Assessing the impact of infiltration and exfiltration in sewer systems using performance indicators: case studies of the APUSS project

2006 ◽  
Vol 1 (1) ◽  
Author(s):  
A. Cardoso
2006 ◽  
Vol 1 (1) ◽  
Author(s):  
A. Cardoso ◽  
V. Prigiobbe ◽  
M. Giulianelli ◽  
E. Baer ◽  
J. De Bénédittis ◽  
...  

The structural quality and functional efficiency of sewer systems are key parameters to guarantee the transfer of domestic, commercial and industrial wastewater to treatment plants without infiltration nor exfiltration. Infiltration of groundwater is particularly detrimental to treatment plant efficiency, while exfiltration of wastewater can lead to groundwater contamination. The APUSS project associating universities, SMEs and municipalities in 7 European countries, developed new methods and techniques to assess and quantify infiltration and exfiltration (I/E) in sewer systems. This paper describes the establishment of a set of performance indicators (PI) developed to assess the impact of I/E on sewer systems and their application to three project case studies, in Italy and France, focusing on sewer systems characteristics, I/E measurements campaigns and PI application results. The methodology for PI definition consists in the selection and development of a sewer network property or state variable, which is expressive of aspects being scrutinized (I/E); the PI values are then calculated; finally, a classification of the PI values is made in relation to good or bad performance. The use of PI allows a standardized and objective comparison of the performance of sewer systems and constitutes a means to technically support the establishment of priorities for rehabilitation and/or construction investments taking into account I/E impacts.


Author(s):  
Alan Treadgold ◽  
Jonathan Reynolds

The retail industry globally is in an era of profound, perhaps unprecedented, change, change which has been further accelerated for many by the impact of the COVID-19 global pandemic and its attendant health and economic crises. This book is intended to serve as a wide-ranging, robust, practical guide to leaders of enterprises tasked with understanding and delivering success in the new landscape of retailing. Part 1 describes the major directions and drivers of change that define the new global landscape of retailing. Accelerating changes in technology, the rise to prominence globally of internet enabled shoppers and the rapid emergence of entirely new retail enterprises and business models are combining to re-shape the very fundamentals of the retail industry. The new landscape of retailing is unforgiving: success can be achieved more quickly than ever before but failure is equally rapid. Opportunities in the new landscape of retailing are profound, but so too are the challenges. Part 2 discusses the structures, skills and capabilities that retail enterprises will need to be successful in this new landscape and the skills and capabilities required of the leaders of retail enterprises. More than 25 detailed case studies of innovative, successful enterprises internationally and more than one hundred smaller examples, all updated and many new since the first edition, are used to illustrate the themes discussed. Frameworks are presented to provide practical guidance for enterprise leaders to understand and contextualize the nature of change re-shaping retail landscapes globally. Clear guidance is given of the capabilities, skills and perspectives needed at both an enterprise and personal leadership level to deliver success in the new landscape of retailing.


2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
M Poldrugovac ◽  
J E Amuah ◽  
H Wei-Randall ◽  
P Sidhom ◽  
K Morris ◽  
...  

Abstract Background Evidence of the impact of public reporting of healthcare performance on quality improvement is not yet sufficient to draw conclusions with certainty, despite the important policy implications. This study explored the impact of implementing public reporting of performance indicators of long-term care facilities in Canada. The objective was to analyse whether improvements can be observed in performance measures after publication. Methods We considered 16 performance indicators in long-term care in Canada, 8 of which are publicly reported at a facility level, while the other 8 are privately reported. We analysed data from the Continuing Care Reporting System managed by the Canadian Institute for Health Information and based on information collection with RAI-MDS 2.0 © between the fiscal years 2011 and 2018. A multilevel model was developed to analyse time trends, before and after publication, which started in 2015. The analysis was also stratified by key sample characteristics, such as the facilities' jurisdiction, size, urban or rural location and performance prior to publication. Results Data from 1087 long-term care facilities were included. Among the 8 publicly reported indicators, the trend in the period after publication did not change significantly in 5 cases, improved in 2 cases and worsened in 1 case. Among the 8 privately reported indicators, no change was observed in 7, and worsening in 1 indicator. The stratification of the data suggests that for those indicators that were already improving prior to public reporting, there was either no change in trend or there was a decrease in the rate of improvement after publication. For those indicators that showed a worsening trend prior to public reporting, the contrary was observed. Conclusions Our findings suggest public reporting of performance data can support change. The trends of performance indicators prior to publication appear to have an impact on whether further change will occur after publication. Key messages Public reporting is likely one of the factors affecting change in performance in long-term care facilities. Public reporting of performance measures in long-term care facilities may support improvements in particular in cases where improvement was not observed before publication.


2021 ◽  
Vol 10 (2) ◽  
pp. e000839
Author(s):  
Heather Cassie ◽  
Vinay Mistry ◽  
Laura Beaton ◽  
Irene Black ◽  
Janet E Clarkson ◽  
...  

ObjectivesEnsuring that healthcare is patient-centred, safe and harm free is the cornerstone of the NHS. The Scottish Patient Safety Programme (SPSP) is a national initiative to support the provision of safe, high-quality care. SPSP promotes a coordinated approach to quality improvement (QI) in primary care by providing evidence-based methods, such as the Institute for Healthcare Improvement’s Breakthrough Series Collaborative methodology. These methods are relatively untested within dentistry. The aim of this study was to evaluate the impact to inform the development and implementation of improvement collaboratives as a means for QI in primary care dentistry.DesignA multimethod study underpinned by the Theoretical Domains Framework and the Kirkpatrick model. Quantitative data were collected using baseline and follow-up questionnaires, designed to explore beliefs and behaviours towards improving quality in practice. Qualitative data were gathered using interviews with dental team members and practice-based case studies.ResultsOne hundred and eleven dental team members completed the baseline questionnaire. Follow-up questionnaires were returned by 79 team members. Twelve practices, including two case studies, participated in evaluation interviews. Findings identified positive beliefs and increased knowledge and skills towards QI, as well as increased confidence about using QI methodologies in practice. Barriers included time, poor patient and team engagement, communication and leadership. Facilitators included team working, clear roles, strong leadership, training, peer support and visible benefits. Participants’ knowledge and skills were identified as an area for improvement.ConclusionsFindings demonstrate increased knowledge, skills and confidence in relation to QI methodology and highlight areas for improvement. This is an example of partnership working between the Scottish Government and NHSScotland towards a shared ambition to provide safe care to every patient. More work is required to evaluate the sustainability and transferability of improvement collaboratives as a means for QI in dentistry and wider primary care.


2021 ◽  
Vol 13 (4) ◽  
pp. 593
Author(s):  
Lorenzo Lastilla ◽  
Valeria Belloni ◽  
Roberta Ravanelli ◽  
Mattia Crespi

DSM generation from satellite imagery is a long-lasting issue and it has been addressed in several ways over the years; however, expert and users are continuously searching for simpler but accurate and reliable software solutions. One of the latest ones is provided by the commercial software Agisoft Metashape (since version 1.6), previously known as Photoscan, which joins other already available open-source and commercial software tools. The present work aims to quantify the potential of the new Agisoft Metashape satellite processing module, considering that to the best knowledge of the authors, only two papers have been published, but none considering cross-sensor imagery. Here we investigated two different case studies to evaluate the accuracy of the generated DSMs. The first dataset consists of a triplet of Pléiades images acquired over the area of Trento and the Adige valley (Northern Italy), which is characterized by a great variety in terms of geomorphology, land uses and land covers. The second consists of a triplet composed of a WorldView-3 stereo pair and a GeoEye-1 image, acquired over the city of Matera (Southern Italy), one of the oldest settlements in the world, with the worldwide famous area of Sassi and a very rugged morphology in the surroundings. First, we carried out the accuracy assessment using the RPCs supplied by the satellite companies as part of the image metadata. Then, we refined the RPCs with an original independent terrain technique able to supply a new set of RPCs, using a set of GCPs adequately distributed across the regions of interest. The DSMs were generated both in a stereo and multi-view (triplet) configuration. We assessed the accuracy and completeness of these DSMs through a comparison with proper references, i.e., DSMs obtained through LiDAR technology. The impact of the RPC refinement on the DSM accuracy is high, ranging from 20 to 40% in terms of LE90. After the RPC refinement, we achieved an average overall LE90 <5.0 m (Trento) and <4.0 m (Matera) for the stereo configuration, and <5.5 m (Trento) and <4.5 m (Matera) for the multi-view (triplet) configuration, with an increase of completeness in the range 5–15% with respect to stereo pairs. Finally, we analyzed the impact of land cover on the accuracy of the generated DSMs; results for three classes (urban, agricultural, forest and semi-natural areas) are also supplied.


Author(s):  
Sheree A Pagsuyoin ◽  
Joost R Santos

Water is a critical natural resource that sustains the productivity of many economic sectors, whether directly or indirectly. Climate change alongside rapid growth and development are a threat to water sustainability and regional productivity. In this paper, we develop an extension to the economic input-output model to assess the impact of water supply disruptions to regional economies. The model utilizes the inoperability variable, which measures the extent to which an infrastructure system or economic sector is unable to deliver its intended output. While the inoperability concept has been utilized in previous applications, this paper offers extensions that capture the time-varying nature of inoperability as the sectors recover from a disruptive event, such as drought. The model extension is capable of inserting inoperability adjustments within the drought timeline to capture time-varying likelihoods and severities, as well as the dependencies of various economic sectors on water. The model was applied to case studies of severe drought in two regions: (1) the state of Massachusetts (MA) and (2) the US National Capital Region (NCR). These regions were selected to contrast drought resilience between a mixed urban–rural region (MA) and a highly urban region (NCR). These regions also have comparable overall gross domestic products despite significant differences in the distribution and share of the economic sectors comprising each region. The results of the case studies indicate that in both regions, the utility and real estate sectors suffer the largest economic loss; nonetheless, results also identify region-specific sectors that incur significant losses. For the NCR, three sectors in the top 10 ranking of highest economic losses are government-related, whereas in the MA, four sectors in the top 10 are manufacturing sectors. Furthermore, the accommodation sector has also been included in the NCR case intuitively because of the high concentration of museums and famous landmarks. In contrast, the Wholesale Trade sector was among the sectors with the highest economic losses in the MA case study because of its large geographic size conducive for warehouses used as nodes for large-scale supply chain networks. Future modeling extensions could potentially include analysis of water demand and supply management strategies that can enhance regional resilience against droughts. Other regional case studies can also be pursued in future efforts to analyze various categories of drought severity beyond the case studies featured in this paper.


2021 ◽  
Vol 13 (3) ◽  
pp. 525
Author(s):  
Yann Forget ◽  
Michal Shimoni ◽  
Marius Gilbert ◽  
Catherine Linard

By 2050, half of the net increase in the world’s population is expected to reside in sub-Saharan Africa (SSA), driving high urbanization rates and drastic land cover changes. However, the data-scarce environment of SSA limits our understanding of the urban dynamics in the region. In this context, Earth Observation (EO) is an opportunity to gather accurate and up-to-date spatial information on urban extents. During the last decade, the adoption of open-access policies by major EO programs (CBERS, Landsat, Sentinel) has allowed the production of several global high resolution (10–30 m) maps of human settlements. However, mapping accuracies in SSA are usually lower, limited by the lack of reference datasets to support the training and the validation of the classification models. Here we propose a mapping approach based on multi-sensor satellite imagery (Landsat, Sentinel-1, Envisat, ERS) and volunteered geographic information (OpenStreetMap) to solve the challenges of urban remote sensing in SSA. The proposed mapping approach is assessed in 17 case studies for an average F1-score of 0.93, and applied in 45 urban areas of SSA to produce a dataset of urban expansion from 1995 to 2015. Across the case studies, built-up areas averaged a compound annual growth rate of 5.5% between 1995 and 2015. The comparison with local population dynamics reveals the heterogeneity of urban dynamics in SSA. Overall, population densities in built-up areas are decreasing. However, the impact of population growth on urban expansion differs depending on the size of the urban area and its income class.


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