Water quality dataset of Jiangcuo Lake (2017)

This is the water quality data of the vertical profile of the observation point in Jiangcuo Lake. There are two observation points. It is observed on July 10, 2017. The data is stored as an excel file.

0 2019-09-11

Water level observation data of Selincuo Lake (2016-2017)

This is the water level observation data of Selincuo Lake. It can be used in Climatology, Environmental Change, Hydrologic Process in Cold Regions and other disciplinary areas. The data is observed from September 17, 2016 to February 15,2017. It is measured by automatic water gauge and a piece of data is recorded every 60 minutes. The data includes the water pressure and water temperature of the water level observation point on the east bank of Selincuo Lake.The original data is precise, with the pressure accurate to 0.001kP and the water temperature 0.001℃. The original data forms a continuous time series after quality control. And the daily mean index data is obtained through calculation. The data is stored as an excel file.

0 2019-09-11

The observation dataset of the Muztagh Ata hydrological station (2013-2017)

The observation data set of the Muztagh Ata hydrological station recorded the water level data of Lake Karakuri and Qiaodumake in the Muztag Ata area, and the ice condition and water quality data of Lake Karakuri (e.g., water temperature, pH, dissolved oxygen, redox potential, and conductivity). The ice condition data were manually measured, including observational data from November 30,2013, to March 26, 2016, which recorded the observational data for each week during December to the next March from 2013 to 2015 (the data collection period sometimes would change due to weather and other reasons); water quality parameter was measured using Hydrolab DS5, including measured data on 2013-07-20, 2014-07-15, 2014-08-28, 2014-09-14, 2015-07-11, and 2015-09-18; water level data were automatically measured by HOBO water level collector, and they included daily measurement records of Lake Karakuri from July 1, 2013, to October 13, 2015, and Qiaodumake from June 3,2013, to September 2, 2015. The data were collected digitally and automatically, and the data set was processed by forming a continuous time sequence after quality controlling the raw data. Observation and collection of the data were performed in strict accordance with the instrument operating specifications. Some obvious error data were removed, and missing data were represented by spaces. Qiaodumake water level collection location: E 75°00.149′, N 38°17.375′, 4130 m Lake Karakuri measuring point location: E 75°02.286′, N 38°26.209′, 3650 m Water level data: Time, Water level, unit: cm Ice condition data: Time, Ice thickness, unit: cm Water quality data: Time, Depth, unit: m Temperature, unit: °C PH, unit: pH Redox potential, unit: mV Photon flux density, unit: μmol/(m2 s) Dissolved oxygen, unit: mg/l

0 2019-09-11

HiWATER:The multi-scale observation experiment on evapotranspiration over heterogeneous land surfaces 2012 (MUSOEXE-12)-Dataset of Intensive runoff observations of No.2 in the middle reaches of the Heihe River Basin

The No. 2 hydrological section is located at 312 Heihe River Bridge (38°59′51.71″ N, 100° 24′38.76″ E, 1485 m a.s.l.) in the middle reaches of the Heihe River Basin, Zhangye, Gansu Province. The dataset contains observations from the No.2 hydrological section from 19 June, 2012, to 24 November, 2012. This section consists of two river sections, i.e., the east section is marked as No. 1 and the west section is marked as No. 2. The width of this section is 90 meters. This section consists of a gravel bed; the cross-sectional area is unstable because of human factors. The water level was measured using SR50 ultrasonic range and the discharge was measured using cross-section reconnaissance by the StreamPro ADCP. The dataset includes the following sections: Water level (recorded every 30 minutes) and Discharge. The data processing and quality control steps were as follows: 1) The water level data which collected from the hydrological station were averaged over intervals of 10 min for a total of 144 records per day. The missing data were denoted by -6999. 2) Data out the normal range records were rejected. 3) Unphysical data were rejected. For more information, please refer to Liu et al. (2016) (for multi-scale observation experiment or sites information), He et al. (2016) (for data processing) in the Citation section.

0 2019-09-11

Water index in the Qilian Mountain Area in 2018

This dataset contains the ground surface water (including liquid water, glacier and perennial snow) distribution in Qilian Mountain Area in 2018. The dataset was produced based on classical Normalized Difference Water Index (NDWI) extraction criterion and manual editing. Landsat images collected in 2018 were used as basic data for water index extraction. Sentinel-2 images and Google images were employed as reference data for adjusting the extraction threshold. The dataset was stored in SHP format and attached with the attributions of coordinates and water area. Consisting of 1 season, the dataset has a temporal resolution of 1 year and a spatial resolution of 30 meters. The accuracy is about 1 pixel (±30 meter). The dataset directly reflects the distribution of water bodies within the Qilian Mountain in 2018, and can be used for quantitative estimation of water resource.

0 2019-09-06

Bacteria distribution in Tibetan lakes (version 1.0) (2015)

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.

0 2019-06-01

Lake surface area dynamics on the Tibetan Plateau (Version 1.0) (1984-2016)

The data set of lake dynamics on the Tibetan Plateau was mainly derived from Landsat remote sensing data. Band ratio and the threshold segmentation method were applied. The temporal coverage of the data set was from 1984 to 2016, with a temporal resolution of 5 years. It covered the whole Tibetan Plateau at a spatial resolution of 30 meters. The water body area extraction method mainly adopted the band ratio (B4/B2) or water body index to construct the classification tree. The algorithm construction considered the spatial and temporal variations of the spectral characteristics of the water body and adjusted the threshold of the decision tree by the slope and the slope aspect information of the water body. The long-term sequence satellite-borne data came from different sensors, e.g., Landsat MSS, TM, ETM+, and OLI. The minimum unit for extracting water body information was 2*2 pixels, and all water body areas less than 0.36*10^-2 Km² were removed. The water body information extracted by high-resolution remote sensing data and the verification of the water body checkpoint determined by visual interpretation indicated that the overall accuracy of the water body area information for the Tibetan Plateau was above 95%. The data were saved as a shape file, and projected by Albers projection, with a central meridian of 105 ° and a double standard latitude of 25 ° and 47 °.

0 2019-05-30

Water depth measurement dataset over the Kering Tso Lake (2017)

This data set includes the water depth measurement data during the Jianghuyuan expedition from June to July 2017 over the Kering Tso Lake. The measurement time is on July 2, 2017. The data was measured by Lowrance HDS-5 sonar sounder. The original data was generated by surfer 13 software and Kriging difference method. The original data contained more invalid depth data, which had been screened out in the later stage of collation. The survey line is reasonable to ensure that the data cover all depth gradients.

0 2019-05-23

WATER: Dataset of regimen change statistics at the hydrological section of the Dayekou watershed reservoir

The dataset of regimen change statistics was obtained at the hydrological section of the Dayekou watershed reservoir from Jan. 1, 2007 to May 23, 2008. Ten days observations were carried out from Oct. 21, 2007 to Apr. 11, 2008, and diurnal observations from Apr. 15 to Oct. 21, 2007, and from Apr. 16 to May 23, 2008. Data record fields included: inflow (m^3/s), water level (m), impoundment (ten thousand m^3/s), outflow (m^3/s), ten days mean inflow (m^3/s), ten days mean outflow (m^3/s), monthly mean inflow (m^3/s), and monthly mean outflow (m^3/s).

0 2019-05-23

WATER: Dataset of dewfall measurements in the Linze station foci experimental area

The dataset of dewfall measurements was obtained in the Linze station foci experimental area from 6 am to 7am and 7pm to 10pm. Two containers were used. One was the unsealed rectangle plastic condensate drain pan from May 26 to Jul. 28, 2008 (one time-continuous observation from Jun. 25 to 27 at intervals of 2 hours), and the other was the sealed and unsealed aluminum cases from Jun. 24 to Jul. 29, 2008 (two time-continuous observations from Jun. 25 to 27 and Jul. 19 to 20, respectively, both at intervals of 2 hours). Dewfall was weighed by G&G TC30K- H scales (accuracy: 1g) for the condensate drain pan and by electronic scales (accuracy: 0.1g) for the aluminum case.

0 2019-05-23