bluuebunny/crossref_metadata_2025 huggingface dataset:
Multi Criteria Decision Analysis to Set the Priority of Interventions in Water Distribution Systems
Authors: Bragalli Cristiana , Giansanti Federica , Zingali Lorenzo , Montanari Alberto
Published: September 2018

Water distribution systems play a fundamental role due to their impact on public health, food, agriculture and energy and consequently, they are identified as critical infrastructures. Integrated urban water management is affected by critical issues that may interfere with the achievement of the best management practice. The work shows a methodology for the identification of interventions priorities in a region where several water distribution systems, with different criticalities, coexist. As metric for critical issues, IWA PIs has been chosen. Multi-criteria Decision Analysis (MCDA) is applied to obtain a sorting of critical issues and thus to define the priorities in the investment planning. The aim is to provide a tool that supports the consistency check between criticalities and interventions planning. The methodology has been applied to 15 management areas within an homogeneous region in the North of Italy.
Towards Transient Experimental Water Surfaces: Strengthening Two-Dimensional SW Model Validation
Authors: Martínez-Aranda Sergio , Fernández-Pato Javier , Caviedes-Voullième Daniel , García-Palacín Ignacio , García-Navarro Pilar
Published: September 2018

The measurement and simulation of 2D free-surface shallow flows is carried out in this work. For the experimental study a 3D-sensing device (Microsoft Kinect) is used to measure both steady and transient water surface elevation fields with different flow characteristics. This procedure provides 640x480 px resolution water surface level point clouds with a frequency ranging from 8 Hz to 30 Hz. The experimental measurements are compared with 2D finite volume simulations carried out by means of a robust and well-balanced numerical scheme able to deal with flow regime transitions and wet/dry fronts. A good agreement is found between experimental and numerical results for all the cases studied, demonstrating the capability of the RGB-D sensor to capture the water free-surface position accurately. This new experimental technique, which allows us to obtain 2D water depth fields in open- channel flows, leads to a wide range of promising capabilities in order to validate new shallow water models and to improve their accuracy and performance.
Influence of Climate Change on the Optimization of Water Supply Systems
Authors: Maiolo Mario , Mendicino Giuseppe , Pantusa Daniela , Senatore Alfonso , Sousa Joaquim
Published: September 2018

In the last decades, climate change is affecting several aspects of human and natural systems worldwide. Concerning water resources, the main impacts are related to the combined effect of temperature increase and changes in availability and distribution of precipitation, which affects both quantity and quality. The Mediterranean is potentially very sensitive to climate change. In Calabria (Southern Italy) the projected reduction suggests a particular care in matching water resource availability and needs. In this paper, the province of Crotone in Calabria was analyzed as a study case. This area is characterized by a sufficient availability of resources as a whole when compared with the needs of the users, but with an unbalanced distribution through its networks. This condition requires the identification of a resource allocation optimization solution. Using a least-cost optimization model, water resource optimization solutions were identified and compared starting from a review of the existing water supply systems, taking into account both current water availability and possible future availability due to climate change.
Distributed Hydrological Model Application for Estimating the Groundwater Resource at Cu De River Catchment, Viet Nam
Authors: Vo Ngoc Duong , Nguyen Quang Binh , Gourbesville Philippe
Published: September 2018

Groundwater is a fundamental component in the water balance of any watershed. It affects considerably on flow regime, especially on base flow. However, it is not easy to survey this component, notably towards the lack of data catchment and developping countries. This study is to present a new approach to overcome the limitation in simulating the ground water. By using the deterministic distributed hydrological model, the study is hope to provide basic information about ground water for a catchment in Vietnam coastal central region, Cu De river catchment. The modelling is realized for an area of 425.2 km2 in period of 2006 – 2010. The results are analyzed in many aspects such as: groundwater spatial distribution, groundwater flow process, groundwater storage, and groundwater recharged volume.
Assessment of Irrigation Water Use Patterns Using Remote Sensing Data in Mexico’s Northeast
Authors: Arciniega Saul , Breña-Naranjo Jose A. , Pedrozo-Acuña Adrián , Hernández-Espriú Antonio
Published: September 2018

Irrigation water use (IWU) or withdrawal is a key component for the water management of a region since it tends to exceed the crops consumptive water use, especially in water-stressed regions where groundwater is the main source of water. Nevertheless, temporal IWU information is missing in many irrigation areas. Remote sensing (RS) data is commonly used for crop water requirements estimations in areas with lack of data, however, IWU is more complex to approach since it also depends on water use efficiency, irrigation system type, irrigation scheduling, and water availability, among others. This work explores the use of remote sensing data (TRMM, MODIS) and land surface hydrological products (GLDAS 2 and MERRA 2) to obtain insights about the space-time annual IWU patterns across croplands located within Mexico’s northeast region. Reported IWU in three irrigation districts (Don Martín, Región Lagunera and Bajo Río Bravo) was used to obtain a functional model using satellite data derived. Results suggest strong relationship between reported IWU with soil moisture content from GLDAS and the maximum annual EVI from MODIS, where a potential regression shown statistical correlations of 0.83 and 0.77, respectively.
Experimental Study on Sorption and Desorption of NaCl to Sand Using a Physical Model
Authors: Mardani Zahra , Ebrahimi Kumars , Jafari Ali
Published: September 2018

In many parts of our planet, salinity has caused numerous problems in the production of goods, especially in arid and semi-arid areas, which account for one third of the planet's surface area. The main purpose of this article is to investigate the NaCl’s adsorption to and desorption from saturated porous media of sand. The NaCl solutions with the concentrations of 2.5, 5 and 10 g/l, and three types of soil textures with the weights of 50, 100 and 200g were used as samples of the experiments. The samples were placed in capped containers. The salinity of the solutions was measured using an EC-metre at 1, 2, 4, 7 and 24 hours from the beginning of the experiment. The results indicated that in the soils with less weight, the adsorption of sodium ions were more, and as soil weight increased, the adsorption of ions decreased, and finally the adsorption phenomenon was departed. Over time, the process of adsorption and desalination eventually stopped.
On the Calibration of the Mathematical Laws for the Water Loss Estimation in Water Distribution Network
Authors: De Marchis Mauro , Milici Barbara
Published: September 2018

The definition of the relationship between the leak outflow, the total head at the leak and other relevant parameters such as the pipe stiffness, the leak dimension and shape has been object of extensive studies in recent decades. The use of the Torricelli equation has been questioned, because some experimental results showed that it can yield unsatisfactory results, and other formulations have been suggested to model water leakages in water distribution networks (WDNs). To investigate the effectiveness of the formulations suggested by different authors, an experimental campaign was carried out at the Environ- mental Hydraulic Laboratory of the University of Enna (Italy) for leaks of different shape and size in polyethylene pipes.
An Innovative ICT Solution for Sewer Systems
Authors: Grau Antoni , Bolea Yolanda , Sanfeliu Alberto , Puig-Pey Ana
Published: September 2018

The objective of this paper is to explain the importance of research in wastewater transportation (sewage systems) using new technologies such as robotics systems and information and communication technologies (ICTs). ECHORD++ (European Coordination Hub for Open Robotics Development) is a very useful tool to foster this research and to meet needs and solutions. In this paper, authors explain the tool as well as the methodology to promote robotics research in urban environments, and the on-going experience will demonstrate that huge advances are made in this field.
Variability of Rainfall in the Semi-Arid Region of Brazil
Authors: Santos Celso , Galvão Carlos , Brasil Neto Reginaldo , Meneses Isabel
Published: September 2018

The Brazilian semi-arid region presents a highly variable rainfall regime in space and time. Although the mechanisms of rainfall have been well described and numerically modelled, reliable forecasts for more than six months in advance cannot be produced yet, as well as projections of climate change in the long term. This paper contributes to the understanding of the variability examining a more than 100-year time series of a rainfall gauge in this region, using three techniques: wavelet analysis, Mann- Kendall and Sen tests. The techniques allow the description of the patterns of variability of rainfall and suggest that there is not still a clear evidence of climate change.
Real-Time Quality Control and Infilling of Precipitation Data Using Neural Networks
Authors: Moslemi Mohammadreza , Joksimovic Darko
Published: September 2018

Due to advancements in instrumentation and communication technologies, monitoring of water infrastructure is experiencing a significant growth worldwide and water managers are increasingly deploying monitoring equipment for decision-making purposes. Hydrological events and relevant datasets including rainfall data are of a complex nature and are potentially susceptible to errors from various sources. Hence, it is essential to develop efficient methods for the quality control of the acquired data. The present work introduces an artificial neural network-based approach for real-time quality control and infilling of rain gauge data. Available rainfall measurements from neighboring rain gauges are employed to train and develop the neural network model. Trained artificial neural network model was able to validate up to about 97% of the data using 95% confidence intervals. This finding suggests that artificial neural networks can be successfully implemented for erroneous data identification/correction and reconstruction of missing data points. Given its short processing time and reportedly superior performance to traditional quality control strategies, neural network methodology can be deployed as an efficient tool for the processing and control of large sets of timeseries with complex natures including precipitation data.
Enhancing Automated Water Level Control at Navigable Waterways by High-Resolution Weather Predictions
Authors: Kasper Julia , Pranner Georg , Simons Franz , Denhard Michael , Thorenz Carsten
Published: September 2018

Heavy rainfall can cause large variations in the water level of navigable waterways when a lot of urban runoff is generated on sealed surfaces and discharged into the river. Due to climate change, extreme weather events will increase in intensity and frequency demanding a better automated water level control at impounded waterways. High- resolution forecasts of catchment rainfall are intended to serve as input to a rainfall- runoff model. Based on the resulting discharge forecasts, a model predictive feed forward controller calculates the ideal water level and discharge across the barrage. The control system is completed by a PI control loop. In this way water level deviations and discharge peaks resulting from stormwater overflow events can be reduced, which enhances the safety of shipping. Regarding the uncertainties of weather predictions, the consequences of an underestimated or overestimated overflow discharge are investigated.
Validation of a Model for Operation Optimization of a Regional Water Supply System
Authors: Arena Claudio , Cannarozzo Marcella , Fortunato Antonino , Lombardo Alessio , Scolaro Ignazio , Mazzola Mario Rosario
Published: September 2018

Sustainable use of water resources requires a modern approach for complex water systems management based on system’s modeling, as unsung operation alternatives may only be devised and tested through a model. The now available IT computing tools enable setting the traditional modelling methodologies for planning and operation of such systems in a new framework. The present work deals with the development of decision support models for optimizing the operation of complex water supply systems with multiple uses and focuses on the validation of the optimization model of the regional water supply systems managed by an Italian water utility. The software used is Aquator, a state-of-the-art commercial tool for generic water resources system simulation and operational optimization. The paper shows and comments the results of the validation of the model and uses them to draw some general principles for the validation of such kind of models: in fact, operational optimization models are conceived for the enhancement of systems management and performance. Consequently, while on the one side model output is expected to reflect the actual state of the system, on the other it can point out significant management enhancements.
Prediction of Water Quality Variation Affected by Tributary Inputs in large Rivers Using ANN Model
Authors: Seo Il Won , Yun Se Hun
Published: September 2018

In this study, an enhanced ANN model was developed to analyze the water quality variation at the river confluence by incorporating the resilient propagation algorithm to increase the model accuracy. An ensemble modeling with stratified sampling method was also developed in order to reduce the influence of the input data and model parameters on the prediction of river water quality. The water quality parameters such as pH, electric conductivity (EC), DO and chlorophyll-a, were predicted using proposed ANN model in the large river which is affected by pollutant inputs from the tributary river. The results of model simulation showed that the pollutant input from the tributary affected the water quality of the mainstream. The model prediction using water quality data of the tributary river as the input data in addition to the mainstream data produced better results than the simulation using mainstream data only, especially for EC and DO, R2 value was improved by 30.9% and 20.6%, respectively.
Real-Time Flood Forecasting and Regulation System of Poyanghu Lake Basin in China
Authors: Xiaoming Jiang , Xiaoyan He , Liuqian Ding , Jiren Li , Hui Li , Fuxin Chai , Guangyuan Kan , Zhongbo Zhang , Fan Wang , Minglei Ren
Published: September 2018

The design and development of Flood Forecasting and Regulation System (FFRS) is an important part of non-structural measures for flood mitigation, and Browser/Server (B/S) system based on WEB technology is one of the main directions of the system development. The framework of FFRS based on B/S system is introduced in this paper, which includes four levels, i.e. the database level, application support platform level, the application level and the user level. The framework can provide several functions, such as flood situation analysis, flood forecasting, flood regulation and system management, which has been used for the FFRS development of Poyanghu Lake Basin in China as technical support for decision making of local flood control. Currently, the system covers almost 102 flood forecast points and 37 reservoirs, for which flood forecasts and regulations are accessible online. This work would also be demonstration for other locations.
Uncertainty Estimations in Different Components of a Hybrid ANN - Fuzzy - Kriging Model for Water Table Level Simulation
Authors: Tapoglou Evdokia , Varouchakis Emmanouil A. , Karatzas George P.
Published: September 2018

The purpose of this study is to examine the uncertainty of a combined artificial neural network (ANN), kriging and fuzzy logic methodology, which can be used for spatial and temporal simulation of hydraulic head in an aquifer. This methodology was applied in the past, while the verification of the model was performed by implementing it in a new study area, in Miami – Dade County, FL, USA. The percentile methodology was applied as a first approach in order to define the ANN uncertainty. As a second approach, the uncertainty of the ANN training is tested through a Monte Carlo procedure. The model was executed 300 times using different training set and initial random values each time. The training results constituted a sensitivity analysis of the ANN training to the kriging part of the algorithm. The training and testing error intervals for the ANNs and the kriging prediction intervals calculated through this procedure can be considered narrow compared to the complexity of the study area. For the third and final approach used in this work, the uncertainty of kriging parameter was calculated through the Bayesian kriging methodology. The results derived can prove that the simulation algorithm can provide consistent and accurate results.
Emerging Pollutants in Developing Countries: Optimising Sustainable Treatment Solutions
Authors: Visanji Zara , Sadr Seyed M.K. , Johns Matthew , Savic Dragan , Memon Fayyaz A.
Published: September 2018

Over the past decade the research surrounding the occurrence, source, fate and removal of emerging pollutants has been increasing. The aim of this study was to create an add-on program which analyses the removal of emerging pollutants, to an existing decision support tool (WiSDOM). The tool was also used to evaluate the performance of each optimal solution in terms of removal of conventional pollutants using Multi Objective Genetic Algorithms and Multi Criteria Decision Analysis. Information was collated regarding minimum and maximum concentrations of emerging pollutants for surface water, groundwater, untreated wastewater, drinking water and treated wastewater. This information was used to populate an Excel Spreadsheet Program (ESP) which analysed the removal efficiencies of 13 different emerging pollutants for 42 wastewater treatment unit processes. The ESP is incorporated into the WiSDOM tool to allow the tool to calculate the removal of emerging pollutants. Three main scenarios were created to test the application of the tool and ESP. Scenario 1 focussed on the removal of emerging pollutants from from areas effected by tourism at different scales. Scenario 2 looked at the treatment suited for the removal of emerging pollutants from different socio- economic regions. Lastly, Scenario 3 looked at removing emerging pollutants from hospital and industrial wastewater. The scenarios were focused on wastewater treatment in India and investigated the removal of 13 emerging pollutants commonly found in India.
Capitalizing RFID Technology as Cost-Effective Real-Time Process Monitoring Tool in Wastewater Treatment: Two Case Studies
Authors: Wouters Johannus Wilhelmus , Seelam Jai Sankar , Agema Klas Jan
Published: September 2018

The legislative norms for treated wastewater diffuse in terms of nitrogen (N) and phosphorus (P) concentrations are becoming increasingly stringent in the EU region. Compliance with the consent values compelled the water authorities to implement moving bed biofilters (MBFs) for tertiary stage effluent polishing. However, on-site and field surveys reveal that numerous MBF units suffer from non-optimal operational conditions, logistical challenges and irregular monitoring. This makes meeting the N-P criterion quite a challenging and expensive affair. It is therefore important to optimize their day-to-day operations, facilitate access to reliable and real-time status updates, and troubleshoot the failures. In this direction, an "internet-of-things", radio frequency ID (RFID) and cloud based monitoring and control tool, Sand-Cycle, was successfully developed, tested and implemented to monitor MBFs. The current study presents full- scale application of the developed remote control and mote technology at two wastewater treatment works. Sand-Cycle illustrated real-time dashboards indicating performance grading factors viz. in-situ average sand circulation rate, active bed volume and filter homogeneity. This presented clear instructions for detected malfunctions and enabled the operators to optimize the MBF output with limited effort. Further technical and technological advancements of such IoT based setups can actively assist in tackling long-term sustainability and wastewater management issues.
Optimal Design of Water Pipeline and Micro-Hydro Turbine by Genetic Algorithm
Authors: Bosco Camillo , Pezzinga Giuseppe , Sinagra Marco , Tucciarelli Tullio
Published: September 2018

The economic value of the potential energy hidden in water resources is becoming more and more relevant for pipe design. In this work a new way to design drinking main waterlines, embedding also the potential hydroelectric production as pipeline benefit, is presented. The optimum design of a cross-flow turbine, on the basis of the available head jump and discharge is first outlined; the description of a genetic algorithm to minimize the total cost (pipeline plus machinery) minus the net benefit (hydropower production) is then presented. Finally, a comparison is carried out among the costs of a case study pipeline assuming a) no hydropower production and traditional design criteria and b) two different scenarios with different values of benefits per unit energy production. The two scenarios lead to hydropower production with constant impeller rotational velocity in one case and with variable impeller rotational velocity in the other one.
Multi-Objective and Multi-Criteria Analysis for Optimal Pump Scheduling in Water Systems
Authors: Carpitella Silvia , Brentan Bruno , Montalvo Idel , Izquierdo Joaquín , Certa Antonella
Published: September 2018

This contribution focuses on the problem of optimal pump scheduling, a fundamental element in pursuing operation optimization of water distribution systems. A combined approach of multi-objective optimization and multi-criteria analysis is herein suggested to first find the Pareto front of non-dominated solutions and then to rank them based on a set of weighted criteria. The Non-Dominated Sorting Genetic Algorithm (NSGA-II) is proposed to solve the multi-objective problem, while the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is used to achieve the final ranking.
Adaptive Multi-Scale Shallow Flow Model: a Wavelet-Based Formulation
Authors: Kesserwani Georges , Sharifian Mohammad Kazem , Shaw James
Published: September 2018

This work outlines the use of wavelet bases to re-formulate a finite volume (FV) local solution of the shallow water equations (SWEs), so as to achieve mesh adaptivity via local compression and truncation of the numerical solution’s details across successive resolution scales with reference to a single threshold error set by the user. The wavelet bases naturally lead to a scalable FV formulation and how they can readily be exploited to achieve adaptive mesh-resolution selection: up-scaling and/or down- scaling by means of the local solutions’ data (i.e. both flow variables and terrain). Our results show a notable promise in using wavelets as a basis for future flood models to achieve conservative and more autonomous simulation at a wide range of length-scales.
Estimation of Streamflow Using Takagi-Sugeno Fuzzy Rule-Based Model
Authors: Akgun Omer Burak , Kentel Elcin
Published: September 2018

In this study, a tool is developed to estimate streamflow at Guvenc River, Ankara by using Takagi-Sugeno

(TS) Fuzzy Rule-Based (RB) model. The model takes precipitation and runoff at time t as predictor (input)

and estimates the runoff at time t + 1. The approach used to generate the TS RB model is based on density

based clustering. Each cluster center is used to generate a fuzzy rule that represents the system behaviour.

Satisfactory results are obtained especially after including the seasonal behaviour of streamflow time series

into the model.
Preliminary GIS Elaborations to Apply Rapid Flood Spreading Models
Authors: Farina Giulia , Bernini Anna , Alvisi Stefano , Franchini Marco
Published: September 2018

Flood risk analysis involves simulating many scenarios from which to draw statistical information about flood extent and depth. Rapid but still sufficiently accurate models enabling flooded areas to be delimited using a DEM have been introduced in the scientific literature. These models, called Rapid Flood Spreading Models (RFSMs), are based on highly simplifying hydraulic assumptions while make large use of GIS information and elaborations. Three different RFSMs are here applied to a test case, largely characterized by flat land. The results obtained are compared with those of a two-dimensional hydraulic model confirming the possibility of preliminarily elaborating topographic GIS data to easily gain geometric information on flooded areas through geospatial analysis.
Parallel Simulations of Shallow Water Solvers for Modelling Overland Flows
Authors: Ginting Bobby Minola , Mundani Ralf-Peter , Rank Ernst
Published: September 2018

In this paper, we simulate overland flows using a cell-centred finite volume (CCFV) method with three solvers – HLLC, central-upwind, and artificial viscosity schemes – and present their parallel efficiency within the framework of our in-house code called NUF- SAW2D. The parallel efficiency is investigated through four explicit time stepping schemes – the first-order Euler and the second, third, and fourth-order Runge Kutta methods. The bed slope terms are solved using a Riemann-solver-free technique and the friction terms are treated semi-implicitly for all time stepping schemes, allowing our model to simulate wet-dry problems with very low water depths on very rough beds. A second-order spatial accuracy is achieved with the Monotonic Upstream-Centred Scheme for Conservation Laws (MUSCL) linear interpolation technique. Since our code is based on an edge-based data structure, the edge-based MinMod limiter function is used to enforce the monotonicity of reconstructed variables. Our code shows accurate results and achieves a good scalability for up to 3.2 million cells or 6.4 million edges using OpenMP parallelisation technique.
A Wave Measurements HF Radar Data Set in the Malta-Sicily Channel: Data Quality, Validation and Gap Filling
Authors: Picone Marco , Orasi Arianna , Drago Aldo , Capodici Fulvio , Ciraolo Giuseppe , Nardone Gabriele , Azzopardi Joel , Gauci Adam , Galea Anthony
Published: September 2018

The CALYPSO HF radar network is a permanent and fully operational observing system currently composed of four CODAR HF stations. The system is providing real- time hourly maps of sea surface currents and wave data in the Malta-Sicily Channel since 2012. Significant wave height derived from the HF radar wave measurements are confirmed to be a reliable source of wave information even in case of extreme events. However, it is noticed that the HF radar wave data are subject to differing interfering noise in the signal from unknown sources that may be competing with transmissions in the same frequency band. These interferences lead to frequent gaps and/or outliers that affect the continuity and reliability of the data set. The aim of this work is to estimate missing values and to detect possible outliers building and fitting a Markov chain mixture model on the significant wave height data collected at the four stations. It is verified that the proposed procedure is sufficiently robust since the model estimates succeed to classify radar observations with a high percentage of missing data and to equally highlight spikes and outliers.
Chaotic Statistical Downscaling (CSD): Application and Comparison in the Bogotá River Basin
Authors: Duarte Freddy , Corzo Gerald , Santos Germán , Hernández Oscar
Published: September 2018

This study presents a new statistical downscaling method called Chaotic Statistical Downscaling (CSD). The method is based on three main steps: Phase space reconstruction for different time steps, identification of deterministic chaos and a general synchronization predictive model. The Bogotá river basin was used to test the methodology. Two sources of climatic information are downscaled: the first corresponds to 47 rainfall gauges stations (1970-2016, daily) and the second is derived from the information of the global climate model MPI-ESM-MR with a resolution of 1,875° x 1,875° daily resolution. These time series were used to reconstruct the phase space using the Method of Time-Delay. The Time-Delay method allows us to find the appropriate values of the time delay and the embedding dimension to capture the dynamics of the attractor. This information was used to calculate the exponents of Lyapunov, which shows the existence of deterministic chaos. Subsequently, a predictive model is created based on the general synchronization of two dynamical systems. Finally, the results obtained are compared with other statistical downscaling models for the Bogota River basin using different measures of error which show that the proposed method is able to reproduce reliable rainfall values (RMSE=73.37).
Entropy Based Multicriterion Evaluation for Rainfall Monitoring Networks under the Impact of Discretization
Authors: Li Heshu , Wang Dong , Singh Vijay P. , Wang Yuankun
Published: September 2018

Rainfall monitoring networks provide fundamental input for hydrological models. Entropy, as a measure of uncertainty or information, is widely used in network evaluation or optimization. Computing entropy requires data discretization with methods like floor function, whereas the parameter selected is crucial and influential. This paper proposed an entropy based multicriterion method for evaluation of rainfall monitoring networks. Two indexes, separately account for information content and redundancy, were integrated with ideal point method. Values of the objective function were then computed to rank the stations and identify the significant ones. To find out the effect of discretization, parameter of the floor function was altered to get different schemes. A rainfall monitoring network containing 95 stations in the western Taihu Lake basin of China was analyzed as case study. Results showed that stations in the northern hilly area are more prominent in the network. Impact of the parameter in floor function is non-negligible as it determines entropy values, including its ranging scale and distribution pattern. Location of the stations rank extremely high and low also varies. As discretization process has an impact on the evaluation, it should be carefully used and sensitivity analysis is needed to avoid subjectivity and arbitrariness.
Building a Nonlinear Relationship Between Dew Point Temperature and Precipitation to Apply a Method to Downscale GCMs Information: Case study in Santa Catarina River Basin, Monterrey
Authors: Del Castillo Castillo Jose Luis , Corzo Perez Gerald A. , Bouwer Laurens , Ramirez Orozco Aldo I. , Bhardwaj Aashish
Published: September 2018

This study will explore the use of a nonlinear relationship between dew point temperature (DPT) and precipitation to apply a method to downscale global circulation models (GCMs) information. Recently, there have been attempts to characterize dew point temperature (DPT) and precipitation intensity. The DPT has shown to be an easier variable to predict, and therefore forecast or prediction on GCM could provide a more reliable estimation. DPT using Clausius-Clapeyron (CC) relationship is one of the methods. This relationship has approximated a non-linear relation into a simple slope coefficient. In a recent study in the Netherlands, DPT was processed by the Advanced Delta Change Method (ADCM) and then converted to precipitation using CC or super CC relation observing better results. In this research work this approach is compared with a non-linear (neural network) model of the relationship. The main contribution of the overall project is to explore the improvement of a better relationship description and how much this could impact in our engineering intensity duration frequency curves. The problem posed is the analysis of the implications of climate change information for civil engineering design in the Metropolitan Area of Monterrey (Santa Catarina River Basin in Mexico).
Interactive Visualisation of Water Distribution Network Optimisation
Authors: Johns Matthew , Walker David , Keedwell Edward , Savic Dragan
Published: September 2018

Evolutionary algorithms have been used to optimize water systems in the literature for over three decades. However, their use for solving real-world water system problems in industry is still very limited. The work presented in this paper details the development of an interactive visualisation client for water distribution network design, which is part of a larger project to bring EAs closer to practicing engineers. The system aims at engaging engineers by actively involving them in the optimization process through the use of advanced visual analytics and novel interactive evolution techniques.
Application of Routine Calibration of Real Water Supply Network with Adjustment of Demand Roughness Parameters Driven by Applied Pressure Real Network of Brazil
Authors: Das Graças Braga Da Silva Fernando , Dias Goulart Thaisa , Mambeli Barros Regina
Published: September 2018

The calibration of water distribution networks is one way to perform such procedures in hydraulic models, but several are the difficulties encountered in calibrating a real network. This work proposes the improvement of modules of the calibration method proposed by Silva (2003), where using the genetic algorithm (GA) search tool, the author calibrates a real water distribution network of a Brazilian city, adjusting parameters mainly from roughness and coefficient of leakage. The enhancement of GA is the introduction of a new decision variable, the nodal demand, which assigns demand values to nodes according to the pressure-driven demand model of Tucciarelli, Criminisi and Termini (1999). The tests of the GAs implemented are tested for this real water distribution network presented by Silva (2003). The effect of the improvement on the calibration results was significant for the network, but the need for more in-depth studies, which are of course required for the application of new algorithms in real-scale networks.
Application of Intelligent Water Network in Water Resource Management: Framework And Case
Authors: Wang Qingming , Zhao Yong , Zhai Jiaqi , Zhu Yongnan , Jiang Shan , He Fan
Published: September 2018

Water security is a global challenge, and intelligent water network is an important way for some countries and companies to solve regional water problems. Intelligent water network is a comprehensive and systematic water management platform, with river and lake water connected as a physical basis, through the introduction and adoption of new frontier information technology aids and advanced water management concepts to achieve water cycle and its associated process system and efficient Control as the goal. This paper studies the framework of intelligent water network, and presents three main elements of water physical network, water information network and water dispatching network, and discusses the case in Beijing.
A Sliding Mode-Based Predictive Strategy for Irrigation Canal Pools
Authors: Oliveira Josenalde , Pinho Tatiana M. , Coelho Joao , Boaventura-Cunha José , Moura Oliveira Paulo
Published: September 2018

This paper evaluates a robust Model Predictive Controller (MPC) based on Sliding Modes (SMPC) for the downstream level control in irrigation canal pools. Its features are compared with the conventional Generalized Predictive Controller (GPC), regarding set point tracking (water level) and output disturbances (offtake discharges). Simulation results suggest feasibility of applying SMPC for gate manipulation, with suitable command signals and robustness.
O processo iconofágico na relação entre o corpo feminino e as imagens midiáticas: o caso Andressa Urach
Authors: Sanches Rodrigo Daniel , Baitello Jr. Norval
Published: September 2018

O presente artigo busca refletir sobre as relações entre o corpo biológico (coagido pela exortação à visibilidade) e o corpo-perfeito que circula no ambiente midiático, partindo do caso amplamente divulgado pela mídia do problema de saúde da modelo Andressa Urach após uma aplicação de hidrogel. Para analisar as transformações corporais vivenciadas pela modelo e noticiadas em escala mundial, adotamos os referenciais teóricos da iconofagia (Baitello, 2005), uma frente de pesquisa antropológica que investiga a atual condição do ser humano numa época em que a proliferação das imagens satura o cotidiano e sua compreensão. O objetivo é discutir e problematizar a representação do corpo feminino no cenário da “beleza midiática” e demonstrar como a iconofagia está presente e se materializa na atualidade em práticas sociais e condutas corporais. A nossa hipótese é a de que as imagens midiáticas sobre o corpo feminino afetam a constituição do sujeito e sua relação com o corpo na atualidade.
O presente artigo busca refletir sobre as relações entre o corpo biológico (coagido pela exortação à visibilidade) e o corpo-perfeito que circula no ambiente midiático, partindo do caso amplamente divulgado pela mídia do problema de saúde da modelo Andressa Urach após uma aplicação de hidrogel. Para analisar as transformações corporais vivenciadas pela modelo e noticiadas em escala mundial, adotamos os referenciais teóricos da iconofagia (Baitello, 2005), uma frente de pesquisa antropológica que investiga a atual condição do ser humano numa época em que a proliferação das imagens satura o cotidiano e sua compreensão. O objetivo é discutir e problematizar a representação do corpo feminino no cenário da “beleza midiática” e demonstrar como a iconofagia está presente e se materializa na atualidade em práticas sociais e condutas corporais. A nossa hipótese é a de que as imagens midiáticas sobre o corpo feminino afetam a constituição do sujeito e sua relação com o corpo na atualidade.
A fenomenologia do videogame
Authors: Bogost Ian
Published: September 2018

Jesper Juul argumentou, convincentemente, que o conflito sobre o objeto adequado de estudo deslocou-se das "regras ou história" para o "jogador ou jogo". Mas um componente-chave dos jogos digitais ainda está ausente em qualquer uma dessas oposições: a do próprio computador. Este artigo oferece um modo de se pensar acerca da fenomenologia do videogame a partir da perspectiva do computador, e não do jogo ou do jogador.
Novo materialismo e não humanização
Authors: Parikka Jussi , Dieter Michael
Published: September 2018

Entrevista com Jussi Parikka por Michael Dieter
Kearifan Lokal Guna Pemecahan Masalah
Authors: Anamofa Jusuf Nikolas
Published: September 2018

Perubahan adalah keniscayaan dalam kehidupan manusia. Perubahan-perubahan yang terjadi bukan saja berhubungan dengan lingkungan fisik, tetapi juga dengan budaya manusia. Hubungan erat antara manusia dan lingkungan kehidupan fisiknya itulah yang melahirkan budaya manusia. Budaya lahir karena kemampuan manusia mensiasati lingkungan hidupnya agar tetap layak untuk ditinggali waktu demi waktu.
Evaluating Rockfish Conservation Areas in Southern British Columbia, Canada using a Random Forest Model of Rocky Reef Habitat
Authors: Haggarty Dana , Yamanaka K. Lynne
Published: September 2018

We developed a rockfish habitat model to evaluate a network of Rockfish Conservation Areas (RCAs) implemented by Fisheries and Oceans Canada to reverse population declines of inshore Pacific rockfishes (Sebastesspp.). We modeled rocky reef habitat in all nearshore waters of southern British Columbia (BC) using a supervised classification of variables derived from a bathymetry model with 20 m^2 resolution. We compared the results from models at intermediate (20 m^2) and fine (5 m^2) resolutions in five test areas where acoustic multibeam echosounder and backscatter data were available. The inclusion of backscatter variables did not substantially improve model accuracy. The intermediate-resolution model performed well with an accuracy of 75%,except in very steep habitats such as coastal inlets; it was used to estimate the total habitat area and the percentof rocky habitat in 144 RCAs in southern BC. We also compared the amount of habitat estimated by our 20 m^2model to the 100 m^2 management model used to designate the RCAs and found that a slightly lower proportion of habitat (18% vs 20%) but a considerably smaller area (400 km^2 vs 1370 km^2) is protected in the RCAs, likely as a result of the poor resolution of the original model. Empirically derived maps of important habitats, such as rocky reefs, are necessary to support effective marine spatial planning and to design and evaluate the efficacy of management and conservation actions.
Predicting impact to assess the efficacy of community‐based marine reserve design
Authors: Smallhorn-West patrick , Bridge Tom C. L. , Malimali Siola'a , Pressey Robert L. , Jones Geoffrey P.
Published: September 2018

During the planning phase the efficacy of different strategies to manage marine resources should ultimately be assessed by their potential impact, or ability to make a difference to ecological and social outcomes. While community‐based and systematic approaches to establishing marine protected areas have their strengths and weaknesses, comparisons of their effectiveness often fail to explicitly address potential impact. Here, we predict conservation impact to compare recently implemented community‐based marine reserves in Tonga to a systematic configuration specifically aimed at maximizing impact. Boosted regression tree outputs indicated that fishing pressure accounted for ∼24% of variation in target species biomass. We estimate that the community‐based approach provides 84% of the recovery potential of the configuration with the greatest potential impact. This high potential impact results from community‐based reserves being located close to villages, where fishing pressure is greatest. These results provide strong support for community‐based marine management, with short‐term benefits likely to accrue even where there is little scope for systematic reserve design.
The effect of ocean acidification on tropical coral calcification: insights from calcification fluid DIC chemistry
Authors: Allison Nicola
Published: September 2018

Ocean acidification typically reduces calcification in tropical marine corals but the mechanism for this process is not understood. We use skeletal boron geochemistry (B/Ca and δ11B) to reconstruct the calcification fluid DIC of corals cultured over both high and low seawater pCO2 (180, 400 and 750 μatm). We observe strong positive correlations between calcification fluid pH and concentrations of the DIC species potentially implicated in aragonite precipitation (be they CO32 , HCO3- or HCO3-+CO32 ). Similarly, with the exception of one outlier, the fluid concentrations of precipitating DIC species are strongly positively correlated with coral calcification rate. Corals cultured at high seawater pCO2 usually have low calcification fluid pH and low concentrations of precipitating DIC, suggesting that a reduction in DIC substrate at the calcification site is responsible for decreased calcification. The outlier coral maintained high pHCF and DICCF at high seawater pCO2 but exhibited a reduced calcification rate indicating that the coral has a limited energy budget to support proton extrusion from the calcification fluid and meet other calcification demands. We find no evidence that increasing seawater pCO2 enhances diffusion of CO2 into the calcification site. Instead the overlying [CO2] available to diffuse into the calcification site appears broadly comparable between seawater pCO2 treatments, implying that metabolic activity (respiration and photosynthesis) generates a similar [CO2] in the vicinity of the calcification site regardless of seawater pCO2.
Do Items Order? The Psychology in IRT Models
Authors: Haaf Julia M. , Merkle Edgar C. , Rouder Jeffrey N.
Published: September 2018

Invariant item ordering refers to the statement that if one item is harder than another for one person, then it is harder for all people. Whether item ordering holds is a psychological statement because it describes how people may qualitatively vary. Yet, modern item response theory (IRT) makes an a priori commitment to item ordering. The Rasch model, for example, posits that items must order. Conversely, the 2PL model posits that items never order. Needed is an IRT model where item ordering or its violation is a function of the data rather than an *a priori* commitment. We develop two-parameter shift-scale models for this purpose, and find that the two-parameter uniform offers many advantages. We show how item ordering may be assessed using Bayes factor model comparison, and discuss computational issues with shift-scale IRT models.
Model of Instrumentalism in the Philosophy of Education of Pragmatism and the Neopragmatism Conception
Authors: Zinchenko Viktor Viktorovych
Published: September 2018

The system-integration aspect of social philosophy and education management is analyzed in the interaction of the concepts of pragmatism and neo-pragmatism instrumentalism in the formation of socio-value orientations. We study the  instrumentalist aspect of social philosophy and management of education, psychology and pedagogy concepts of pragmatism and neopragmatism as industry management knowledge about the development of man and society. Carried out an analysis of the concept of management and philosophy of instrumentalism, and classification of the essence of the existing schools, trends and ideological contradictions between them are revealed.
Cognitive Networks: Interactivity, Intersubjectivity, and Synergy
Authors: Knyazeva Helena
Published: September 2018

Some properties of cognitive networks are discussed in the article in the context of the modern achievements of the network science. It is the study in network structures and their surprising properties that gives a new impetus to the development of the theory of complex systems (synergetics). The analysis of cognitive processes from the point of view of the network structures that arise in them not only fits with such concepts already existing in cognitive science and epistemology, as cognitive niches, cognitive maps, cognitive coherence, etc.), but also brings some new aspects to the understanding of interactivity, intersubjectivity, synergy in cognition and creative activities, empathy.