The Antarctic and Arctic bacterial distribution data set provides distribution characteristics of bacteria in the Arctic and Antarctic. The collection period of the samples was from December 13,2005, to December 8,2006; 52 samples were obtained from 3 Arctic regions (Spitsbergen Slijeringa, Spitsbergen Vestpynten, and Alexandra Fjord_Highlands), and 171 samples were obtained from 5 Antarctic regions (the Mitchell Peninsula, Casey station main Power house, Robinsons Ridge, Herring Island, and Browning Peninsula). The soil surface samples were stored in liquid nitrogen after collection, shipped to a Sydney laboratory, and extracted using the FastPrep DNA kit. The extracted DNA samples were processed by 27F (5'-GAGTTTGATCNTGGCTCA-3' and 519R (5'-GTNTTACNGCGGCKGCTG-3') to amplify the 16S rRNA gene fragments. The amplified fragments were sequenced by the 454 method, and the raw data were analyzed by Mothur software. First, the sequences with poor sequencing quality were removed, the sequences were then sorted, and the chimera sequences were removed. The similarities between the sequences were calculated, the sequences with similarities above 97% were clustered into one OTU, and the OTU representative sequence was defined. By comparison with the Silva database, the OTU sequences with reliabilities greater than 80% were identified as level one. This data system compared the diversity of microorganisms in the eastern Antarctic with that in the Arctic and is of great significance for the study of the distributions of microorganisms in the Antarctic and Arctic.
JI Mukan
Microbial diversity data of lakes on the Tibetan Plateau. One hundred and thirty-eight samples were collected from July 1st to July 15th, 2015, from 28 lakes (Bamco, Baima Lake, Bange Salt Lake, Bangong Lake, Bengco, Bieruozeco, Cuoeco, Cuoe (Pingcuo North), Dawaco, Dangqiongco, Dangreyongco, Dongco, Eyacuoqiong, Gongzhuco, Guogenco, Jiarebuco, Mapangyongco, Namco, Nieerco (Salt Lake), Normaco, Pengyanco, Pengco, Qiangyong, Selinco, Wuruco, Wumaco, Zharinanmuco, and Zhaxico). The salinity gradients range from 0.07-118 ppm. The DNA extraction method: The DNA was extracted using an MO BIO PowerSoil DNA kit after the lake water was filtered onto a 0.45 membrane. The 16S rRNA gene fragment amplification primers were 515F (5'-GTGCCAGCMGCCGCGGTAA-3') and 909r (5'-GGACTACHVGGGTWTCTAAT-3'). The sequencing method was Illumina MiSeq PE250, and the raw data were analyzed by Mothur software, including quality filtering and chimera removal. The sequence classification was based on the Silva109 database, and archaea, eukaryotic and unknown source sequences have been removed. OTUs were classified by 97% similarity, and sequences that appear once in the database were then removed. Finally, each sample was resampled to 7,230 sequences/sample. GPS coordinates, evolutionary information, and environmental factors are listed in the data.
JI Mukan
According to the principle of optimization of water diversion scheme and the economic, social and ecological development status of Heihe River Basin, the following three optimization schemes of water diversion scheme are proposed. In Scheme 1, the water consumption in the middle reaches is 630 million m3 in each coming year. In Scheme 2, the water consumption in the middle reaches is 180 million m3 and 60 million m3 in 90% and 75% coming years respectively. In Scheme 3, when the water consumption in Yingluo Gorge is more than 1.9 billion m3, the water consumption in excess of 1.9 billion m3 is distributed by 40% in the middle reaches and 60% in the lower reaches. At the same time, in order to maintain the annual average inflow of 1.58 billion m3 from Yingluo Gorge, 950 million m3 from Zhengyi Gorge, and when the inflow of Yingluo Gorge is less than 1.29 billion m3, 60% of the inflow of less than 1.29 billion m3 will be distributed in the middle reaches and 40% in the lower reaches.
JIANG Xiaohui
The data of water use scenario analysis in heihe river basin is mainly used in water right management model. Space scope: sunan county, ganzhou district, minle county, linze county, gaotai county, shandan county, jinta county, ejin na, suzhou district, jiayuguan; Time frames: 2020 and 2030 Data content: forecast water consumption (tons) Number of transfers: 9kb
WANG Zhongjing, ZHENG Hang
The data set include crop leaf stomatal conductance observed at four sample regions, that is the soil moisture control experimental field at Daman county, and the super station, and Shiqiao sample plots at Wuxing village in Zhangye city. 1) Objective Crop leaf stomatal conductance, a key biophysical parameter, was observed as model parameter or a priori knowledge for crop growth model, or evapotranspiration estimation. 2) Measuring instruments Leaf porometer. 3) Measuring site a. the soil moisture control experimental field at Daman county, Twelve soil water treatments are set. The crop leaf stomatal conductance for each treatment is measured on 17, 23 and 29 May, and 3, 9, 14 and 24 June, and 5 and 12 July. b. the Super Station The crop leaf stomatal conductance at the super station is measured on 22 and 28 May, 5, 11, 18, and 25 June, and 1, 8, 15, 22 and 31 July, 9, 15 and 22 August, and 3 and 11 September. c. the Shiqiao sample site The crop leaf stomatal conductance at the Shiqiao village is measured on 17, 22 and 28 May, 4, 11, 17 and 25 June, 1, 8, 15, 22, and 30 July, 8, 16 and 27 August, and 9 September. 4) Data processing The observational data was recorded in the sheets and reorganized in the EXCEL sheets. The time used in this dataset is in UTC+8 Time.
Xu Fengying, Wang Jing, Huang Yongsheng, LI Xin, MA Mingguo
The dataset includes two parts that are: 1) channel flow, crop pattern, field management, and socio-economy data measured at super-station in 2008, 2010, 2011, 2012 (UTC+8), respectively. 2) irrigation data, crop pattern, and socio-economy data investigated at Daman irrigation district and Yingke irrigation district, respectively. 1.1 Objective of investigation Objectives of investigation for two parts data are to obtain crop pattern and irrigation water volume change with time, and to supply parameter for irrigation water optimal allocation model. 1.2 Investigation spots and items Investigation spots include six water management stations that are Dangzhai, Hua’er, Daman, Xiaoman, Jiantan, and Ershilidun, respectively, at Daman irrigation district. Investigation items comprise water allocation time, branch channel inflow, Dou channel inflow, irrigation area, channel water use efficiency, water price, and water fee. Investigation time is described as followed: 2012.03.16 to 2012.04.04, Spring irrigation; 2012.04.04 to 2012.05.14, Summer irrigation; 2012.05.20 to 2012.06.24, Summer irrigation; 2012.05.16 to 2012.07.06, Summer irrigation; 2012.07.15 to 2012.08.02, Autumn irrigation; 2012.08.10 to 2012.08.26, Autumn irrigation. Investigation spots include eight water management station that are Chang’an, Shangqin, Dangzhai, Liangjiadun, Shimiao, Xiaoman, Xindun, and Yangou, respectively, at Yingke irrigation district. Investigation time and items is described as followed: Year Data items Spots 2008, 2010, 2011 Irrigation data: Irrigation time, water level of Dou channel, channel flow, irrigation area Xiaoman county, Shangtouzha village 2012 Irrigation data: Irrigation time, water level of Dou channel, channel flow, irrigation area Chang’an, Shangqin, Dangzhai, Liangjiadun, Shimiao, Xiaoman, Xindun, Yangou 2012 Well data: Well deep, groundwater abstraction, irrigation area Chang’an, Liangjiadun, Shangqin 2012 Socio-economy data: population, agricultural income, un-agricultural income, water use for living, average residential area, education Chang’an, Xiaoman, Liangjiadun, Shangqin 2012 Field management: fertilizer name, fertilization time, fertilization rate, pesticide name, pesticide rate, time Chang’an, Xiaoman, Liangjiadun, Shangqin 2008, 2010, 2011, 2012 Crop pattern: crop name, seed time, harvest time, crop area, irrigation quota, field water use efficiency, crop yield, crop production value Xiaoman, Chang’an, Liangjiadun, Shangqin 1.3 Data collection Data was collected by cooperating with water management department of Yingke and Daman.
GE Yingchun, Xu Fengying, LI Xin
This dataset provides the estimated results of land cover change (IGBP classification) in 2040, 2070 and 2100 of Heihe River under the latest cmip5 based greenhouse gas emission scenario RCPs (representative concentration pathways). Spatial resolution: 1km. Time period: RCP (2.6, 4.5, 8.5) three scenarios, each scenario corresponding to three time periods: t1:2040, t2:2070, t3:2100. File naming rules: take "HLCs rcp26_" as an example to explain: in the naming, "HLCs" refers to the land cover scenario of Heihe River Basin, rcp26 refers to the rcp2.6 scenario of cmip5, "_40" refers to the future scenario period of 2040, the complete file name means the land cover prediction data of Heihe River Basin in 2040 under the rcp26 scenario, and so on.
FAN Zemeng, YUE Tianxiang
Water demand in the middle and lower reaches of Heihe River (mainly including water demand for living, livestock, industry, agriculture, tertiary industry, artificial forest and grass ecology in the middle reaches of Heihe River in current year, 2020 and 2030; water demand for living, industry, tertiary industry and ecology in Ejina Banner in the middle reaches of Heihe River in current year, 2020 and 2030)
JIANG Xiaohui
Input and output table of Heihe River Basin in Gansu Province in 2002 and 2007, including 144 departments
DENG XiangZheng
Data investigation method: obtained from investigation of Heihe River Basin Authority. Summary of data content: data of water consumption of Heihe, Shiyang and Shule River Basins in 1980, 1985, 1990, 2000, 2005, 2009 and 2009, including industrial water and agricultural water. Data temporal and spatial range: Heihe, Shiyang and Shule river basins 1980, 1985, 1990, 2000, 2005, 2009 and 2009.
WANG Zhongjing
Data source: survey data of Heihe River Basin Authority; Data introduction: in 2010, Sunan County, Ganzhou District, Minle County, Linze County, Gaotai County, Shandan County, Jinta County, Ejina, Suzhou District and Jiayuguan used water for living, industry, agriculture, urban and rural ecology.
WANG Zhongjing
Data analysis method: macroeconomic development forecast Space scope: Sunan County, Ganzhou District, Minle County, Linze County, Gaotai County, Shandan County, Jinta County, Ejina, Suzhou District, Jiayuguan Time frame: 2020, 2030 Data: GDP (1 million yuan), GDP growth rate, primary production (1 million yuan), primary production growth rate, secondary production (million yuan), secondary production growth rate, tertiary production (million yuan), tertiary production growth rate, primary production rate Second rate, third rate
WANG Zhongjing
Industrial transformation refers to the state or process of significant changes in industrial structure, industrial scale, industrial organization, industrial technology and equipment in the main composition of a country or region's national economy. From this point of view, industrial transformation is a comprehensive process, including industrial transformation in structure, organization and technology. Another explanation refers to the reallocation of resource stock among industries in an industry, that is, the process of transferring capital, labor and other production factors from declining industries to emerging industries Data include industrial output impact data of water resources industrial structure adjustment (primary industry technology, secondary industry technology, tertiary industry technology)
DENG XiangZheng
Water resources bulletin is a comprehensive annual report reflecting the situation of water resources. It is the basic work of unified planning, management and protection of water resources. It is an important basis for the preparation of national economic and social development planning, and also an important responsibility of water administrative departments. The contents of the water resources bulletin include precipitation, surface water resources, groundwater resources, total water resources, water storage dynamics, social and economic indicators, water supply, water consumption, water consumption, water use indicators, water pollution overview and important water affairs, etc. data and information are provided according to administrative divisions and flow area divisions respectively. The data set contains various statistical data of Gansu Provincial Water Resources Bulletin from 2000 to 2011.
DENG XiangZheng
Through the questionnaire survey of different water users in Zhangye City, the data on the implementation of water-saving society construction policies in Zhangye City are sorted out. The survey is mainly carried out on farmers and urban residents in all counties under Zhangye City's jurisdiction. The main contents include: people's awareness of water resources, water pollution, water-saving policies and willingness to participate in water conservation; The social and economic situation, gender, age, educational level, occupation, etc. of the interviewees. Survey objects: urban and rural residents over 18 years old in Minle County, Shandan County, Ganzhou District, Linze County, Gaotai County and Sunan County of Zhangye City.
ZHANG Zhiqiang
"Hydrologic - ecological - economic process coupling and evolution of heihe Basin governance under the framework of water rights" (91125018) project data exchange 4-basin-plan-mdb 1. Data overview: a watershed plan revision for the Murray darling river in Australia, adopted in 2012, for catchment comparisons 2. Data content: the public plan
WANG Zhongjing
Irrigation area data of Zhangye City from 1999 to 2011, including total irrigation area (effective irrigation area, forest irrigation area, orchard irrigation area, forage irrigation area and other irrigation areas), water-saving irrigation area (sprinkler irrigation area, micro irrigation area, low-pressure pipe irrigation area, canal seepage prevention area and other water-saving irrigation areas), effective irrigation area data, and Ganzhou District, Shandan District Corresponding data of county, Gaotai County, Sunan County, Linze County and Minle County
ZHANG Dawei
Input output table of 11 districts and counties in Heihe River Basin in 2012
DENG XiangZheng
Data of industrial structure change and water use evolution trend of social and economic development in Heihe River Basin
DENG XiangZheng
Zhangye basin mainly includes 20 irrigation areas. Under the restriction of water diversion, the surface water consumption of the irrigation area is under control, but the groundwater exploitation is increased, resulting in the groundwater level drop in the middle reaches, resulting in potential ecological environment risks. Due to the complex and frequent exchange of surface water and groundwater in the study area, it is possible to realize the overall water resource saving by optimizing the utilization ratio of surface water and groundwater in each irrigation area. In this project, on the premise of not changing the water demand of the middle reaches irrigation area, the two problems of maximizing the outflow of Zhengyi Gorge (given groundwater reserve constraint) and maximizing the outflow of Zhengyi Gorge (given groundwater reserve constraint) are studied.
ZHENG Yi
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