Game-based Learning (Interactive Demo)

What does the lesson “Finding Citations,” the game “Trivial Pursuit,” and the mechanic “Bluffing” all have in common? In this bootcamp brainstorm facilitated by a CUNY professor, attendees are broken up into design teams whose job it is to enhance a traditional lesson with the mechanics of popular board games in only 20 minutes. Whether you have to teach the rules of citation or the rules of interviewing, there is usually a game plan that can help. This game teaches you how to integrate educational games into your classroom, while providing a fun introduction to the principles of game-based learning.

Interactive Lightning Session: Game-based Learning in Higher Education

Games are known for leveraging enthusiasm, engagement, energy, knowledge, and passion on gamers; areas that are fundamentally important in higher education. Our panelists will share their perspectives on how Higher Education can take advantage of the potential of game based learning to create a more engaging student learning experien

A Spatial-Temporal Downscaling Approach To Construction Of Rainfall Intensity-Duration-Frequency Relations In The Context Of Climate Change

This paper proposes a spatial-temporal downscaling approach to construction of the intensity-duration-frequency (IDF) relations at a local site in the context of climate change and variability. More specifically, the proposed approach is based on a combination of a spatial downscaling method to link large-scale climate variables given by General Circulation Model (GCM) simulations with daily extreme precipitations at a site and a temporal downscaling procedure to describe the relationships between daily and sub-daily extreme precipitations based on the scaling General Extreme Value (GEV) distribution. The feasibility and accuracy of the suggested method were assessed using rainfall data available at eight stations in Quebec (Canada) for the 1961-2000 period and climate simulations under four different climate change scenarios provided by the Canadian (CGCM3) and UK (HadCM3) GCM models. Results of this application have indicated that it is feasible to link sub-daily extreme rainfalls at a local site with large-scale GCM-based daily climate predictors for the construction of the IDF relations for present (1961-1990) and future (2020s, 2050s, and 2080s) periods at a given site under different climate change scenarios. In addition, it was found that annual maximum rainfalls downscaled from the HadCM3 displayed a smaller change in the future, while those values estimated from the CGCM3 indicated a large increasing trend for future periods. This result has demonstrated the presence of high uncertainty in climate simulations provided by different GCMs. In summary, the proposed spatial-temporal downscaling method provided an essential tool for the estimation of extreme rainfalls that are required for various climate-related impact assessment studies for a given region.

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.

Leakage Detection And Localization Method Based On A Hybrid Inverse/Direct Modelling Approach Suitable For Handling Multiple-Leak Scenarios

When an accurate hydraulic network model is available, direct modeling techniques are very straightforward and reliable for on-line leakage detection and localization applied to large class of water distribution networks. In general, this type of techniques based on analytical models can be seen as an application of the well-known fault detection and isolation theory for complex industrial systems. Nonetheless, the assumption of single leak scenarios is usually made considering a certain leak size pattern which may not hold in real applications. Upgrading a leak detection and localization method based on a direct modeling approach to handle multiple-leak scenarios can be, on one hand, quite straightforward but, on the other hand, highly computational demanding for large class of water distribution networks given the huge number of potential water loss hotspots. This paper presents a leakage detection and localization method suitable for multiple-leak scenarios and large class of water distribution networks. This method can be seen as an upgrade of the above mentioned method based on a direct modeling approach in which a global search method based on genetic algorithms has been integrated in order to estimate those network water loss hotspots and the size of the leaks. This is an inverse / direct modeling method which tries to take benefit from both approaches: on one hand, the exploration capability of genetic algorithms to estimate network water loss hotspots and the size of the leaks and on the other hand, the straightforwardness and reliability offered by the availability of an accurate hydraulic model to assess those close network areas around the estimated hotspots. The application of the resulting method in a DMA of the Barcelona water distribution network is provided and discussed. The obtained results show that leakage detection and localization under multiple-leak scenarios may be performed efficiently following an easy procedure.

City Of Toronto’S Approach On Implementing The New Federal Wastewater Effluent Regulations Using A GIS-Based Hydrologic And Hydraulic Model

Canada releases over 150 billion litres of untreated and undertreated wastewater into the water environment every year1. To clean up urban wastewater, new Federal Wastewater Systems Effluent Regulations (WSER) on establishing national baseline effluent quality standards that are achievable through secondary wastewater treatment were enacted on July 18, 2012. With respect to the wastewater from the combined sewer overflows (CSO), the Regulations require the municipalities to report the annual quantity and frequency of effluent discharges. The City of Toronto currently has about 300 CSO locations within an area of approximately 16,550 hectares. The total sewer length of the CSO area is about 3,450 km and the number of sewer manholes is about 51,100. A system-wide monitoring of all CSO locations has never been undertaken due to the cost and practicality. Instead, the City has relied on estimation methods and modelling approaches in the past to allow funds that would otherwise be used for monitoring to be applied to the reduction of the impacts of the CSOs. To fulfill the WSER requirements, the City is now undertaking a study in which GIS-based hydrologic and hydraulic modelling is the approach. Results show the usefulness of this for 1) determining the flows contributing to the combined sewer system in the local and trunk sewers for dry weather flow, wet weather flow, and snowmelt conditions; 2) assessing hydraulic grade line and surface water depth in all the local and trunk sewers under heavy rain events; 3) analysis of local and trunk sewer capacities for future growth; and 4) reporting of the annual quantity and frequency of CSOs as per the requirements in the new Regulations. This modelling approach has also allowed funds to be applied toward reducing and ultimately eliminating the adverse impacts of CSOs rather than expending resources on unnecessary and costly monitoring.

Meteomap: Generation Of Meteorological Variables For Distributed Physically-Based Hydrological Modeling

Distributed energy and water balance models require time-series surfaces of the meteorological variables involved in hydrological processes. Most of the hydrological GIS-based models apply simple interpolation techniques to extrapolate the point scale values registered at weather stations at a watershed scale. In mountainous areas, where the monitoring network ineffectively covers the complex terrain heterogeneity, simple geostatistical methods for spatial interpolation are not always representative enough, and algorithms that explicitly or implicitly account for the features creating strong local gradients in the meteorological variables must be applied. Originally developed as a meteorological pre-processing tool for a complete hydrological model (WiMMed), MeteoMap has become an independent software. The individual interpolation algorithms used to approximate the spatial distribution of each meteorological variable were carefully selected taking into account both, the specific variable being mapped, and the common lack of input data from Mediterranean mountainous areas. They include corrections with height for both rainfall and temperature (Herrero et al., 2007), and topographic corrections for solar radiation (Aguilar et al., 2010). MeteoMap is a GIS-based freeware upon registration. Input data include weather station records and topographic data and the output consists of tables and maps of the meteorological variables at hourly, daily, predefined rainfall event duration or annual scales. It offers its own pre and post-processing tools, including video outlook, map printing and the possibility of exporting the maps to images or ASCII ArcGIS formats. This study presents the friendly user interface of the software and shows some case studies with applications to hydrological modeling.