By applying Supply-demand Balance Analysis, the water resource supply and demand of the whole river basin and each county or district were calculated and used to evaluate the vulnerability of the water resources system of the basin. The IPAT equation was used to set a future water resource demand scenario to establish the scenario by setting variables such as future population growth rate, economic growth rate, and unit GDP water consumption. By taking 2005 as the base year and using assorted forecasting data of population size and economic scale, the future water demand scenarios of various counties and cities from 2010 to 2050 were predicted. By applying the basic structure of the HBV conceptual hydrological model of the Swedish Hydrometeorological Institute, a model of the variation tendency of the basin under climate change was designed. The glacial melting scenario was used as the model input to construct the runoff scenario under climate change. According to the national regulations of the water resources allocation of the basin, a water distribution plan was set up to calculate the water supply comprehensively. Considering of the supply and demand situation, the water resource system vulnerability was evaluated by the water shortage rate. By calculating the (grain production) land pressure index of the major counties and cities in the basin, the balance of supply and demand of land resources under the climate change, glacial melt and population growth scenarios was analyzed, and the vulnerability of the agricultural system was evaluated. The Miami formula and HANPP model were used to calculate the human appropriation of net primary biomass and primary biomass in the major counties and cities for the future, and the vulnerability of ecosystems from the perspective of supply and demand balance was assessed.
YANG Linsheng, ZHONG Fanglei
The data set include crop leaf stomatal conductance observed at four sample regions, that is the soil moisture control experimental field at Daman county, and the super station, and Shiqiao sample plots at Wuxing village in Zhangye city. 1) Objective Crop leaf stomatal conductance, a key biophysical parameter, was observed as model parameter or a priori knowledge for crop growth model, or evapotranspiration estimation. 2) Measuring instruments Leaf porometer. 3) Measuring site a. the soil moisture control experimental field at Daman county, Twelve soil water treatments are set. The crop leaf stomatal conductance for each treatment is measured on 17, 23 and 29 May, and 3, 9, 14 and 24 June, and 5 and 12 July. b. the Super Station The crop leaf stomatal conductance at the super station is measured on 22 and 28 May, 5, 11, 18, and 25 June, and 1, 8, 15, 22 and 31 July, 9, 15 and 22 August, and 3 and 11 September. c. the Shiqiao sample site The crop leaf stomatal conductance at the Shiqiao village is measured on 17, 22 and 28 May, 4, 11, 17 and 25 June, 1, 8, 15, 22, and 30 July, 8, 16 and 27 August, and 9 September. 4) Data processing The observational data was recorded in the sheets and reorganized in the EXCEL sheets. The time used in this dataset is in UTC+8 Time.
Xu Fengying, Wang Jing, Huang Yongsheng, LI Xin, MA Mingguo
According to the characteristics of the selected field and its surrounding area, a trime tube is arranged in the corn field, and 5 trime tubes are arranged in a direction perpendicular to the field path. When monitoring soil moisture content in the TDR vertical direction, the unit is every 10cm. Monitor down. Location: N 38 ° 52′27.6 ″ E 100 ° 21′14.0 ″ The submitted data includes the water content of the farmland and its surrounding soil (TDR monitoring) after three irrigations in a selected farmland in Yingke Irrigation District, encrypted monitoring after irrigation, one group every 3 hours within 24 hours, and 3 groups per day for the next 5 days. -10 days are two groups per day, and 10-15 days are one group per day.
HUANG Guanhua, JIANG Yao
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