African Journal of Biotechnology Vol. 9(54), pp. 9108-9117, 29 December, 2010 Available online at http://www.academicjournals.org/AJB ISSN 1684–5315 © 2010 Academic Journals Review Division of the water-saving crop planning system in the Heihe River basin Yubao Wang1,2,3,4, Pute Wu1,2,3*, Xining Zhao1,2,3 and Jiming Jin4 1Institute of Water Saving Agriculture in Arid regions of China, Northwest A & F University, Yangling, China 2Key Laboratory for Agricultural Soil and Water Engineering in Arid Area of Ministry of Education, Northwest A & F University, Yangling, China 3National Engineering Laboratory for Crop Water Efficient Use, Yangling, China 4Departments of Watershed Sciences and Plants, Soils and Climate, Utah State University, Logan, Utah, USA. Accepted 10 December, 2010 Instituting water-saving crop planning (WSCP) is an effective way for the Heihe River basin to reverse its current growing scarcity of water resources and continuing environmental deterioration. However, because different areas of the river basin have different natural resources and diverse social and economic conditions, the planting structure for the region must be divided before the optimal adjustment of WSCP. The influencing factors for this division are chosen based on the analysis of the WSCP system. The appropriate indicators are selected from the overall influencing factors according to the existing hydro-meteorological, socio-economic and agricultural water conservancy conditions in each county in the river basin. Several unrelated main components that reflect most information from the original variables are extracted using factor analysis (FA) with the Statistical Package for the Social Sciences (SPSS) software and are then clustered using the K-means clustering algorithm (KMCA). Based on the clustering results, the basin is divided into six subzones: (1) Forage grass with dry farming, (2) grain and cash crops with rain-fed irrigation, (3) grain and cash crops with irrigation, (4) fruits and vegetables with irrigation, (5) cash crops with irrigation and (6) forage grass and cash crops with irrigation. Suitable development programs for each subzone were then drafted. This method avoids the overlap of related variables, reduces the difficulty of treatment and is convenient for indicator selection and information collection. Key words: Division of water-saving crop planning, Heihe River basin, factor analysis, K-means clustering algorithm. INTRODUCTION The Heihe River basin, located in the middle of Gansu covers about 1.43 × 105 km2. As shown in Figure 1, the Corridor, is the second largest inland river basin in North- upper reaches belong to Qilian County of Qinghai west China and lies roughly between 37°44 and 42°40N Province and Sunan County of Gansu Province, the and 97°37 and 102°06E. The Heihe River is 821 km long middle reaches belong to the counties of Shandan, Minle, from its source in the Qilian Mountains to its terminus in Ganzhou, Linze, Gaotai, Jiayuguan and Suzhou in Gansu Juyan Lake. It flows through three provinces and its basin Province, and the lower reaches belong to Jinta County of Gansu Province and Ejina of the Inner Mongolia Autonomous Region. According to modern surface water and groundwater hydraulic links, the Heihe River basin *Corresponding author. E-mail: [email protected]. Tel: +86- can be divided into eastern, central and western water 29-87082802. Fax: +86-29-87082802. subsystems. The main rivers in the western water 4 2 subsystem (with a total watershed area of 2.1 × 10 km ) Abbreviations: WSCP, Water-saving crop planning; FA, factor are the Hongshui and Taolai rivers, which flow into the analysis; SPSS, statistical package for the social sciences; Jinta Basin. The central water subsystem (with a total KMCA, K-means clustering algorithm. area of 6 × 103 km2) contains the Maying and Fengle Wang et al. 9109 rivers, which flow into the Gaotai Salt Lake and Minghua implemented before the optimization of water-saving crop Depression. The eastern water subsystem (with a total planning (WSCP), and then the planting structures of area of 1.16 × 105 km2) includes the main forks of the each subzone must be optimized to obtain the desired Heihe and Liyuan rivers as well as more than 20 results (Jolayemi, 1996, Nevo et al., 1994, Pereira, 1982). tributaries. The total surface runoff of the Heihe River basin is 37.28 × 108 m3 and the total groundwater is 4.31 × 108 m3, so the total water in the basin is 41.59 × 108 m3. THE DIVIDING METHOD The Heihe River basin is located far inland in central Asia and has a dry climate with abundant sunshine, There is little research on specific methods for dividing scarce but concentrated precipitation, strong winds, intense planting structure; the existing relevant research is more evaporation and an extreme shortage of water resources about agricultural economic structure and land-use (Ministry of Water Resources, China, 2002). Because of patterning methods. For example, the agricultural econo- the continuous pressure of population growth and mic structure of different administrative areas was divided excessive economic development, water consumption by using the fuzzy clustering analysis method and has been steadily increasing in the basin for many years, choosing factors that play a leading role in agricultural especially in the central portion. Utilization of water economic development, such as average annual precipi- resources in 2006 reached 95% (statistical data from the tation, mean annual temperature, per capita grain yield water resources department of Gansu Province), which and per capita net income (Hall and Arnberg, 2002; Liu far exceeds the rational exploitation limit of 40% set by and Samal, 2002, Ma et al., 2000). Programs for optimal international consensus. This excessive water consump- soil and water use were determined through the analysis tion by humans has resulted in continued environmental of the regional ecological construction methods and deterioration, which has become a serious threat to sus- resources, noting the advantages found under different tainable social and economic development in the basin. land-use patterns. The programs were then assigned to Agricultural water use accounted for about 94% of the space unit plots by the Geographic information systems total social and economic water consumption in 2006, but (GIS) (Chambers, 2005, Yule et al., 1996, Yao et al., the water use efficiency and the benefit thereof were very 2004). The division of wheat cultivation was completed low. Agricultural water conservation is the key to according to the index of different lands’ rents under the reversing the current growing water shortage and the principle of grain security (Tratnik et al., 2009). continuing environmental deterioration. However, if water Common dividing methods currently include the use efficiency is enhanced only through improving following: Decision tree, statistics, nearest neighbor, irrigation facilities or increasing the level of irrigation empirical quality-deciding, indicator, type, overlap, step- district management, the cost per cubic meter of water wise discrimination analysis, clustering and fuzzy saved will continue to increase (Wang et al., 2010, Sethi clustering (Dinpashoh et al., 2004, Qiao et al., 2002). This et al., 2002, Sarker and Ray, 2009). So, to improve water study completely drafts the influencing factors based on use efficiency, the planting structure must be adjusted by the analysis of the WSCP system and then selects the increasing the input only slightly, reducing the proportion appropriate indicators from the overall influencing factors of high-water-consuming crops and coordinating crop by using the existing hydro-meteorological, socio- planning better with the effective precipitation, incoming economic and agricultural water conservancy conditions river water, available groundwater and crop water in each county in the Heihe River basin. Next, a few demand (Wang et al., 2010, Adeyemo and Otieno, 2010). unrelated components that reflect most of the information The Heihe River basin includes three major types of from the original variables are extracted using factor geomorphologic zones: Mountains, basins and deserts. analysis (FA) with the Statistical Package for the Social Therefore, the climate, topography, soil, water and other Sciences (SPSS) software, and then are clustered using natural resources are different from region to region. For K-means clustering algorithm (KMCA). Based on the example, the mean annual precipitation varies from 406.7 clustering results, the basin is divided into six subzones, mm in Qilian County in the upper basin to 37.0 mm in and suitable development programs for each subzone are Ejina County in the lower basin, and the annual evapo- drafted. This method avoids the overlap of related ration ranges from 1191.9 mm in Qilian County to 3841.5 variables, reduces the difficulty of treatment, and is con- mm in Ejina County. There is also considerable diversity venient for indicator selection and information collection. in market sales, labor, quantity of land, policies and regu- The calculations can be completed quickly, accurately lations, farmers’ culture, investment abilities, cultivation and conveniently using SPSS. habits and other socio-economic conditions. As an illustration, in 2007, the level of urbanization in Minle DIVISION OF WSCP IN THE HEIHE RIVER BASIN County was 12.86%, but in Jiayuguan City, it was 76.71% (Gansu Yearbook Editorial Board, 2007). Both natural Influencing factors