International literature on murray-darling river basin research is collected from SCI - E and SSCI citation databases in web of science database.Using Murray - the darling river basin related name, the name of the wetland, lake, river, name of the dam or reservoir, and Murray darling river flows through the administrative areas of name give priority to inscription for retrieval, and use the language (English) and the types of literature (articles), and Murray - the darling river basin water resources research related research direction selection, finally get the document of 1912-2012.

This data set consists of three parts: the first part is the monthly flow data of Yingluo gorge and caotanzhuang water conservancy project from 1979 to 2014; the second part is the S213 bridge (N38 ° 54'43.55 ", E100 ° 20'41.05") on the main stream of Heihe River from 1979 to 2014, G312 bridge (N38 ° 59'51.71 ", E100 ° 24'38.76"), railway bridge (n39 ° 2'33.08 ", E100 ° 25'49.42"), Gaoya bridge (n39 ° 08'06.35 ", E100 ° 25'58.23") and Pingchuan bridge (n39 ° The third part is the daily discharge and water level data of S213 bridge, G312 bridge, railway bridge, Gaoya bridge and Pingchuan bridge in the main stream of Heihe River from 1979 to 2014. Among them, the flow data refers to the section flow of Heihe River, and the water level data refers to the water level at the runoff densification observation point in the middle reaches of hiwater. The reliability of monthly data is higher than that of daily data, and the reliability of flow is higher than that of water level.

The data came from the badain jilin 1:500,000 wind-sand landform data set compiled by the desert research institute of the Chinese academy of sciences (now the institute of cold and drought of the Chinese academy of sciences. The dataset mainly includes :dimao(landform),height(dune height),lake(lake),lvzhou(oasis), river(river), road (road).

Based on the field survey results of this project, the previous hydrogeological survey results and the prediction and judgment of desert depressions, we obtained more than 600 known water level points in badain jaran desert and its surrounding areas, and drew a first-order approximate contour map of the groundwater level in badan jaran desert by using the measured or predicted groundwater level data.This isometric chart fills a gap in the study of groundwater in badain jaran desert. The so-called first-order approximation is the distribution of the macroscopic groundwater level, which reaches a resolution of 1 km on the spatial scale, and it is assumed that the groundwater level in the shallow and deep layers is the same, and the groundwater in the quaternary and bedrock distribution areas remains continuous.The error level of the first-order approximate contour is ± 10 m, which mainly comes from the uncertainty of ground elevation data. This data set contains a vector diagram of the groundwater level contour line and a raster data file.

This dataset contains three basic remote sensing data of digital topography (DEM), TM remote sensing image and NDVI vegetation index of badan jilin desert. 1. DEM, digital terrain data, from the SRTM1 data set released by NASA in the United States, was cropped in the desert area.The resolution is 30 m.The data is stored in the DEM folder, and the dm.ovr file can be opened by ArcGIS. 2. TM image data.The composite data of Landsat TM/ETM + 543 band released by NASA were cropped in the desert lake group distribution area.The resolution is 30 m.From 1990 to 2010, one scene was selected in summer and one scene in autumn every five years to analyze the long-term changes of the lake.In 2002, there was a scene for each quarter to analyze the changes of the lake during the year.The data is stored in TM folder, TIFF format, can be opened by ArcGIS or ENVI software.The file naming rule is yyyymm.tif, where yyyy refers to the year and mm to the month. For example, 199009 refers to the time corresponding to the impact data of September 1990. 3. NDVI, vegetation index.The modis-ndvi product MOD13Q1, released by NASA, was cropped in desert areas.The NDVI data of every ten days of the growing season (June, July, August and September) from 2000 to 2012 are included. The spatial resolution is 250 m and the temporal resolution is 16 days.Stored in NDVI folder, TIFF format, can be opened by ArcGIS or ENVI software.Mosaic_tmp_yyyyddd.hdfout.250m_16_days_ndvi_roi.tif, Where yyyy represents the year and DDD represents the day of DDD of the year.

Data of four hydrogeological boreholes constructed in the badain jaran desert area of alxa right banner in 2013 are provided, including borehole construction reports, borehole location plans and borehole profiles.Adopt the core of quaternary and bedrock, install the filter tube at the bottom of the well, wash the well. Quantity of work: 4 boreholes with Numbers of K1, K2, K3 and K4.The total footage is designed according to 240 m, with an average single hole depth of 60 m. The actual depth control standard is the exposure of bedrock.

The evapotranspiration and soil evapotranspiration of lycium rubra and red sand of small shrubs in typical desert weather were observed by using infrared gas analyzer to measure water vapor flux. The measurement system consists of li-8100 closed-circuit automatic measurement of soil carbon flux (li-cor, USA) and an assimilation box designed and manufactured by Beijing ligotai technology co., LTD. Li-8100 is an instrument produced by li-cor for soil carbon flux measurement. It USES an infrared gas analyzer to measure the concentration of CO2 and H2O.The length, width and height of the assimilation box are all 50cm.The assimilation box is controlled by li-8100. After setting up the measurement parameters, the instrument can run automatically.

As determined in mid-august 2013, planting species: bubbly spines (different habitats are mid-range intermountain lowland and gobi), red sand (different habitats are mid-range gobi and downstream gobi). Using the brother company of LI - 6400 Portable Photosynthesis System (Portable Photosynthesis System, LI - COR, USA) and LI - 3100 leaf area meter, etc., to the desert plant photosynthetic physiological characteristics were observed. The symbolic meaning of the observed data is as follows: Obs，observation frequency ； Photo ，net photosynthetic rate，μmol CO2•m–2•s–1； Cond stomatal conductance，mol H2O•m–2•s–1 ; Ci, Intercellular CO2 concentration, μmol CO2•mol-1； Trmmol，transpiration rate，mmol H2O•m–2•s–1； Vpdl，Vapor pressure deficit，kPa； Area，leaf area，cm2； Tair，free air temperature ，℃； Tleaf，Leaf temperature，℃； CO2R，Reference chamber CO2 concentration，μmol CO2•mol-1； CO2S，Sample chamber CO2 concentration，μmol CO2•mol-1； H2OR，Reference chamber moisture，mmol H2O•mol-1； H2OS，Sample chamber moisture，mmol H2O•mol-1； PARo，photon flux density，μmol•m–2•s–1； RH-R，Reference room air relative humidity，%； RH-S，Relative humidity of air in sample room，%； PARi，Photosynthetic effective radiation，μmol•m–2•s–1； Press，barometric pressure，kPa； Others are the state parameters of the instrument at the time of measurement.

Sponsored by the European commission VEGETATION sensors in March 1998 by SPOT - 4 was deployed, from April 1998 to receive SPOTVGT for global VEGETATION observation data, the data by the Swedish Kiruna ground station is responsible for receiving, the image quality monitoring center in Toulouse, France is responsible for the image quality and provide the related parameters (e.g., scaling),Eventually, Belgium's Flemish Institute for Technological Research (Vito) 's VEGETATION processing Centre (CTIV) was responsible for pre-processing the data into 1km of daily global data.Preprocessing includes atmospheric correction, radiometric correction, and geometric correction to produce the maximum synthesis of NDVI data in 10 days, and set the value from -1 to -0.1 to -0.1, and then convert to the DN value of 0-250 through the formula DN= (NDVI+0.1)/0.004. This data set is mainly for normalized vegetation index (NDVI) of the qaidam river basin in the long time series, including spectral reflectance of four bands synthesized every 10 days from 1998 to 2008 and maximum NDVI in 10 days. The spatial resolution is 1km and the temporal resolution is 10 days.File formats :.hfr and.img.The file naming rule is CHN_NDV_YYYYMMDD, where YYYYMMDD is the date of the day that the file represents and is the main identifier that distinguishes it from other files.Remote sensing image files with suffixes.img and.hdf, which are used by users to analyze vegetation index, can be opened in ENVI and ERDAS software

According to the characteristics of the selected field and its surrounding areas, one Trime pipe was arranged in the corn field, and three Trime pipes were arranged in the direction perpendicular to the field path. When the soil moisture content was monitored in the vertical direction of TDR, it was monitored downward in every 10cm.It is located in the farmland of daman irrigated area. The data include the soil moisture content of the farmland and its surrounding areas (TDR monitoring) after three irrigation of the selected farmland in yingke irrigated area, which is encrypted and monitored every 3 hours within 24 hours, 3 groups every day for 5 days, 2 groups every day for 5-10 days, and 1 group every day for 10-15 days.

1. The data is digitized in the map of the development degree of desertification in daqintara (1958) from the drawing. The specific information of the map is as follows: * chief editor: zhu zhenda, qiu xingmin * editor: wang yimou * drawing: feng yu-sun, yao fa-fen, wu wei, wang jianhua, wang zhou-long * cartographic unit: desert laboratory, Chinese academy of sciences * publishing house: xi 'an map publishing house, unified isbn: 12461.26 二. The data is stored in ESRI Shapefile format, including the following layers: 1, * desertification development degree map (1958) : desertification1958.shp 2, * double river: river_double-shp 3, * single river: river_single-shp 4, Road: SHP 5, Lake: lake.shp 6, street: Stree. SHP 7, Railway: Railway. SHP 8, forest belt: Tree_networks 9. Residential land: residential. SHP 10. Map: map_margin.shp 三, desertification development degree figure property fields and encoding attribute: (1) desertification degree (Type) : a flow of sand (Semi - shifting Sandy Land), sand form class (Shapes), grass (Grassland), forest Land, Woodland and forest density (W_density), the cultivated Land (Farmland) (2) sand Shapes: Barchan Dunes, Flat Sandy Land, undulated Sandy Land, Vegetated Dunes (3) the grass (Grassland) (4) Woodland: Woodland. (5) woodland density (W_density): Sparse Woodlot (6) Farmland: Dryfarming and Abandoned Farmland, Irrigated Fields

1. The data is digitized in the map of the development degree of desertification in daqintara (1974) from the drawing. The specific information of the map is as follows: * chief editor: zhu zhenda, qiu xingmin * editor: wang yimou * drawing: feng yu-sun, yao fa-fen, wu wei, wang jianhua, wang zhou-long * cartographic unit: desert laboratory, Chinese academy of sciences * publishing house: xi 'an map publishing house, unified isbn: 12461.26 二. The data is stored in ESRI Shapefile format, including the following layers: 1, * desertification development degree map (1974) : desertification1974.shp 2, * double river: river_double-shp 3, * single river: river_single-shp 4, Road: SHP 5, Lake: lake.shp 6, street: Stree. SHP 7, Railway: Railway. SHP 8, forest belt: Tree_networks 9. Residential land: residential. SHP 10. Map: map_margin.shp 三, desertification development degree figure property fields and encoding attribute: (1) desertification degree (Type) : a flow of sand (Semi - shifting Sandy Land), sand form class (Shapes), grass (Grassland), forest Land, Woodland and forest density (W_density), the cultivated Land (Farmland) (2) sand Shapes: Barchan Dunes, Flat Sandy Land, undulated Sandy Land, Vegetated Dunes (3) the grass (Grassland) (4) Woodland: Woodland. (5) woodland density (W_density): Sparse Woodlot (6) Farmland: Dryfarming and Abandoned Farmland, Irrigated Fields