Optimized Water Demand Management Through Intelligent Sensing And Analytics: The WISDOM Approach

New business and technology platforms are required to sustainably manage urban water resources [1,2]. However, any proposed solutions must be cognisant of security, privacy and other factors that may inhibit adoption and hence impact. The FP7 WISDOM project (funded by the European Commission - GA 619795) aims to achieve a step change in water and energy savings via the integration of innovative Information and Communication Technologies (ICT) frameworks to optimize water distribution networks and to enable change in consumer behavior through innovative demand management and adaptive pricing schemes [1,2,3]. The WISDOM concept centres on the integration of water distribution, sensor monitoring and communication systems coupled with semantic modelling (using ontologies, potentially connected to BIM, to serve as intelligent linkages throughout the entire framework) and control capabilities to provide for near real-time management of urban water resources. Fundamental to this framework are the needs and operational requirements of users and stakeholders at domestic, corporate and city levels and this requires the interoperability of a number of demand and operational models, fed with data from diverse sources such as sensor networks and crowsourced information. This has implications regarding the provenance and trustworthiness of such data and how it can be used in not only the understanding of system and user behaviours, but more importantly in the real-time control of such systems. Adaptive and intelligent analytics will be used to produce decision support systems that will drive the ability to increase the variability of both supply and consumption [3]. This in turn paves the way for adaptive pricing incentives and a greater understanding of the water-energy nexus. This integration is complex and uncertain yet being typical of a cyber-physical system, and its relevance transcends the water resource management domain. The WISDOM framework will be modeled and simulated with initial testing at an experimental facility in France (AQUASIM – a full-scale test-bed facility to study sustainable water management), then deployed and evaluated in in two pilots in Cardiff (UK) and La Spezia (Italy). These demonstrators will evaluate the integrated concept providing insight for wider adoption.

Evaluation Of Reservoir Model Integration With Deterministic And Probabilistic Streamflow Forecasts

Due to the increase in water demand and hydropower energy, it is getting more important to operate hydraulic structures in an efficient manner while sustaining multiple demands. Especially, companies, governmental agencies, consultant offices require effective, practical integrated tools and decision support frameworks to operate reservoirs, cascades of run-of-river plants and related elements such as canals by merging hydrological and reservoir simulation/optimization models with various numerical weather predictions, radar and satellite data. The model performance is highly related with the streamflow forecast, related uncertainty and its consideration in the decision making. While deterministic weather predictions and its corresponding streamflow forecasts directly restrict the manager to single deterministic trajectories, probabilistic forecasts can be a key solution by including uncertainty in flow forecast scenarios for dam operation. The objective of this study is to compare deterministic and probabilistic streamflow forecasts on an earlier developed basin/reservoir model for short term reservoir management. The study is applied to the Yuvacık Reservoir and its upstream basin which is the main water supply of Kocaeli City located in the northwestern part of Turkey. The reservoir represents a typical example by its limited capacity, downstream channel restrictions and high snowmelt potential. Mesoscale Model 5 and Ensemble Prediction System data are used as a main input and the flow forecasts are done for 2012 year using HEC-HMS. Hydrometeorological rule-based reservoir simulation model is accomplished with HEC-ResSim and integrated with forecasts. Since EPS based hydrological model produce a large number of equal probable scenarios, it will indicate how uncertainty spreads in the future. Thus, it will provide risk ranges in terms of spillway discharges and reservoir level for operator when it is compared with deterministic approach. The framework is fully data driven, applicable, useful to the profession and the knowledge can be transferred to other similar reservoir systems.

Model Prediction Control For Water Management Using Adaptive Prediction Accuracy

In the field of operational water management, Model Predictive Control (MPC) has gained popularity owing to its versatility and flexibility. The MPC controller, which takes predictions, time delay and uncertainties into account, can be designed for multi-objective management problems and for large-scale systems. Nonetheless, a critical obstacle, which needs to be overcome in MPC, is the large computational burden when a large-scale system is considered or a long prediction horizon is involved. In order to solve this problem, we use an adaptive prediction accuracy (APA) approach that can reduce the computational burden almost by half. The proposed MPC scheme with this scheme is tested on the northern Dutch water system, which comprises Lake IJssel, Lake Marker, the River IJssel and the North Sea Canal. The simulation results show that by using the MPC-APA scheme, the computational time can be reduced to a large extent and a flood protection problem over longer prediction horizons can be well solved.

From Smart Meters To Smart Decisions: Web-Based Support For The Water Efficient Household

Smart water metering technologies for residential buildings offer, in principle, great opportunities for sustainable urban water management. However, much of this potential is as yet unrealized. Despite that several ICT solutions have already been deployed aiming at optimum operations on the water utilities side (e.g. real time control for water networks, dynamic pump scheduling etc.), little work has been done to date on the consumer side. This paper presents a web-based platform targeting primarily the household end user. The platform enables consumers to monitor, on a real-time basis, the water demand of their household, providing feedback not only on the total water consumption and relevant costs but also on the efficiency (or otherwise) of specific indoor and outdoor uses. Targeting the reduction of consumption, the provided feedback is combined with notifications about possible leakages\bursts, and customised suggestions to improve the efficiency of existing household uses. It also enables various comparisons, with past consumption or even with that of similar households, aiming to motivate further the householder to become an active player in the water efficiency challenge. The issue of enhancing the platform’s functionality with energy timeseries is also discussed in view of recent advances in smart metering and the concept of “smart cities”. The paper presents a prototype of this web-based application and critically discusses first testing results and insights. It also presents the way in which the platform communicates with central databases, at the water utility level. It is suggested that such developments are closing the gap between technology availability and usefulness to end users and could help both the uptake of smart metering and awareness raising leading, potentially, to significant reductions of urban water consumption. The work has received funding from the European Union FP7 Programme through the iWIDGET Project, under grant agreement no318272.

Parameterization Of Turbulence Models Using 3DVAR Data Assimilation

In this research the 3DVAR data assimilation scheme is implemented in the numerical model DIVAST in order to optimize the performance of the numerical model by selecting an appropriate turbulence scheme and tuning its parameters. Two turbulence closure schemes: the Prandtl mixing length model and the two-equation k-ε model were incorporated into DIVAST and examined with respect to their universality of application, complexity of solutions, computational efficiency and numerical stability. A square harbour with one symmetrical entrance subject to tide-induced flows was selected to investigate the structure of turbulent flows. The experimental part of the research was conducted in a tidal basin. A significant advantage of such laboratory experiment is a fully controlled environment where domain setup and forcing are user-defined. The research shows that the Prandtl mixing length model and the two-equation k-ε model, with default parameterization predefined according to literature recommendations, overestimate eddy viscosity which in turn results in a significant underestimation of velocity magnitudes in the harbour. The data assimilation of the model-predicted velocity and laboratory observations significantly improves model predictions for both turbulence models by adjusting modelled flows in the harbour to match de-errored observations. 3DVAR allows also to identify and quantify shortcomings of the numerical model. Such comprehensive analysis gives an optimal solution based on which numerical model parameters can be estimated. The process of turbulence model optimization by reparameterization and tuning towards optimal state led to new constants that may be potentially applied to complex turbulent flows, such as rapidly developing flows or recirculating flows.

A Serious Gaming Approach For Serious Stakeholder Participation

Serious games are a category of games which are designed for a specific purpose other than for pure entertainment. It is not a new concept but serious games using real data, coupled with real time modelling and combining model results with social and economic factors opens up a new paradigm for active stakeholder participation. DHI and UNEP-DHI Centre initiated a project called Aqua Republica where a virtual world is developed which allows participants to develop a river basin and visualise the consequences of their decisions. The aim of this project is to raise awareness of the interconnectivity of water and educate on integrated water resources management. Aqua Republica combines a game layer with a water allocation model, MIKE BASIN, to create an interactive, realistic virtual environment where players play the role of a catchment manager of an undeveloped river catchment. Their main objective is to develop the river catchment to be as prosperous as it can be. To achieve that, they will need to generate a good economy in the catchment to provide the funds needed for development, have a steady food supply for their population and enough energy and water for the catchment. Through these actions by the player, a meaningful play is established to engage players and to educate them about the complex relationships between developmental actions in a river basin and the natural environment as well as their consequences. The game layer also consists of a reward system to encourage learning. People can play and replay the game, get rewarded from performing the right principles and penalised from failures in the game. This abstract will explain the concept of the game and how it has been used in a stakeholder participation environment.

Comparison Of Demand Pattern Calibration In Water Distribution Networks With Geographic And Non-Geographic Parameterization

Demands are one of the most uncertain parameters in a water distribution network model. A good calibration of the model demands leads to better solutions when using the model for any purpose. A demand pattern calibration methodology that uses a priori information has been developed for calibrating the behaviour of demand groups. Generally, the behaviours of demands in cities are mixed all over the network, contrary to smaller villages where demands are clearly sectorised in residential neighbourhoods, commercial zones and industrial sectors. Demand pattern calibration has a final use for leakage detection and isolation. Detecting a leakage in a pattern that covers nodes spread all over the network makes the isolation unfeasible. Besides, demands in the same zone may be more similar due to the common pressure of the area rather than for the type of contract. For this reason, the demand pattern calibration methodology is applied to a real network with synthetic non-geographic demands for calibrating geographic demand patterns. The results are compared with a previous work where the calibrated patterns were also non-geographic.

Hydropower Energy Simulation Using Mike 11 Model; A Case Study In South Germany's Small Run-Of-River Hydropower Plants

Renewable energy production is a basic supplement to stabilize rapidly increasing global energy demand and skyrocketing energy price as well as to balance the fluctuation of supply from non-renewable energy sources at electrical grid hubs. The European energy traders, government and private company energy providers and other stakeholders have been, since recently, a major beneficiary, customer and clients of Hydropower simulation solutions. The relationship between rainfall-runoff model outputs and energy productions of hydropower plants has not been clearly studied. In this research, association of rainfall, catchment characteristics, river network and runoff with energy production of a particular hydropower station is examined. The essence of this study is to justify the correspondence between runoff extracted from calibrated catchment and energy production of hydropower plant located at a catchment outlet; to employ a unique technique to convert runoff to energy based on statistical and graphical trend analysis of the two, and to provide environment for energy forecast. For rainfall-runoff model setup and calibration, MIKE 11 NAM model is applied, meanwhile MIKE 11 SO model is used to track, adopt and set a control strategy at hydropower location for runoff-energy correlation. The model is tested at two selected micro run-of-river hydropower plants located in South Germany. Two consecutive calibration is compromised to test the model; one for rainfall-runoff model and other for energy simulation. Calibration results and supporting verification plots of two case studies indicated that simulated discharge and energy production is comparable with the measured discharge and energy production respectively.

Decision Tree Classification Model In Water Supply Network

With the service life of water supply network (WSN) growth, the growing phenomenon of aging pipe network has become exceedingly serious. As urban water supply network is hidden underground asset, it is difficult for monitoring staff to make a direct classification towards the faults of pipe network by means of the modern detecting technology. In this paper, based on the basic property data (e.g. diameter, material, pressure, distance to pump, distance to tank, load, etc.) of water supply network, decision tree algorithm (C4.5) has been carried out to classify the specific situation of water supply pipeline. Part of the historical data was used to establish a decision tree classification model, and the remaining historical data was used to validate this established model. Adopting statistical methods were used to access the decision tree model including basic statistical method, Receiver Operating Characteristic (ROC) and Recall-Precision Curves (RPC). These methods has been successfully used to assess the accuracy of this established classification model of water pipe network. The purpose of classification model was to classify the specific condition of water pipe network. It is important to maintain the pipeline according to the classification results including asset unserviceable (AU), near perfect condition (NPC) and serious deterioration (SD). Finally, this research focused on pipe classification which plays a significant role in maintaining water supply networks in the future.

A Gradient-Type Method For Real-Time State Estimation Of Water Distribution Networks

Drinking water distribution networks risk exposure to malicious or accidental contamination. Several levels of responses are conceivable. One of them consists to install a sensor network to monitor the system on real time. Once a contamination has been detected, this is also important to take appropriate counter-measures. In the SMaRT-OnlineWDN project, this relies on modeling to predict both hydraulics and water quality. An online model use makes identification of the contaminant source and simulation of the contaminated area possible. The objective of this paper is to present SMaRT-OnlineWDN experience and research results for hydraulic state estimation with sampling frequency of few minutes. A least squares problem with bound constraints is formulated to adjust demand class coefficient to best fit the observed values at a given time. The criterion is a Huber function to limit the influence of outliers. A Tikhonov regularization is introduced for consideration of prior information on the parameter vector. Then the Levenberg-Marquardt algorithm is applied that use derivative information for limiting the number of iterations. Confidence intervals for the state prediction are also given. The results are presented and discussed on real networks in France and Germany.

Model Configuration And Data Management In The Short-Term Water Information Forecasting Tools

The Short-term Water Information and Forecasting Tools (SWIFT) is a suite of tools for flood and short-term streamflow forecasting, consisting of a collection of hydrologic model components and utilities. Catchments are modeled using conceptual subareas and a node-link structure for channel routing. The tools comprise modules for calibration, model state updating, output error correction, ensemble runs and data assimilation. Given the combinatorial nature of the modelling experiments and the sub-daily time steps typically used for simulations, the volume of model configurations and time series data is substantial and its management is not trivial. SWIFT is currently used mostly for research purposes but has also been used operationally, with intersecting but significantly different requirements. Early versions of SWIFT used mostly ad-hoc text files handled via Fortran code, with limited use of netCDF for time series data. The configuration and data handling modules have since been redesigned. The model configuration now follows a design where the data model is decoupled from the on-disk persistence mechanism. For research purposes the preferred on-disk format is JSON, to leverage numerous software libraries in a variety of languages, while retaining the legacy option of custom tab-separated text formats when it is a preferred access arrangement for the researcher. By decoupling data model and data persistence, it is much easier to interchangeably use for instance relational databases to provide stricter provenance and audit trail capabilities in an operational flood forecasting context. For the time series data, given the volume and required throughput, text based formats are usually inadequate. A schema derived from CF conventions has been designed to efficiently handle time series for SWIFT.

Verification Of The Standard Vector Data Model For Interoperability Of River-Geospatial Information

Recently, two international standard organizations, ISO and OGC, have done the work of standardization for GIS. Current standardization work for providing interoperability among GIS DB focuses on the design of open interfaces. But, this work has not considered procedures and methods for designing river geospatial data. Eventually, river geospatial data has its own model. When we share the data by open interface among heterogeneous GIS DB, differences between models result in the loss of information. In this study a plan was suggested both to respond to these changes in the information envirnment and to provide a future Smart River-based river information service by understanding the current state of river geospatial data model, improving, redesigning the database. Therefore, primary and foreign key, which can distinguish attribute information and entity linkages, were redefined to increase the usability. Database construction of attribute information and entity relationship diagram have been newly redefined to redesign linkages among tables from the perspective of a river standard database. In addition, this study was undertaken to expand the current supplier-oriented operating system to a demand-oriented operating system by establishing an efficient management of river-related information and a utilization system, capable of adapting to the changes of a river management paradigm.