The multi-decadal lake number and area changes in China during 1960s–2020 are derived from historical topographic maps and >42151 Landsat satellite images, including lakes as fine as ≥1 km^2 in size for the past 60 years (1960s, 1970s, 1990, 1995, 2000, 2005, 2010, 2015, 2020). From the 1960s to 2020, the total number of lakes (≥ 1 km ^ 2) in China increased from 2127 to 2621, and the area expanded from 68537 km ^ 2 to 82302 km ^ 2.
ZHANG Guoqing
The long-term sequence data set of lake areas on the Tibetan Plateau contains area data of 364 lakes with areas greater than 10 square kilometers from 1970s to 2013. Based on Landsat images, Landsat data in October are mainly used, and one data is taken every three years to reduce seasonal variation and make the available data reach the maximum. The data set is extracted by the NDWI Water Index, and each lake undergoes manual visual inspection and edition. The data set can be used to study lake change, lake water balance and climate change on the Tibetan Plateau. Data type: Vector data. Projection: WGS84.
ZHANG Guoqing
The dataset of runoff plot observations was obtained in the Binggou watershed foci experimental area from Jun. 19 to Oct. 17, 2008. The runoff plot (38°03′, 100°13′, 3472m, with a slope of 20.16°) was 10m long, 5m wide and 80cm deep, with soil depth about 50cm and sandy clay and gravels beneath (50-80cm). The main vegetation type is scrub (about 20cm high) and grass (about 3cm high). Observation items included the surface flow, interflow (80cm down the land surface), and precipitation at a fixed point at the right of the runoff plot. One subfolder and two data files (directions on data observations and raw data) were archived.
LI Hongyi, LI Zhe, BAI Yunjie, XIN Bingjie
In the mid-latitude region of Asia, the southeastern region is humid and affected by monsoon circulation (thus, it is referred to as the monsoon region), and the inland region is arid and controlled by the other circulation patterns (these areas include the cold and arid regions in the northern Tibetan Plateau, referred to as the westerly region). Based on the generalization of the climate change records published in recent years, the westerly region was humid in the mid-late Holocene, which was significantly different from the pattern of the Asian monsoon in the early-middle Holocene. In the past few millennia, the westerly region was arid during the Medieval Warm Period but relatively humid during the Little Ice Age. In contrast, the oxygen isotope records derived from a stalagmite in the Wanxiang Karst Cave showed that the monsoon precipitation was high in the Medieval Warm Period and low during the Little Ice Age. In the last century, especially in the last 50 years, the humidity of the arid regions in the northwest has increased, while the eastern areas of northwestern and northern China affected by the monsoon have become more arid. Moreover, in the northern and southern parts of the Tibetan Plateau, which are affected by the westerlies and the monsoon, respectively, the precipitation changes on the interdecadal and century scales have also shown an inverse phase. Based on these findings, we propose that the control zone of the westerly belt in central Asia has different humidity (precipitation) variation patterns than the monsoon region on every time scale (from millennial to interdecadal) in the modern interglacial period. The integrated research project on Holocene climate change in the arid and semi-arid regions of western China was a major research component of the project Environmental and Ecological Science for West China, which was funded by the National Natural Science Foundation of China. The leading executive of the project was Professor Fahu Chen from Lanzhou University. The project ran from January 2006 to December 2009. The data collected by the project include the following: 1. The integrate humidity data over the Holocene in the arid regions of Central-East Asia and 12 lakes (11000-0 cal yr BP): including Lake Van, Aral Sea, Issyk-Kul, Ulunguhai Lake, Bosten Lake, Barkol Lake, Bayan Nuur, Telmen Lake, Hovsgol Nuur, Juyan Lake, Gun Nuur and Hulun Nuur. 2. The integrated humidity data over the past millennium in the arid regions of Central-East Asia and at five research sites (1000-2000): including Aral Sea, Guliya, Bosten Lake, Sugan Lake, and the Badain Juran desert. Data format: excel table.
CHEN Fahu
The dataset of runoff measuring weir observations at the hydrological section was obtained in the Pailugou watershed foci experiment area during two full years from Oct. 2006 to Oct. 2008. The ice flow measurement and the container aet were used manually. The measurement was carried out every five days from Oct. 2006 to Apr. 2007, three times a day from May to Sep. 2007, every five days from Oct. 2007 to Apr. 2008, once a day from May to Sep. 2008, and every five days during Oct. 2008. Data were archived in Excel format.
WANG Shunli, LUO Longfa, JING Wenmao, WANG Rongxin, ZHANG Xuelong, NIU Yun
The dataset includes channel flow measured at the second irrigation stage in spring (22 May, 2012), the third irrigation stage in spring (18 June, 2012) and the first irrigation stage in autumn (16 July, 2012). The time used in this dataset is in UTC+8 Time. 1.1 Objective of measurement Objective of measuring channel flow are to provide the conference data for irrigation water optimal allocation model according to obtain reality water volume measured at Dou channel and Mao channel. Data set also is used to reference data for other observations such as eddy, biophysical parameters. 1.2 Observation measures and principle Measures: flow meter named Flowatch, which is made in Switzerland, observation precision: 0.1m/s; and rule, observation of which is 1cm. Principle: Flowatch, which is mechanical-based, is used to compute the velocity of the fluid according to vanes speed. The flow of channels is computed by using observed flow velocity and channel sectional area calculated on the basis of channel engineer sectional parameters and water level. 1.3 Observation location and items Observation spots include Yingyi branch San dou (Liu She, Shang’er She, and Xia’er She of Shiqiao village), Si Dou (Qi She, Ba She, and Jiu She of Shiqiao village), and Wu Dou (Yi She of Shiqiao village) at Yingke irrigation district, and seven Mao channels branched from five star branch channel Si Dou San Nong. Observation time is described as followed: Second stage irrigation in summer: 2012-5-22: Si Dou, Yingyi branch channel: Jiu She (Shiqiao village) 2012-5-23: Si Dou, Yingyi branch channel: Ba She (Shiqiao village) 2012-5-24 to 2012-5-25: Si Dou, Yingyi branch channel: Qi She (Shiqiao village) 2012-5-26 to 2012-5-28: Wu Dou, Yingyi branch channel: Yi She (Shiqiao village) 2012-5-28 to 2012-5-29: San Dou, Yingyi branch channel: Xia’er She (Shiqiao village) 2012-5-29 to 2012-5-30: San Dou, Yingyi branch channel: Shang’er She (Shiqiao village) 2012-5-30 to 2012-6-2: San Dou, Yingyi branch channel: Liu She (Shiqiao village) 2012-6-6: Yi Mao, Er Mao, San Mao, Si Mao, and Wu Mao branched from Five star branch channel Si Dou San Nong: Five star village 2012-6-7: Liu Mao, and Qi Mao branched from Five star branch channel Si Dou San Nong: Five stars village Third stage irrigation in summer: 2012-6-18 to 2012-6-19: Si Dou, Yingyi branch channel: Jiu She (Shiqiao village) 2012-6-19 to 2012-6-20: Si Dou, Yingyi branch channel: Ba She (Shiqiao village) 2012-6-20 to 2012-6-21: Si Dou, Yingyi branch channel: Qi She (Shiqiao village) 2012-6-22 to 2012-6-24: Wu Dou, Yingyi branch channel: Yi She (Shiqiao village) 2012-6-24 to 2012-6-26: San Dou, Yingyi branch channel: Xia’er She (Shiqiao village) 2012-6-26 to 2012-6-27: San Dou, Yingyi branch channel: Shang’er She (Shiqiao village) 2012-6-27 to 2012-6-30: San Dou, Yingyi branch channel: Liu She (Shiqiao village) 2012-7-1 to 2012-7-2: Yi Mao, Er Mao, San Mao, Si Mao, Wu Mao, Liu Mao, and Qi Mao branched from Five star branch channel Si Dou San Nong: Five stars village First stage irrigation in Autumn: 2012-7-16 to 2012-7-18: Si Dou, Yingyi branch channel: Jiu She (Shiqiao village) 2012-7-18 to 2012-7-19: Si Dou, Yingyi branch channel: Ba She (Shiqiao village) 2012-7-19 to 2012-7-21: Si Dou, Yingyi branch channel: Qi She (Shiqiao village) 2012-7-21 to 2012-7-24: Wu Dou, Yingyi branch channel: Yi She (Shiqiao village) 2012-7-24 to 2012-7-25: San Dou, Yingyi branch channel: Xia’er She (Shiqiao village) 2012-7-25 to 2012-7-27: San Dou, Yingyi branch channel: Shang’er She (Shiqiao village) 2012-7-27 to 2012-7-31: San Dou, Yingyi branch channel: Liu She (Shiqiao village) 2012-7-27 to 2012-7-28: Yi Mao, Er Mao, San Mao, Si Mao, Wu Mao, Liu Mao, and Qi Mao branched from Five star branch channel Si Dou San Nong: Five stars village Second stage irrigation in Autumn: 2012-8-8 to 2012-8-9: Si Dou, Yingyi branch channel: Jiu She (Shiqiao village) 2012-8-9 to 2012-8-10: Si Dou, Yingyi branch channel: Ba She (Shiqiao village) 2012-8-10 to 2012-8-12: Si Dou, Yingyi branch channel: Qi She (Shiqiao village) 2012-8-13 to 2012-8-15: Wu Dou, Yingyi branch channel: Yi She (Shiqiao village) 2012-8-15 to 2012-8-17: San Dou, Yingyi branch channel: Xia’er She (Shiqiao village) 2012-8-17 to 2012-8-19: San Dou, Yingyi branch channel: Shang’er She (Shiqiao village) 2012-8-19 to 2012-8-22: San Dou, Yingyi branch channel: Liu She (Shiqiao village) 2012-8-24 to 2012-8-25: Yi Mao, Er Mao, San Mao, Si Mao, Wu Mao, Liu Mao, and Qi Mao branched from Five star branch channel Si Dou San Nong: Five stars village Observed items: average flow velocity of channel (m/s), water level of channel (m), water temperature (℃), engineer sectional parameters of channel (investigation). Average flow velocity and water level of channel are measured one time per hour when channel flow is stable. However, the two items are measured two times or more times when channel flow is unstable. 1.4 Data process Observed data is saved in excel sheet, types of which include channel flow velocity, channel sectional area, water level, and water temperature. Channel flow and irrigation water volume are calculated by using observed data according to data per-process approach.
GE Yingchun, MA Chunfeng, Xu Fengying, LI Xin
I. Overview The Yellow River is the second longest river in our country. The problem of the Yellow River's sediment has attracted the attention of people all over the world. Based on the vector map of the 14 million rivers in China as a base map, the upper reaches of the Yellow River basin were cut out. The vector map of the river is a key element for extracting the boundary of the basin by using the topographic map, and it is also a key element for flood evolution and sediment evolution. Ⅱ. Data processing description Using the national vector map of the 14 million rivers as the data source, it is cut out by using the boundary of the upper reaches of the Yellow River. Ⅲ. Data content description The map is stored in ArcGIS, .shp files, including vector diagrams of the main and tributaries from the source area of the Yellow River to Toudaoguai. Ⅳ. Data usage description The vector map of the river is a key element for extracting the boundary of the watershed by using the topographic map, and it is also a key element for flood evolution and sediment evolution.
XUE Xian, DU Heqiang
Based on the meteorological data of 105 meteorological stations in and around the Qinghai Tibet Plateau from 1980 to 2019, the National Meteorological Science Data Center of China Meteorological Administration (CMA) was established. By calculating the oxygen content, it is found that there is a significant linear correlation between oxygen content and altitude, y = - 0.0263x + 283.8, R2 = 0.9819. Therefore, the oxygen content distribution map can be calculated based on DEM data grid. Due to the limitation of the natural environment in the Qinghai Tibet Plateau, there are few related fixed-point observation institutions. This data can reflect the distribution of oxygen content in the Qinghai Tibet Plateau to a certain extent, and has certain reference significance for the research of human living environment in the Qinghai Tibet Plateau.
HE Xiaobo, ZHANG Jian, NING Tianxiang, HUANG Xiaoming, JIANG Heng, LIU Shaomin, LI Xin
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).
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
Data overview: This set of data mainly includes perennial River, seasonal river, river trunk, surface main channel, surface branch channel and other water system conditions in the Heihe River Basin. The data base year is 2009. Data preparation process: obtained from 1:100000 topographic map and 2009 TM remote sensing image digitization. Data content description: the data mainly has three important attributes, namely, grade, GB and name. The river classification is based on the Strahler classification method, and the final level of the main stream reaches seven levels. River coding is based on the national basic geographic information element dictionary. The standard of basic geographic information element data dictionary is adopted.
National Basic Geographic Information Center
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.
HE Xiaobo, LIU Shaomin, LI Xin, XU Ziwei
Land surface temperature (LST) is a key variable for high temperature and drought monitoring and climate and ecological environment research. Due to the sparse distribution of ground observation stations, thermal infrared remote sensing technology has become an important means of quickly obtaining ground temperature over large areas. However, there are many missing and low-quality values in satellite-based LST data because clouds cover more than 60% of the global surface every day. This article presents a unique LST dataset with a monthly temporal resolution for China from 2003 to 2017 that makes full use of the advantages of MODIS data and meteorological station data to overcome the defects of cloud influence via a reconstruction model. We specifically describe the reconstruction model, which uses a combination of MODIS daily data, monthly data and meteorological station data to reconstruct the LST in areas with cloud coverage and for grid cells with elevated LST error, and the data performance is then further improved by establishing a regression analysis model. The validation indicates that the new LST dataset is highly consistent with in situ observations. For the six natural subregions with different climatic conditions in China, verification using ground observation data shows that the root mean square error (RMSE) ranges from 1.24 to 1.58 K, the mean absolute error (MAE) varies from 1.23 to 1.37 K and the Pearson coefficient (R2) ranges from 0.93 to 0.99. The new dataset adequately captures the spatiotemporal variations in LST at annual, seasonal and monthly scales. From 2003 to 2017, the overall annual mean LST in China showed a weak increase. Moreover, the positive trend was remarkably unevenly distributed across China. The most significant warming occurred in the central and western areas of the Inner Mongolia Plateau in the Northwest Region, and the average annual temperature change is greater than 0.1K (R>0:71, P<0:05), and a strong negative trend was observed in some parts of the Northeast Region and South China Region. Seasonally, there was significant warming in western China in winter, which was most pronounced in December. The reconstructed dataset exhibits significant improvements and can be used for the spatiotemporal evaluation of LST in high-temperature and drought-monitoring studies. More detail please refer to Zhao et al (2020). doi.org/10.5281/zenodo.3528024
MAO Kebiao
The Land Surface Temperature in China dataset contains land surface temperature data for China (about 9.6 million square kilometers of land) during the period of 2003-2017, in Celsius, in monthly temporal and 5600 m spatial resolution. It is produced by combing MODIS daily data(MOD11C1 and MYD11C1), monthly data(MOD11C3 and MYD11C3) and meteorological station data to reconstruct real LST under cloud coverage in monthly LST images, and then a regression analysis model is constructed to further improve accuracy in six natural subregions with different climatic conditions.
MAO Kebiao
Lakes on the Tibetan Plateau (TP) are an indicator and sentinel of climatic changes. We extended lake area changes on the TP from 2010 to 2021, and provided a long and dense lake observations between the 1970s and 2021. We found that the number of lakes, with area larger than 1 k㎡ , has increased to ~1400 in 2021 from ~1000 in the 1970s. The total area of these lakes decreased between the 1970s and ~1995, and then showed a robust increase, with the exception of a slight decrease in 2015. This expansion of the lakes on the highest plateau in the world is a response to a hydrological cycle intensified by recent climate changes.
ZHANG Guoqing
The No. 1 hydrological section is located at 213 Heihe River Bridge (38°54′43.55″ N, 100° 20′41.05″ E, 1546 m a.s.l.) in the middle reaches of the Heihe River Basin, Zhangye, Gansu Province. The dataset contains observations from the No.1 hydrological section from 13 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 330 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.
ZHANG Jian, NING Tianxiang, HUANG Xiaoming, JIANG Heng, LIU Shaomin, LI Xin
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.
ZHANG Jian, NING Tianxiang, HUANG Xiaoming, JIANG Heng, LIU Shaomin, LI Xin
The data set includes the river level observation data of point 2 in the dense runoff observation of the middle reaches of Heihe River from January 1, 2015 to December 31, 2015. The observation point is located in Heihe bridge, 312 National Road, Zhangye City, Gansu Province. The riverbed is sandy gravel with unstable section. The longitude and latitude of the observation point are n38.996667 °, e100.427222 °, altitude 1485m, river width 70m and 20m. Sr50 ultrasonic range finder is used for water level observation, with acquisition frequency of 30 minutes. The data includes the following parts: Water level observation, observation frequency 30 minutes, unit (CM); In 2015, the section of bridge no.2-312 was frequently disturbed by human beings. The dam was built within 1km of the upstream and downstream of the section. The unstable area of the hydrological section led to the disorder of the water level and flow curve. During the measurement, the stable flow and water level curve could not be obtained. The observation of water level is based on the manual observation of water level at 0:00 on January 1, 2015. In the later stage, the hydrological section of river undercut changes. The result is that the datum water level changes and negative value appears; Refer to Li et al. (2013) for hydrometeorological network or station information, and he et al. (2016) for observation data processing
HE Xiaobo, LIU Shaomin, LI Xin, XU Ziwei
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.
BAI Yanfen, DING Songchuang, HAO Xiaohua, Qian Jinbo, SHU Lele, SONG Yi, WANG Yang, XU Zhen, ZHU Shijie
The No. 8 hydrological section is located at Gaotai Heihe River Bridge (39 ° 23′22 .93 ″ N, 99 ° 49′37 .29″ E, 1347 m a.s.l.) in the middle reaches of the Heihe River Basin, Zhangye, Gansu Province. The dataset contains observations from the No.8 hydrological section from 17 June, 2012, to 24 November, 2012. The width of this section is 130 meters. 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.
HE Xiaobo, ZHANG Jian, NING Tianxiang, HUANG Xiaoming, JIANG Heng, LIU Shaomin, LI Xin
The data set includes the observation data of river water level and velocity at No.7 point in the dense observation of runoff in the middle reaches of Heihe River from January 1, 2015 to March 11, 2016. The sensor was abnormal at the end of 2014, and the commissioning was normal on March 25 after maintenance. The observation point is located in Heihe bridge, Pingchuan Township, Linze County, Zhangye City, Gansu Province. The riverbed is sandy gravel with unstable section. The longitude and latitude of the observation point are n39.331667 °, e100.099722 °, altitude 1375 meters, and channel width 130 meters. In 2015, sr50 ultrasonic distance meter was used for water level observation, with acquisition frequency of 30 minutes. Data description includes: Water level observation, observation frequency 30 minutes, unit (cm); 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).
LIU Shaomin, LI Xin, XU Ziwei
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
The No. 7 hydrological section is located at Pingchuan Heihe River Bridge (39 ° 20′2.03 ″ N, 100° 5′49.63″ E, 1375 m a.s.l.) in the middle reaches of the Heihe River Basin, Zhangye, Gansu Province. The dataset contains observations from the No.7 hydrological section from 13 June, 2012, to 24 November, 2012. The width of this section is 130 meters. 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.
ZHANG Jian, NING Tianxiang, HUANG Xiaoming, JIANG Heng, LIU Shaomin, LI Xin
In the transition zone from Heihe River to desert oasis in Pingchuan oasis of Linze, soil texture, bulk density, field capacity, saturated capacity, soil organic matter, total nitrogen and inorganic carbon content of 118 plots were studied. PH value, conductivity, total carbon, SiC, C / N were monitored to determine the physical and chemical properties of 0-20cm arable soil, and the soil particle composition of 0-20cm and 20-80cm soil layers.
SU Yongzhong
In the transition zone from Heihe River to desert oasis in Pingchuan oasis of Linze, soil texture, bulk density, field capacity, saturated water capacity, soil organic matter, total nitrogen and inorganic carbon content were studied. PH value, electrical conductivity, total carbon, SiC and C / N were monitored to determine the physical and chemical properties of 0-20cm topsoil and the soil particle size composition of 0-20cm and 20-80cm soil layers. According to the soil properties of five different soil in cotton field, cotton irrigation experiment was carried out: irrigation amount, seed cotton yield, straw parameters, lint percentage, coat index, seed index, single boll weight, flower rate before frost, unit boll number, single boll weight, irrigation water productivity, etc.
SU Yongzhong
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).
HE Xiaobo, LIU Shaomin, LI Xin, XU Ziwei
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.
YANG Dawen
Data overview: from September 23 to September 30, 2005 and from November 5 to November 9, 2005, the remote sensing Office of hanhanyuan Institute of Chinese Academy of Sciences measured 21 hydrological sections between Yingluoxia hydrological station and zhengzhengxia hydrological station in the middle reaches of Heihe River. Data acquisition process: using two sets of zhonghaida hd8080 GPS receivers and one set of DS3 level of Southern surveying and mapping company, combining GPS and leveling. Section survey mainly includes two steps. Firstly, two differential GPS are used to select high-precision control points on both sides of the river bank or on one side of the selected section, and two GPS receivers are used to observe for 30 minutes simultaneously. Then, on the basis of these control points, the level is used for continuous measurement of the section. According to the river width, a certain number of sounding plumb lines are arranged on the section to measure the water depth and the starting point distance of each sounding plumb line. The measuring points are relatively dense in the main channel part, and the beach is relatively sparse. The distance between the two points of the main channel part is 2m. This data can provide the key basic data for the hydrological simulation of surface groundwater in the middle reaches of Heihe River.
MA Mingguo
The No. 3 hydrological section is located at Railway Heihe River Bridge (39°02′33.08″ N, 100° 25′49.42″ E, 1443 m a.s.l.) in the middle reaches of the Heihe River Basin, Zhangye, Gansu Province. The dataset contains observations from the No.3 hydrological section from 14 June, 2012, to 24 November, 2012. The width of this section is 50 meters. 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.
ZHANG Jian, NING Tianxiang, HUANG Xiaoming, JIANG Heng, LIU Shaomin, LI Xin
The No. 6 hydrological section is located at Ban Heihe River Bridge (39°15′32.41″ N,100°16′33.95″ E, 1398 m a.s.l.) in the middle reaches of the Heihe River Basin, Zhangye, Gansu Province. The dataset contains observations from the No.6 hydrological section from 19 June, 2012, to 10 August, 2012. The width of this section is 270 meters. The water level was measured using HOBO pressure 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.
ZHANG Jian, NING Tianxiang, HUANG Xiaoming, JIANG Heng, LIU Shaomin, LI Xin
The data set includes the observation data of river water level and velocity at No.2 point in the runoff densification observation of the middle reaches of Heihe River from January 1, 2014 to December 31, 2014. The observation point is located in Heihe bridge, 312 National Road, Zhangye City, Gansu Province. The riverbed is sandy gravel with unstable section. The longitude and latitude of the observation points are N38 ° 59 ′ 51.71 ″, E100 ° 24 ′ 38.76 ″, with an altitude of 1485 meters, and a channel width of 70 meters and 20 meters. Sr50 ultrasonic range finder is used for water level observation, 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 December 31, 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 section of bridge no.2-312 is frequently disturbed by human beings, and the unstable area of hydrological section leads to the disorder of water level and flow curve. During the measurement, the stable flow and water level curve cannot be obtained. 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.
HE Xiaobo, LIU Shaomin, LI Xin, XU Ziwei
We comprehensively estimated water volume changes for 1132 lakes larger than 1 km2. Overall, the water mass stored in the lakes increased by 169.7±15.1 Gt (3.9±0.4 Gt yr-1) between 1976 and 2019, mainly in the Inner-TP (157.6±11.6 or 3.7±0.3 Gt yr-1). A substantial increase in mass occurred between 1995 and 2019 (214.9±12.7 Gt or 9.0±0.5 Gt yr-1), following a period of decrease (-45.2±8.2 Gt or -2.4±0.4 Gt yr-1) prior to 1995. A slowdown in the rate of water mass increase occurred between 2010 and 2015 (23.1±6.5 Gt or 4.6±1.3 Gt yr-1), followed again by a high value between 2015 and 2019 (65.7±6.7 Gt or 16.4±1.7 Gt yr-1). The increased lake-water mass occurred predominately in glacier-fed lakes (127.1±14.3 Gt) in contrast to non-glacier-fed lakes (42.6±4.9 Gt), and in endorheic lakes (161.9±14.0 Gt) against exorheic lakes (7.8±5.8 Gt) over 1976−2019.
ZHANG Guoqing
The No. 5 hydrological section is located at Gaoya Hydrological Station (39°08′06.35″ N,100°25′58.23″ E, 1420 m a.s.l.) in the middle reaches of the Heihe River Basin, Zhangye, Gansu Province. This hydrological section is for intercomparison of flow measurement between ADCP and manual method. The dataset contains observations from the No.5 hydrological section from 10 August, 2012, to 24 November, 2012. The width of this section is 58 meters. The water level was measured using HOBO pressure 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.
ZHANG Jian, NING Tianxiang, HUANG Xiaoming, JIANG Heng, LIU Shaomin, LI Xin
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: 1980-2010. The data included precipitation, 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.
YANG Dawen
Reservoir refers to the artificial water area formed in valley, river or low-lying area by dam, dike, sluice, weir and other projects. It is the main measure used for runoff regulation to change the distribution process of natural water resources and plays an important role in social and economic development. Many reservoirs have been built in Heihe River Basin, which has an important impact on the utilization of water resources in this area. In order to facilitate the mapping needs of users, we use topographic map and remote sensing image to prepare the reservoir distribution map of the Heihe River Basin. The location and shape of the reservoir are mainly obtained by manual interpretation based on Google map image, which basically shows the current situation of the reservoir distribution in the Heihe River Basin around 2010.
National Basic Geographic Information Center
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.
ZHANG Zhiqiang
The experimental data of Yingke Daman in Heihe River Basin is supported by the key fund project of Heihe River plan, "eco hydrological effect of agricultural water saving in Heihe River Basin and multi-scale water use efficiency evaluation". Including: soil bulk density, soil water content, soil texture, corn sample biomass, cross-section flow, etc Data Description: 1. Sampling location of Lai and aboveground biomass: Yingke irrigation district; sampling time: May 2012 to September 2012; Lai and aboveground biomass of maize were measured by canopy analyzer (lp-80), and aboveground biomass was measured by sampling drying method; sample number: 16. 2. Soil texture: Sampling location: Yingke irrigation district and Shiqiao Wudou Er Nongqu farmland in Yingke irrigation district; soil sampling depth is 140 cm, sampling levels are 0-20 cm every 10 cm, 20-80 cm every 20 cm, 80-140 cm every 30 cm; sampling time: 2012; measurement method: laboratory laser particle size analyzer; sample number: 38. 3. Soil bulk density: Sampling location: Yingke irrigation district and Daman irrigation district; sampling depth of soil bulk density is 100 cm, sampling levels are 0-50 cm and 50-100 cm respectively; sampling time: 2012; measurement method: ring knife method; number of sample points: 34. 4. Soil moisture content: this data is part of the monitoring content of hydrological elements in Yingke irrigation district. The specific sampling location is: Shiqiao Wudou Er Nongqu farmland in Yingke Irrigation District, planting corn for seed production; soil moisture sampling depth is 140 cm, sampling levels are 0-20 cm every 10 cm, 20-80 cm every 20 cm, 80-140 cm every 30 cm Methods: soil drying method and TDR measurement; sample number: 17. 5. Cross section flow: Sampling location: the farmland of Wudou Er Nong canal in Shiqiao, Yingke irrigation district; measure the flow velocity, water level and water temperature of different canal system sections during each irrigation, record the time and calculated flow, monitor once every 3 hours until the end of irrigation; sampling time: 2012.5-2012.9; measurement method: Doppler ultrasonic flow velocity meter (hoh-l-01, Measurement times: Yingke irrigation data of four times.
HUANG Guanhua, JIANG Yao
This glacial lake inventory is supported by the International Centre for Integrated Mountain Development (ICIMOD) and the United Nations Environment Programme/Regional Resource Centre, Asia and The Pacific (UNEP/RRC-AP). 1. The glacial lake inventory incorporates topographic map data and reflects the status of glacial lakes in the region in 2000. 2. The spatial coverage of the glacial lake inventory is as follows: Pa Chu Sub-basin, Mo Chu Sub-basin, Thim Chu Sub-basin, Pho Chu Sub-basin, Mangde Chu Sub-basin, Chamkhar Chu Sub-basin, Kuri Chu Sub-basin, Dangme Chu Sub-basin, Northern Basin, etc. 3. The glacial lake inventory includes the following data fields: glacial lake code, glacial lake types, glacial lake orientation, glacial lake width, glacial lake area, glacial lake depth, glacial lake length, etc. 4. Data projection: Projection: Polyconic Ellipsoid: Everest (India 1956) Datum: Indian (India, Nepal) False easting: 2,743,196.4 False northing: 914,398.80 Central meridian: 90°0'00'' E Central parallel: 26°0'00'' N Scale factor: 0.998786 For a detailed description of the data, please refer to the data file and report.
International Centre for Integrated Mountain Development (ICIMOD)
The data set includes the river level observation data of No. 4 point in the dense runoff observation of the middle reaches of Heihe River from May 20, 2015 to March 11, 2016. The instrument maintenance was completed again on May 20, 2015. 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 n39.065 °, e100.433056 °, 1431m above sea level, and 58m wide river channel. 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. On June 25, 2014, the instrument was damaged and re purchased. The record was restarted on May 20, 2015. The data includes the following parts: Water level observation, observation frequency 30 minutes, unit (cm); 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).
HE Xiaobo, LIU Shaomin, LI Xin, XU Ziwei
一. data description The data included the precipitation, river water and groundwater in the small calabash valley from July to September 2015 2H, 18O, with a sampling frequency of 2 weeks/time. 二. Sampling location (1) the precipitation sampling point is located in the ecological hydrology station of the institute of cold and dry regions, Chinese academy of sciences, with the latitude and longitude of 99 ° 53 '06.66 "E, 38 ° 16' 18.35" N. (2) the sampling point of the river is located at the outlet flow weir of haugugou small watershed in the upper reaches of the heihe river, with the latitude and longitude of 99 ° 52 '47.7 "E and 38 ° 16' 11" N.The water sampling point number 2 position for heihe river upstream hoist ditch Ⅱ area exports, latitude and longitude 99 ° 52 '58.40 "E, 38 ° 14' 36.85" N. (3) underground water spring and well water sampling points.The sampling point of spring water is located at 20m to the east of the outlet of the basin, with the latitude and longitude of 99°52 '50.9 "E, 38°16' 11.44" N. The well water sampling point is located near the intersection of east and west branches, with the latitude and longitude of 99 ° 52 '45.38 "E, 38 ° 15' 21.27" N. 三. Test method The δ2H and δ18O values of the samples were measured by PICARRO L2130-i ultra-high precision liquid water and water vapor isotope analyzer. The results were expressed by the test accuracy value of v-smow relative to the international standard substance, and the measurement accuracy was 0.038‰ and 0.011‰, respectively.
MA Rui , XING Wenle
1、 Data Description: from June 2012 to June 2013, the rainfall, river water and soil water in the basin were sampled and analyzed. 2、 Sampling location: rainfall sampling point is located in Qilian station of Chinese Academy of Sciences, with longitude and latitude of 99 ° 52 ′ 39.4 ″ e, 38 ° 15 ′ 47 ″ n; river water sampling point is located at the outlet of hulugou watershed, with longitude and latitude of 99 ° 52 ′ 47.7 ″ e, 38 ° 16 ′ 11 ″ n, with sampling frequency of once a week; soil water sampling point is located in the middle and lower part of hongnigou catchment, with sampling depth of 180cm underground and longitude and latitude of 99 ° 52 ′ 25.98 ″ E, 38 ° 15 ′ 36.11 ″ n, only one sample is taken. 3、 Test method: thermofisher TM flash 2000 and mat 253 gas stable isotope ratio mass spectrometer were used to measure the samples in 2012; l2130-i ultra-high precision liquid water and water vapor isotope analyzer was used to measure the samples in 2013.
SUN Ziyong, CHANG Qixin
1、 Data Description: from May 2013 to July 2014, the observation frequency of automatic observation data is 1 time / 15 minutes. The solinst levellogger automatic water level gauge is used to observe the river water level, and the flow data is calculated through the water level flow curve. The actual flow observation is manually observed through the self-made flow weir (see the thumbnail). Due to the limited amount of manual observation data, further supplementary observation is needed to improve the water level discharge curve. 2、 Sampling location: it is located at the outlet catchment of the alluvial delta Valley, and the south side is the shrub area. A small flow weir is built. Coordinates of observation points (99 ° 52 ′ 58 ″ e, 38 ° 14 ′ 36 ″ n)
SUN Ziyong, CHANG Qixin
From 2000 to 2011, the main control sections of the main stream of Heihe River were Yingluo Gorge (100 ° 11 ′e , 38 ° 49 ′ n), Zhengyi Gorge (99 ° 28 ′ e, 39 ° 49 ′ n), shaomaying (99 ° 59 ′ e, 40 ° 25 ′ n), Shangdong River and Xihe River (100 ° 20 ′ e, 41 ° 02 ′ n), Juyanhai (101 ° 06 ′ e, 42 ° 13 ′ n) monthly average flow.
JIANG Xiaohui
The data set includes the observation data of river water level and velocity at No.7 point in the dense observation of runoff in the middle reaches of Heihe River from January 1, 2014 to December 28, 2014. The observation point is located in Heihe bridge, Pingchuan Township, Linze County, Zhangye City, Gansu Province. The riverbed is sandy gravel with unstable section. The longitude and latitude of the observation point are n39 ° 20'2.03 ", E100 ° 5'49.63", with an altitude of 1375m and a channel width of 130m. In 2014, sr50 ultrasonic distance meter was used for water level observation, with acquisition frequency of 30 minutes. Data description includes the following two parts: Water level observation, observation frequency 30 minutes, unit (cm); The data covers the period from January 1, 2014 to December 28, 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).
HE Xiaobo, LIU Shaomin, LI Xin, XU Ziwei
1、 Data Description: the data includes the river temperature of the river section in No.2 catchment area of hulugou small watershed and the river section at the intersection of the East and West Branch ditches from July 2014 to September 2014. 2、 Sampling location: the coordinates of river section in No.2 catchment area are 99 ° 52 ′ 58.40 ″ e, 38 ° 14 ′ 36.85 ″ n. The cross section coordinates of the river at the junction of the East and West Branch ditches are 99 ° 52'45 "E, 38 ° 15'26.60" n.
MA Rui
Agricultural irrigation consumes a large amount of available freshwater resources and is the most immediate human disturbance to the natural water cycle process, with accelerated regional water cycles accompanied by cooling effects. Therefore, estimating irrigation water use (IWU) is important for exploring the impact of human activities on the natural water cycle, quantifying water resources budget, and optimizing agricultural water management. However, the current irrigation data are mainly based on the survey statistics, which is scattered and lacks uniformity, and cannot meet the demand for estimating the spatial and temporal changes of IWU. The Global Irrigation Water Use Estimation Dataset (2011-2018) is calculated by the satellite soil moisture, precipitation, vegetation index, and meteorological data (such as incoming radiation and temperature) based on the principle of soil water balance. The framework of IWU estimation in this study coupled the remotely sensed evapotranspiration process module and the data-model fusion algorithm based on differential evolution. The IWU estimates provided from this dataset have small bias at different spatial scales (e.g., regional, state/province and national) compared to traditional discrete survey statistics, such as at Chinese provinces for 2015 (bias = −3.10 km^3), at U.S. states for 2013 (bias = −0.42 km^3), and at various FAO countries (bias = −10.84 km^3). Also, the ensemble IWU estimates show lower uncertainty compared to the results derived from individual precipitation and soil moisture satellite products. The dataset is unified using a global geographic latitude and longitude grid, with associated metadata stored in corresponding NetCDF file. The spatial resolution is about 25 km, the time resolution is monthly, and the time span is 2011-2018. This dataset will help to quantitatively assess the spatial and temporal patterns of agricultural irrigation water use during the historical period and support scientific agricultural water management.
ZHANG Kun, LI Xin, ZHENG Donghai, ZHANG Ling, ZHU Gaofeng
The No. 1 hydrological section is located at 213 Heihe River Bridge (100.345° E, 38.912° N, 1546 m) in the midstream of the Heihe River Basin, Zhangye city, Gansu Province. The dataset contains observations recorded by the No.1 hydrological section from 13 June, 2012, to 6 September, 2013. This section consists of two river sections, i.e., the east section,which is denoted as No. 1 and the west section, which is denoted as No. 2. The width of this section is 330 meters and consists of a gravel bed; the cross-sectional area is unstable because of human factors. The water level was measured using an SR50 ultrasonic range and the discharge was measured using cross-section reconnaissance by the StreamPro ADCP. The dataset includes the following parameters: water level (recorded every 30 minutes) and discharge. The missing and incorrect (outside the normal range) data were replaced with -6999. For more information, please refer to Li et al. (2013) (for hydrometeorological observation network or sites information), He et al. (2016) (for data processing) in the Citation section.
HE Xiaobo, LIU Shaomin, LI Xin, XU Ziwei
The No. 2 hydrological section is located at 312 Heihe River Bridge (100.411° E, 38.998° N, 1485 m) in the midstream of the Heihe River Basin, Zhangye city, Gansu Province. The dataset contains observations recorded by the No.2 hydrological section from 19 June, 2012, to 31 December, 2013. This section consists of two river sections, i.e., the east section, which is denoted as No. 1 and the west section, which is denoted as No. 2. The width of this section is 90 meters and consists of a gravel bed; the cross-sectional area is unstable because of human factors. The water level was measured using an SR50 ultrasonic range and the discharge was measured using cross-section reconnaissance by the StreamPro ADCP. The dataset includes the following parameters: water level (recorded every 30 minutes) and discharge. The missing and incorrect (outside the normal range) data were replaced with -6999. For more information, please refer to Li et al. (2013) (for hydrometeorological observation network or sites information), He et al. (2016) (for data processing) in the Citation section.
HE Xiaobo, LIU Shaomin, LI Xin, XU Ziwei
1、 Data Description: the data includes the samples of anions and anions of river water and groundwater in hulugou small watershed from July to September 2015 for test and analysis. The sampling frequency is once every two weeks. 2、 Sampling location: (1) there are two river water sampling points. One is located at the outlet flow weir of hulugou small watershed in the upper reaches of Heihe River, with latitude and longitude of 99 ° 52 ′ 47.7 ″ E and 38 ° 16 ′ 11 ″ n. The second sampling point of the river is located at the outlet of hulugou area II at the upper reaches of Heihe River, with the longitude and latitude of 99 ° 52 ′ 58.40 ″ E and 38 ° 14 ′ 36.85 ″ n. (2) Underground water spring and well water sampling points are 20 m to the east of the drainage basin outlet, with longitude and latitude of 99 ° 52 ′ 50.9 ″ E and 38 ° 16 ′ 11.44 ″ n. The well water sampling point is located near the intersection of the East and West Branch ditches, with the longitude and latitude of 99 ° 52 ′ 45.38 ″ E and 38 ° 15 ′ 21.27 ″ n. 3、 Test method: the cation of sample is tested by inductively coupled plasma atomic emission spectrometer (ICP-AES), the test accuracy is 0.05mg/l, and the anion is tested by ion chromatograph (ics1100), the test accuracy is 0.002mg/l.
MA Rui , HU Yalu
Agricultural irrigation, which accounts for about 80% of human water consumption, is the most important part of human water resources management and closely related to human survival and development.Irrigation is also an important part of the water cycle. Large-scale irrigation can affect the water cycle and even the local climate by affecting evapotranspiration.Excessive diversion of irrigation water will lead to unsustainable utilization of water resources, and at the same time, will reduce river flow and aquifer water reserves, thus harming the ecological environment. Therefore, determining the spatial and temporal distribution and variation of irrigation is critical to studying past human water use, the impact of irrigation on ecological and hydrological processes, the environment and climate, and the development of future irrigation plans. By integrating the irrigation amount of channel diversion water and irrigation amount of groundwater intake from different data sources, and combining the evapotranspiration data of land surface model CLM4.5 simulation and remote sensing inversion, a set of spatio-temporal continuous surface water and groundwater irrigation amount data set with spatial resolution of 30 arcseconds (0.0083 degrees) on the scale of 1981-2013 in heihe river basin was made. It has been verified that this data set has a high reliability from 2000 to 2013, and a lower reliability from 1981 to 1999 than from 2000 to 2013 due to the absence of remote sensing data and the absence of soil utilization changes. The document is described as follows: Monthly surfacewater irrigation volume file name: monthly_surfacewater_irrigation gation_1981-2013.nc Monthly groundwater_irrigation gation_1981-2013.nc The data is in netcdf format.There are three dimensions, which are month, lat, and lon. Where, month is a month, and the value is 0-395, representing each month from 1981 to 2013. Lat is grid latitude information, and lon is grid longitude information.
XIE Zhenghui
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