Data set of spatial and temporal distribution of water resources in Indus from 2001 to 2017

This data is a 5km monthly hydrological data set, including grid runoff and evaporation (if evaporation is less than 0, it means condensation; if runoff is less than 0, it means precipitation is less than evaporation), simulated and output through the WEB-DHM distributed hydrological model of the Indus River basin, with temperature, precipitation, barometric pressure, etc. as input data.

0 2022-11-21

Microbial data set of Qinghai Tibet Plateau Lakes (2015)

This data includes bacterial 16S ribosomal RNA gene sequence data from 25 lakes in the middle of the Qinghai Tibet Plateau. The sample was collected from July to August 2015, and the surface water was sampled three times with a 2.5 liter sampler. The samples were immediately taken back to the Ecological Laboratory of the Beijing Qinghai Tibet Plateau Research Institute, and the salinity gradient of the salt lake was 0.14~118.07 g/L. This data is the result of amplification sequencing. Concentrate the lake water to 0.22 at 0.6 atm filtration pressure μ The 16S rRNA gene fragment amplification primers were 515F (5 '- GTGCCAAGCCGCGGTAA-3') and 909r (5 '- GGACTACHVGGGTWTCTAAT-3'). The Illumina MiSeq PE250 sequencer was used for end-to-end sequencing. The original data was analyzed by Mothur software. The sequence was compared with the Silva128 database and divided into operation classification units (OTUs) with 97% homology. This data can be used to analyze the microbial diversity of lakes in the Qinghai Tibet Plateau.

0 2022-10-14

Data set of water balance elements in the source of the Yellow River and Qilian Mountains

This data set is a multi-scale data set of water balance elements in the source area of the Yellow River and the Heihe River Basin of Qilian Mountains, which can provide basis and reference for water resources management and water balance analysis. The data are based on the simulation results of SWAT model, and then analyzed and counted by ArcGIS and Excel software. The water balance elements include precipitation, snowfall, evapotranspiration, groundwater, soil water and runoff. The time scale includes annual scale and monthly scale, while the spatial scale includes watershed scale, river reach scale, sub basin scale, altitude zone scale and vegetation type scale. The data has been applied to water resources evaluation, benefit evaluation and operation guidance of artificial precipitation enhancement.

0 2022-10-09

HiWATER: Dataset of hydrometeorological observation network (No.6 runoff observation system of Gaoya hydrological station, 2014)

The data set includes the observation data of river water level and velocity at No. 6 point in the dense observation of runoff in the middle reaches of Heihe River from January 1, 2014 to December 31, 2014. The observation point is located in Gaoya National Hydrological Station, zhaojiatunzhuang, Ganzhou District, Zhangye City, Gansu Province. The riverbed is sandy gravel with stable section. The longitude and latitude of the observation point are n39 ° 08'06.35 ", E100 ° 25'58.23", 1420 m above sea level, and 50 m wide river channel. Hobo pressure water level gauge is used for water level observation, with acquisition frequency of 60 minutes. Data description includes the following two parts: Water level observation, 60 minutes in unit (cm) in 2014; Data covers the period of January 1, 2014 solstice December 31, 2014; Flow observation, unit (m3); According to the monitoring flow of different water levels, the flow curve of water levels was obtained, and the change process of runoff was obtained by observing the process of water levels.The missing data are uniformly represented by the string -6999. For information of hydrometeorological network or station, please refer to Li et al.(2013), and for observation data processing, please refer to He et al.(2016).

0 2022-09-20

Spatial distribution data set of water resource service value in the cryosphere of five river source areas of the Qinghai Tibet Plateau (2005-2010)

Known as the "Asian water tower", the Qinghai Tibet Plateau is the source of many rivers in Southeast Asia. As an important and easily accessible water resource, the runoff provided by it supports the production and life of billions of people around it and the diversity of the ecosystem. The glacier runoff data set in the five river source areas of the Qinghai Tibet Plateau covers the period from 2005 to 2010, with a time resolution of every five years. It covers the source areas of the five major rivers in the Qinghai Tibet Plateau (the source of the Yellow River, the source of the Yangtze River, the source of the Lancang River, the source of the Nujiang River, and the source of the Yarlung Zangbo River). The spatial resolution is 1km. Based on multi-source remote sensing, simulation, statistics, and measured data, GIS methods and ecological economics methods are used, The value of water resources service in the cryosphere in the source area of the river and river is quantified, and all its data are subject to quality control.

0 2022-09-13

Glacier runoff segmentation data set in the five river source areas of the Qinghai Tibet Plateau (1971-2015)

The Qinghai Tibet Plateau is known as the "Asian water tower", and its runoff, as an important and easily accessible water resource, supports the production and life of billions of people around, and supports the diversity of ecosystems. Accurately estimating the runoff of the Qinghai Tibet Plateau and revealing the variation law of runoff are conducive to water resources management and disaster risk avoidance in the plateau and its surrounding areas. The glacier runoff segmentation data set covers the five river source areas of the Qinghai Tibet Plateau from 1971 to 2015, with a time resolution of year by year, covering the five river source areas of the Qinghai Tibet Plateau (the source of the Yellow River, the source of the Yangtze River, the source of the Lancang River, the source of the Nujiang River, and the source of the Yarlung Zangbo River), and the spatial resolution is the watershed. Based on multi-source remote sensing and measured data, it is simulated using the distributed hydrological model vic-cas coupled with the glacier module, The simulation results are verified with the measured data of the station, and all the data are subject to quality control.

0 2022-07-06

Qilian Mountains integrated observatory network: Dataset of Qinghai Lake integrated observatory network (an observation system of Meteorological elements gradient of Yulei station on Qinghai lake, 2021)

This dataset includes data recorded by the Qinghai Lake integrated observatory network obtained from an observation system of Meteorological elements gradient of Yulei station on Qinghai lake from Janurary 1 to December 31, 2021. The site (100° 29' 59.726'' E, 36° 35' 27.337'' N) was located on the Yulei Platform in Erlangjian scenic area, Qinghai Province. The elevation is 3209m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (HMP155; 12 and 12.5 m above the water surface, towards north), wind speed and direction profile (windsonic; 14 m above the water surface, towards north) , rain gauge (TE525M; 10m above the water surface in the eastern part of the Yulei platform ), four-component radiometer (NR01; 10 m above the water surface, towards south), one infrared temperature sensors (SI-111; 10 m above the water surface, towards south, vertically downward), photosynthetically active radiation (LI190SB; 10 m above the water surface, towards south), water temperature profile (109, -0.2, -0.5, -1.0, -2.0, and -3.0 m). The observations included the following: air temperature and humidity (Ta_12 m, Ta_12.5 m; RH_12 m, RH_12.5 m) (℃ and %, respectively), wind speed (Ws_14 m) (m/s), wind direction (WD_14 m) (°) , precipitation (rain) (mm), four-component radiation (DR, incoming shortwave radiation; UR, outgoing shortwave radiation; DLR_Cor, incoming longwave radiation; ULR_Cor, outgoing longwave radiation; Rn, net radiation) (W/m^2), infrared temperature (IRT_1) (℃), photosynthetically active radiation (PAR) (μmol/ (s m-2)), water temperature (Tw_20cm、Tw_50cm、Tw_100cm、Tw_200cm、Tw_300cm) (℃). The data processing and quality control steps were as follows: (1) The AWS data were averaged over intervals of 10 min for a total of 144 records per day. As the lake water freezes in winter, the water temperature probe is withdrawn, so there is no water temperature data record during October 19, 2020 to December 31, 2020. The missing data were denoted by -6999. (2) Data in duplicate records were rejected. (3) Unphysical data were rejected. (4) The data marked in red are problematic data. (5) The format of the date and time was unified, and the date and time were collected in the same column, for example, date and time: 2018-1-1 10:30. Moreover, suspicious data were marked in red.

0 2022-06-30

Data set of flow-sediment processes in the Yarlung Zangbo River (2021)

To further investigate the transport process and temporal-spatial evolution of solid material in the Yarlung Zangbo River basin, the Sitting Bottom Bionic Water and sediment Observation System, which is the first set of good at the strong hydrodynamic condition and can continuously measure flow-sediment processes in real-time, was installed at Yangcun hydrology station by the sedimentary Dynamics observation team of Sichuan University on May 15, 2021. The bionic system was equipped with different types of observation equipment for water and sediment characteristics, which can measure the critical characteristics of water and sediment motion with high time resolution for a long time, continuously and synchronously. This data set contains the continuous data of 1) vertical velocity distribution (ADCP20210515.xlsx), 2) instantaneous velocity and turbulence of a single point near-bed, 3) Suspended sediment concentration measured by super turbidimeter (AOBS20210515.xlsx), 4) water depth, suspended sediment concentration and size distribution measured by Laser granulometer (Lisst20210515.xlsx). The data set with nearly a month recorded synchronous and continuous observation data of water and sediment characters with high temporal resolution per 10 minutes, which successfully observed the coupling change process of water and sediment under the increasing discharge of Yarlung Zangbo River. The simultaneous and continuous observation technology of water and sediment based on the bionic observation system provides technical support and scientific basis for revealing the source to sink process and evolution of Yarlung Zangbo River, bedload transport, flood numerical simulation, flash flood disaster warning and prevention, and major infrastructure construction.

0 2022-06-08

Data set of surface grain size distribution along the Nyangqu River in the Yarlung Zangbo River (2021)

The riverbed surface of the main channel in Nyangqu river is composed of gravel particles with wide grain size distribution. there are abundant gravel particles on the beach and riverbed. In this investigation, the bed surface grain size distribution of the main channel and tributaries of the Nyangqu river was measured. This data set contains the information of the five sampling locations in five main channels and two locations in tributaries of the Nyangqu River Basin (Table 1) and the bed surface grain size distribution (Table 2). The sampling locations were generally selected near the cross-section with obvious riverbed. It was considered that water flow through these sections in the straight channel for a long. At the same time, because it was a dry season, the bed grain size distribution on the river beach could be considered as the movement of gravel bedload carried by the last flood season. Therefore, it was considered that the bed grain size distribution in the sampling area on the river beach in the dry season was the bedload size distribution in the flood season. The grain size distributions were measured by the automatic identification method of full particle size based on image processing (e.g., Baserain software), with high identification accuracy of sediment particles is high. It is of great value to the scientific research on the evolution of source to sink process,bedlaod transport, and flood numerical simualtion, as well as the basic research on the flash flood prevention and control.

0 2022-06-07

Water index in the Qilian Mountain Area (2021)

This dataset contains the ground surface water (including liquid water, glacier and perennial snow) distribution in Qilian Mountain Area in 2021. The dataset was produced based on classical Normalized Difference Water Index (NDWI) extraction criterion and manual editing. Landsat images collected in 2021 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 2021, and can be used for quantitative estimation of water resource.

0 2022-06-05