Scientific Results

This catalogue is obtained by conducting a systematic literature review of scientific studies and reviews related to monitoring, forecasting, and simulating the inland water cycle. The analysis maps scientific expertise across research groups and classifies findings by the type of inland water studied, application focus, and geographical scope. A gap analysis will identify missing research areas and assess their relevance to policymaking.

ID ▲	Type	Year	Authors	Title	Venue/Journal	DOI	Abstract
publications-3761	article	2021	Neethirajan, Suresh and Neethirajan, Suresh and Kemp, B. and Kemp, Bas and Kemp, Bas	Digital Twins in Livestock Farming.	Animal	10.3390/ani11041008	Artificial intelligence (AI), machine learning (ML) and big data are consistently called upon to analyze and comprehend many facets of modern daily life. AI and ML in particular are widely used in animal husbandry to monitor both the animals and environment around the clock, which leads to a better understanding of animal behavior and distress, disease control and prevention, and effective business decisions for the farmer. One particularly promising area that advances upon AI is digital twin technology, which is currently used to improve efficiencies and reduce costs across multiple industries and sectors. In contrast to a model, a digital twin is a digital replica of a real-world entity that is kept current with a constant influx of data. The application of digital twins within the livestock farming sector is the next frontier and has the potential to be used to improve large-scale precision livestock farming practices, machinery and equipment usage, and the health and well-being of a wide variety of farm animals. The mental and emotional states of animals can be monitored using recognition technology that examines facial features, such as ear postures and eye white regions. Used with modeling, simulation and augmented reality technologies, digital twins can help farmers to build more energy-efficient housing structures, predict heat cycles for breeding, discourage negative behaviors of livestock, and potentially much more. As with all disruptive technological advances, the implementation of digital twin technology will demand a thorough cost and benefit analysis of individual farms. Our goal in this review is to assess the progress toward the use of digital twin technology in livestock farming, with the goal of revolutionizing animal husbandry in the future.
publications-3762	article	2021	Kim, Dongwoo and Kim, Dongwoo and Yim, Taesu and Yim, Taesu and Lee, Jae Yong and Lee, Jae Yong	Analytical study on changes in domestic hot water use caused by COVID-19 pandemic	Energy	10.1016/j.energy.2021.120915	Abstract COVID-19 made considerable changes in the lifestyle of people, which have led to a rise in energy use in homes. So, this study investigated the relationship between COVID-19 and domestic hot water demands. For this purpose, a nondimensional and principal component analysis were conducted to find out the influencing factors using demand data before and after COVID-19 from our study site. Analysis showed that the COVID-19 outbreak affected the daily peak time and the amount of domestic hot water usage, the active case number of COVID-19 was a good indicator for correlating the changes in hot water demand and patterns. Based on this, a machine learning model with an artificial neural network was developed to predict hot water demand depending on the severity of COVID-19 and the relevant correlation was also derived. The model analysis showed that the increase in the number of active cases in the region affected the hot water demand increased at a certain rate and the maximum demand peak in morning during weekdays and weekends decreased. Furthermore, if the number of active cases reached more than 4000, the peak in morning moved to afternoon so that the energy use patterns of weekdays and weekends are assimilated.
publications-3763	article	2021	Feizizadeh, Bakhtiar and Feizizadeh, Bakhtiar and Feizizadeh, Bakhtiar and Feizizadeh, Bakhtiar and Omarzadeh, Davoud and Omarzadeh, Davoud and Ronagh, Zahra and Ronagh, Zahra and Sharifi, Ayyoob and Sharifi, Ayyoob and Blaschke, Thomas and Blaschke, Thomas and Lakes, Tobia and Lakes, Tobia	A scenario-based approach for urban water management in the context of the COVID-19 pandemic and a case study for the Tabriz metropolitan area, Iran.	Science of The Total Environment	10.1016/j.scitotenv.2021.148272	The world's poorest countries were hit hardest by COVID-19 due to their limited capacities to combat the pandemic. The urban water supply and water consumption are affected by the pandemic because it intensified the existing deficits in the urban water supply and sanitation services. In this study, we develop an integrated spatial analysis approach to investigate the impacts of COVID-19 on multi-dimensional Urban Water Consumption Patterns (UWCPs) with the aim of forecasting the water demand. We selected the Tabriz metropolitan area as a case study area and applied an integrated approach of GIS spatial analysis and regression-based autocorrelation assessment to develop the UWCPs for 2018, 2019 and 2020. We then employed GIS-based multi-criteria decision analysis and a CA-Markov model to analyze the water demand under the impacts of COVID-19 and to forecast the UWCPs for 2021, 2022 and 2023. In addition, we tested the spatial uncertainty of the prediction maps using the Dempster Shafer Theory. The results show that the domestic water consumption increased by 17.57\% during the year 2020 as a result of the COVID-19 pandemic. The maximum increase in water consumption was observed in spring 2020 (April-June) when strict quarantine regulations were in place. Based on our results, the annual water deficit in Tabriz has increased from ~18\% to about 30\% in 2020. In addition, our projections show that this may further increase to about 40-45\% in 2021. Relevant stakeholders can use the findings to develop evidence-informed strategies for sustainable water resource management in the post-COVID era. This research also makes other significant contributions. From the environmental perspective, since COVID-19 has affected resource management in many parts of the world, the proposed method can be applied to similar contexts to mitigate the adverse impacts and developed better informed recovery plans.
publications-3764	article	2021	Abulibdeh, Ammar and Abulibdeh, Ammar and Abulibdeh, Ammar	Spatiotemporal analysis of water-electricity consumption in the context of the COVID-19 pandemic across six socioeconomic sectors in Doha City, Qatar.	Applied Energy	10.1016/j.apenergy.2021.117864	This study investigates the water β€“ electricity consumption in the context of the COVID-19 pandemic across six socioeconomic sectors. Due to inadequate research on spatial modelling of water β€“ electricity consumption in the context of the COVID-19 pandemic, this study investigated geographical block-level variation in water and electricity consumption in Doha city of Qatar. Spatial analyses were performed to investigate the spatial differences in each sector. Five geospatial techniques in a Geographical Information System (GIS) context were used in the study. Moranβ€™s I, Anselin Local Moran's I, and Getis-Ord Giβ— statistics tools were used to identify the hot spots and cold spots of water and electricity consumption in each sector. Furthermore, Ordinary Least Square (OLS) and Geographically Weighted Regression (GWR) models were employed to investigate the spatial relationship between water and electricity consumption during the pandemic year. The findings show that there is a distinction in water and electricity consumption at the block level across all sectors and over time. Hot spot and spatial regression analysis reveal spatial and temporal heterogeneities in the study area across the six socioeconomic sectors. The intensity of hot spots of water and electricity consumption are found in the southern and western parts of the city due to high population density and the concentration of the commercial and industrial areas. Furthermore, analyzing the spatiotemporal correlation between the water and electricity consumption across the six sectors shows variation within and between these sectors over space and time. The results show a positive relationship between water and electricity consumption in some blocks and over time of each sector. During the lockdown phase, strong positive correlation between water and electricity consumption have exist in the residential sector due to extra water and electricity footprints in this sector. Conversely, the water and electricity consumption were positively correlated but declined in the industrial and commercial sector due to the curtailment in production, economic activities, and reduction in peopleβ€™s mobility. Mapping the hot spot blocks and the blocks with high relationship between water and electricity consumption could provide useful insight to decision-makers for targeted interventions.
publications-3765	article	2022	Almulhim, Abdulaziz I. and Almulhim, Abdulaziz I. and Aina, Yusuf A. and Aina, Yusuf A.	Understanding Household Water-Use Behavior and Consumption Patterns during COVID-19 Lockdown in Saudi Arabia	Water	10.3390/w14030314	With the COVID-19 lockdown impacting the livelihood of people globally, changes in household behaviors, water consumption patterns, etc., have implications on sanitation, hygiene, and disease control. An online questionnaire survey was conducted, and officials were interviewed to assess the impact of the lockdown on water consumption patterns in the Dammam Metropolitan Area, Saudi Arabia. The multiple regression analysis on responses from the survey indicates that water consumption increased by 50\% in 86\% of the respondents, leading to higher utility bills. Socioeconomic factors also influenced water consumption. The officials interviewed emphasized the need for integrating water policies with disaster management actions. This study contributes to the prospering empirical literature on the pandemic COVID-19 and water consumption/usage behavioral practices by exploring the behavior of household water during COVID-19 in Saudi Arabia. This study can help decision-makers in Saudi Arabia and other developing countries in boosting awareness related to water management in crisis time.
publications-3766	article	2022		A Strategic Digital Transformation for the Water Industry		10.2166/9781789063400	This book is a compilation of the knowledge shared and generated so far in the IWA Digital Water Programme. It is an insightful collection of white papers covering best practices, linking academic and industrial studies/insights with applications to give real-world examples of digital transformation. These White Papers are designed to help utilities, water professionals and all those interested in water management and stewardship issues to better understand the opportunities of digital technologies. This book covers a plethora of topics including: Instrumentation and data generationArtificial intelligence and digital twinsThe digital transformation and public healthMapping the digital transformation journey into the future With these topics, the aim is to present an all-encompassing reference for practitioners to use in their day-to-day activities. Through the Digital Water Programme, the IWA leverages its worldwide member expertise to guide a new generation of water and wastewater utilities on their digital journey towards the uptake of digital technologies and their integration into water services. ISBN: 9781789063394 (Paperback) ISBN: 9781789063400 (eBook) ISBN: 9781789063417 (ePUB)
publications-3767	article	2023	Manny, Liliane	Socio-technical challenges towards data-driven and integrated urban water management: A socio-technical network approach		10.1016/j.scs.2022.104360	Data-driven and integrated urban water management have been proposed to reduce surface water pollution in light of climate change and urbanization impacts. Besides technological innovation, data-driven and integrated management require information exchange among many actors, e.g., operators, engineers, or authorities. With the aim of achieving a more profound understanding of socio-technical infrastructures, such as urban water systems, I draw on the approach of socio-technical networks to study actors and infrastructure elements as well as multiple relations in-between. In this article, I investigate whether underlying socio-technical dependencies influence social interactions such as information exchange. More specifically related to data-driven and integrated management, I analyze potential challenges, such as organizational fragmentation, data access, and diverging perceptions. Based on empirical data from three case studies in Switzerland, I provide inferential results obtained from fitting exponential random graph models. Findings showed that actorsβ€™ relatedness to infrastructure elements affects their information exchange. Among the cases, the presence of the three challenges varied and is potentially contingent upon system size, organizational form, or progress in terms of data-driven and integrated management. Thus, incorporating a socio-technical perspective on social actors and infrastructure elements could help to improve policy design and implementation aiming to achieve more sustainable cities.
publications-3768	article	2013	Fair, Barbara and Fair, Barbara A. and Fair, Barbara A. and Safley, Charles D. and Safley, Charles D. and Safley, Charles	Residential landscape water use in 13 North Carolina communities	Journal American Water Works Association	10.5942/jawwa.2013.105.0120	In 2009, North Carolina State University researchers conducted a survey of residents from 13 North Carolina communities to gather information on attitudes and behaviors related to landscape water use. The survey gathered information on landscape type, water use, and the effectiveness of watering restrictions. Actual waterβ€use data for a twoβ€year period was anonymously matched with participating households. The survey achieved a 49\% response rate. Most respondents indicated that more than 75\% of their landscape consisted of lawn, with 60\% using warmβ€season turfgrass species. Those whose lawns were planted with coolβ€season grass used more water than those whose lawns were planted with warmβ€season species. A total of 42\% of respondents restricted their landscape water use to new plantings or stressed plants. More than 88\% of respondents watered by hand. In most communities, no watering restrictions were in place during this survey. Water purveyors can use the results of this survey to better understand their customers' outdoor water use and thus develop effective education programs on water conservation techniques related to landscape irrigation.
publications-3769	article	2015	Rokstad, Marius MΓΈller and Rokstad, Marius MΓƒΒΈller and Rokstad, Marius MΓΈller and Ugarelli, Rita Maria and Ugarelli, Rita Maria	Minimising the total cost of renewal and risk of water infrastructure assets by grouping renewal interventions	Reliability Engineering & System Safety	10.1016/j.ress.2015.05.014
publications-3770	article	2015	Cominola, Andrea and Cominola, Andrea and Giuliani, Matteo and Giuliani, Matteo and Piga, Dario and Piga, Dario and Castelletti, Andrea and Castelletti, Andrea and Rizzoli, Andrea Emilio and Rizzoli, Andrea Emilio	Benefits and challenges of using smart meters for advancing residential water demand modeling and management	Environmental Modelling and Software	10.1016/j.envsoft.2015.07.012	Over the last two decades, water smart metering programs have been launched in a number of medium to large cities worldwide to nearly continuously monitor water consumption at the single household level. The availability of data at such very high spatial and temporal resolution advanced the ability in characterizing, modeling, and, ultimately, designing user-oriented residential water demand management strategies. Research to date has been focusing on one or more of these aspects but with limited integration between the specialized methodologies developed so far. This manuscript is the first comprehensive review of the literature in this quickly evolving water research domain. The paper contributes a general framework for the classification of residential water demand modeling studies, which allows revising consolidated approaches, describing emerging trends, and identifying potential future developments. In particular, the future challenges posed by growing population demands, constrained sources of water supply and climate change impacts are expected to require more and more integrated procedures for effectively supporting residential water demand modeling and management in several countries across the world. We review high resolution residential water demand modeling studies.We provide a classification of existing technologies and methodologies.We identify current trends, challenges and opportunities for future development.