Your search found 3 records
1 Pattinson, N. B.; Taylor, J.; Dickens, Chris W. S.; Graham, P. M. 2023. Digital innovation in citizen science to enhance water quality monitoring in developing countries. Colombo, Sri Lanka: International Water Management Institute (IWMI). 37p. (IWMI Working Paper 210) [doi: https://doi.org/10.5337/2024.201]
Digital innovation ; Citizen science ; Water quality ; Monitoring ; Developing countries ; Freshwater ecosystems ; Water resources ; Water management ; Decision support ; Community involvement ; Data collection ; Digital technology ; Sensors ; Databases ; Smartphones ; Mobile applications ; Innovation adoption ; Big data ; Sustainable Development Goals ; Goal 6 Clean water and sanitation ; Parameters ; Mitigation
(Location: IWMI HQ Call no: IWMI Record No: H052509)
(1.02 MB)
Freshwater systems are disproportionately adversely affected by the ongoing, global environmental crisis. The effective and efficient water resource conservation and management necessary to mitigate the crisis requires monitoring data, especially on water quality. This is recognized by Sustainable Development Goal (SDG) 6, particularly indicator 6.3.2., which requires all UN member states to measure and report the ‘proportion of water bodies with good ambient water quality’. However, gathering sufficient data on water quality is reliant on data collection at spatial and temporal scales that are generally outside the capacity of institutions using conventional methods. Digital technologies, such as wireless sensor networks and remote sensing, have come to the fore as promising avenues to increase the scope of data collection and reporting. Citizen science (which goes by many names, e.g., participatory science or community-based monitoring) has also been earmarked as a powerful mechanism to improve monitoring. However, both avenues have drawbacks and limitations. The synergy between the strengths of modern technologies and citizen science presents an opportunity to use the best features of each to mitigate the shortcomings of the other. This paper briefly synthesizes recent research illustrating how smartphones, sometimes in conjunction with other sensors, present a nexus point method for citizen scientists to engage with and use sophisticated modern technology for water quality monitoring. This paper also presents a brief, non-exhaustive research synthesis of some examples of current technological upgrades or innovations regarding smartphones in citizen science water quality monitoring in developing countries and how these can assist in objective, comprehensive, and improved data collection, management and reporting. While digital innovations are being rapidly developed worldwide, there remains a paucity of scientific and socioeconomic validation of their suitability and usefulness within citizen science. This perhaps contributes to the fact that the uptake and upscaling of smartphone-assisted citizen science continues to underperform compared to its potential within water resource management and SDG reporting. Ultimately, we recommend that more rigorous scientific research efforts be dedicated to exploring the suitability of digital innovations in citizen science in the context of developing countries and SDG reporting.
2 Jie, Y.; Xiaoshu, C.; Jun, Y.; Zhewen, K.; Jianxia, C.; Yimin, W. 2024. Geographical big data and data mining: a new opportunity for “water-energy-food” nexus analysis. Journal of Geographical Sciences, 34(2):203-228. [doi: https://doi.org/10.1007/s11442-024-2202-6]
Food security ; Water resources ; Water quality ; Energy ; Climate change ; Nexus approaches ; Big data ; Data mining ; Interactions ; Sustainability ; Sustainable development ; Urbanization ; Land use ; Socioeconomic aspects ; Policies ; Artificial intelligence ; Machine learning ; Models ; Decision-support systems
(Location: IWMI HQ Call no: e-copy only Record No: H052609)
(2.54 MB)
Since the Bonn 2011 conference, the “water-energy-food” (WEF) nexus has aroused global concern to promote sustainable development. The WEF nexus is a complex, dynamic, and open system containing interrelated and interdependent elements. However, the nexus studies have mainly focused on natural elements based on massive earth observation data. Human elements (e.g., society, economy, politics, culture) are described insufficiently, because traditional earth observation technologies cannot effectively perceive socioeconomic characteristics, especially human feelings, emotions, and experiences. Thus, it is difficult to simulate the complex WEF nexus. With the development of earth observation sensor technologies and human activity perception methods, geographical big data covering both human activities and natural elements offers a new opportunity for in-depth WEF nexus analysis. This study proposes a five-step framework by leveraging geographical big data mining to dig for the hidden value in the data of various natural and human elements. This framework can enable a thorough and comprehensive analysis of the WEF nexus. Some application examples of the framework, major challenges, and possible solutions are discussed. Geographical big data mining is a promising approach to enhance the analysis of the WEF nexus, strengthen the coordinated management of resources and sectors, and facilitate the progress toward sustainable development.
3 Zhou, G.; Li, Z.; Wang, W.; Wang, Q.; Yu, J. 2024. Understanding the impact of population dynamics on water use utilizing multi-source big data. Journal of Hydroinformatics, jh2024179. (Online first) [doi: https://doi.org/10.2166/hydro.2024.179]
Water use ; Big data ; Water supply ; Water demand ; Sewage ; Towns ; Villages ; Water resources ; Water levels ; Wastewater treatment / China / Beijing / Haidian / Shangzhuang Town / Xibeiwang Town / Wenquan Town / Sujiatuo Town
(Location: IWMI HQ Call no: e-copy only Record No: H052622)
https://iwaponline.com/jh/article-pdf/doi/10.2166/hydro.2024.179/1356725/jh2024179.pdf
https://vlibrary.iwmi.org/pdf/H052622.pdf
https://vlibrary.iwmi.org/pdf/H052622.pdf
(1.42 MB) (1.42 MB)
Population movement, such as commuting, can affect water supply pressure and efficiency in modern cities. However, there is a gap in the research concerning the relationship between water use and population mobility, which is of great significance for urban water supply planning and supporting urban sustainable development. In this study, we analyzed the spatial–temporal dynamics of the population and its underlying mechanisms, using multi-source geospatial big data, including Baidu heat maps (BHMs), land use parcels, and point of interest. Combined with water consumption, sewage volume, and river depth data, the impact of population dynamics on water use was investigated. The results showed that there were obvious differences in population dynamics between weekdays and weekends with a ratio of 1.11 for the total population. Spatially, the population concentration was mainly observed in areas associated with enterprises, industries, shopping, and leisure activities during the daytime, while at nighttime, it primarily centered around residential areas. Moreover, the population showed a significant impact on water use, resulting in co-periods of 24 h and 7 days, and the water consumption as well as the wastewater production were observed to be proportional to the population density. This study can offer valuable implications for urban water resource allocation strategies.
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