Long-term runoff observation with ten-days interval of Yingluoxia and Zhengyixia gorges in Heihe River Basin (1994-2010)

This data mainly includes ten day runoff data of Yingluo gorge and Zhengyi gorge in Heihe River Basin, among which the time range of Yingluo gorge data is 1944-2010 and Zhengyi gorge data is 1947-2010. Source: Heihe River Basin Authority. Data unit: 100 million cubic meters / 10 days. Data format: Excel "Yingluo gorge 2" and "Yingluo gorge 2 (2)" in the data table are the ten day runoff data of Yingluo gorge, the same as "Yingluo gorge" in the data table, and Yingluo gorge 2 (2) contains the chart.

0 2020-09-14

Data set of spatial and temporal distribution of water resources in Yarlung Zangbo River from 1998 to 2016

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). 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).

0 2020-08-27

Modeling ecohydrological processes and spatial patterns in the Upstream of Heihe River Basin (2000-2012) V2.0

The output data of the distributed eco-hydrological model (GBEHM) of the upper reaches of the black river include the spatial distribution data series of 1-km grid. Region: upper reaches of heihe river (yingxiaoxia), time resolution: month scale, spatial resolution: 1km, time period: 2000-2012. The data include evapotranspiration, runoff depth and soil volumetric water content (0-100cm). All data is in ASCII format. See basan.asc file in the reference directory for the basin space range. The projection parameter of the model result is Sphere_ARC_INFO_Lambert_Azimuthal_Equal_Area.

0 2020-08-10

Monthly average flow statistics of Baishuihe station in Jinsha River Basin of Yunnan Province (2018)

1.The data content: Monthly mean flow statistics data of white river station at the jinsha river basin of yunnan province, 2018. 2. Data sources and processing methods: Australia Unidata ultrasonic velocity sensor automatic measuring river flow velocity in the the white river hydrology section , using the water level data recorded by the HOBO water level meter and the corresponding hydrological section area data,, volume and velocity relationship formula, flow data is calculated. 3.Data quality description: automatic continuous access to data 4.Data application results and prospects: provide data support for snow - runoff model simulation

0 2020-06-01

Daily runoff data of Akjar hydrological station from Syr Darya (2018)

This data is the daily runoff data of akjar hydrological station in Tajikistan in 2018. The data is from the hydrological and Meteorological Bureau of Tajikistan. The data are processed according to the hydrological observation specifications and quality control process of the country. The data can be used for scientific research and water conservancy engineering services such as water resources assessment in Central Asia mountainous areas. (name of hydrological station: akjar; river: Sir Darya; location: 40.666667 ° n / 70.733333 ° E; altitude: 367M; data period: January 1, 2018 to December 31, 2018; data element: daily runoff; unit: m3 / s)

0 2020-05-28

Data on glacial lakes in the TPE (V1.0) (1990, 2000, 2010)

There are three types of glacial lakes: supraglacial lakes, lakes attached to the end of the glacier and lakes not attached to the end of the glacier. Based on this classification, the following properties are studied: the variation in the number and area of glacial lakes in different basins in the Third Pole region, the changes in extent in terms of size and area, distance from glaciers, the differences in area changes between lakes with and without the supply of glacial melt water runoff, the characteristics of changes in the glacial lake area with respect to elevation, etc. Data source: Landsat TM/ETM+ 1990, 2000, 2010. The data were visually interpreted, which included checking and editing by comparing the original image with Google Earth images when the area was greater than 0.003 square kilometres. The data were applied to glacial lake changes and glacial lake outburst flood assessments in the Third Pole region. Data type: Vector data. Projected Coordinate System: Albers Conical Equal Area.

0 2020-05-04

Basic data set for water resources research in Southeast Asian countries andLancang-Mekong River Basin (1901-2010)

The basic data set of water resources research of Southeast Asian countries and Lancang Mekong basin (1901-2010) collected and sorted out the main hydrometeorological data of Southeast Asian countries and Lancang Mekong basin, including precipitation, average temperature, maximum temperature, minimum temperature, water vapor pressure, etc. the data came from CRU TS v. 4.03 (clinical research unit time series version 4.03), which is widely used in the whole world The format is NC, the time resolution is month by month, and the time length is from January 1901 to December 2018. Hydrological data includes surface runoff and underground runoff simulated by the hydrological model. The data comes from GLDAS (Global Land Data Assimilation System). The data format is NC, the time resolution is month by month, and the time length is from January 1979 to February 2019.

0 2020-04-09

Monitoring dataset of Gansu water quality automatic station (2012-2014)

This data is from the central station of environmental monitoring in gansu province. The data includes three observation elements that are disclosed on the network, namely PH, permanganate index and ammonia nitrogen. The data format is a text file. The first column is the city name, the second column is PH, the third column is permanganate index, the fourth column is ammonia nitrogen, and the fifth column is the observation date. The data include 6 sections of gushuizi, niubei village, wufo temple, shichuan bridge, xincheng bridge and bikou. Gansu section of the Yellow River: xincheng bridge (lanzhou upstream section), shichuan bridge (lanzhou - baiyin junction section), wufo temple (gansu-ningxia junction section), niubei village (gansu-shaanxi junction section).Bailong river wudu section :(section of gushuizi village). Lanzhou city bridge automatic water quality monitoring station is located in xigu district, lanzhou city, gansu province.Point coordinates 103 degrees 35 minutes 02 seconds east longitude, 36 degrees 07 minutes 20 seconds north latitude.Yellow River system (Yellow River main stream), state - controlled provincial boundary section.By lanzhou city environmental monitoring station custody.It's 35 kilometers away.Built in March 2001. PH: the index that characterizes the acidity and alkalinity of water. When the pH value is 7, it is neutral, less than 7 is acidic, and greater than 7 is alkaline.The pH value of natural surface water is generally between 6 and 9. When algae grow in the water, they absorb carbon dioxide due to photosynthesis, resulting in an increase in surface pH value. Permanganate index (CODMn) : the amount consumed when treating surface water samples with potassium permanganate as the oxidant, expressed as mg/L of oxygen.Under these conditions, reductive inorganic substances (ferrous salts, sulphides, etc.) and organic pollutants in water can consume potassium permanganate, which is often used as a comprehensive indicator of the degree of surface water pollution by organic pollutants.Also known as the chemical oxygen demand potassium permanganate method, as distinct from the chemical oxygen demand (COD) of the potassium dichromate method, which is often used to monitor wastewater discharge. Ammonia nitrogen (nh3-n) : ammonia nitrogen exists in water in the form of dissolved ammonia (also known as free ammonia, NH3) and ammonium salt (NH4+). The ratio of the two depends on the pH value and water temperature of the water, and the content of ammonia nitrogen is expressed by the amount of N element.The main sources of ammonia nitrogen in the water are domestic sewage and some industrial wastewater (such as coking and ammonia synthesis industry) and surface runoff (mainly refers to the fertilizer used in farmland entering rivers, lakes, etc.). This data will be updated automatically and continuously according to the data source.

0 2020-04-01

Surface runoff data of Pailougou Watershed recorded by measuring weir

The runoff record of Pailugou watershed in the upper reaches of Heihe River, dated from January 2011 to September 2012. The data measuring device is the measuring weir at the exit of the small watershed, the unit of the data is m³/day.

0 2020-03-31

HiWATER: Dataset of hydrometeorological observation network (No.4 runoff observation system of Wujing bridge on the Heihe River, 2014)

The data set includes the observation data of river water level and velocity at No. 4 point in the dense observation of runoff in the middle reaches of Heihe River from January 1 to June 25, 2014. The observation point is located in Heihe bridge, Shangbao village, Jing'an Township, Zhangye City, Gansu Province. The riverbed is sandy gravel with unstable section. The longitude and latitude of the observation point are n39 ° 03'53.23 ", E100 ° 25'59.31", with an altitude of 1431m and a width of 58m. In 2012, hobo pressure type water level gauge was used for water level observation with acquisition frequency of 30 minutes; since 2013, sr50 ultrasonic distance meter was used with acquisition frequency of 30 minutes. The data description includes the following parts: For water level observation, the observation frequency is 30 minutes, unit (CM); the data covers the period from January 1, 2014 to June 25, 2014; for flow observation, unit (M3); for flow monitoring according to different water levels, the water level flow curve is obtained, and the runoff change process is obtained based on the observation of water level process. The missing data is uniformly represented by string-6999. Refer to Li et al. (2013) for hydrometeorological network or station information and he et al. (2016) for observation data processing.

0 2020-03-14