bluuebunny/crossref_metadata_2025 huggingface dataset:
Improving Performance of NMT Using Semantic Concept of WordNet Synset
Authors: Liu Fangxu , Xu Jinan , Miao Guoyi , Chen Yufeng , Zhang Yujie
Published: September 2018

Neural machine translation (NMT) has shown promising progress in recent years. However, for reducing the computational complexity, NMT typically needs to limit its vocabulary scale to a fixed or relatively acceptable size, which leads to the problem of rare word and out-of-vocabulary (OOV). In this paper, we present that the semantic concept information of word can help NMT learn better semantic representation of word and improve the translation accuracy. The key idea is to utilize the external semantic knowledge base WordNet to replace rare words and OOVs with their semantic concepts of WordNet synsets. More specifically, we propose two semantic similarity models to obtain the most similar concepts of rare words and OOVs. Experimental results on 4 translation tasks show that our method outperforms the baseline RNNSearch by 2.38~2.88 BLEU points. Furthermore, the proposed hybrid method by combining BPE and our proposed method can also gain 0.39~0.97 BLEU points improvement over BPE. Experiments and analysis presented in this study also demonstrate that the proposed method can significantly improve translation quality of OOVs in NMT.
Water Distribution Network Reliability: are Surrogate Measures Reliable?
Authors: Muranho João , Sousa Joaquim , Sá Marques Alfeu , Gomes Ricardo
Published: September 2018

Water distribution networks (WDNs) must be reliable infrastructures since they provide an essential service to society. Reliability assessment is a complex task and involves various aspects: mechanical, hydraulic, water quality, water safety, among others. This paper focuses on the hydraulic reliability. Hydraulic reliability is computationally hard to measure directly, therefore researchers came up with surrogate measures, like the resilience index, the modified resilience index, the flow entropy or the diameter-sensitive flow entropy, that are simple and fast to compute. But, are these surrogate measures reliable to be used in the design of WDNs?

This paper proposes a new reliability index based on the surplus flow available on each node to mitigate the effects of a pipe failure. To illustrate the applicability of this new index, a WDN example is optimally designed using a simulated annealing algorithm. Results show that the solutions based on the flow entropy or on the proposed index are more reliable than the others, and, also, the maximization of the other reliability indexes gives only a residual contribution to the global reliability (or even no contribution at all).
A Blockchain Aided Metric for Predictive Delivery Performance in Supply Chain Management
Authors: Meng Mark H. , Qian Yaou
Published: September 2018

The topic of blockchain has been inundated with the fanaticism of cryptocurrencies' enthusiasts in recent years. In fact, the theory of blockchain and technologies behind are more worthy to be discussed to bring revolution to nowadays business operation. In this paper, we conduct an interdisciplinary study on business logistics as well as the cutting edge information technologies. We discuss the ongoing projects of blockchain in business industry, and then we propose our assessment model and blockchain framework to seek an enhanced metric for delivery performance with real-time feature and higher accuracy. Based on the our analysis, we identify the shortcomings of traditional assessment on delivery performance in contemporary global supply chain management and we discuss the potential benefits brought by adoption of our proposed framework.
Multispectral Approach Assessment for Detection of Losses in Water Transmission Systems by Airborne Remote Sensing
Authors: Chatelard Christian , Krapez Jean-Claude , Barillot Philippe , Déliot Philippe , Frédéric Yves-Michel , Pierro Jean , Nouvel Jean-François , Hélias Franck , Louvet Yolande , Le Goff Isabelle , Serra Guillaume
Published: September 2018

Water losses have a high environmental impact in terms of natural resources depletion (water, energy, ecosystems). This work aims at developing an airborne water leak detection surveillance service to provide water utilities with adequate information on leaks in water transportation mains outside urban areas. As a first step, a series of measurement campaigns were performed with hyperspectral cameras and a thermal infrared camera for selecting the most appropriate wavelengths and combinations thereof for revealing at best high moisture areas and artificial leaks. Further measurements will be performed with thereby optimized instrumentation onboard a plane and a UAV in an operational environment.
Impact of Climate Change on Irrigated Agriculture in Sardinia Region
Authors: Masia Sara , Sušnik Janez , Marras Serena , Mereu Simone , Spano Donatella , Trabucco Antonio
Published: September 2018

Increased drought risk in Southern Europe is expected due to changing rainfall patterns and increasing evapotranspiration. Water availability is crucial in semi-arid Mediterranean countries, where irrigation is essential for crop production.

In this work, irrigated agriculture vulnerability of three Sardinian irrigation districts and their associated reservoirs is assessed. The simultaneous impact of climate change on water inflow to the reservoir, open surface evaporation, and water supply is evaluated and then integrated into indicators. Vulnerability Index is calculated to define future reservoir adequacy in guaranteeing irrigated crops. The analysis is conducted by comparing the baseline (1976-2005) with the future (2036-2065) climate under RCP 4.5 and 8.5. The Simulation of Evapotranspiration of Applied Water model is incorporated into a GIS platform to compute crop irrigation demand. Changes in water inflow to reservoirs and evaporation losses are estimated. Results show a decreasing resilience and increasing vulnerability of irrigated agriculture under climate change in each case study. The highest resilience is estimated in Monte Pranu and Stretta di Calamaiu reservoir while the highest vulnerability in the Cuga-Alto Temo system. Climate change may only partially affect irrigation in resilient systems, where storage capacity and water entering into the reservoir is higher than water outflow.
Hydrological Model Calibration in Data-Limited Catchments Using Non-Continuous Data Series with Different Lengths
Authors: Li Chuanzhe , Liu Jia , Yu Fuliang , Tian Jiyang , Wang Yang , Qiu Qingtai
Published: September 2018

This paper evaluates the effects of calibration data series length on the performance of a hydrological model in data-limited catchments where data are non-continuous and fragmental. Non-continuous calibration periods were used for more independent streamflow data for SIMHYD model calibration. Nash-Sutcliffe efficiency and percentage water balance error were used as performance measures. The particle swarm optimization method was used to calibrate the rainfall-runoff models. Different lengths of data series ranging from one year to ten years were used to study the impact of calibration data series length. Fifty-five relatively unimpaired catchments located all over Australia with daily precipitation, potential evapotranspiration, and streamflow data were tested to obtain more general conclusions. The results show that longer calibration data series do not necessarily result in better model performance. Our results may have useful and interesting implications for the efficiency of using limited observation data for hydrological model calibration in different climates.
Adaptation and Resilience of Roads to Extreme Hydrological Events
Authors: López Marco , Pedrozo Acuña Adrian , Breña Naranjo José Agustín
Published: September 2018

Road infrastructure networks are exposed to multiple damages caused by the occurrence of floods, generally, associated to hydrometeorological extreme phenomena. This can be attributed to the lack of drainage efficiency in the current designed hydraulic infrastructure. In order to renew the current methodologies for designing and improving the performance of road drainage, we proposed an approach that allows to revise the road drainage under current and future climate scenarios. For this, digital elevation information combined with a simplified shallow water equations model were used to reproduce the transversal flows to a highway located in the state of Oaxaca, Mexico. The drainage performance for both scenarios was tested along a set of identified critical points of the highway, and in those locations where hydrological design showed to be insufficient, adaptation measures were provided. This approach proved to be scalable and useful for identifying points where road drainage redesign or adaptation were needed and, to prioritize actions that minimize direct and indirect damages on roads.
Investigating the Optimization Strategies on Performance of Rainfall-Runoff Modeling
Authors: Goodarzi Mehdi Sheikh , Amiri Bahman Jabbarian , Navardi Shabnam
Published: September 2018

Regarding to importance of modeling calibration, this study will be focused on probabilistic role of different strategies in calibration and verification steps. Tank lumped conceptual model was selected as a hydrological platform to investigate the effects of each optimization strategy on model performance.

However, much considerable efforts are required to calibrate a large number of parameters in conceptual models to obtain better results. With development of artificial intelligence, three probabilistic Global Search Algorithms (GSAs) including Shuffled Complex Evolution (SCE), Genetic Algorithm (GA) and Rosenbrock Multi-Start Search (RBN) and also three Objective Functions (OFs) consisted of Nash-Sutcliffe (NSE), Root Mean Square Error (RMSE) and mean absolute error (MAE) were employed for model calibration (comparing the performance of different GSAs versus OFs). The best set of parameters, which is derived from the calibration step, will be used as prediction coefficients for the model verification stage. Performance evaluation of the simulation results was undertaken using Coefficient of Correlation (r) and Descriptive Statistics.

Results indicated that all of optimization strategies have a relative ability to retrieve optimal values of eighteen parameters of the Tank model. However, the best GSAs for daily runoff simulation are SCE (0.871) and GA (0.864), respectively, for calibration and verification phases. In case of the OFs result, NSE (0.763) and RMSE (0.834) are more performant for calibration and verification of the model. Finally, the best strategy was selected by combining the results of GSAs and OFs models. Finally, SCE*MAE (0.906) and GA*RMSE (0.868) were selected as a top series.
QGIS FLO-2D Integration
Authors: O'Brian Karen , Gonzalez-Ramirez Noemi , Nardi Fernando
Published: September 2018

Cities and agencies worldwide are predicting complex urban flooding by simulating the exchange between the surface water and storm drain system with the FLO-2D model. The FLO-2D modeling system is now supported by the robust pre- and post-processor tools in the Quantum Graphical Information Systems (QGIS) geographic information software. The QGIS tool prepares the FLO-2D data base that includes analyzing and editing spatial information as well as exporting detailed and high-resolution flood hazard maps. This paper outlines the resources and modeling tools available to engineers in an open source and free cross platform geographic information tool that supports the viewing, creation and editing of the spatial and tabular data as well as graphical and mapping output. This paper discusses the features of this unique, free, efficient and comprehensive data processing tool. A case study for the application of the QGIS tool for a FLO-2D urban project is presented.
Error Evolution Patterns in Multi-Step Ahead Streamflow Forecasting
Authors: Papacharalampous Georgia , Tyralis Hristos , Koutsoyiannis Demetris
Published: September 2018

Multi-step ahead streamflow forecasting is of practical interest. We examine the error evolution in multi-step ahead forecasting by conducting six simulation experiments. Within each of these experiments we compare the error evolution patterns created by 16 forecasting methods, when the latter are applied to 2 000 time series. Our findings suggest that the error evolution can differ significantly from the one forecasting method to the other and that some forecasting methods are more useful than others. However, the errors computed at each time step of a forecast horizon for a specific single-case study strongly depend on the case examined and can be either small or large, regardless of the used forecasting method and the time step of interest. This fact is illustrated with a comparative case study using 92 monthly time series of streamflow.
Predicting Turbidity in Water Distribution Trunk Mains Using Nonlinear Autoregressive Exogenous Artificial Neural Networks
Authors: Kazemi Ehsan , Mounce Stephen , Husband Stewart , Boxall Joby
Published: September 2018

A nonlinear autoregressive exogenous artificial neural network model was developed to predict turbidity response in two different trunk mains with measured flow and turbidity data. Models were initially established to prepare the data and automatically select the appropriate events for model training. Then, an autoregressive exogenous network model was developed and applied to predict turbidity responses based on past events in the time series. A per site continual data driven calculation of turbidity event risk was included as an additional input to capture the effect of temporal distance between the selected events as well as increasing the accuracy of the predictions. The calculated normalised mean square error and mean absolute error showed that the developed model combined with the data preparation and pre- processing models provides good regressions on a future event with a period of 7 to 10 hours for a multi-step ahead prediction. Furthermore, the result of the autoregressive exogenous network was compared with the output of a feed-forward network where the former significantly outperformed the latter (R value of approximately 0.97 compared to 0.66).
Research and Design of Hydrological Big-data Sharing Platform
Authors: Xu Jian , Chen Hua
Published: September 2018

In this paper, the methodology of hydrological big-data standardization is discussed upon analyzing on the characteristics of hydrological data. Three main standards of hydrological data in China are considered in the standardization, which are respectively "Structure and identifier for real-time hydrological information database", "standard for structure and identifier in fundamental hydrological database" and "Structure and identifier for water quality database". Solutions on data pre-processing, data indexing and highly efficient data reading and writing are also introduced. The mass storage capacity and high speed computing capability of Hadoop are utilized for designing and implementing hydrological big-data sharing platform. Then a prototype of the hydrological big-data sharing platform is introduced in this article. Accordingly, the platform can be the technical support for information sharing and space integration between water conservancy industries and other industries, as well as the interdisciplinary sustainable development.
A Customized GIS-based Model for Stormwater Mitigation by LID Controls
Authors: Chiaradia Enrico Antonio , Ercolani Giulia , Bischetti Gian Battista , Gandolfi Claudio , Castelli Fabio , Masseroni Daniele
Published: September 2018

The effects of urbanization on hydrology, water quality, habitats, as well as ecological and environmental compartments, represent issues of primary importance for multiple agencies at the national, regional and local levels. In the context of the SMART-GREEN project, funded by Fondazione Cariplo, a new tool called SMARTGREEN plugin is under development in a desktop GIS framework.The software will provide: 1) a user friendly interface to help analysts in the hydrologic-hydraulic modelling of urban watersheds and drainage networks through the model MOBIDIC-U, with the possibility of considering Low Impact Development (LID) solutions, 2) a set of tools to easily import information from existing databases, 3) a set of tools to check the database quality, highlight missing or incorrect data, and suggest possible fixes automatically, 4) an easy and faster way to speed up the analysis of the results. In this work, we show the main functionalities of the plugin through a basic test case. The software aims at supporting water service management companies in planning LID implementation in urban areas.
Flood Modelling and Citizen Observatories: Analysing Pathways for Data Collection in the Sontea-Fortuna Case Study
Authors: Assumpção Thaine H. , Venturini André B. , Popescu Ioana , Jonoski Andreja , Solomatine Dimitri P.
Published: September 2018

Accurate flood models require large amounts of data inputs which are not always available. Recently data coming from other sources, such as crowdsourced data, have been increasingly explored in the scientific literature. However, there is no clear methodology showing where willing citizens could go for data collection. Thus, this study proposes an optimization framework to generate and prioritize pathways that citizens could take while collecting data. The proposed framework is tested on the Sontea-Fortuna area, part of the Danube Delta, where water stagnation is threatening the local ecosystems. Among the pathways generated, results analysis showed that pathways closer to the starting point were more effective.
A Data-Driven Hybrid Urban Flood Modelling Approach
Authors: Li Xiaohan , Willems Patrick
Published: September 2018

Urban flood pre-warning decisions made upon urban flood modeling is crucial for human and property management in urban area. However, urbanization, changing environmental conditions and climate change are challenging urban sewer models for their adaptability. While hydraulic models are capable of making accurate flood predictions, they are less flexible and more computationally expensive compared with conceptual models, which are simpler and more efficient. In the era of exploding data availability and computing techniques, data-driven models are gaining popularity in urban flood modelling, but meanwhile suffer from data sparseness. To overcome this issue, a hybrid urban flood modeling approach is proposed in this study. It incorporates a conceptual model to account for the dominant sewer hydrological processes and a logistic regression model able to predict the probabilities of flooding on a sub-urban scale. This approach is demonstrated for a highly urbanized area in Antwerp, Belgium. After comparison with a 1D/0D hydrodynamic model, its ability is shown with promising results to make probabilistic flood predictions, regardless of rainfall types or seasonal variation. In addition, the model has higher tolerance on data input quality and is fully adaptive for real time applications.
Comparison Between Calibration and Sensitivity Approach in Water Network Management in Emergency Conditions
Authors: Fiorini Morosini Attilio , Caruso Olga , Veltri Paolo
Published: September 2018

When a network works in emergency conditions, due to a pipe failure, an appropriate management of the system is necessary. These events can cause a bad service for the users, because the pressure in some nodes of the network (critical nodes) decreases and the required demand is not guaranteed. In fact, a pipe failure causes the isolation of the intervention area, modifies the circulating flow along pipes and can produce a pressure reduction in some nodes.

In network management the aim is to increase the pressure, and consequently the flow rate delivered at critical nodes in order to minimize disruptions during the time between the failure and the repair.

In this paper, a methodology based on the nodal demand control is proposed. The nodal demand control proposed is possible by using control valves and by identifying the nodes where the control should be done. The control nodes can be chosen by using sensitivity matrices or an approach based on calibration techniques. A case study shows the results obtained with both methods for the real network of Praia a Mare in the South of Italy.
Detection of Rainfall and Runoff Trends of the Adda River in Lecco (1845-2014) at Different Time Scales
Authors: Ranzi Roberto , Tomirotti Massimo , Brunetti Michele , Crespi Alice , Maugeri Maurizio
Published: September 2018

A recovery of ancient records of the Como Lake water levels at the Fortilizio in Lecco hydrometric station enabled the reconstruction of a time series of daily water level and runoff from the Como Lake spanning the 1845-2014 period. In parallel, the monthly areal precipitation at the Adda river catchment scale was estimated for the same 170 years- long period. This time series, which is one of the longest available for Italian riverbasins will support analyses of the reasons of changes in the runoff regime in response to climatic and anthropogenic changes. A comparison of the two series applying the Mann- Kendall, Spearman and Theil-Sen trend tests, shows a decline, in the long term, of runoff and a more significant one of precipitation. Because some changes in the operation at the outlet of the Como Lake occurred after 1946 and also in the storage capacity of the upstream reservoirs the time series was splitted in two periods, before and after 1946. The results of the statistical tests for both precipitation and runoff in three time periods are consistent, but only for the time series of annual runoff the decline is statistically significant with 5% significance level. To analyse if changes occurred at different time scales the wavelet transform was applied to the daily runoff series. Finally the Fourier power spectrum of the the daily runoff data shows a signal of higher energy corresponding to a period between 11 and 13 years, close to the sunspots cycle period, and its significance is under investigation.
Improving Detection of Events at Water Treatment Works: A UK Case Study
Authors: Riss Gerald , Romano Michele , Woodward Kevin , Kapelan Zoran , Memon Fayyaz Ali
Published: September 2018

This paper presents a study aimed at improving the event detection capabilities of the existing, threshold-based detection system at a selected Water Treatment Works operated by United Utilities. The study shows that improvements can be achieved by using optimised threshold and persistence values identified by performing a sensitivity type analysis. The main findings from this study show that, although an overall increase in the true detection rate and decrease in the number of false alarms can be achieved, the high number of false alarms remains an issue. To address this problem a new event detection system based on suitable relations across multiple signals will be developed as part of future work.
An Advanced Software to Manage a Smart Water Network with Innovative Metrics and Tools Based on Social Network Theory
Authors: Di Nardo Armando , Di Natale Michele , Di Mauro Anna , Martínez Díaz Eva , Blázquez Garcia Jose Antonio , Santonastaso Giovanni Francesco , Tuccinardi Francesco Paolo
Published: September 2018

The recent development and applications of social network theory in many fields of engineering (electricity, gas, transport, water, etc.) allows both the understanding of networks and to improve their management. Social network theory coupled to the availability of real time data and big data analysis techniques can change drastically the traditional approaches to manage civil networks. Recently, some authors are working to apply this novel approach, based on social network theory, on the water distribution networks using: a) graph partitioning algorithms to define optimal district meter areas both for water losses identification and for water network protection, b) innovative topological, energy and hydraulic indices to analyze performance; and c) GIS (Geographical Information System) to provide a more effective display of results and to improve network behavior in specific operational conditions. In this paper, a novel release 3.5 of SWANP software, that implements all these features, was tested on a real large water network in Alcalá de Henares, Spain.
Impacts of Regional Climate Model Spatial Resolution on Summer Flood Simulation
Authors: Castaneda-Gonzalez Mariana , Poulin Annie , Romero-Lopez Rabindranarth , Arsenault Richard , Brissette François , Chaumont Diane , Paquin Dominique
Published: September 2018

This study aims to evaluate the impact of the Canadian Regional Climate Model’s (CRCM) spatial resolution on summer floods simulation. Four different climate simulations issued from the fourth version of the CRCM (two driven by the Canadian General Circulation Model (CGCM) and two driven by the ERA40c reanalysis) are employed. One simulation at 45 km resolution and another one at 15km resolution for each driver were compared on a daily time-step for the 1960-1990 period. These four simulations are used as inputs for two hydrological models of varying complexity (HSAMI and MOHYSE). Each model is calibrated using three different objective functions based on the Kling-Gupta Efficiency criterion (KGE) to target floods. Two seasonal indices are used to evaluate the CRCM outputs: bias (temperature) and relative bias (precipitation). For the streamflow simulations analysis, the seasonal values of KGE and relative bias are used. The results show an impact of spatial resolution on climate model outputs, on streamflow simulation and flood indicators in the hydrological models. However, other elements such as climate model driver and domain size can influence the results, highlighting the need for further research to assess the impact of spatial resolution on summer floods.
Drainage Network Modelling with a Novel Algorithm for Junction Calculation
Authors: Li Qian , Xia Xilin , Liang Qiuhua , Xiao Wen
Published: September 2018

Most of the existing drainage network models focus on capturing different flow regimes in sewer pipes. Despite being important to produce reliable results of urban flood simulation, the development of robust scheme to describe the coupled conditions at pipe-to-pipe intersections has received less research attention. In this work, the two-component pressure approach (TPA) is chosen to support pipe flow calculation due to its superior capability in simulating complicated transient flow between the free-surface and pressurized conditions in pipes. To avoid the complicated boundary conditions as required by a TPA model to approximate the junction connections, a novel strategy is proposed in this work where the flow at a junction is calculated using the 2D shallow water equations (SWEs). In junctions, irregular grids are created automatically according to the layout of connecting pipes, on which a first-order Godunov-type finite volume scheme is implemented to solve the 2D SWEs to simulate the junction flow. The 2D SWEs model is driven by the boundary conditions provided from the pipe calculations and rainfall input in necessary, which in turn creates boundary conditions for pipe calculations at the next time step. It is expected that the new approach as proposed will support large-scale drainage network modelling with higher efficiency and stability.
Application of Delft3d for Designing and Assessing New Solutions to Improve Sediment Input to an Erosion Prone Coast
Authors: Pinho José , Coelho José , Venâncio Stênio , Vieira Luís , Vieira Bárbara , Vieira Jose
Published: September 2018

The construction of harbor defense structures changes the natural sedimentary fluxes that contribute to feed the coastal drift in the adjacent beaches, in many harbors of the world located at river mouths. This paper presents a numerical modelling work, based on the Delft3D software, to study morphodynamics at the river Lima estuary, Portugal. This model was implemented recurring to a hydroinformatic environment that was constructed at University of Minho along the last two decades. Considering specific hydrodynamic conditions and typical characteristics of the estuarine sediments, the capacity of hypothetical structures to improve transport of sediments to the coast was assessed: (i) a submerged transverse non-erodible dam and (ii) an emerged groin linked to the left embankment located at the upstream section of the harbor. The implemented hydroinformatic environment presents capacities to simulate the complex morphodynamic behavior of river mouths. The preliminary results reveals that the proposed structures can have a positive impact throughout dredging works facilitation by transferring depositional areas during flood events to a location near the coast inside the harbor. Ongoing field acquisition data will be essential to validate depositional patterns under different river discharges and wave conditions.
Risk Assessment and Development of Maintenance Strategy for Pipe Rehabilitation Using WDNetXL
Authors: Raspati Gema Sakti , Selseth Ingrid , Berardi Luigi , Giustolisi Orazio , Ugarelli Rita
Published: September 2018

This paper shows potential application of mechanical reliability analysis in WDNetXL in a risk-based asset management applied to a distribution network in Norway. Evaluation of hydraulic importance of the network's pipe segments, based on quantification of pressure deficiency and unsupplied customer demand during simulated service interruptions, allows risk assessment on individual pipe level with the inclusion of statistical information about break rate of the pipe. From risk assessment of individual pipe, a priority ranking for pipe rehabilitation can then be developed. Such an approach should benefit the rehabilitation planning by highlighting criticality of a specific pipe and its impact on the service of the network. This approach can also be extended to evaluate the risk reduction reached once the rehabilitation plan is executed.
Numerical Simulation of Overland Flows Using Godunov Scheme Based on Finite Volume Method
Authors: Zhang Dawei , Quan Jin , Wang Zhili , Zhang Hongbin , Ma Jianming
Published: September 2018

A new numerical model for simulating overland flows has been developed using Godunov scheme based on the two-dimensional fully dynamic shallow water equations (SWEs). There are a number of frequently and partially submerged cells due to steep slopes, coarse meshes and small depth when simulating the surface runoff propagation, which are different from the original hydraulic applications such as flooding. In order to provide an accurate numerical solution for overland flows, the model in this work uses the Roe’s approximate Riemann solver for the calculation of fluxes on the triangulated unstructured grid based on the flow sheet regime, and the bottom slope terms are calculated directly by applying the Green’s theorem. To control the global stability of the model, the semi-implicit discretization method is adopted to deal with the highly nonlinear friction terms. The new model provides more comprehensive calculation capabilities, which are proved by several case studies, and the numerical results match well with analytical solutions, experimental data or results computed by other numerical models.
Optimal District Metered Area Design by Simulated Annealing
Authors: Gomes Ricardo , Sousa Joaquim , Sá Marques Alfeu , Muranho João
Published: September 2018

Water losses reduction in Water Distribution Systems (WDSs) is nowadays an issue of growing importance for water companies to ensure the economic sustainability of these public services. In this context, the implementation of District Metered Areas (DMAs) and/or pressure management are considered effective tools for leakage control, particularly in large networks and in systems with deteriorated infrastructures and with high pressure.

Based in previous studies performed by the authors (Gomes et al., 2012; Gomes et al., 2015; Sousa et al., 2015), the methodology described in this paper follows the ‘water losses management international best practices’ and makes it possible to evaluate the Net Present Value (NPV) of DMAs project, as well as the benefits that can be achieved by pressure management in WDS, particularly in terms of water production reduction. Leakage assessment is performed using the analysis of the minimum night flow and the FAVAD concept, and it uses a pressure driven simulation model to predict the network hydraulic behaviour under different pressure conditions. The optimal location of DMAs entry points, pipes reinforcement/replacement and locations/settings of the Pressure Reduction Valves (PRVs) are identified by a Simulated Annealing algorithm. The potential of this methodology is illustrated through an hypothetical case study.
Distributed Input-Delay Model Predictive Control of Inland Waterways
Authors: Segovia Pau , Rajaoarisoa Lala , Nejjari Fatiha , Duviella Eric , Puig Vicenç
Published: September 2018

Inland waterways are large, complex systems composed of interconnected navigation reaches dedicated mainly to navigation. These reaches are generally characterized by negligible bottom slopes and large time delays. The latter requires ensuring the coordination of the current control actions and their delayed effects in the network. Centralized control strategies are often impractical to implement due to the size of the system. To overcome this issue, a distributed Model Predictive Control (MPC) approach is proposed. The system partitioning is based on a reordering of the optimality conditions matrix, and the control actions are coordinated by means of the Optimality Condition Decomposition (OCD) methodology. The case study is inspired by a real inland waterways system and shows the performance of the approach.
Reconstruction of Hydrometric Data Using a Network Optimization Model
Authors: Ayoub Tahiri , Ladevèze David , Chiron Pascale , Archimède Bernard
Published: September 2018

Water resource managers need to implement precise and efficient water management methods particularly in the context of low flow water management. The management objectives are complex because managers must satisfy both water demands for human activities and environmental goals. More often the flow objectives are defined at specific strategic points in which hydrometric stations are based. In order to allow the manager to better understand the hydrographical network behavior, in particular for inter-basin water transfer, these strategic hydrometric stations must be reinforced by some intermediate hydrometric stations, by modeling the network behavior, and by introducing weather forecast data in order to simulate the evolution in time and space of the river. For an efficient management, it is essential that the data collected and the output of the models (the natural flow and the withdrawals) must be reliable. For this purpose, a network optimization model was developed for analyzing the consistency of the available data set (measurements and model outputs) on a hydraulic system. Herein, a reconstruction of hydrometric data using this network optimization model is applied to the Arrats watershed management.
SWRL2SPIN: Converting SWRL to SPIN
Authors: Bassiliades Nick
Published: September 2018

SWRL is a semantic web rule language that combines OWL ontologies with Horn Logic rules of the RuleML family of rule languages. Being supported by Protégé as well as by popular rule engines and ontology reasoners, such as Jess, Drools and Pellet, SWRL has become a very popular choice for developing rule-based applications on top of ontologies. However, being doubtful whether SWRL will become a W3C standard, it is difficult to reach out to the industrial world. On the other hand, SPIN has become a de-facto industry standard to rep-resent SPARQL rules and constraints on Semantic Web models, building on the widespread acceptance of the SPARQL query language. In this paper, we argue that the life of existing SWRL rule-based ontology applications can be prolonged by being transformed into SPIN. To this end, we have developed a prototype tool using SWI-Prolog that takes as input an OWL ontology with a SWRL rule base and transforms SWRL rules into SPIN rules in the same ontology, taking into consideration the object-oriented scent of SPIN, i.e. linking rules to the appropri-ate ontology classes as derived by analyzing the rule conditions.
Comparative Study on the Open Boundary Conditions of Shallow Flows
Authors: Jung Jaeyoung , Hwang Jin Hwan
Published: September 2018

In order to accurately simulate physical phenomena, appropriate boundary conditions must be implemented. Where some information propagate along the characteristic curves as in the hyperbolic system such as shallow water equations (SWEs), open boundary conditions (OBCs) must be designed so that such an event should also be maintained even at the boundaries. In other words, OBCs of SWEs must pass information out of the domain and receive the incoming information without any numerical distortion. If OBCs do not reflect the characteristics of SWE, errors will occur and contaminate the information in the internal domain. This study compares several OBCs based on the hyperbolic characteristics of SWE and shows that OBCs derived using hyperbolic characteristic performs better in the several OBCs.
Identifying Critical Components in Water Networks Using Time-Dependent Data
Authors: Aydin Nazli Yonca
Published: September 2018

Water supply systems are under stress due to population increase, climate change, aging infrastructures, terrorist attacks etc. all of which have an impact on the operation of water infrastructures resulting in failures/disruptions. The aim of this research is to evaluate the structural and operational properties of water supply systems together and identify the most critical locations in water networks and evaluate the systems’ functionalities. Graph-based metrics, called the entropic degree, is used to identify the critical locations on different network structures using the flow as a weighting parameter on links. The results would assist authorities, decision-makers in strategic plans for prioritizing and rehabilitating network components, identifying vulnerable locations as well as in enhancing the resilience of future water supply systems.
The Effect of Lateral Boundary Conditions on Results of One-Way Nested Ocean Regional Circulation Model
Authors: Pham Van Sy , Hwang Jin Hwan
Published: September 2018

This research evaluated two main sources of impact on the results of the ocean regional circulation model (ORCMs) during downscaling and nesting the results from the ocean global circulation model (OGCMs). Representative two sources should be the spatial resolution difference between driving and driven data, and the frequency for up- dating LBCs. The Big-Brother method investigated the effect of them on the results of the ORCMs separately. The results showed that the lateral boundary conditions (LBCs) potentially degraded the results of ORCMs. The errors developed at the boundaries propagate slowly into the center of the nested domain as time passes. The simulation results of the ORCMs significantly depend not only on spatial resolution but also on the frequency for updating the lateral boundary conditions. The ratio resolution of spatial resolution between driving data and driven model can be up to 3 and the updating frequency of the LBCs can be up to every 6 hours per day.
Relationship Between Extreme Rainfall and Surface Temperature in Sicily (Italy)
Authors: Pumo Dario , Carlino Giuseppina , Arnone Elisa , Noto Leonardo
Published: September 2018

The study of the relationship between extreme rainfall events and surface temperature represents an important issue in hydrology and meteorology and it could be of capital importance for evaluating the effect of global warming on future precipitation. Various approaches have been tested across different parts of the world, and, in many cases, it has been observed an intensification of precipitation with increasing temperature consistently with the thermodynamic Clausius-Clapeyron relation (CC-rate of 6-7% °C-1), according to which a warmer atmosphere is capable of holding more moisture. Nevertheless, in different locations, the scaling rate between temperature and extreme precipitation has resulted significantly different with respect to the CC-rate, in some cases sensibly higher (super-CC) and in other relevantly lower (sub-CC). In this work, an analysis of the scaling relationship between sub-daily extreme rainfall events and surface temperature is carried out, using data from a large number of rain and temperature gauges across Sicily (Italy). Results highlight the relevant importance of some modeling choices and, particularly, of rainfall duration, for this type of analysis in semi-arid region. An overall sub-CC scaling rate has been detected for most part of the region.
Optimization of the Midterm Electricity Generation Mix Considering the Effects of Water, Land and Carbon Footprints
Authors: Bozorg Mohsen , Mazandarani Zadeh Hamed , Savic Dragan
Published: September 2018

Electric energy plays a key role in the development of modern societies. Each of the electric power generation technologies (e.g., hydroelectric, wind, solar, thermal, etc.) has some advantages and disadvantages with respect to the fundamental resource indicators, including water footprint, land footprint, carbon footprint, as well as electricity generation costs. Due to the shortage and frequent crisis associated with the above resources, optimal selection of the mix of electricity generation technologies is very important and the share of each technology in the capacity expansion of the generation system must be carefully defined. Iran is in an arid and semi-arid region, with less than one third of the average world precipitation. Moreover, the available water resources are restricted due to the water crises in the Middle-East region. In this paper, we first estimated the peak power consumption of Iran in 2024, based on the time-series data from 2004 to 2014. Then, we formulated an optimization problem to find the share of each electric power generation technology to cover the required extra generation capacity for supplying the power consumption in the target year 2024, considering the effect of the four aforementioned performance indicators. The optimization problem is solved using Genetic Algorithm. Numerical results show that in the target year, 20 GW of electricity should be added to the generation capacity. The results also show that, solar thermal and solar photovoltaic are the best electric generation technologies regarding the available resources.
A Cellular Automata Urban Growth Model for Water Resources Strategic Planning
Authors: Nikolopoulos Dionysios , Risva Konstantina , Makropoulos Christos
Published: September 2018

The alarming rate of urbanization poses immediate problems to water resources management, mainly, but not limited to water supply, flood risk management, wastewater treatment and water quality control. Ideally, strategic planning of water systems should be fully aware of the prospects of future urban growth in order to maintain high reliability of services provided and satisfy customers in the long term. Typically, urban growth is handled in a static manner via the development of future scenarios based on previous urban planning studies. Generally, these scenarios focus solely on population increase and ignore the spatial allocation dynamics. Modern urban water strategic thinking needs to incorporate robust tools and methodologies in management practices, able to predict and quantify the outcome possibility of future urban growth. To cope with the aforementioned challenge, this study proposes a novel cellular automata urban growth model as well as, a supplementary remote sensing methodology to preprocess input data.
Comparison of Two Data-Driven Streamflow Forecast Approaches in an Adaptive Optimal Reservoir Operation Model
Authors: Gavahi Kayhan , Mousavi S. Jamshid , Ponnambalam Kumaraswamy
Published: September 2018

This study investigates the effect of two data-driven inflow prediction methods on the performance of a proposed adaptive real-time optimum reservoir operation model. The model consists of three modules; a forecasting module, which predicts the monthly future inflows, a reservoir operation optimization module, determining monthly optimum reservoir releases up to the end of a year, and an updating module, updating the current state of the system and provides the other two modules with the latest observed information on future inflows. K-nearest neighbor (KNN) and adaptive neuro- fuzzy inference system (ANFIS) approaches are used to forecast monthly inflows to the reservoir. The results demonstrate that ANFIS outperforms the KNN approach by 25, 23, 27 and 10 percent with respect to RMSE, PWRMSE, NSCE and correlation coefficient indices, respectively. However, the objective function values of the reservoir operation optimization model associated with each of those forecast models reveal that ANFIS-based adaptive reservoir operation model is only 5% better than the KNN-based model. This observation highlights the significance role of adaptation and updating procedure in the reduction of streamflow forecast errors.
Simulation of Floating Debris in Violent Shallow Flows
Authors: Xiong Yan , Mahaffey Samantha , Liang Qiuhua
Published: September 2018

Storm surge and tsunami may induce violent shallow flows and carry dense debris, causing tremendous damage to human lives, buildings and structures. This work presents a series of laboratory experiments to investigate the debris movement in the extreme flows. Subsequently, a new modeling tool featured with a finite volume shock-capturing hydrodynamic model fully coupled with a discrete element model is introduced. A new coupling method totally depending on the hydrodynamic characteristics is proposed to simulate the complex debris-enriched floods induced by tsunamis or storm surges. The experimental measurements are used to validate the reliability of the coupled model. The numerical results agree satisfactorily with the experimental measurements, demonstrating the model’s capability in simulating the complex fluid-debris interactions induced by violent shallow flows.
Resenha de Universe Of Things de Steven Shaviro
Authors: Veiga Ádamo Bouças Escossia Da
Published: September 2018

Resenha do livro "Universe of Things" de Steven Shaviro.
Contribuições para uma crítica da exatidão
Authors: Silva Gustavo Castro
Published: September 2018

Crítica e problematização da noção de exatidão como palavra-chave para o projeto de ciência e modelo de rigor científico. Analisaremos a noção de “Exatidão”, de ítalo Calvino (1990) e as ideias de Heidegger (1998) de uma ciência “inexata”. Buscaremos complementar estas duas visões com as noções de fantasia, logro e ilusão presentes em Cyrulnik (1999) e Wulf (2006) como cognição necessária e complementar àquela de realidade. Nossa metodologia será interpretativa e fenomenológica, buscando compreender como a crença nas noções de “exatidão” e realidade objetiva se tornou paradigma para a ciência e o jornalismo. Estas, por sua vez, passaram a relegar e desprestigiar noções como fantasia, imaginário e conhecimento aproximativo. Nossas conclusões apontam para a necessidade de retomar a crítica à noção de realidade sobretudo na maneira como o jornalismo a compreendeu.
Iteração, reiteração, repetição - Uma análise especulativa do signo desprovido de sentido
Authors: Meillassoux Quentin
Published: September 2018

Este ensaio fornece uma crítica à filosofia pós-kantiana, organizada em torno da ideia de que só temos acesso à correlação entre o pensamento e o ser. Contra o "correlacionismo" - isto é, a doutrina de que mente e mundo, ou representação e realidade, não podem ser concebidos isoladamente um do outro - este artigo desenvolve um materialismo especulativo que fornece os recursos conceituais para pensar uma realidade que é independente do pensamento.