Project County Selection of WFP Interventions In Gansu Province, China Under Country Programme 2001-2005 Han Zheng WFP/IFAD China Vulnerability Analysis and Mapping (VAM) Unit July 2002 1 Background In the WFP China Country Programme of 2001-2005, 25 counties in south of Gansu province are identified as candidate counties of WFP Gansu Intervention. This identification was agreed between WFP and MOA, based on 1) the VAM 2000 China County Analysis, which put forward 459 counties as most vulnerable and eligible for further study, and 2) the project counties suggested by the Government. The 25 counties are located in the central and south part of Gansu, which is on the stretches of Minshan Mountains bordering the Tibetan Plateau and extends onto the Loess Plateau and Qingling Mountains. More than 80% of the total area is mountainous and suffering from frequent natural disasters. Due to limited resource, further targeting is needed to scale down the project area and concentrate the food aid on the most needy people, therefore, further county and township targeting is required1. General Situation of the Candidate Counties2 South of Gansu is home of quite a number of national poverty-stricken counties. The 25 candidate counties for WFP intervention are among the 43 priority counties designated by the Chinese Government for poverty reduction. According to the data collected from the 25 counties, the total population of the 25 counties is more than 8 million, living in an area of 6 million hectares. Rural labor force accounts for about 50% of the rural population. The average mountainous area within a township is 63% and the cultivated land is only 0.14 ha per capita. Various natural disasters hit the area frequently and the agriculture is backward. The average per capita grain production in the 25 counties is less than 250 kg in latest five years and the average rural net income of 2001 is about 1100 Yuan. The main crops of food supply are wheat, maize, tuber and some beans. Rice is rarely planted in some counties on the south border of Gansu where climatic conditions is a little better. The crop-planting pattern differs largely in different counties and the yield of each crop varies. The average wheat yield per mu is 130 kg, and the yield of maize is 200kg. The annual variability of grain is about 0.2, means the grain production is not very stable between years. In some township, this indicator can reach 0.6. Chart 1 shows the average composition of grain output in the 25 counties. Wheat production accounts for one-third of the total grain production, however, maize and potato have a proportion of about 50% of the total outputs. 1 Maps in this report are prepared by Yu Jing, VAM Assistant of WFP China. 2 All analysis of this report are based on township data provided by Gansu PMO. 2 Chart 1 – Composition of Grain Production in Candidate Counties Composition of Grain Production 11% 7% 34% wheat/grain maize/grain tuber/grain bean/grain 24% others/grain 24% Husbandry is important in the life of farmers in this region. The per capita pasture land is about 1.4 mu. However, the livestock raising shows no increase in the number of goats and/or sheep, and big animals raised by each household. No trend of increase in pig raising as well. In average, each household has one draught animal, and two households have three pigs and goats and/or sheep. Chart 2 shows the situation. Chart 2 – Livestock Raising in the Candidate Counties in Last Five Years Livestock Raising 1.80 1.60 1.40 1.20 1997 1.00 1998 1999 2000 0.80 2001 0.60 0.40 0.20 0.00 big animal per household goat&sheep per household pig per household 3 The data of adult education show that female education is worse than that of men. Although there are quite a proportion of adult have gone to primary school, there are more than 40% of female never entered school. The primary education today is also worrying because the drop out rate is more than 10% for both boys and girls. Chart 3 – Adult Education in Candidate Counties Adult Education never go to school female adult average primary school graduates 0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00 40.00 45.00 50.00 Infrastructure is backward in this region. About one-third of townships don’t have irrigation, while the irrigated land is about 15% of the total cultivated land in the townships that have irrigation. Only 25 percent of administrative villages have tap water, 70% of administrative villages have a village clinic. Methodology 1. County selection criteria It is well known that in China the intra-county disparity is huge in terms of economic development and physical conditions, thus the best way to targeting the vulnerable area at this stage is to cluster the townships and identify the most vulnerable ones. The counties with high percentage of vulnerable townships or vulnerable people should be considered for assistance, and the vulnerable townships within the county can be project townships. 2. Data and map collection 4 In accordance to the above principle, which has proved successful, township data should be collected from all the 594 townships in the 25 candidate counties. The data collection form was prepared by WFP Beijing based on the field observations of a VAM mission to that region. Based on the county data analysis and the field visit in the candidate counties, it can be seen that vulnerability of people in this areas is highly related to food production, livestock raising, income sources and social development. People in this area are living heavily on their own production, with limited supplementation of migration income. Livestock raising is popular but at a very small scale, mainly for cash income. Social infrastructure, especially road, drinking water and hospital, is backward and hinders the local development. Many people living in mountains at a high altitude above sea level don’t have much access to markets and other social facilities. Therefore, information about agriculture, income, disaster, husbandry, road, clinics and education are collected. Gansu Provincial PMO provided all the required data to WFP Beijing on time and worked closely with the VAM Unit on data verification and revising. In the meantime, maps of the 25 counties with township boundaries and the location of administrative villages are digitized and processed in order to illustrate the final analysis results. 3. Data verification and revising Data verification is essential to the analysis. After the data is sent to Beijing, they are imported to a MS ACCESS database for data verification. There are about 150,000 figures in the data set and the first round checking marked less than 10% skeptical or wrong data, which is much less than some other project provinces. The skeptical or wrong data are sent back to Gansu for revising and clarification. The checking-and- revising circle went twice until the data set is clean and reliable. 4. Indicator Selection The indicator selection is in accordance with WFP definition of vulnerability, which is a composition of risk to food security and inability to cope with the risks. The higher the risk and the lower the ability to cope, the higher the vulnerability of population/area is. Social development level is also considered a part of the coping capacity. In order to obtain a comprehensive profile of the area and distinguish the vulnerable townships from the others, indicators covering demography, farming, husbandry, income, natural disaster, social infrastructure and education are calculated. By screening the indicators, only those that are available for most of the townships are studied further. For example, the indicators about natural disasters have to be excluded although they are important for that they are available for only a small number of townships. For the indicators of farming, husbandry and income, average annual growth rate and/or coefficient of variation between years are computed to show the growth trend in recent years. Following indicators are included in further analysis. 5 Table 1 – Indicators Used in Township Vulnerability Analysis of Gansu No. Indicators Category 1 Annual growth rate of rural population Risk (97-2001) (%) 2 Average per capita grain production Risk (kg) (97-2001) 3 Coefficient of variation of per capita Risk grain production (97-2001) 4 Per capita cultivated land (ha) (2001) Risk 5 Per capita agricultural land (ha) (2001) Risk 6 Per capita pasture land (ha) (2001) Risk 7 Per capita rural net income (yuan) Coping ability (2001) 8 Annual growth rate of rural net income Coping ability (97-2001) (%) 9 Average no. of goats & sheep per Coping ability household (98-2001) 10 Average no. of pigs per household (98- Coping ability 2001) 11 Annual growth rate of pig raising (98- Coping ability 2001) 12 Annual growth rate of goats and sheep Coping ability raising (98-2001) 13 % Of non-grain sown area/crop sown Coping ability area (2001) 14 %Village with tap water (2001) Social development 15 % Of primary dropouts (2001) Social development 16 % Of primary female dropouts (2001) Social development 17 % Adults never going to school (2001) Social development 18 % Female adults never going to school Social development (2001) 19 % Villages with complete primary Social development school (2001) 20 % Of villages with village clinics (2001) Social development 21 Dependent ratio Social development The correlation between indicators is computed to find out the relations between indicators (Annex 1). From the correlation sheet, statistically significant correlations between certain pairs of indicators are not found. But the general relations can be seen.