Document Type : Research Article

Authors

1 Sari Agricultural Sciences and Natural Resources University

2 Sari agriculture and natural resource University

Abstract

Introduction: In today’s traditional agriculture and trade, it may not be possible to increase yields per hectare without applying some types of chemical fertilizers and pesticides. By producing 950 thousand tons of rice Mazandaran province supplies 42% of rice of the country. In the internal and external studies, it has been dealt with the study of entering nitrate into water technically. According to the destructive effects of nitrogen water-soluble on health and to the fact that Mazandaran province is the main producer of rice in Iran and applying the fertilizers containing nitrate is common in rice cultivation; the purpose of this study was to examine the effective factors on the entrance of nitrate into groundwater in cultivating rice in Sari. The aim of the present study is also to examine the effective factors on absorption pure nitrogen in the water used to cultivate rice.
Materials and Methods: The dependent variable in this study indicates the amount of pure nitrogen used water by i th farmer that has been divided into three categories. Calculating the dependent variable is such that the total amount of urea consumed by farmer is obtained by interview with farmers, the dependent variable of the amount of Nitrate pollution used groundwater was divided into three classes of low, medium and high. Considering such studies and the nature of dependent variable of the present study, that is as ordered discrete, the best model to respond the research objective is to use logit ordered pattern, but if the parallel regression assumption has not been considered, the advanced generalized ordered logit pattern should be used. In generalized ordered logit, the estimating parameters of independent variables that have rejected the assumption of parallel regression, cannot be same for different groups or levels. In other words, each level not only has separate intercept but also different coefficients. In order to select the samples, simple random sampling method has been used. Data used in this section has been collected by survey research method in 2015 for Sari. In order to determine the sample size, a pre-study has been conducted based on Cochran relation. The sample size of farmers’ was set at 98 farmers but finally 106 questionnaires were completed. Estimating the model and their results were conducted through Stata v.12 software.
Results and Discussion: According to the results, the dependent variable has been divided into three groups. About 43% of rice producers are the farms who used a moderate amount of nitrate into water, but 64% of them used medium and high amount of nitrate pollution that should be noticed. The results of parallel regression test for individual independent variables showed that among 17 independent variables, seven variables have been violated the condition of parallel regression. Therefore, the generalized ordered logit model was used. The variable income that has not been violated the assumption of parallel regression, has the coefficient of 0.83 in the first and second groups, that has been significant at the level of 10%. It means that, by increasing the level of farmers’ income and stability of other conditions, the possibility that the farmer will be in the group with more pollution will increase. As expected, the significant variable such as applying animal fertilizer, paying water expenses and agreement with omitting subsidy have negative and significant effect on the amount of nitrate used water. In other words, by increase in each variable, the possibility of placing farmers in the group of more pollution decreases. If farmers’ income increases as one unit, the possibility of placing the farmer in the group of low pollution decreases 0.2 unit and placing in the group of high pollution increases 0.17 unit. Being familiar with cultivating organic production will increases the possibility of placing the farmer in the group of low pollution in 0.55 unit, while the possibility of placing in the group with high pollution increase in less amount. On the other hand, the more positive attitude in rice cultivator towards supportive and public organization, the possibility of their placing in the group of low pollution of Nitrate decreases 0.13 units and the possibility of their placement in the group of high pollution on Nitrate increases 0.11 units.
Conclusions: Based on the obtained results and coefficient for every level of dependent variable, entrance of Nitrate in to groundwater in cultivating rice in Sari and interpreting the final effects of significant variables, the recommendations are offered for optimal utilization of fertilizers containing Nitrate and improving health of groundwater in cultivating rice as follows According to the factors effective on income and this variable that cultivating rice could not afford life express of 77% of the surveyed people, public supportive, private and insurance organizations should pay specific attention to this significant and important section. Revising supportive policies of the supportive public and private organizations for rice cultivators can be effective so that the policy making should have been lead into facilitate solving production and improving the farmers’ income than subsidiary supports of fertilizers. Revising in owner share and share on transaction under the supervision organs of agriculture are recommended. Of course income support and facilitating the sales of owner farmer can avoid renting the farm. Applying natural fertilizers and being familiar with cultivating organic and healthy products, have placed the rice cultivator in the level of minimum usage of chemical fertilizer as well as nitrate entrance into groundwater. Therefore, promoting, advertising and encouraging farmers to cultivate organic can be a strategy accompanied with financial and security incentive and finally, it is recommended to design and perform efficient policy making of water market in Mazandaran province to approach the real price of water.

Keywords

1- Bakhshi A., Shahnazari H., and Tahmasebi R. 2013. Simulated nitrate transport paddy rice fields of Mazandaran in canola growing season for water resources management. Journal of Water and Irrigation Management (Journal of Agriculture), 3(2): 29-42. (In Persian).
2- Antweiler W., Copeland R. B., and Taylor M. S. 2001. Is Free Trade Good for the Environment? The American Economic Review; 4(2): 877- 908.
3- Asteriou D. 2007. Applied econometrics: a modern approach using Eviews and Microfit Rev.ed. 2007: 236-442.
4- Azmoodeh M. 2013. History of economic thought. Nashre Nei. (In Persian)
5- Babiker I.S., Mohamed M.A.A., Hayama T., and Kato K. 2005. A GIS-based DRASTIC: model for assessing aquifer vulnerability in Kakamigahara heights, Gifu Prefecture, central Japan. Journal of Science of the Total Environment, 345(1-3): 127-40.
6- Baltagi H. 2002. Econometrics Analysis of Data, second Edition، John Wileys Sons، Ltd: 216-288.
7- Beghin J., Dessus S., et al. 1997. The trade and environment nexus in Mexican agriculture. A general equilibrium analysis. Agricultural Economics, 17(2–3): 115-131.31
8- Dehkordi A., Afioni M., and Mosavi S. F. 2005. Assessment of changes in nitrate concentrations in groundwater in in zayandehrood, Isfahan province, Journal of Ecology, 39: 33-40. (In Persian)
9- Di H. J., and Cameron K. C. 2002. Nitrate leaching and pasture production from different nitrogen sources on a shallow stony soil under flood-irrigated dairy pasture. Australian Journal of Soil Research, 40(2): 317-334.
10- Dinardo N. John. 1997. Econometric methods, 4th Ed, c1997, 124-136.
11- Fazeli M., Kalantari F., Rahimi M.H., and Khubyari A. 2011. Investigating the temporal and spatial distribution of nitrate pollution of groundwater Zydun plains. Water Engineering Journal, 4(8):45-51. (In Persian)
12- Fewtrell L. 2004. Drinking-water nitrate, methemoglobinemia, and global burden of disease. A discussion. Environmental Health Perspective, 112 (14): 1371-1374.
13- Fronsec P. 2001. Quantitative models in marketing research, the dependent variable is the two-choice: 97-116.
14- Gibson RS., Vanderkooy PC., Mclennanc CE., et al. 1987. Contribution of tap water to mineral intakes of Canadian preschool children. Arch Environ Health, 42(3): 165-172.
15- Goolsby D. A. 2000. Mississippi Basin nitrogen flux believed to cause Gulf hypoxia. Eos, Transactions American Geophysical Union, 81(29):321-327.
16- Grazhdani D. 2015. Contingent Valuation of Residents’ Attitudes and Willingness to- Pay for Non-Point Source Pollution Control: A Case Study in AL-Prespa, Southeastern Albania, Environmental Management 56:81–93.
17- Green W.H. 1993. Econometric Analysis, second Edition, Macmillan.
18- Grossman G.M., and Krueger A.B. 1995. Economic growth and the environment Quarterly, Journal of Economics, May, 353– 358.
19- Gujarati D.N. 2005. Basic Econometrics, McGraw-Hill.
20- Hsiao C. 1986. Autoregressive Modeling and Money-Income Causality Detection. Journal of Monetary Economics, pp. 85-106.
21- Jalali Koutenaei N., Naseri A., and Salahshour J. 2008. Water requirement and crop coefficient of rice (case study: Tarom cultivar) by lysimetric type N-Type in Mazandaran province Mahmoud Abad city. 2nd National Conference on Irrigation and Drainage Network Management, Ahwaz, Chamran University. (In Persian)
22- Josuma G., et al. 1987. Groundwater contamination: Use of models in decision- making, kluwer Academic Publisher, 178p.
23- Kamiab Talysh F., Razavipour Komala D., and Rezaei M. 2011. Evaluation of nitrate leaching losses during rice growing season. 12th Congress of Soil Sciences, Tabriz, Iran 12- 14 September 2011. (In Persian)
24- Khazaei S.H., Khorasani N., Talebi Jahromi KH., and Ehteshami M. 2010. Investigation of the groundwater contamination due to the use of Diazinon insecticide in Mazandaran province (case study: Mahmoud Abad City). Journal of Natural Environmental, Iranian Journal of Natural Resources, 63(1): 23-32. (In Persian with English abstract)
25- Knobeloch L., et al. 2000. Et al Blue babies and nitrate contaminated well water. Environmental Health Perspective, 108 (7): 675-678.
26- Krapac I. G., et al. 2002. Impacts of swine manure pits on groundwater quality. Environ Pollute, 120 (2): 475-92.
27- Lee C.-C., Chiu Y.B., et al. 2010. The environmental Kuznets curve hypothesis for water pollution: Do regions matter? Energy Policy, 38(1): 12-23.
28- Liao S.H. 1994. Knowledge Management Technologies and Applications- Literature Review from 1985 to 1994. Expert Systems and Applications, 25 (2): 155-164.
29- Madala G. S. 1998. Unit roots, Cointegration and Structural change, Econometica, 47, 261-266.
30- Managi S., A Hibiki A., et al. 2009. "Does trade openness improve environmental quality?" Journal of Environmental Economics and Management, 58(3): 346-363.
31- Matyas L. 1992. Proper Econometric Specification of the Gravity Model", The Model for assessing aquifer vulnerability in Kakamigahara heights, Kifu Prefecture.
32- Mazandaran Regional Water Organization. Department of Water Resources basic studies. The statistical report. 2014. Ministry of Energy. (In Persian)
33- Ministry of Agriculture. 2015. Statistical Yearbook. (in Persian)
34- Mohammadi H., Moarefi Mohammad A., and Nojavan Solmaz. 2017. Factors Affecting Farmer’s Chemical Fertilizers Consumption and Water Pollution in Northeastern Iran. Journal of Agricultural Science. 9 (2): 234-241.
35- Moradzadeh M., Moazed E., and Sayyad G. A. 2013. Simulate nitrate leaching in a sandy loam soil treated with zeolite using software Hydrus-1D. Knowledge of soil and water, 23(1):95-108. (In Persian)
36- Nolen BT. 2001. Relating Nitrogen Sources and Aquifer Susceptibility to Nitrate in Shallow Ground Water of the United States. Ground Water, 39(2): 35-48.
37- O’Donoghue C., Buckley C., Chyzheuskaya A., Grealis E., Green S., Howley P., Hynes S., and Upton V. 2015. The Spatial Impact of Economic Change on RiverWater Quality 1991- 2010, European Association of Agricultural Economists, 150th Seminar, October 22-23, 2015, Edinburgh, Scotland.
38- Ouedraogo I., and Vanclooster M. 2016. A meta-analysis and statistical modelling of nitrates in groundwater at the African scale, Hydrology and Earth System Sciences, 20, 2353–2381.
39- Phelps E. S. 1961. The Golden Rule of Accumulation: A Fable for Growthmen, American Economic Review, Vol1: 638-643.
40- Rodriguez-Galiano V., Paula Mendes M., Jose Garcia-Soldado M., Chica-Olmo M., and Ribeiro L. 2014. Predictive modeling of groundwater nitrate pollution using Random Forest and multisource variables related to intrinsic and specific vulnerability: A case study in an agricultural setting (Southern Spain), Science of the Total Environment, 476–477, 189–206.
41- Sedaghat M. Earth and Water Resourcees (Groundwater). Tehran: Payame Noor university publication; 2008. (In Persian)
42- Shahnoushi N., Firouz Zareh A., Zhaleh Rajabi M., Dourandish A., and Shahidi Yasaghi S.A. 2012. Bread waste products (causes and consequences). Ferdowsi University of Mashhad. Mashhad. (In Persian)
43- Shariat Panahi M. 1998. Quality principles of water and wastewater treatment. Tehran University. Tehran. (In Persian)
44- Sheikh Zeineddin A., Esmaeili A., and Zibaei M. 2016. Policy incentives to reduce nitrate leaching in farmlands: Case study irrigation and drainage network Doroudzan. Journal of Agricultural Economics and Development, 30(2): 127-135. (In Persian)
45- Singh M. P. 1985. Import Policy for a Developing Economy. Allahabad, India: Chugh Publications.
46- Suri A. Econometrics (Advanced) along with the use of Eviews 8 and Stata 12. The Ethnography. (In Persian)
47- Williams R. 2006. Generalized ordered logit / partial proportional odds models for ordinal dependent.
48- Williams R. 2010. Generalized ordered logit models. Midwest sociological meetings, Chicago.
49- Wooldridge Jeffrey M. 2005. Introductory econometrics, 3rd, c2005 World Economy, 20, No.3, Blackwell Publishers. Oxford.
50- Zare Abyaneh H., Nouri H., Liaghat A., Karim V., and Nouri H. 2011. Calibration of nitrate leaching and water table fluctuation in paddy rice fields using DRAINMOD-N software. Journal of Soil and Water Sciences, 15 (57): 49-60. (In Persian).
CAPTCHA Image