HiWATER: Dataset of investigation on channel flow and socio-economy in the midstream of the Heihe River Basin

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.

0 2019-09-15

Soil texture dataset of the Heihe River Basin (2011)

The soil texture dataset of the Heihe River Basin (2011) is compiled by LIU Chao et al. (2011) by using the SOLIM model. Based on the famous Jenny equation of soil science, and according to the environmental factors such as climate, biology, topography and parent material, knowledge mining and fuzzy logic are combined on the basis of existing soil texture maps and soil profiles in Heihe River Basin. It is produced and integrated with thematic maps of glaciers and lakes. According to the different characteristics of the six ecological zones in Heihe River Basin, different mapping methods are used in the upper, middle and lower reaches. According to the different characteristics of six ecological zones in Heihe River Basin, different mapping methods are used in the upper, middle and lower reaches. The data is in grid format with 1KM spatial resolution and WGS-84 projection. Soil texture attributes and categories represent 0-30 cm topsoil texture attributes, derived from depth-weighted averages. The texname in the attribute table indicates the soil texture type name. Sandrange, siltrange, and clayrange respectively represent the sand, powder, and clay content ranges in the USDA soil triangle. Sandaverage, siltaverage and clayaverage are taken from the measured soil profiles, the average content of sand, silt and clay particles as the sand, silt and clay content of the soil type. (Note: The soil particle content of clay loam is derived from the soil quality map of Beijing Normal University). The soil texture classification standard is USDA, the sand grain size is defined as (2~0.05mm), the silt particle size is (0.05~0.002mm) and the clay size is defined as (<0.002mm).

0 2019-09-15

Dataset of investigation of eco-hydrology transect in the downstream of the Heihe River Basin (2011)

The Eco-hydrology Transect Investigation data mainly includes vegetation data, soil physical and chemical properties and hydrological data. Vegetation investigation were conducted according to various community types within the same transect. The investigation mainly include trees, shrubs and herbs. The size and investigation indicators of each plot are as follows: arbor 20m*20m,whose investigation indicators include tree height, crown width, and diameter at breast height; shrub 10m*10m,whose investigation indicators include height, ground diameter, crown width, biomass; herb 1m*1m,whose investigation indicators include height,tree number, and biomass; The data includes 61 excel files, and each xls file contains several plot records of transect investigation with specific latitude and longitude information and plot number.

0 2019-09-15

HiWATER: Land cover map of the Heihe River Basin

The datasets of “Land Cover Map of Heihe River Basin” provide monthly land cover classification data in 2012-2013. The HJ-1/CCD data with both high spatial resolution (30 m) and high temporal (2 days) frequency was used to construct the time series data. The NDVI curves from the time series HJ-1/CCD data can depict the variation of typical land surface. Different land use type has different NDVI curve. Rules were set to extract every land use type information. The datasets of “Land Cover Map of Heihe River Basin” hold the traditional land use types including water bodies, urban and built-up, croplands, evergreen coniferous forests, deciduous broadleaf forests and so on. Crop type classification (including maize, spring wheat, highland barely, rape and so on), snow and ice and glaciers information updates, make the datasets more detailed. Compared with previous land cover map and other products, the classification result of the datasets is visually bette. Especially in middle stream, the accuracy of crop classification is quite high compared with the data from the ground campaign. The accuracy of land cover map of the datasets in 2012 was evaluated using very high spatial resolution remote sensing data within Google Earth and data from campaign, and the overall accuracy can be as high as 92.19%. In a word, the datasets of “Land Cover Map of Heihe River Basin” is not only high in overall accuracy, but also more detailed in crop fine classification. Furthermore, it updated some new classes like glaciers and snow. The datasets of “Land Cover Map of Heihe River Basin” are consequently the classification datasets with the highest accuracy and most detailed information up to now.

0 2019-09-15