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A Study on Water Resources Consumption by Principal Component Analysis in Qingtongxia Irrigation Areas of Yinchuan Plain, China

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A Study on Water Resources Consumption by Principal Component Analysis in Qingtongxia Irrigation Areas of Yinchuan Plain, China WFL Publisher Science and Technology Meri-Rastilantie 3 B, FI-00980 Journal of Food, Agriculture & Environment Vol.7 (3&4) : 734-738. 2009 www.world-food.net Helsinki, Finland e-mail: [email protected] A study on water resources consumption by principal component analysis in Qingtongxia irrigation areas of Yinchuan Plain, China De Zhou 1*, Rongqun Zhang 2*, Liming Liu 1, Lingling Gao 2 and Simin Cai 2 1 College of Resources and Environment, China Agricultural University, Yuanmingyuan West Rd, Haidian District, Beijing, 100193, China. 2 College of Information and Electrical Engineering, China Agricultural University, 17 Tsinghua East Rd, Haidian District, Beijing 100083, China. *e-mail:[email protected], [email protected] Received 22 July 2009, accepted 6 October 2009. Abstract Principal component analysis (PCA) is a valid method used for data compression and information extraction in water resources. PCA finds linear combinations of the original measurement variables that describe the significant variations in the data. In this paper, PCA is used to extract three principle components from 12 factors such as population size (PS), value of industrial output (VIO), gross output value of agriculture (GVA), sown area of rice (SAR), sown area of wheat (SAW), sown area of corn (SAC), agricultural water consumption (AWC), industrial water consumption (IWC), urban water consumption (UWC), rural people and livestock water consumption (RPLWC), annual water amount (AWA), annual water discharge amount (AWDA) which reflect the status of water resources consumption in Yinchuan Plain, China, and our calculations show that the comprehensive scores of water resources consumption is dropping year by year during 1996-2002. The result shows that the use of water resources in Yinchuan Plain is faced with a lot of pressure. This paper has testified the scientific nature of PCA, and provided evidence for decision-making of rational use of regional water resource. Key words: Principle component analysis, Yinchuan Plain, water resources consumption. Introduction With the completed of Qingtongxia Water Conservancy Hubs, and (3) the maximum of regional water resources carrying capacity. the history that the farmers bring in water directly to irrigate from In the meantime, a lot of research methods were created, such as the Yellow river has come to an end in Qingtongxia irrigation areas comprehensive index method, fuzzy comprehensive evaluation in Yinchuan Plain. At the same time, the capacity of water supply method and principle component analysis. Therefore, carrying and the modulus of water supply for the industrial and agricultural capacity of water resources can be calculated according to the production were enhanced. So, if there is no irrigation there would above method. Fu and Ji 9 adopted the principle component be no agricultural production 1. However, with the development analysis method to undertake comprehensive evaluation of the of socio-economic and the area increasing of agricultural irrigation, regional water resource carrying capacity. They obtained the contradictions among agricultural water consumption, correspondent classifying standard of the principle component industrial water consumption and other aspects were increased to judge water resources carrying by the use of the principle continuously. Therefore, the unreasonable utilization of water component analysis 9. Zheng and Wang focused on the resources is becoming serious. That is to say, how to reasonable construction of evaluation of water resources, systematic analyze use of water resources were depended primarily on the modes of the quantity of water resources, main utility condition and quality production and the ways of life. So, how to enhance the level of of water environment, evaluation of regional development to the water resources sustainable use has received substantial attention need of water resources and bearing property 10. Some foreign of scholars both at home and abroad 2-4.The concept of water researchers have conducted many studies of water resources by resource carrying capacity was first posted by the China Xinjiang principle component analysis 11-13. Bengraine and Marhaba applied Water Resource Soft-Science Research Panel 5. It is clear that the the PCA to monitor spatial and temporal changes in water quality, study of water resources carrying capacity becomes a new focus and this study shows the importance of environmental monitoring these days. However, an explicit definition of this concept has associated with simple but powerful statistics to better understand generally not been acknowledged at home and abroad up until a complex water system 14. In this paper we analysed the main now 6. Lot of scholars have conducted in-depth study for water trends in the development of water resources consumption by resources carrying capacity 6-8, and the theory and method of means of PCA, using data of nature, society, economics and water water resources carrying capacity is only at the exploratory stage. resources of the Yinchuan Plain in 1996-2002. The aim of the study Generally speaking, the following major objectives: was to solve the contradiction between water resources (1) the evaluation of regional water resources carrying capacity, exploitation and utilization in Yinchuan Plain and provide decision (2) the certain status of regional water resources carrying capacity support for making policies. 734 Journal of Food, Agriculture & Environment, Vol.7 (3&4), July-October 2009 Materials and Methods The amount of annual rainfall totals about 185 mm, most of which Study area: Yinchuan Plain is located in the north part of Ningxia falls during the summer months between June and September. Autonomous Region (Fig. 1), northwest China. From west to east, The annual evaporation is 1825 mm, nearly ten times more than the plain consists of the tilted plain of Helan mountain, the alluvial- annual precipitation, and drought index is 6.5. The annual average proluvial plain of the Yellow River, and an alluvial-lacustrine runoff in the Yellow River is 1030 m3/s and the total volume of plain15. Its northern boundary is adjacent to Helan Mountain’s annual water flow through the Yinchuan Plain is 3.25×1010 m 310. southwest border; in the east it is adjacent to Ordos Plateau. The Soil is fertile and it has good irrigation conditions. Therefore, the Yellow River passes through the plain along the east boundary plain is one of bases of grain production. with a total length of about 193 km. It is 7,790 km2 in area, and wide east-west about 42-60 km. Its altitude is 1100-1150 m. Native Data and method: In this study, the data were mainly collected vegetation is typical desert steppe, and vegetation is mainly from Ningxia Statistical Yearbook 1996-2007, Water Resources artificial oasis now. The main soil types are irrigation-silted soil, Communique of Ningxia Autonomous Region 1996-2007, the sierozem and bog soil, etc. Main crops are wheat, rice, maize etc. Optimal Allocation of Water Resources and Sustainable Use of Yinchuan Plain is located in the temperate arid zone, which has Strategic Research in Ningxia, Medinm and long-term planning of continental climate with the average annual temperature of 9°C. water resources in Ningxia Autonomous Region, which include basic history and status of the water resources use in the Yinchuan Plain, such as population size (PS),value of industrial output (VIO), gross output value of agriculture (GVA), sown area of rice (SAR), N sown area of wheat (SAW), sown area of corn (SAC), agricultural Helan Ordos water consumption (AWC), industrial water consumption (IWC), Mountain urban water consumption (UWC), rural people and livestock water consumption (RPLWC), annual water amount (AWA) and annual Plateau water discharge amount (AWDA). In addition, the standardized values of factors were calculated from the original data by SPSS 16-17 (Table 1). The above 12 factors can reflect water resources consumption fundamentally. Therefore, in order to choose rational index system and evaluate the water consumption of the Yinchuan Channel Plain scientifically, it is necessary to choose some indexes which can reflect the water resources consumption and utilization Darain situation, the relationship between supply and demand. NingXia Plain boundary Principal component analysis: Principal component analysis City (PCA) is a statistical technique for determining the key variables YinChuan Plain in a multidimensional data set that explains the differences in the Figure 1. Location of the study area on the Yinchuan Plain in China. observations and can be used to simplify the analysis and visualization of multidimensional data sets 18. In recent years, the Table 1. Standardization values of original data during 1996-2002. Population Value of industrial Gross output value of Sown area of Sown area of Sown area of Year size (x1) output (x2) agriculture (x3) rice (x4) wheat (x5) corn (x6) 1996 -1.2550 -1.1033 -1.2665 -1.2024 -1.3875 -1.3495 1997 -0.9001 -0.7670 0.6839 0.1469 -0.4904 -0.6472 1998 -0.5340 -0.6320 1.7477 0.0184 0.7578 0.7573 1999 -0.2123 -0.3850 0.3293 1.3034 1.2259 1.5275 2000 0.4976 0.3036 -0.5572 0.9179 0.4458 -0.8285 2001 -1.2550 -1.1033 -1.2665 -1.2024 -1.3875 -1.3495 2002 -0.9001 -0.7670 0.6839 0.1469 -0.4904 -0.6472 Table 1. (Continue). Agricultural Rural people and Annual Annual water Industrial water Urban water Year water livestock water water discharge consumption (x8) consumption (x9) consumption (x7) consumption (x10) amount (x11) amount (x12) 1996 -1.5949 0.2706 -0.2862 -1.1603 0.1649 0.3857 1997 1.3818 1.3668 1.1522 -0.7101 0.7905 -0.0644 1998 0.4309 1.0847 0.8439 -0.6741 0.8983 1.3379 1999 -0.5623 -1.1883 -1.8787 -0.4580 1.1140 1.1578 2000 0.3568 0.0046 -0.3376 0.4425 -0.5102 -0.9819 2001 0.6713 -0.3903 0.0220 1.1989 -1.1293 -1.1031 2002 -0.6835 -1.1480 0.4843 1.3610 -1.3282 -0.7319 Journal of Food, Agriculture & Environment, Vol.7 (3&4), July-October 2009 735 Table 2.
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