Your search found 26 records
1 Wang, X.; Liu, M.; Liu, X.; Xing, X.; Mao, X. 1992. Water use and water use efficiency of winter wheat in a water-deficient and salt-affected area in Hebei province. In Shalhevet, J.; Liu, C.; Xu, Y. (Eds.) Water use efficiency in agriculture: Proceedings of the Binational China-Israel Workshop, Beijing, China, 22-26 April 1991. Rehovot, Israel: Priel Publishers. pp.136-146.
(Location: IWMI-HQ Call no: 631.7.2 G592 SHE Record No: H011011)
2 Wang, X.; Xing, X. 1993. Optimized utilization of agricultural water resources in Jizhong Plain of China. In Tingsanchali, T. (Ed.), Proceedings of the International Conference on Environmentally Sound Water Resources Utilization, Bangkok, Thailand, 8-11 November 1993. Vol.1. Bangkok, Thailand: AIT. pp.I-107-111.
Water resource management ; Groundwater ; Recharge ; Water conservation ; Water allocation ; Mathematical models / China
(Location: IWMI-HQ Call no: 333.91 G000 TIN Record No: H015771)
3 Wang, X.; Yin, Z. Y. 1997. Using GIS to assess the relationship between land use and water quality at a watershed level. Environment International, 23(1):103-114.
GIS ; Land use ; Water quality ; Indicators ; Watersheds ; Statistical analysis / USA / Great Miami River
(Location: IWMI-HQ Call no: P 4724 Record No: H022060)
4 Zhang, H.; Wang, X.; You, M.; Liu, C. 1999. Water-yield relations and water-use efficiency of winter wheat in the North China Plain. Irrigation Science, 19(1):37-45.
Wheat ; Water use efficiency ; Irrigation efficiency ; Water stress ; Evapotranspiration ; Crop yield ; Soil water ; Measurement / China
(Location: IWMI-HQ Call no: PER Record No: H025348)
5 Fu, G.; Min, Q.; Ouyang, Z.; Wang, X.; Wang, R.; Zhang, Q. 2000. China water security scenario. In Wang, R.; Ren, H.; Ouyang, Z. (Eds.), China water vision: The eco-sphere of water, life, environment and development. Beijing, China: China Meteorological Press. pp.52-82.
Water use efficiency ; Food security ; Population ; Water demand ; Economic aspects ; Environmental effects ; Water availability / China
(Location: IWMI-HQ Call no: 333.91 G592 WAN Record No: H026835)
6 Wang, R.; Ouyang, Z.; Fu, G.; Min, Q.; Wang, X.; Hu, D. 2000. Risk and opportunity: Summary of China water vision in the first quarter of 21st century. In Wang, R.; Ren, H.; Ouyang, Z. (Eds.), China water vision: The eco-sphere of water, life, environment and development. Beijing, China: China Meteorological Press. pp.164-172.
(Location: IWMI-HQ Call no: 333.91 G592 WAN Record No: H026838)
7 Wang, X.. 2001. Integrating water-quality management and land-use planning in a watershed context. Journal of Environmental Management, 61:25-36.
Watershed management ; Water quality ; Land use ; Planning ; GIS ; Wastewater ; Pollution control / USA / Little Miami River
(Location: IWMI-HQ Call no: P 6191 Record No: H031215)
8 Mao, X.; Liu, M.; Wang, X.; Liu, C.; Hou, Z.; Shi, J. 2003. Effects of deficit irrigation on yield and water use of greenhouse grown cucumber in the North China Plain. Agricultural Water Management, 61(3):219-228.
Water deficit ; Water use efficiency ; Vegetables ; Crop yield ; Water stress ; Irrigated farming ; Evapotranspiration / China / North China Plain
(Location: IWMI-HQ Call no: PER Record No: H032263)
9 Wang, X.; Hollanders, P. H. J.; Wang, S.; Fang, S. 2004. Effect of field groundwater table control on water and salinity balance and crop yield in the Qingtongxia Irrigation District, China. Irrigation and Drainage, 53(3):263-275.
Groundwater ; Water table ; Simulation models ; Calibration ; Salinity ; Water quality ; Irrigation water ; Crop yield ; Water conservation ; Drainage / China
(Location: IWMI-HQ Call no: PER Record No: H035697)
10 Ongley, E. D.; Wang, X.. 2004. Transjurisdictional water pollution management in China: The legal and institutional framework. Water International, 29(3):270-281.
Water pollution ; Pollution control ; Water management ; Water law ; Institutions ; River basins ; Water use / China
(Location: IWMI-HQ Call no: PER Record No: H035964)
11 Wang, X.; Ongley, E. D. 2004. Transjurisdictional water pollution disputes and measures of resolution: Examples from the Yellow River Basin, China. Water International, 29(3):282-289.
(Location: IWMI-HQ Call no: PER Record No: H035965)
(0.09 MB)
12 Li, C.; Yang, Z.; Wang, X.. 2004. Trends of annual natural runoff in the Yellow River Basin. Water International, 29(4):447-454.
(Location: IWMI-HQ Call no: PER Record No: H036712)
13 Wang, X.; Mosley, C. T.; Frankenberger, J. R.; Kladivko, E. J. 2006. Subsurface drain flow and crop yield predictions for different drain spacings using DRAINMOD. Agricultural Water Management, 79(2):113-136.
(Location: IWMI-HQ Call no: PER Record No: H038288)
14 Wang, X.; Tuppad, P.; Williams, J. R. 2011. Modelling agricultural management systems with APEX [Agricultural Policy Environmental eXtender]. In Shukla, M. K. (Ed.) Soil hydrology, land use and agriculture: measurement and modelling. Wallingford, UK: CABI. pp.117-136.
Agricultural policy ; Simulation models ; Calibration ; Hydrology ; Water erosion ; Elements ; Cycling ; Watersheds ; Stream flow ; Crop yield ; Erosion ; Tillage / USA / Texas / Bosque River
(Location: IWMI HQ Call no: e-copy SF Record No: H045776)
15 Wu, J.; Wang, X.; Zhong, B.; Yang, A.; Jue, K.; Wu, J.; Zhang, L.; Xu, W.; Wu, S.; Zhang, N.; Liu, Q. 2020. Ecological environment assessment for greater Mekong Subregion based on pressure-state-response framework by remote sensing. Ecological Indicators, 117:106521. (Online first) [doi: https://doi.org/10.1016/j.ecolind.2020.106521]
Environmental Impact Assessment ; Ecological indicators ; Remote sensing ; Landsat ; Biodiversity ; Vegetation ; Land use ; Land cover ; Spatial distribution ; Farmland ; Ecosystems ; Anthropogenic factors ; Evapotranspiration ; Sustainable development / China / Myanmar / Lao People's Democratic Republic / Greater Mekong Subregion / Yunnan / Sipsongpanna
(Location: IWMI HQ Call no: e-copy only Record No: H049753)
(6.71 MB)
The environment project in the greater Mekong sub-region was the largest multi-field environmental cooperation launched by six countries (China, Vietnam, Laos, Myanmar, Thailand and Cambodia) in 2006, since the cooperation mechanism was established by Asian Development Bank (ADB) in 1992. How to establish the indicators to assess the achievements of the biological corridor construction and the status of ecological environment quantitatively is one of the prerequisites for the future project ongoing phase. The popular Pressure-State-Response (PSR) framework was employed in this study to assess the natural and human pressure, the healthy state of regional natural environment, and the subsequent response of ecosystem dynamic change in the Greater Mekong Subregion. Instead of using surveying based data as driving parameters, large amount of driving factors were retrieved from multi-source remote sensing data from 2000 to 2017, which provides access to larger updated and real-time databases, more tangible data allowing more objective goal management, and better spatially covered. The driving factors for pressure analysis included digital elevation, land surface temperature, evapotranspiration, light index, road network map, land cover dynamic change and land use degree, which were derived directly and indirectly from remote sensing. The indicators for state evaluation were composed of vegetation index, leaf area index, and fractional vegetation cover from remote sensing directly. The comprehensive response index was mainly determined by the pressure and state indicators. Through the analysis based on an overlay technique, it showed that the ecological environment deteriorated firstly from 2000 to 2010 and then started to improve from 2010 to 2017. The proofs indicated that the natural forest and wetland ecosystems were improved and the farmland area was decreased between 2000 and 2017. This study explored effective indicators from remote sensing for the ecological and environmental assessment, which can provide a strong decision-making basis for promoting the sustainable development of the ecological environment in the greater Mekong subregion, as well as the technological support for the construction of the biodiversity corridor.
16 Song, P.; Zheng, X.; Li, Y.; Zhang, K.; Huang, J.; Li, H.; Zhang, H.; Liu, L.; Wei, C.; Mansaray, L. R.; Wang, D.; Wang, X.. 2020. Estimating reed loss caused by locusta migratoria manilensis using UAV [Unmanned Aerial Vehicle] -based hyperspectral data. Science of the Total Environment, 719:137519. [doi: https://doi.org/10.1016/j.scitotenv.2020.137519]
Crop losses ; Estimation ; Locusta migratoria ; Unmanned aerial vehicles ; Monitoring ; Forecasting ; Models ; Satellite observation ; Remote sensing ; Vegetation index / China / Kenli / Dongying / Shandong
(Location: IWMI HQ Call no: e-copy only Record No: H049853)
(3.89 MB)
Locusta migratoria manilensis has caused major damage to vegetation and crops. Quantitative evaluation studies of vegetation loss estimation from locust damage have seldom been found in traditional satellite-remote-sensing-based research due to insufficient temporal-spatial resolution available from most current satellite-based observations. We used remote sensing data acquired from an unmanned aerial vehicle (UAV) over a simulated Locusta migratoria manilensis damage experiment on a reed (Phragmites australis) canopy in Kenli District, China during July 2017. The experiment was conducted on 72 reed plots, and included three damage duration treatments with each treatment including six locust density levels. To establish the appropriate loss estimation models after locust damage, a hyperspectral imager was mounted on a UAV to collect reed canopy spectra. Loss components of six vegetation indices (RVI, NDVI, SAVI, MSAVI, GNDVI, and IPVI) and two “red edge” parameters (Dr and SDr) were used for constructing the loss estimation models. Results showed that: (1) Among the six selected vegetation indices, loss components of NDVI, MSAVI, and GNDVI were more sensitive to the variation of dry weight loss of reed green leaves and produced smaller estimation errors during the model test process, with RMSEs ranging from 8.8 to 9.1 g/m;. (2) Corresponding model test results based on loss components of the two selected red edge parameters yielded RMSEs of 27.5 g/m2 and 26.1 g/m2 for Dr and SDr respectively, suggesting an inferior performance of red edge parameters compared with vegetation indices for reed loss estimation. These results demonstrate the great potential of UAV-based loss estimation models for evaluating and quantifying degree of locust damage in an efficient and quantitative manner. The methodology has promise for being transferred to satellite remote sensing data in the future for better monitoring of locust damage of larger geographical areas.
17 Wang, X.; Chen, Y.; Li, Z.; Fang, G.; Wang, Y. 2020. Development and utilization of water resources and assessment of water security in Central Asia. Agricultural Water Management, 240:106297. (Online first) [doi: https://doi.org/10.1016/j.agwat.2020.106297]
Water resources development ; Water security ; Assessment ; Agriculture ; Water use ; Water supply ; Water demand ; International waters ; River basins ; Ecological factors ; Socioeconomic environment ; Indicators ; Forecasting ; Models / Central Asia / Kazakhstan / Kyrgyzstan / Tajikistan / Turkmenistan / Uzbekistan
(Location: IWMI HQ Call no: e-copy only Record No: H049902)
(2.23 MB)
The utilization of water resources and water security in Central Asia are critical to the stability of the region. This paper assesses the water security of the five Central Asian countries (Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan) by using the projection pursuit model based on particle swarm optimization (PSO-PEE). The results show that the average annual water consumption in Central Asia is about 1255.57 × 108 m3, and the proportion of agricultural water consumption decreased due in large part to the changes of crop planting structure. For the ecological security, Kazakhstan, Tajikistan and Kyrgyzstan have improved their status, but Turkmenistan is getting worse. For the quantity security of water resources, Tajikistan and Kyrgyzstan are relatively safe, whereas Uzbekistan is at risk. For the socio-economic conditions, Kazakhstan scored the highest, while Tajikistan and Uzbekistan scored the lowest, water consumption per 10,000 dollars of GDP across all five countries is relatively high but shows a significant decreasing trend. For the water supply and demand security, the status of Kazakhstan, Kyrgyzstan and Tajikistan are better than that of Turkmenistan and Uzbekistan. Kazakhstan has achieved a relatively safe level (level ) and the degree of water security is high. Kyrgyzstan, Tajikistan and Turkmenistan are only in the basically safe level (level III). Uzbekistan is under significant pressure with regard to water security (level IV), which indicates that the country needs to strictly control population growth and strengthen the comprehensive management of water resources.
18 Liu, D.; Wang, X.; Aminjafari, S.; Yang, W.; Cui, B.; Yan, S.; Zhang, Y.; Zhu, J.; Jaramillo, F. 2020. Using InSAR [Interferometric Synthetic Aperture Radar] to identify hydrological connectivity and barriers in a highly fragmented wetland. Hydrological Processes, 14p. (Online first) [doi: https://doi.org/10.1002/hyp.13899]
Wetlands ; Hydrological factors ; SAR (radar) ; Radar imagery ; Water levels ; Satellites ; Remote sensing ; Interferometry ; Barriers ; Ecosystems ; Grasslands ; Vegetation / China / Baiyangdian Wetland
(Location: IWMI HQ Call no: e-copy only Record No: H049975)
https://onlinelibrary.wiley.com/doi/epdf/10.1002/hyp.13899
https://vlibrary.iwmi.org/pdf/H049975.pdf
https://vlibrary.iwmi.org/pdf/H049975.pdf
(3.71 MB) (3.71 MB)
Hydrological connectivity is a critical determinant of wetland functions and health, especially in wetlands that have been heavily fragmented and regulated by human activities. However, investigating hydrological connectivity in these wetlands is challenging due to the costs of high-resolution and large-scale monitoring required in order to identify hydrological barriers within the wetlands. To overcome this challenge, we here propose an interferometric synthetic aperture radar (InSAR)-based methodology to map hydrologic connectivity and identify hydrological barriers in fragmented wetlands. This methodology was applied along 70 transects across the Baiyangdian, the largest freshwater wetland in northern China, using Sentinel 1A and 1B data, covering the period 2016–2019. We generated 58 interferograms providing information on relative water level changes across the transects that showed the high coherence needed for the assessment of hydrological connectivity. We mapped the permanent and conditional (temporary) barriers affecting connectivity. In total, 11% of all transects are permanently disconnected by hydrological barriers across all interferograms and 58% of the transects are conditionally disconnected. Areas covered by reed grasslands show the most undisturbed hydrological connectivity while some of these barriers are the result of ditches and channels within the wetland and low water levels during different periods of the year. This study highlights the potential of the application of Wetland InSAR to determine hydrological connectivity and location of hydrological barriers in highly fragmented wetlands, and facilitates the study of hydrological processes from large spatial scales and long-time scales using remote sensing technique.
19 Zhou, G.; Wang, X.; Chen, W.; Li, X.; Chen, Z. 2020. Realization and application of geological cloud platform. Big Earth Data, 16p. (Online first) [doi: https://doi.org/10.1080/20964471.2020.1820175]
Geological data ; Technology ; Data processing ; Data analysis ; Spatial data ; Geographical information systems ; Models / USA / Nevada
(Location: IWMI HQ Call no: e-copy only Record No: H050029)
https://www.tandfonline.com/doi/abs/10.1080/20964471.2020.1820175?needAccess=true#aHR0cHM6Ly93d3cudGFuZGZvbmxpbmUuY29tL2RvaS9wZGYvMTAuMTA4MC8yMDk2NDQ3MS4yMDIwLjE4MjAxNzU/bmVlZEFjY2Vzcz10cnVlQEBAMA==
https://vlibrary.iwmi.org/pdf/H050029.pdf
https://vlibrary.iwmi.org/pdf/H050029.pdf
(9.27 MB) (9.27 MB)
In recent years, with the progress of computer technology, some traditional industries such as geology are facing changes in industrial structure and application mode. So we try to apply big data and virtualization technology in the field of geoscience. This study aims at addressing the existing problems in geological applications, such as data sharing, data processing and computing performance. A Geological Cloud Platform has been designed and realized preliminarily with big data and virtualization technology. The application of the Geological Cloud Platform can be divided into two parts: 1) to nest the geological computing model in cloud platform and visualize the results and 2) to use relevant software to conduct data analysis and processing in virtual machines of Windows or Linux system. Finally, we prospect Carlin-type deposits in Nevada by using the spatial data model ArcSDM in the virtual machine.
20 Chen, Y.; Fang, G.; Hao, H.; Wang, X.. 2020. Water use efficiency data from 2000 to 2019 in measuring progress towards SDGs in Central Asia. Big Earth Data, 14p. (Online first) [doi: https://doi.org/10.1080/20964471.2020.1851891]
Water use efficiency ; Sustainable Development Goals ; Agricultural water use ; Water resources ; Evapotranspiration ; Ecosystems ; Remote sensing ; Moderate resolution imaging spectroradiometer ; Datasets / Central Asia / Kazakhstan / Kyrgyzstan / Tajikistan / Turkmenistan / Uzbekistan
(Location: IWMI HQ Call no: e-copy only Record No: H050142)
https://www.tandfonline.com/doi/pdf/10.1080/20964471.2020.1851891?needAccess=true
https://vlibrary.iwmi.org/pdf/H050142.pdf
https://vlibrary.iwmi.org/pdf/H050142.pdf
(5.50 MB) (5.50 MB)
Central Asia, located in the hinterland of the Eurasian continent, is characterized with sparse rainfall, frequent droughts and low water use efficiency. Limited water resources have become a key factor restricting the sustainable development of this region. Accurately assessing the efficiency of water resources utilization is the first step to achieve the UN Sustainable Development Goals (SDGs) in Central Asia. However, since the collapse of the Soviet Union, the evaluation of water use efficiency is difficult due to low data availability and poor consistency. To fill this gap, this paper developed a Water Use Efficiency dataset (WUE) based on the Moderate Resolution Imaging Spectroradiometer (MODIS) Gross Primary Production (GPP) data and the MODIS evapotranspiration (ET) data. The WUE dataset ranges from 2000 to 2019 with a spatial resolution of 500 m. The agricultural WUE was then extracted based on the Global map of irrigated areas and MODIS land use map. As a complementary, the water use amount per GDP was estimated for each country. The present dataset could reflect changes in water use efficiency of agriculture and other sectors.
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