Scholarly article on topic 'Evaluation of Subsurface Drainage Design Based on Projection Pursuit'

Evaluation of Subsurface Drainage Design Based on Projection Pursuit Academic research paper on "Agriculture, forestry, and fisheries"

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Abstract of research paper on Agriculture, forestry, and fisheries, author of scientific article — X.H. Shao, M.M. Hou, L.H. Chen, T.T. Chang, W.N. Wang

Abstract Soil salinization is a type of soil degradation, which is one of the biggist problems in protected agriculture. A welldesigned subsurface drainage system with reasonable drain space and depth contributes to large ratio of desalination and high crop yield. For selecting the optimization design, it is important to find out how the subsurface drainage systems affect the soil conditions and improve the harvest. In this experiment, the drainage pipes were arranged by two different patterns, the dynamics of surface soil EC was measured by salinity sensors, and the tomato yield was calculated. In order to comprehensively evaluate the rationality of subsurface drainage system, a PP(projection pursuit) model was also established. The results showed that the monthly variation of subsurface soil EC was in a trend of decline in general, drainage treatment Tr1 and Tr2 performed much better than non-drainage treatment CK. Based on the model's calculations, drain spacing 8m and drain depth 0.7m(Tr2) was selected as the preferable subsurface drainage parameter. The desalination ratio of Tr2 was 9.59% larger than CK, and 1.7% larger than Tr1; tomato yield of Tr2 reached 38796.5kg/hm2, which was 31889.9kg/hm2 higher than CK, and 6823kg/hm2 higher than Tr1.

Academic research paper on topic "Evaluation of Subsurface Drainage Design Based on Projection Pursuit"

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Energy Procedía 16 (2012) 747 - 752

Energy

Procedía

2012 International Conference on Future Energy, Environment, and Materials

Evaluation of Subsurface Drainage Design Based on

Projection Pursuit

X. H. Shao a,b*, M. M. Hou a,b, L.H.Chena,b, T.T.Changa,b, W.N.Wanga,b

a Key Laboratory of Efficient Irrigation-Drainage and Agricultural Soil-Water Environment in Southern China(Hohai University),

Ministry of Education, Nanjing210098, China b College of Water Conservancy and Hydropower, Hohai University, Nanjing210098, China

Abstract

Soil salinization is a type of soil degradation, which is one of the biggist problems in protected agriculture. A well-designed subsurface drainage system with reasonable drain space and depth contributes to large ratio of desalination and high crop yield. For selecting the optimization design, it is important to find out how the subsurface drainage systems affect the soil conditions and improve the harvest. In this experiment, the drainage pipes were arranged by two different patterns, the dynamics of surface soil EC was measured by salinity sensors, and the tomato yield was calculated. In order to comprehensively evaluate the rationality of subsurface drainage system, a PP(projection pursuit) model was also established. The results showed that the monthly variation of subsurface soil EC was in a trend of decline in general, drainage treatment Tr1 and Tr2 performed much better than non-drainage treatment CK. Based on the model's calculations, drain spacing 8m and drain depth 0.7m(Tr2) was selected as the preferable subsurface drainage parameter. The desalination ratio of Tr2 was 9.59% larger than CK, and 1.7% larger than Tr1; tomato yield of Tr2 reached 38796.5kg/hm2, which was 31889.9 kg/hm2 higher than CK, and 6823 kg/hm2 higher than Tr1.

© 2011 Published by ElsevierB. V. Selection anid/or peer-review under responsibility of International Materials Sciencz Society. Keywords: subsurface drainage, tomato yield, EC, yield, projection pursuit

1. Introduction

Soil salinity, defined as the concentration of soluble mineral salt that exists in the soil, is one of the

Corresponding author: X. H. Shao; Tel.: 13951005013; fax: 025-83786511.

E-mail address: shaoxiaohou@163.com.

1876-6102 © 2011 Published by Elsevier B.V. Selection and/or peer-review under responsibility of International Materials Science Society. doi:10.1016/j.egypro.2012.01.120

X.H. Shao et al. /¡Energy Procedía 16 (2012) 747 - 752

most severe environmental factors limiting the productivity of agricultural crops[1] and baffling agricultural sustainable development of China. Continuous attention had been paid to soil salinization and secondary salinization for many years by scientists around the world. At present, many researches focus on the application of subsurface drainage in reducing soil salinity, improving soil conditions and increasing crop yield[2-5]. Ritzema H P [6] and Ghumman A R [7]showed that in one period of crop growth, the utilization of subsurface drainage system can reduce the EC value by 50% and 17%.

On the other hand, drainage design associated with placing the drains at different depths or spacings would change the drainage intensity and affect the efficiency of desalination[8-10]. Therefore, reasonable design of drainage system and the selection of related parameters play a decisive role in determining the stand or fall of a drainage system. In addition, a well-designed drainage design should not only consider the ratio of desalination and crop yield, but also the costs, ratio of resalination, water productivity and environmental benefits.

2. Materials and Methods

2.1 Experimental site.

The experiments were initiated in a plastic sheet covered greenhouse in the Vegetables and Flowers Institute of Jiangning (latitude 31° 43' N, longitude 118° 46'E), Nanjing, China. The average annual rainfall is about 1106.5mm, with the rainy season from the end of June to the middle of September, and the average yearly temperature is approximately 15.7°C and average humidity is about 81%.

2.2. Soil conditions.

Soil texture and data of some physical and chemical properties of the soil in the experimental plot are shown in Table 1.

Table 1. Soil properties of the 0-0.6 m layer in the experiment plot.

Depth (cm) Soil Texture EC (ms/cm) PH Ki0 (10-4cm/s) Bulk Density (g/cm3) Porosity (%)

0-20 20-40 40-60 Heavy Clay Loam 529 295 205 5.4 5.6 5.7 0.91 0.41 0.21 1.39 1.50 1.53 47.55 43.23 42.26

2.3 Experimental design

The experiments were carried out in the greenhouse and the observation was from May 2010 to August 2010, perennial farming and irregular management result in the secondary soil salinization.The secondary salinized greenhouse soils were treated by two designs on the basis of previous study and three treatments were arranged as follows:

Tr1: drain space 6m and drain depth 0.4m

Tr2: drain space 8m and drain depth 0.7m.

CK served as controls, with no subsurface drainage treatment.

The seepage control facilities were installed using the cement and brick made channels to prevent external influences.Drainage ponds were excavated on the side of Tr1 and Tr2 to collect the outflow from

X.H. Shao et al. /Energy Procedía 06 (2012) 707 - '752

the subsurface drainage tubes, and a water pump was used to debouch the water in the ponds. The tubes were plastic corrugated pipe with the diameter of 5cm, non-woven fabrics were used to cover these pipes. The material of leader drain pipes was PVC.

Seeds of tomato were sown in seedling trays each with 60 wells of 5 mm X 5 mm. Six weeks after seeds were sown, the young tomato plants with 6 expanded leaves were transplanted to saline soil in the greenhouse. During the period of growth, conventional field management was conducted, with no differences among the treatments.

2.4 Main tested index and methods

Surface soil EC(electricity conductivity) was observed using a HH2/WET soil values electronic tachymeter made by Delta-t Company in the UK, the monitoring points were selected as: points right above drainage pipes of Tr1 and Tr2 were recorded as Tr1.1 and Tr2.1 respectively; points above the middle of two pipes of Tr1 were recorded as Tr1.2, similarly, points above the middle of two pipes of Tr2 were recorded as Tr2.2, with non-drainage treatment CK serving as controls, there were five monitoring points in total, and each monitoring point made three repetitions during the observation. The surface soil EC was chosen between two irrigation time intervals, at the same time, dynamics of EC in certain irrigation cycle was observed.

The tomatoes were picked when they were ripe, then the weight of single fruit was measured and the total yield in the experimental field was calculated.

2.5 Main evaluated index and calculation methods

Build costs: The costs mainly included labor cost and material cost, the cost of communal drain pond would not be counted for the total build costs. The detail compute methods were as follows:

V , „ „ V

C1 = n1 xLxU + Tx ——— C2 = n2 xLxU + Tx- 2

V + V2t V + V2

Where Ci is the build costs($) of Tr1, C2 is the build costs($) of Tr2; ni, n2 is respectively the drain pipes number of Tr1 and Tr2; L is the length(m) of one drain pipe; U is the unit price($/m) ; T is the total labor cost($); Vi is the total excavated volume(m3) of Tr1, V2 is the total excavated volume(m3) of Tr2. Yield: Tomato yield was the sum of yield of the first, second and third inflorescence. EC value of Tr1 was the average of Tr1.1 and Tr1.2, the same with Tr2.

3. Evaluation models

The projection pursuit model is used to evaluate the rationality of subsurface drainage arrangement and related parameters design in this paper. Projection pursuit(PP) is a new method of analyzing and disposing high dimensional data, especially dealing with nonlinearity or non-norm distribution of the data. The essence is making use of computer technology to project high dimensional data to lower dimension, searching for the projection which could well reflect the characters of high dimensional data and studying data structures in low dimensional space, in order to achieve the aim of analyzing and disposing high dimensional data[11-15]. Model creation method sees reference [15].

4. Results and Discussion

X.H. Shao et al. /¡Energy Procedia 16 (2012) 747 - 752

4.1 Main evaluation indexes

Previous studies about subsurface drainage focused mostly on the changes of soil physical and chemical properties. In many cases, the option of drain spacing and depth was based on the desalination effects or human experiences. A reasonable drainage system should comprehensively consider many aspects. This paper evaluated the subsurface drainage system from five main factors: Build costs, ratio of desalination, ratio of resalination, tomato yield, and water productivity. The calculated indexes were displayed in Table 2.

Table 2. The Evaluation Index of Drainage and Non-drainage Treatments

Treatment Build Costs ($) Ratio of Desalination (%) Ratio of Resalination (%) Yield (kg/hm2) WPc (kg/m3)

CK 0 6.25 10.61 6906.6 2.89

Tri 242 14.14 9.09 31973.5 13.39

Tr2 421 15.84 8.13 38796.5 16.25

4.2 Model calculations

As was shown in Table 2, build costs and ratio of resalination were two indexes which should be controlled as small as possible, while ratio of desalination, yield and WPc were "the high the better".

Projection pursuit classification model(PP) was built by Matlab 7.1 based on the indexes in Table.3, and RAGA was used to optimize the PP method. In the course of optimization, the main parameters were set as: the original population size n=400; the probabilities of crossover Pc=0.8; the probabilities of mutation Pm=0.8; number of excellent individuals was 20; a=0.05; accelerating 20 times. According to the model's calculations, the maximum index value of projection was 0.3254; the best projection direction was aj)*=(0.0016, 0.5109, 0.4782, 0.5050, 0.5052), the projection value of CK, Tr1, Tr2 was ordered to be Z(i)*=(0.0016, 1.5081, 1.9994). By the rules of projection value "the bigger the better", Tr2 was optimum subsurface drainage system on account of the highest projection value.

4.3 Evaluation of subsurface drainage design

The buried spacing and depth are two important impact factors. Buring too deep leads to the large area of land damage and hard to popularize. If the pipes spaced too narrow, the material costs is too high and will finally increase the total build costs. In this experiment, the results obtained indicated that under the condition of drain spacing 8m and drain depth 0.7m(Tr2), the ability of desalination, controlling resalination, increasing crop yield and improving WPc were higher than Tr1,which demonstrated Tr2 was the preferable design.

The soil surface layer(0-20cm) was the key layer for the development of crop roots, previous crop could not live, exactly on account of severe soil salinization on surface soil layer. While under the condition of subsurface drainage with drain spacing 8m and drain depth 0.7m(Tr2), the soil condition was satisfactorily improved. The desalination ratio reached 15.84%, which was a very high level compared with Tr1. It was proved that under Tr2 design, the soil salinity could be taken smoothly away through the drain pipes with the irrigation water. Likewise, ability of suppressing resalination is also an important index for evaluating the rationality of the drainage design. From Table 2 it can be seen the resalination ratio of Tr2 was the highest, which suggest that Tr2 design could not only effectively reduced the surface soil salinity, but also ensured the greatest degree of restraining the uprise of soil salinity.

X.H. Shao et al. /Energy Procedía 06 (2012) 707 - '752

From the angle of crop yield and WPc, Tr2 design was also preferable, tomato yield of first experimental cycle reached 38796.5 kg/hm2, and the yield of second year was supposed to be more than the first year along with the operation of the drainage system.

Build costs was a remarkable index which was often ignored by theoretical research. Under the design of Tr2, it was found the build costs was 421$, and the economic output of the experimental field was 273$(the unit price of tomato was supposed as 0.47$/kg), it could be roughly predicted that the costs would be regained in two or three years include the consideration of other costs such as water, fertilizer, pesticide and seedlings.

In general, Tr2 design was recommended as the preferable design, although build costs was higher than Tr1, it could be taken back in the short term without any cost risk. In the long run, subsurface drainage is a significant project once and for all, it brings not only economic benefits, but also huge environmental and social benefits.

5. Conclusion

Compared with the results of the five measuring points with different treatments, it was demonstrated that subsurface drainage was significant in reducing soil salinity and suppressing the resalination for secondary salinization greenhouse soil, and also had remarkable influences in increasing crop yield. The results showed that from 27th May to 26th July, the ratio of desalination of drainage treatments was 14.14% and 15.84% respectively, which was much higher than non-drainage treatment(CK). Fruit yield of drainage treatment Tr1 and Tr2 was 31973.5kg/hm2and 38796.5kg/hm2, also much higher than CK.

A PP model was built to comprehensively evaluate two subsurface drainage designs according to five main evaluation indexes, calculation result proved that drain spacing 8m and drain depth 0.7m(Tr2) was more beneficial to improve soil conditions and increase crop yield. It showed that ratio of desalination of Tr2 was 1.7% higher than Tr1; fruit yield of Tr2 was 6823 kg/hm2 higher than Tr1. Tr2 design would bring the humanity huge economic benefits, environmental benefits and social benefits. The study conclusions can provide theoretical and practical basis for the amelioration of soil and optimal design of subsurface drainage system in protected cultivation.

Acknowledgements

This work was financed by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD), Natural Science Foundation of Jiangsu Province of China (Project BK2009342) and the Special Fund for the Scientific Research of the Agricultural Welfare Project(200903001-05).

References

[1] Pitman, M., Lauchli, A., 2002. Global impacts of salinity and agricultural ecosystems. In: Lauchli, A., Lüttge, U. (Eds.), Salinity: Environment-Plants-Molecules. Kluwer Academic Publishers, New York, pp. 3-20.

[2] Ai Tian-cheng, Li Fang-min. Effect of subdrainage on layer soil physical and chemical characteristics in waterlogged land. Journal of Yangtze University (Nat Sci Edit) Agri Sci, 2007, 4(2): 4-5,8.

[3] A.B. Botcher, E.J. Monke and L.F. Huggins, Nutrient and sediment loadings from a subsurface drainage system, Trans. ASAE, 24, 5 (1981): 1221-1226.

[4] R.W. Skaggs and Tibrizi Abdolhossim Nasssehzabeh. Effect of Drainage System Design on Surface and Subsurface Runoff from Artificially Drained Lands, Proc. Inst. Symp. Rainfall-Runoff Modeling, Mississippi State University, 1982, pp. 142-157.

[5] J.W. Hornbuckle et al. Evaluating a multi-level subsurface drainage system for improved drainage water quality. Agricultural water management, 2007, 89: 208-216.

X.H. Shao et al. /Energy Procedia 16 (2012) 747 - 752

[6] Ritzema H P, Satyanarayana T V,Raman S. et al.Subsurface drainage to combat waterlogging and salinity in irrigated lands in India:Lessons learned in farmers' fields. Agricultural Water Management, 2008, 95: 179-189.

[7] Ghumman A R,Ghazaw Y M, Niazi M F et al.Impact assessment of subsurface drainage on waterlogged and saline lands.Environ Monit Assess, 2010.

[8] Algoazany, A.S., Kalita, P.K., Czapar, G.F., Mitchell, J.K.. Phosphorus transport through subsurface drainage and surface runoff from a flat watershed in east central Illinois, USA. Journal of Environmental Quality, 2007, 36 (3), 681 - 693.

[9] Cooke, R.A., Nehmelman, J.E., Kalita, P.K., 2002. Effect of Tile Depth on Nitrate Transport from Tile Drainage Systems. ASAE Paper No. 022017. American Society of Agricultural Engineers, 2950 Niles Rd. St. Joseph, MI. 49085.

[10] Mitchell, J.K., McIsaac, G.F., Walker, S.E., Hirschi, M.C., 2000. Nitrate in river and subsurface drainage flows from an east central Illinois watershed. Transactions of the ASAE 43 (2), 337 - 342.

[11] Fu Qiang, Fu Hong. Applying PPE model based on RAGA in the investment decision making of water saving irrigation project [J]. Nature & Science. (USA ) 2003, 11 (1) : 72- 77.

[12] Fu Qiang, Jin Juliang, Liang Chuan. Application of projection pursuit model to optimize paddy irrigation schedule[J]. Journal of Hydraulic Engineering, 2002, 33(10): 39-45.

[13] Feng Zhiming, Zheng Haixia, Liu baoqin. Comprehensive evaluation of agricultural water use efficiency based on genetic projection pursuit model[J]. Transactions of the CSAE, 2005, 21(3): 66-70.

[14] Zhang Libing, Cheng Jilin, Jin Juliang, et al. Projection pursuit model for comprehensive evaluation of agricultural irrigation water quality[J]. Transactions of the CSAE, 2006, 22(4): 15-18.

[15] Fu Qiang, Zhao Xiaoyong. Theory and Practice of PP Model[M]. Science Press, 2007.