major ion and heavy metal analyses were carried out under laboratory conditions. Additionally, the relationship between major ion concentrations and TDS values of Işıklı Lake water samples was determined by correlation analysis. According to the results obtained, it is seen that especially Mg, Ca and HCO₃ ions are dominant in the lake water, and it has been determined that the lake water is in the Ca-Mg-HCO₃ water facies. According to statistical analysis, a strong and positive relationship was found between the TDS value and bicarbonate and calcium (R² = 0.61 and 0.7, respectively). However, no significant relationship was detected between the TDS value and other chemical elements. Although the waters are generally in water quality class I, they are in class IV in terms of sulfur and aluminum. It is included in the water quality class. This situation is due to the rock-water interaction in the region. When the analysis results of the lake water were compared with the drinking water limit values specified by TSE-266 (2005) and WHO (2017), it was determined that it was not suitable for drinking water use in terms of Pb, Se, As, and Cr. When the waters were evaluated in terms of pollution, it was determined that 50% of the samples carried pollution loads in terms of Al, As, Fe, NO3, and Cu.

Keywords: Işıklı Lake, water chemistry, water quality, pollution, arsenic, Denizli

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Authors: Sherine A. El Baradei

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Global warming and climatic change are very important topics that are being studied and investigated nowadays as they have lots of diverse impacts on mankind, water quality, aquatic life, wildlife,…etc. Also, many water and hydraulics structures like dams and barrages are being built every day to satisfy water consumption needs, irrigation purposes and power generating purposes. Each of global warming and water structures alone has diversity of impacts on water quality and aquatic life in rivers. This research is investigating the dual combined effect of both water structures and global warming on the water quality and aquatic life through mathematical modeling. A case study of the Esna Barrage on the Nile River in Egypt is being studied. This research study is taking into account the effects of both seasons; namely, winter and summer and their effects on air and hence water temperature of the Nile reach under study. To do so, the study is conducted on the last 23 years to investigate the effect of global warming and climatic change on the studied river water. The mathematical model is then combining the dual effect of the Esna barrage and the global warming on the water quality; as well as, on aquatic life of the Nile reach under study. From the results of the mathematical model, it could be concluded that the dual effect of water structures and global warming is very negative on the water quality and the aquatic life in rivers upstream those structures.

Keywords: aquatic life, barrages, climatic change, dissolved oxygen, global warming, river, water quality, water structures

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Authors: Hyun-Woo Cho

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Detection of incipient abnormal events in production processes is important to improve safety and reliability of manufacturing operations and reduce losses caused by failures. The construction of calibration models for predicting faulty conditions is quite essential in making decisions on when to perform preventive maintenance. This paper presents a multivariate calibration monitoring approach based on the statistical analysis of process measurement data. The calibration model is used to predict faulty conditions from historical reference data. This approach utilizes variable selection techniques, and the predictive performance of several prediction methods are evaluated using real data. The results shows that the calibration model based on supervised probabilistic model yielded best performance in this work. By adopting a proper variable selection scheme in calibration models, the prediction performance can be improved by excluding non-informative variables from their model building steps.

Keywords: calibration model, monitoring, quality improvement, feature selection

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Authors: Xiangtuo Chen, Paul-Henry Cournéde

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Crop yield prediction is a paramount issue in agriculture. The main idea of this paper is to find out efficient way to predict the yield of corn based meteorological records. The prediction models used in this paper can be classified into model-driven approaches and data-driven approaches, according to the different modeling methodologies. The model-driven approaches are based on crop mechanistic modeling. They describe crop growth in interaction with their environment as dynamical systems. But the calibration process of the dynamic system comes up with much difficulty, because it turns out to be a multidimensional non-convex optimization problem. An original contribution of this paper is to propose a statistical methodology, Multi-Scenarios Parameters Estimation (MSPE), for the parametrization of potentially complex mechanistic models from a new type of datasets (climatic data, final yield in many situations). It is tested with CORNFLO, a crop model for maize growth. On the other hand, the data-driven approach for yield prediction is free of the complex biophysical process. But it has some strict requirements about the dataset. A second contribution of the paper is the comparison of these model-driven methods with classical data-driven methods. For this purpose, we consider two classes of regression methods, methods derived from linear regression (Ridge and Lasso Regression, Principal Components Regression or Partial Least Squares Regression) and machine learning methods (Random Forest, k-Nearest Neighbor, Artificial Neural Network and SVM regression). The dataset consists of 720 records of corn yield at county scale provided by the United States Department of Agriculture (USDA) and the associated climatic data. A 5-folds cross-validation process and two accuracy metrics: root mean square error of prediction(RMSEP), mean absolute error of prediction(MAEP) were used to evaluate the crop prediction capacity. The results show that among the data-driven approaches, Random Forest is the most robust and generally achieves the best prediction error (MAEP 4.27%). It also outperforms our model-driven approach (MAEP 6.11%). However, the method to calibrate the mechanistic model from dataset easy to access offers several side-perspectives. The mechanistic model can potentially help to underline the stresses suffered by the crop or to identify the biological parameters of interest for breeding purposes. For this reason, an interesting perspective is to combine these two types of approaches.

Keywords: crop yield prediction, crop model, sensitivity analysis, paramater estimation, particle swarm optimization, random forest

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Authors: Yang Zhou, Heli Sun, Jianbin Huang, Jizhong Zhao, Shaojie Qiao

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Traffic prediction is a fundamental problem in urban environment, facilitating the smart management of various businesses, such as taxi dispatching, bike relocation, and stampede alert. Most earlier methods rely on identifying the intrinsic spatial-temporal correlation to forecast. However, the complex nature of this problem entails a more sophisticated solution that can simultaneously capture the mutual influence of both adjacent and far-flung areas, with the information of time-dimension also incorporated seamlessly. To tackle this difficulty, we propose a new multi-phase architecture, DSTDS (Dual Spatial-Temporal Data Scheme for traffic prediction), that aims to reveal the underlying relationship that determines future traffic trend. First, a graph-based neural network with an attention mechanism is devised to obtain the static features of the road network. Then, a multi-granularity recurrent neural network is built in conjunction with the knowledge from a grid-based model. Subsequently, the preceding output is fed into a spatial-temporal super-resolution module. With this 3-phase structure, we carry out extensive experiments on several real-world datasets to demonstrate the effectiveness of our approach, which surpasses several state-of-the-art methods.

Keywords: traffic prediction, spatial-temporal, recurrent neural network, dual data scheme

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Authors: Volkmar Nolting

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Fatigue crack growth prediction has become an important topic in both engineering and non-destructive evaluation. Crack propagation is influenced by the mechanical properties of the material and is conveniently modelled by the Paris-Erdogan equation. The critical crack size and the total number of load cycles are calculated. From a Larson-Miller plot the maximum operational temperature can for a given stress level be determined so that failure does not occur within a given time interval t. The study is used to determine a reasonable inspection cycle and thus enhances operational safety and reduces costs.

Keywords: fracturemechanics, crack growth prediction, lifetime of a component, structural health monitoring

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Authors: Prince Amartey

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Water is critical to public health, quality of life, environmental preservation, economic activity, and long-term growth. In this environment, it is critical to ensure the ongoing improvement of all processes and practices that contribute to the quality and safety of water. Water safety plans (WSPs) developed by water companies are an essential public policy instrument for achieving these objectives. This manuscript examines international evidence of water safety planning adoption and implementation and reports on the current situation in Portugal as part of the necessary adaptation of the national legal framework to the publication of the Directive on water quality for human consumption. The goal is to take lessons from various successful WSP projects throughout the world while writing new legislation in Ghana and elsewhere. According to the findings, four crucial aspects and key factors of success in establishing and implementing WSPs exist commitment from leadership, technical proficiency, administration, and cooperation among agencies.

Keywords: safe drinking, risk, policy, implementation

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Authors: Abdou Khafor Ndiaye

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The article examines clean water and sanitation in Saint-Louis region schools. It finds that 59% have clean water, with disparities between departments, urban/rural areas, and school types. Podor and Dagana lack water due to distance and costs. 70% have sanitation, but rural schools lack it due to low investment. Podor and Dagana suffer the most. Many sanitation facilities need renovation. Wastewater treatment is effective, reducing pollutants and nitrogen, but adjustments are needed for nitrates. Treated water meets Senegalese standards and can be used for irrigation but needs monitoring for strict standards. In conclusion, the wastewater system is good for regions with limited water. Meeting stricter European standards and monitoring for health and environmental standards are needed.

Keywords: water, constructed wetland, sanitation, hygiene

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Authors: Emmanuel Sachikumba, Micheal Msoni, Westone Mafuleka

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Zambia has a good climate with favourable rainfall pattern; this provides sufficient recharge for the surface and groundwater resources. In spite of the sufficient surface and ground water resources, accessibility to water at household levels is problematic both in quality and quantity. The study examined water accessibility as well as water quality at the household level. The research looked at the sources of water for the households and considered the complications of accessibility to water and the available opportunities therein. The investigation involved fifty households and the data was collected by the use of questionnaires (to assess accessibility) and laboratory tests (for ascertaining water quality). In addition to this, government departments such as the health, agriculture, forestry and education as well as the municipal council were interviewed on the topic under study. The study was descriptive in nature where clustered sampling procedures using simple random methods were utilised to select the households which were to participate in the study. The key findings were that; accessibility to water household levels is still a challenge in the settlement as most of the point sources (shallow wells, the stream and the river) were found to be contaminated. In addition to this, it was found that there was no direct relationship between the economic performance of a household and the accessibility to water. The study also observed that there were opportunities for the people in the settlement as they were increasingly getting into the education system, and adult literacy was being encouraged in the settlement. Furthermore, the settlement has groundwater resources which indicate that there can be sufficient water provision for the settlers.

Keywords: accessibility, household, water, settlement

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Authors: S. Adjiri-Bailiche, S. M. Boudia, H. Daaou, S. Hadouche, A. Benzaoui

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In this work the study of changes in the wind speed depending on the altitude is calculated and described by the model of the neural networks, the use of measured data, the speed and direction of wind, temperature and the humidity at 10 m are used as input data and as data targets at 50m above sea level. Comparing predict wind speeds and extrapolated at 50 m above sea level is performed. The results show that the prediction by the method of artificial neural networks is very accurate.

Keywords: MATLAB, neural network, power low, vertical extrapolation, wind energy, wind speed

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Authors: Sijing Xiong, Ran Su, Lit-Hsin Loo, Daniele Zink

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The kidney is a major target for toxic effects of drugs, industrial and environmental chemicals and other compounds. Typically, nephrotoxicity is detected late during drug development, and regulatory animal models could not solve this problem. Validated or accepted in silico or in vitro methods for the prediction of nephrotoxicity are not available. We have established the first and currently only pre-validated in vitro models for the accurate prediction of nephrotoxicity in humans and the first predictive platforms based on renal cells derived from human pluripotent stem cells. In order to further improve the efficiency of our predictive models, we recently developed a high content screening (HCS) platform. This platform employed automated imaging in combination with automated quantitative phenotypic profiling and machine learning methods. 129 image-based phenotypic features were analyzed with respect to their predictive performance in combination with 44 compounds with different chemical structures that included drugs, environmental and industrial chemicals and herbal and fungal compounds. The nephrotoxicity of these compounds in humans is well characterized. A combination of chromatin and cytoskeletal features resulted in high predictivity with respect to nephrotoxicity in humans. Test balanced accuracies of 82% or 89% were obtained with human primary or immortalized renal proximal tubular cells, respectively. Furthermore, our results revealed that a DNA damage response is commonly induced by different PTC-toxicants with diverse chemical structures and injury mechanisms. Together, the results show that the automated HCS platform allows efficient and accurate nephrotoxicity prediction for compounds with diverse chemical structures.

Keywords: high content screening, in vitro models, nephrotoxicity, toxicity prediction

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Authors: Peter G. Youssef, Saad M. Mahmoud, Raya K. AL-Dadah

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Many water desalination technologies have been developed but in general they are energy intensive and have high cost and adverse environmental impact. Recently, adsorption technology for water desalination has been investigated showing the potential of using low temperature waste heat (50-85oC) thus reducing energy consumption and CO2 emissions. This work mathematically compares the performance of an adsorption cycle that produces two useful effects namely, fresh water and cooling using two different adsorbents, silica-gel and an advanced zeolite material AQSOA-ZO2, produced by Mitsubishi plastics. It was found that at low chilled water temperatures, typically below 20oC, the AQSOA-Z02 is more efficient than silica-gel as the cycle can produce 5.8 m3 of fresh water per day and 50.1 Rton of cooling per tonne of AQSOA-ZO2. Above 20oC silica-gel is still better as the cycle production reaches 8.4 m3 per day and 62.4 Rton per tonne of silica-gel. These results show the potential of using the AQSOA-Z02 at low chilled water temperature for water desalination and cooling applications.

Keywords: adsorption, desalination, refrigeration, seawater

Procedia PDF Downloads 495

Authors: Dnyandip K. Bhamare, Manish K Rathod, Jyotirmay Banerjee

Abstract:

This paper aims to study performance of a thermosiphon solar water heating system with the help of the proposed analytical model. This proposed model predicts the temperature and mass flow rate in a thermosiphon solar water heating system depending on radiation intensity and ambient temperature. The performance of the thermosiphon solar water heating system is evaluated in the Indian context. For this, eight cities in India are selected considering radiation intensity and geographical positions. Predicted performance at various cities reveals the potential for thermosiphon solar water in India.

Keywords: solar water heater, collector outlet temperature, thermosyphon, India

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Authors: Yingkun Huang, Li Guo, Zekang Lan, Kai Tian

Abstract:

Hard disk drives (HDD) failure of the exascale supercomputing system may lead to service interruption and invalidate previous calculations, and it will cause permanent data loss. Therefore, initiating corrective actions before hard drive failures materialize is critical to the continued operation of jobs. In this paper, a highly accurate analysis model based on CNN-LSTM and oversampling technique was proposed, which can correctly predict the necessity of a disk replacement even ten days in advance. Generally, the learning-based method performs poorly on a training dataset with long-tail distribution, especially fault prediction is a very classic situation as the scarcity of failure data. To overcome the puzzle, a new oversampling was employed to augment the data, and then, an improved CNN-LSTM with the shortcut was built to learn more effective features. The shortcut transmits the results of the previous layer of CNN and is used as the input of the LSTM model after weighted fusion with the output of the next layer. Finally, a detailed, empirical comparison of 6 prediction methods is presented and discussed on a public dataset for evaluation. The experiments indicate that the proposed method predicts disk failure with 0.91 Precision, 0.91 Recall, 0.91 F-measure, and 0.90 MCC for 10 days prediction horizon. Thus, the proposed algorithm is an efficient algorithm for predicting HDD failure in supercomputing.

Keywords: HDD replacement, failure, CNN-LSTM, oversampling, prediction

Procedia PDF Downloads 80