Persian
Language
Geographical Research is Published in Persian Fulltext.
Volume 34, Issue 3 (2019)
GeoRes 2019, 34(3): 347-355 |
Back to browse issues page
Article Type:
Subject:
History
Received: 2018/09/11 | Accepted: 2019/07/24 | Published: 2019/09/7
Received: 2018/09/11 | Accepted: 2019/07/24 | Published: 2019/09/7
How to cite this article
Paroon S, Yavari G R, Rezazadeh M. Impacts of Climate Change on Watermelon and Cucumber Agriculture in Hormozgan Province and Prediction of Long-Term Pattern. GeoRes 2019; 34 (3) :347-355
URL: http://georesearch.ir/article-1-603-en.html
URL: http://georesearch.ir/article-1-603-en.html
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Rights and permissions
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
1- Department of Agriculture, Faculty of Agricultural Economic, Payame Noor University, Tehran, Iran , sparoon@pnu.ac.ir
2- Department of Agriculture, Faculty of Agricultural Economic, Payame Noor University, Tehran, Iran
3- Department of Agriculture, Faculty of Marine Science & Technology, Hormozgan University, Bandar Abbas, Iran
2- Department of Agriculture, Faculty of Agricultural Economic, Payame Noor University, Tehran, Iran
3- Department of Agriculture, Faculty of Marine Science & Technology, Hormozgan University, Bandar Abbas, Iran
Abstract (3878 Views)
Aims & Backgrounds: The agricultural sector is one of the most important economic sectors due to extensive interaction with the environment. The agricultural sector affects climate change and is also affected by climate change. Climate change, on the one hand, affects agricultural performance and, on the other hand, affects the price of products, supply, demand and welfare of consumers and producers. The purpose of this study was to assess climate change and predict its effects on yield, cropping and production of watermelon and cucumber.
Methodology: Data were gathered in the form of Panel data for cucumber and watermelon product during the years 2003-2017. Using predicted weather scenarios, yields, cropping levels, and harvesting products from 2025 to 2100 were predicted. Finally, consumer welfare, producer welfare and overall welfare were calculated using nonlinear programming model. During the years 2025 to 2100 to predict the welfare of partial equilibrium method was used.
Findings: In order to estimate the precise function of horticultural crop yield response to climate factors, indicators of climatic zonation region of the province were divided into two. Changes in performance under the weather scenarios for the cucumber product are increasing and the watermelon product follows a decreasing trend. The results showed that temperature had a positive impact on cucumber and had a negative impact on watermelon. Rainfall only had a negative impact on cucumber in the first region and in other cases had a direct impact on product performance. Amon uncontrollable factors, humidity had a reverse impact on both products in the first region. Technology had a positive impact and management had a negative impact.
Conclusion: the overall welfare show a decreasing trend in the coming years. Meaning that consumers experience less loss than producers.
Methodology: Data were gathered in the form of Panel data for cucumber and watermelon product during the years 2003-2017. Using predicted weather scenarios, yields, cropping levels, and harvesting products from 2025 to 2100 were predicted. Finally, consumer welfare, producer welfare and overall welfare were calculated using nonlinear programming model. During the years 2025 to 2100 to predict the welfare of partial equilibrium method was used.
Findings: In order to estimate the precise function of horticultural crop yield response to climate factors, indicators of climatic zonation region of the province were divided into two. Changes in performance under the weather scenarios for the cucumber product are increasing and the watermelon product follows a decreasing trend. The results showed that temperature had a positive impact on cucumber and had a negative impact on watermelon. Rainfall only had a negative impact on cucumber in the first region and in other cases had a direct impact on product performance. Amon uncontrollable factors, humidity had a reverse impact on both products in the first region. Technology had a positive impact and management had a negative impact.
Conclusion: the overall welfare show a decreasing trend in the coming years. Meaning that consumers experience less loss than producers.
References
1. Abbasi F, Babayan I, Habibi Nokhandan M, Golimokhtari L, Melbosi S (2010). The impact of climate change on Iran's temperatures and precipitation over decades with the MAGICC-SCENGEN model. Natural Geography Research. 72:91-110. [Persian]
2. Abbasi F, Babaian I, Melbosi S, Asmari M, Golimokhtari L (2012). Assessment of Iran's climate change in the decades (2025-2100) using the measurement scale of Joe's general circulation model. Quarterly Journal of Research Geographical. 27(1):205-230. [Persian]
3. Hormozgan Agritulture Jahad Organization [Internet] Bandar Abbas: Official Website of Hormozgan Agritulture Jahad Organization [Cited 2018, 23 February]. Available From: http://hormozgan-agri-jahad.com/ [Persian]
4. Ajdari S, Mortazavi SA, Moosavi S, Vakilpoor MH (2013). The effect of reducing the waste of bread on the welfare of the country's consumers. Agriculture and Development Economics. 21(82):69-89. [Persian]
5. Alijani F, Karbasi A, Mozaffarimossin M (2011). Effect of temperature and precipitation on the yield of wheat in Iran. Agricultural Economics and Development. 19(76):143-167. [Persian]
6. Andresen JA (1989). Prediction of county-level yield using an energy-crop growth index. Journal of Climate. 2:48-56.
https://doi.org/10.1175/1520-0442(1989)002<0048:POCLCY>2.0.CO;2 [DOI:10.1175/1520-0442(1989)0022.0.CO;2]
7. Apata TG, Samuel KD, Adeola AO (2009). Analysis of Climate change perception and adaptation among Arable food crop farmers in south western Nigeria. Conference of International Association of Agricultural Economists. 2009, 16-22 August: Beijing, China. p. 209.
8. Attavanich W, McCarl AB (2011). The effect of climate change, CO2 fertilization, and crop production Technology on crop yields and its economic implications on market outcomes and welfare distribution. Agricultural & Applied Economics Association's & NAREA Joint Annual Meeting. 2011, 24-26 July: Pittsburgh, Pennsylvania.
9. Azizi Gh (2006). Climatic zoning of Northwest of Iran using the lithin Skiing Method (GIS). Geosciences Journal. 5(6-7):11-27. [Persian]
10. Bagheri M, Najafi B (2011). Investigating the welfare effects of imports into the rice market. Agricultural Economic Research. 3(1):181-194. [Persian]
11. Bagheri M, Moazzai F (2013). Investigating the Side
12. effects of groundwater extraction on Iran's Pistachio Market. Agricultural Economics Research. 5(20):161-184. [Persian]
13. Baltagi BH (2005). Econometric analysis of panel data. 3rd ed. New York: John Wiley & Sons Inc.
14. Chalise L, Ghimire R (2013). Effects of climate change on peanut's yield in the state of Georgia, USA. Southern Agricultural Economics Association Annual Meeting. 2013, 3-5 February: Orlando. pp. 1-14.
15. Chang CC (2002). The potential impacts of climate change on Taiwan's agriculture. Agricultural Economics. 27(1):51-64. [DOI:10.1111/j.1574-0862.2002.tb00104.x]
16. Chang CC, Chen CC, McCarl B (2012). Evaluating the economic impacts of crop yield change and sea level rise induced by climate change on Taiwan's agricultural sector. Agricultural Economics. 43(2):205-214. [DOI:10.1111/j.1574-0862.2011.00577.x]
17. Chen CC, McCarl BA, Schimmelpfennig DE (2004). Yield variability as influenced by climate: A Statistical Investigation. Climatic Change. 66(1-2):239-61. [DOI:10.1023/B:CLIM.0000043159.33816.e5]
18. Chen CC, Chang CC (2005). The impact of weather on crop yield distribution in Taiwan: some new evidence from panel data models and implications for crop insurance. Agricultural Economics. 33(3):503-511. [DOI:10.1111/j.1574-0864.2005.00097.x]
19. Cline WR (2007). Global warming and agriculture: Impact estimates by country. Washington, DC: Centre for Global Development and Peterson Institute for International Economics.
20. Dixon BL, Hollinger SE, Garcia P, Tirupattur V (1994). Estimating corn yield response models to predict impacts of climate change. Journal of Agricultural and Resource Economics. 19(1):58-68.
21. Gbetibouo GA, Hassan RM (2005). Measuring the economic impsct of climate change on major South African field crops: A ricardian approach. Global and Planetary Change. 47:143-152. [DOI:10.1016/j.gloplacha.2004.10.009]
22. Haji Hasani A, Zandrzami AS, Ferdowsizadeh MI (2012). General Agriculture and Gardening, Agricultural and Horticultural Affairs - Animal Sciences, Agricultural College, School of Technical and Vocational Education, Publishing Company A lesson in Iran. [Persian]
23. Holden NM, Brereton AJ, Fealy R, Sweeney J. (2003). Possible change in Irish climate and its impact on barley and potato yields. Agriculture and Forest Meteorology.116:181-196. [DOI:10.1016/S0168-1923(03)00002-9]
24. Kamali Gh, Mullahi P, Bahyar MB (2010). Preparation of rainbow atlas of Zanjan province using climate data and GIS. Water and Soil Journal. 24(5):894-907. [Persian]
25. Kaufmann RK, Snell SE (1997). A biophysical model of corn yield: integrating climatic and social determinants. American Journal of Agricultural Economics. 79(1):178-190. [DOI:10.2307/1243952]
26. Khalilian S, Shamshadi K, Mortazavi SA, Ahmadian M (2014). Investigating the welfare effects of climate change on wheat crop in Iran. Journal of Agricultural Economics and Development. 28(3):292-300. [Persian]
27. Leakey ADB (2009). Rising atmospheric carbon dioxide concentration and the future of C4 crops for food and fuel. Royal Society. 276:2333-2343. [DOI:10.1098/rspb.2008.1517] [PMID] [PMCID]
28. Li X, Takahashi T, Suzuki N, Kaiser HM (2011). The impact of climate change on maize yields in the United States and China. Agricultural System. 104:348-353. [DOI:10.1016/j.agsy.2010.12.006]
29. Lobell DB, Burke MB, Tebaldi C, Mastrandrea MD, Falcon WP, Naylor RL (2008). Prioritizing climate change adaptation needs for food security in 2030. Scienc. 319(5863):607-610. [DOI:10.1126/science.1152339] [PMID]
30. McCarl B, Villavicencio X, Wu X (2008). Climate change
31. and future analysis: is stationarity dying? American Journal of Agricultural Economics. 90(5):1241-1247. [DOI:10.1111/j.1467-8276.2008.01211.x]
32. Momeni S, Zibaee M (2013). The potential impacts of climate change on agriculture in Fars Province. Journal of Agricultural Economics and Development. 27(3):169-179. [Persian]
33. Montazeri M, Bay N (2012). Climatic zoning of the Caspian region using multivariate statistical methods. Geographical Researches. 27(2):77-90. [Persian]
34. Montazeri M (2013). Application of multivariate statistical methods in cluster zoning case study: Isfahan province. Geographical Researches. 28(3):1-16. [Persian]
35. Mortimore M, Ba M, Mahamane A, Rostom RS, Serra del Pozo P, Turner B (2005). Changing systems and changing landscapes: Measuring and interpreting land use transformations in African drylands. Geografisk Tidsskrift-Danish Journal of Geography. 105(1):101-118. [DOI:10.1080/00167223.2005.10649530]
36. Mosavi S, Esmaili AK (2011). Analysis of the effects of import tariff policy on Iran's rice market. Agricultural Economics Research. 3(10):1-20. [Persian]
37. Mosavi S, Esmaeli AK, Azhdari S (2014). Evaluating economic effects of exchange rate depreciation on the rice market in Iran. Journal of Agricultural Science and Technology. 16(4):705-715.
38. Niu X, Esterling W, Hays CJ, Jacobs A, Mearns L (2009). Reliability and input-data induced uncertainty of the EPIC model to estimate climate change impact on sorghum yields in the U.S. Grate Plains. Agriculture, Ecosystems and Environment. 129(1-3):268-276. [DOI:10.1016/j.agee.2008.09.012]
39. Nunez HM, Onal H, Khanna M (2013). Land use and economic effects of alternative biofuel policies in Brazil and the United States. Agricultural Economists. 44(4-5):487-499. [DOI:10.1111/agec.12032]
40. Parhizkari A, Mozaffari MM, Hosseini Khodadadi M (2014). Economic analysis of climate change effects on blue wheat yield in Shahrood watershed. Agricultural and Natural Resources Journal. 18(4):88-100. [Persian]
41. Paroon S, Yavari G, Rezazadeh M (2019). The climate zonation of Hormozgan province using classical methods. Geography Quarterly (Regional Planning). 9(1):115-127. [Persian]
42. Samuelson PA (1952). Spatial price equilibrium and linear programming. American Economic Review. 42(3):283-303.
43. Ravan V (2010). Signs of climate change on temperature and precipitation tensis in the central zone of Fars province for the period 2040-2011 with the use of ECHAM5 model. [dissertation]. Shiraz: Shiraz University. [Persian]
44. Soltani S, Mousavi S (2015). Evaluation of potential impacts of climate change on yield and value added of agricultural sector in Hamadan plain. Agricultural Economics. 9(1):95-115. [Persian]
45. Stern N (2007). Stern review: The economics of climate change. Cambridge: Cambridge University Press. [DOI:10.1017/CBO9780511817434]
46. Takayama T, Judge GG (1964). Equilibrium among spatially separated markets: A reformulation. Econometirca. 32(4):510-524. [DOI:10.2307/1910175]
47. Vaseghi E, Esmaili A (2008). Effect of climate change on Iran's agricultural sector: Ricardin Method case study: Wheat. Science and Technology of Agriculture and Natural Resources. 12(45):685-696. [Persian]
48. Wu H (1996). The impact of climate change on rice yield in Taiwan. In: Mendelsohn R, Shaw D, editors. The Economics of Pollution Control in the Asia Pacific. Cheltenham, UK: Edward Elgar Publishing.