Your search found 10 records
1 Kite, G. W.; Danard, M.; Li, B.. 1998. Simulating long series of streamflow using data from an atmospheric model. Hydrological Sciences Journal, 43(3):391-407.
Simulation models ; Stream flow ; Hydrology ; Climate ; Forecasting ; Land use ; Runoff ; Precipitation ; Watersheds / Canada / Upper Columbia Basin
(Location: IWMI-HQ Call no: IIMI 551.488 G000 KIT Record No: H024682)
2 Zhang, J.; Sui, X.; Li, B.; Su, B.; Li, J.; Zhou, D. 1998. An improved water-use efficiency for winter wheat grown under reduced irrigation. Field Crops Research, 59:91-98.
Wheat ; Water use efficiency ; Irrigation practices ; Experiments ; Soil water ; Plant growth / China / Beijing
(Location: IWMI-HQ Call no: P 5383 Record No: H025655)
3 LI, B.; Chen, Z; Huan, G. 2003. Control volume function approximation methods and their applications to modeling porus media flow. Advances in Water Resources, 26(4):435-444.
(Location: IWMI-HQ Call no: PER Record No: H031615)
4 Li, J.; Li, B.; Rao, M. 2005. Spatial and temporal distributions of nitrogen and crop yield as affected by nonuniformity of sprinkler fertigation. Agricultural Water Management, 76(3):160-180.
Sprinkler irrigation ; Fertigation ; Nitrogen ; Environmental effects ; Percolation ; Wheat ; Yields
(Location: IWMI-HQ Call no: PER Record No: H037140)
5 Chen, D.; White, R.; Li, Y.; Zhang, J.; Li, B.; Zhang, Y.; Edis, R.; Huang, Y.; Cai, G.; Wei, Y.; Zhu, A.; Hu, K.; Li, G.; Zhu, Z. 2006. Conservation management of water and nitrogen in the North China Plain using a GIS-based water and nitrogen management model and agricultural decision support tool. In Willett, I. R.; Gao, Z. (Eds.) Agricultural water management in China: Proceedings of a workshop held in Beijing, China, 14 September 2005. Canberra, Australia: ACIAR. pp.26-38.
Water conservation ; Irrigated farming ; Nitrogen ; Fertilizers ; Wheat ; Maize ; GIS ; Decision support tools / China / North China Plain
(Location: IWMI-HQ Call no: 631.7 G592 WIL Record No: H039219)
6 Wei, Y.; Chen, D.; Edis, R.; White, R.; Davidson, B.; Zhang, J.; Li, B.. 2006. The perspective of farmers on why the adoption rate of water-saving irrigation techniques is low in China. In Willett, I. R.; Gao, Z. (Eds.) Agricultural water management in China: Proceedings of a workshop held in Beijing, China, 14 September 2005. Canberra, Australia: ACIAR. pp.153-160.
Water conservation ; Farmers’ attitudes ; Irrigation water ; Farm surveys / China / Henan Province / Fengqiu County
(Location: IWMI-HQ Call no: 631.7 G592 WIL Record No: H039229)
7 Bhanja, S. N.; Rodell, M.; Li, B.; Saha, D.; Mukherjee, A. 2017. Spatio-temporal variability of groundwater storage in India. Journal of Hydrology, 544:428-437. [doi: https://doi.org/10.1016/j.jhydrol.2016.11.052]
Groundwater table ; Water storage ; Spatial variation ; River basins ; Hydrogeology ; Models ; Precipitation ; Monsoon climate ; Wells ; Measurement ; Monitoring ; Satellite observation ; Costs / India
(Location: IWMI HQ Call no: e-copy only Record No: H047956)
(4.60 MB)
Groundwater level measurements from 3907 monitoring wells, distributed within 22 major river basins of India, are assessed to characterize their spatial and temporal variability. Groundwater storage (GWS) anomalies (relative to the long-term mean) exhibit strong seasonality, with annual maxima observed during the monsoon season and minima during pre-monsoon season. Spatial variability of GWS anomalies increases with the extent of measurements, following the power law relationship, i.e., log-(spatial variability) is linearly dependent on log-(spatial extent). In addition, the impact of well spacing on spatial variability and the power law relationship is investigated. We found that the mean GWS anomaly sampled at a 0.25 degree grid scale closes to unweighted average over all wells. The absolute error corresponding to each basin grows with increasing scale, i.e., from 0.25 degree to 1 degree. It was observed that small changes in extent could create very large changes in spatial variability at large grid scales. Spatial variability of GWS anomaly has been found to vary with climatic conditions. To our knowledge, this is the first study of the effects of well spacing on groundwater spatial variability. The results may be useful for interpreting large scale groundwater variations from unevenly spaced or sparse groundwater well observations or for siting and prioritizing wells in a network for groundwater management. The output of this study could be used to maintain a cost effective groundwater monitoring network in the study region and the approach can also be used in other parts of the globe.
8 Yue, L.; Li, B.; Zhu, S.; Yuan, Q.; Shen, H. 2023. A fully automatic and high-accuracy surface water mapping framework on google earth engine using landsat time-series. International Journal of Digital Earth, 16(1):210-233. [doi: https://doi.org/10.1080/17538947.2023.2166606]
Surface water ; Mapping ; Frameworks ; Landsat ; Remote sensing ; Satellite imagery ; Models ; Water extraction / China / Wuhan
(Location: IWMI HQ Call no: e-copy only Record No: H051708)
https://www.tandfonline.com/doi/epdf/10.1080/17538947.2023.2166606?needAccess=true&role=button
https://vlibrary.iwmi.org/pdf/H051708.pdf
https://vlibrary.iwmi.org/pdf/H051708.pdf
(7.71 MB) (7.71 MB)
Efficient and continuous monitoring of surface water is essential for water resource management. Much effort has been devoted to the task of water mapping based on remote sensing images. However, few studies have fully considered the diverse spectral properties of water for the collection of reference samples in an automatic manner. Moreover, water area statistics are sensitive to the satellite image observation quality. This study aims to develop a fully automatic surface water mapping framework based on Google Earth Engine (GEE) with a supervised random forest classifier. A robust scheme was built to automatically construct training samples by merging the information from multi-source water occurrence products. The samples for permanent and seasonal water were mapped and collected separately, so that the supplement of seasonal samples can increase the spectral diversity of the sample space. To reduce the uncertainty of the derived water occurrences, temporal correction was applied to repair the classification maps with invalid observations. Extensive experiments showed that the proposed method can generate reliable samples and produce good-quality water mapping results. Comparative tests indicated that the proposed method produced water maps with a higher quality than the index-based detection methods, as well as the GSWD and GLAD datasets.
9 Li, B.; Zhang, W.; Long, J.; Chen, M.; Nie, J.; Liu, P. 2023. Regional water resources security assessment and optimization path analysis in karst areas based on emergy ecological footprint. Applied Water Science, 13(6):142. [doi: https://doi.org/10.1007/s13201-023-01951-0]
Water resources ; Ecological footprint ; Water security ; Sustainable development ; Karst ; Economic development / China / Anshun
(Location: IWMI HQ Call no: e-copy only Record No: H051944)
https://link.springer.com/content/pdf/10.1007/s13201-023-01951-0.pdf?pdf=button
https://vlibrary.iwmi.org/pdf/H051944.pdf
https://vlibrary.iwmi.org/pdf/H051944.pdf
(1.19 MB) (1.19 MB)
With the continuous growth of the world's social economy and population, problems such as water shortage and water environment deterioration need to be solved urgently. Combining the emergy carrying capacity of water resources and the emergy ecological footprint method, the water security and sustainable development status of the typical city in the karst region (Anshun City) was evaluated, and the internal driving factors and optimization suggestions were discussed. The research results of water security in Anshun City show that: The water resources carrying capacity fluctuates greatly with rainfall and is generally in a low-level surplus state. The ecological pressure index and the sustainable utilization index show a downward trend. The pressure intensity of social and economic systems on water resources is increasing, and the sustainable development of water resources is not optimistic. Water resources security is mainly affected by natural ecological mechanisms centered on mountain systems, geological structures and hydrological systems, as well as social mechanisms centered on changes in population scale, land development and utilization, and urban development. In the future, the sustainable development of water resources can be promoted by changing the mode of economic development, optimizing the allocation of water resources, and protecting the ecological environment.
10 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.
Powered by DB/Text WebPublisher, from
