Your search found 5 records
1 Zuo, W.; Zhou, H. Z.; Zhu, X. H.; Wang, Q.; Wang, W. J.; Wu, X. Q. 2005. Integrated evaluation of ecological security at different scales using remote sensing: A case study of Zhongxian County, the Three Gorges Area, China. Pedosphere, 15(4):456-464.
Watersheds ; Ecology ; Models ; Remote sensing ; Case studies / China / Zhongxian County / Three Gorges Area
(Location: IWMI-HQ Call no: PER Record No: H037916)
2 Yang, Y.; Watanabe, M.; Zhang, X.; Zhang, J.; Wang, Q.; Hayashi, S. 2006. Optimizing irrigation management for wheat to reduce groundwater depletion in the Piedmont Region of the Taihang Mountains in the North China Plain. Agricultural Water Management, 82(1/2):25-44.
Irrigation management ; Wheat ; Soil water ; Simulation models ; Water conservation ; Water use efficiency ; Groundwater depletion / China / Piedmont Region / North China Plain / Taihang Mountains
(Location: IWMI-HQ Call no: PER Record No: H038675)
3 Lin, J.; Bryan, B. A.; Zhou, X.; Lin, P.; Do, H. X.; Gao, L.; Gu, X.; Liu, Z.; Wan, L.; Tong, S.; Huang, J.; Wang, Q.; Zhang, Y.; Gao, H.; Yin, J.; Chen, Z.; Duan, W.; Xie, Z.; Cui, T.; Liu, J.; Li, M.; Li, X.; Xu, Z.; Guo, F.; Shu, L.; Li, B.; Zhang, J.; Zhang, P.; Fan, B.; Wang, Y.; Zhang, Y.; Huang, J.; Li, X.; Cai, Y.; Yang, Z. 2023. Making China’s water data accessible, usable and shareable. Nature Water, 1:328-335. [doi: https://doi.org/10.1038/s44221-023-00039-y]
Water resources ; Data collection ; Databases ; Monitoring ; Modelling ; Water quality ; Wastewater treatment ; Stream flow ; Transboundary waters ; Water demand ; Infrastructure ; Policies / China
(Location: IWMI HQ Call no: e-copy only Record No: H052133)
(1.42 MB)
Water data are essential for monitoring, managing, modelling and projecting water resources. Yet despite such data—including water quantity, quality, demand and ecology—being extensively collected in China, it remains difficult to access, use and share them. These challenges have led to poor data quality, duplication of effort and wasting of resources, limiting their utility for supporting decision-making in water resources policy and management. In this Perspective we discuss the current state of China’s water data collection, governance and sharing, the barriers to open-access water data and its impacts, and outline a path to establishing a national water data infrastructure to reform water resource management in China and support global water-data sharing initiatives.
4 Yu, S.; Peng, J.; Xia, P.; Wang, Q.; Grabowski, R. C.; Azhoni, A.; Bala, B.; Shankar, V.; Meersmans, J. 2023. Network analysis of water-related ecosystem services in search of solutions for sustainable catchment management: a case study in Sutlej-Beas River systems, India. Ecosystem Services, 63:101557. [doi: https://doi.org/10.1016/j.ecoser.2023.101557]
Ecosystem services ; Watershed management ; Network analysis ; Land use ; Flooding ; Mitigation ; Stakeholders ; Water conservation ; Water power ; Case studies / India / Sutlej-Beas River
(Location: IWMI HQ Call no: e-copy only Record No: H052352)
(8.57 MB)
Hydrological processes and ecosystem interactions are instrumental in sustaining local populations by providing various water-related ecosystem services (ES). Numerous studies gave priority to the theories and methods of building networks that emphasized different stakeholders. However, little study has examined the complex relationships among water-related ES themselves and how relevant human activities affect ES networks. To narrow this gap, in this study we quantified four critical water-related ES (flood mitigation, hydropower production, soil retention, and water conservation), set up six ES network types based on the synergy relationship, and further explored the effect of human activities on these networks. The results showed that among six ES network categories, networks with four fully linked ES occupied a large percentage of 23.20% while the network with one central ES linking two others accounted for the lowest percentage (9.28%). Compared with other ES, soil retention tended to be less centralized within the networks. In addition, land use intensity was found to greatly influence the ES networks compared with other indicators, especially for less complex networks. Our results highlighted the importance of network analysis in searching solutions for sustainable catchment management.
5 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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