Water Poverty Theory And Its Application To Inland River Basin

Ganzhou,Zhangye City, locates at the north-western inland areas,belongs to the upper and middle watershed of Heihe river, an unique oasis agriculture formed for long-term roles of climate , surface material, vegetation, soil and human activities. With the watershed management in recent years, Ganzhou area spills its water to the downstream, Ejinaqi, when water from Yingluoxia, the upperstream reaches to 1.58 billion m3, it discharges 950 million m3 to the downstream, So water shortage becomes an serious issue in this area. It is known that water resources occupys the core in the complex giant system compsoed by five modules, water - soil -gas– living creature- human socioeconomic activities, water shortage will inevitably affect the rest of the component units. Traditional water resources assessment only focus on water resources internal system and neglects its intrinsic relation with human being's socio-economic system. Therefore,the concept of water poverty is introduced. The concept is on the basis of the general theory of poverty, sustainable livelihoods and geographical environment. For more accurate measurement of water poverty in Ganzhou area, WPI composite index approach is used, which is developed by University of Oxford Ecohydrological Research Center (CEH), the United Kingdom Institute of Geography. this method is to divide WPI into five level-1 indicators, each level-1 indicators is also divided into 3 to 10 levle-2 indicators. With the current situation of water poverty in Ganzhou area in Zhangye City,the same CEH level-1 indicators are used , taking into account the availability of data, combined with water resources development, utilization, protection and management of the actual situation in this area, 25 secondary indicatorsare are identified. By field survey, questionnaire and literature review, Yearbook and reports, respectively got the first-hand and secondary data. with the trend data and by use of balanced method gains the 5 sub-indicator scores on water resources, water supply facilities acess, utilization efficiency and structure, water capacity and water environment situation in eight irrigation areas among Ganzhou,Zhangye City and in this basis, the WPI total score is obtained for the eight irrigation areas. Among the sub-indicator of water resources,Wujiang irrigation area scores 74 pionts, Huazai irrigaiton area is 9 points; Among the sub-indicator of water supply facilities, Ganjun is 61 points, Anyang and Wujiang is the same score 29 point; For the sub-indicator of utilization efficiency and structure, Yingke irrigation area scores 85,Anyang is 9; For water capacity Yingke is 79, Huazai is 0; Among sub-indicator for water environment, Yingke is 97,Anyang is 30. For the total score of WPI, Yingke ranks the top with 72.6 point, Anyang is on the bottom with 16.2 point. In order to know the sub-indicators and the spatial distribution of WPI, arcviewGIS3.2 is applicated to get WPI spatial distribution map of every irrigation area. In WPI analytical methods 25 variables will have to be used, 25 variables is an excess number, in addition many variables have a high degree of correlation, In order to know which variables contributes more , PCA method is used to analyse the principal component of the 25 variables. By process of trending and standardization of original variables, with contribution rate of variance and cumulative variance, extracted four principal components from the original 25 variables. In the basis of the principal component scores caculation,by the variance contribution rate of each principal component to achieve comprehensive evaluation equation for the principal component,by this way achieved the comprehensive evaluation of the principal component scores in the 8 irrigation areas in Ganzhou area and ranked them. The result is consistent with what gained by WPI composite index , the scoring rank of other irrigated areas has not changed, Yingke still ranks the first, Daman the second, Xigan is the third, GanJun ranks the fourth , Huazai is the seventh, Anyang is on the bottom , only just in the WPI, Shangsan ranks the fifth, Wujiang ranks the sixth , in the principal component analysis Wujiang the fifth and Shangsan ranks the sixth. In order to further understand the 25 variables impact on principal component scores , input principal component scores as the dependent variable, the 25 original variables as variables for principal component regression, the results shows 18 variables were automatically removed, the other 7 variables determine the quantity of principle component scores. In order to explore the main factors affect the WPI ,input WPI scores as the dependent variable , the total number of staff in each irrigation areas, the per capita net income of farmers and the social capital in each irrigation area as variables to carry out multiple regression analysis, the results shows that the rlation between social capital and WPI linear was not significant, while the per capita net income of farmers and water pipes scale with the total number of staff in irrigation area have identified significant with WPI linear. What the relation for the 18 removed variables and principal component scores as well as relation between social capital and WPI are still for future research.