Optimization of cultivation pattern and density under climate change conditions (case study of Damaneh-Daran plain)

Document Type : Research Article

Authors

1 Ph.D student, Water resource engineering, Department of Water Science and Engineering, Faculty of agriculture, Birjand university

2 university of birjand,

3 Assist. Professor, Department of Water Science and Engineering, Minab higher education center, University of Hormozgan

Abstract

In most countries, agriculture is the largest consumer of water due to its biological nature and strong dependence on nature. As a result, water management in this sector plays an essential role in determining how countries use their water resources. The present study was conducted to optimize the area under cultivation, allocate irrigation water, and maximize crops’ benefit in the Damaneh-Daran plain, Isfahan, Iran, from 2017-2030 under the RPC8.5 scenario using a genetic algorithm. Following monthly runoff estimating by the AWBM model under climate change conditions within a correlation coefficient of 75% indicated that the values of RMSE, MBE, and R of the microscale parameters measured by the Statistical Micro-Scale Model (SDSM) were equal to 8.34, 7.51 and 0.98 in the temperature parameter and -1.28, 6.28, and 0.78 in the precipitation parameter, respectively. Wheat, barley, sugar beet, and fodder corn cultivation were reduced by 2130.6, 1176.1, 112.8, and 516 hectares, respectively, by pattern optimization. The expansion of potato cultivation by 3935.5 hectares reduced water usage by 18.21 Mm3and generated a total profit of 163 million tomans for farmers between 2017 and 30.

Keywords

References

[1]. Ashraf Vaghefi S, Abbaspour N, Kamali B, Abbaspour K.C. A toolkit for climate change analysis and pattern recognition for extreme weather conditions – Case study: California-Baja California Peninsula. Environmental Modelling & Software. 2017; 96: 181-198.
[2]. Ouyang F, Zhu Y, Fu G, Lü H, Zhang A, Yu Z, Chen X. Impacts of climate change under CMIP5 RCP scenarios on streamflow in the Huangnizhuang catchment. Stochastic Environmental Research and Risk Assessment. 2015; 29(7): 1781- 1795.
[3]. Van Vuuren, D.P, Edmonds J, Kainuma M, Riahi K, Thomson A, Hibbard K, Hurtt G.C, Kram T, Krey V, Lamarque J.F, Masui T, Meinshausen M, Nakicenovic N, Smith S.J, Rose S.K. The representative concentration pathways: an overview. Climatic Change. 2011; 109: 1- 5.
[4]. Ho J. T, Thompson J. R, Brierley C. Projections of hydrology in the Tocantins Araguaia Basin, Brazil: uncertainty assessment using the CMIP5 ensemble. Hydrological Sciences Journal. 2016; 61(3): 551-567.
[5]. Kim J, Choi J, Choi C, Park S. Impacts of changes in climate and land use/land cover under IPCC RCP scenarios on streamflow in the Hoeya River Basin, Korea. Science of the Total Environment. 2013; 452: 181-195.
[6]. Kwak J, Kim S, Singh V.P, Kim H.S, Kim D, Hong S, Lee K.. Impact of climate change on hydrological droughts in the upper Namhan River basin, Korea. KSCE Journal of Civil Engineering. 2015; 19(2): 376-384.
[7]. Tan M. L, Ibrahim A. L, Yusop Z, Chua V. P, Chan N. W. Climate change impacts under CMIP5 RCP scenarios on water resources of the Kelantan River Basin, Malaysia. Atmospheric Research. 2017; 189: 1-10.
[8]. Vaighan A. A, Talebbeydokhti N, Bavani A. M. Assessing the impacts of climate and land use change on streamflow, water quality and suspended sediment in the Kor River Basin, Southwest of Iran. Environmental Earth Sciences. 2017; 76(15): 1- 18.
[9]. Houshmand Kouchi D, Esmaili K, Faridhosseini A, Sanaei-Nejad S. H, Khalili D. Simulation of climate change impacts using fifth assessment report models
under RCP scenarios on water resources in the upper basin of Salman Farsi dam. Iranian journal of irrigation and drainage. 2019; 2(13): 243- 258. (In Persian).
 
[10]. Blanco M, Cortignani R, Severini S. Evaluating changes in cropping patterns due to the 2003 CAP reform, an ex-post analysis of different pmp approaches considering new activities. Presentation at the 107th EAAE Seminar Modelling of Agricultural and Rural Development Policies. 2007: 15 P.
[11]. Withey P, Kooten C. The effect of climate change on land use and wetlands conservation in western Canada.Resource Economics & Policy Analysis. Research Group Department of Economics University of Victoria. 2011. 23 P.
[12]. Terry G. Climate, change and insecurity: Views from a Gisu hillside. Doctoral thesis, University of East Anglia. 2011.
[13]. Chijioke O.B, Haile M, Waschkeit C. Implication of climate change on crop yeild and food accessibility in sub-Sahran Africa. MSc Thesis, Bon University. 2011. 31 P.
[14]. Soleymaninejan S, Dourandish A, Sabouhisabouni M. Banayanaval M. The effects of climate change on cropping pattern (Case study: Mashhad plain). Iranian journal of agricultural economics and development research. 2019; 50(2): 249- 263. (In Persian).
[15]. Azuara J, Howitt R, MacEwan D, Lund J. Economic impacts of climate-related changes to California agriculture. Journal of Climatic Change. 2011; 109: 387-405.
[16]. Connor J, Kirby M, Schwabe K, Liukasiewics A, Kaczan D. Impacts of reduced water availability on lower murray irrigation, Australia, socio-economics and the environment in discussion. CSIRO working paper series. 2008. 7- 11.
[17]. Ozkan B, Akcaoz H. Impacts of climate factors on yields for selected crops in southern Turkey. Journal of Mitigation and Adaptation Strategies for Global Change. 2002; 7: 367–380.
[18]. Semenov M.A. Simulation of extreme weather events by a stochastic weather generator. Climate Research. 2008; 35: 203-212.
[19]. Mislan M, Haviluddin H, Hardwinarto S, Sumaryono B, Aipassa M. Rainfall monthly prediction based on Artificial Neural Network: A case study in Tenggarong Station, East Kalimantan – Indonesia. Journal of Computer Science. 2015; 59: 142 –151.
[20]. Shafie A.H, El-Shafie A, Hasan G, Mazoghi A, Mohd R. Artificial neural network technique for rainfall forecasting applied to Alexandria. International Journal of the Physical Sciences. 2011; 6: 1306-1316.
[21]. Aksorn P, Srinilta Ch. Statistical Downscaling for rainfall and temperature prediction in Thailand. Proceedings of the international multi conference of engineers and computer scientists. 2011; MARCH 16 – 18, Hong Kong.
[22]. Ashofteh P. S, Haddad O. B, Mariño M. Climate Change Impact on Reservoir Performance Indexes in Agricultural Water Supply. Journal of Irrigation and Drainage Engineering. 2013; 139(2): 85–97.
[23]. Zhou Y, Guo S. Incorporating ecological requirement into multipurpose reservoir operating rule curves for adaptation to climate change. Journal of Hydrology. 2013; 498: 153–164
[24]. Huang J, Zhang J, Zhang Z, Sun S, Yao J. Simulation of extreme precipitation indices in the Yangtze River basin by using statistical downscaling method (SDSM). Theoretical and Applied Climatology. 2012; 108(3–4): 325–343.
[25]. Coulibaly P, Dibike Y. B, Anctil F, Coulibaly P, Dibike Y. B, Anctil F. Downscaling precipitation and temperature with temporal neural networks. Journal of Hydrometeorology. 2005; 6(4): 483–496.
[26]. Goodarzi E, Dastorani M, Massahbavani A, Talebi A. Evaluation of the change-factor and LARS-WG methods of downscaling for simulation of climatic variables in the future (Case study: Herat Azam Watershed, Yazd - Iran). ECOPERSIA. 2015; 3(1): 833–846. (In Persian).
[27]. Zarrin H, Moghadamnia A, Namdroust J, Sadeghi S. H. Evaluation of AWBM model performance in simulation of rainfall -runoff process in nNon-statistics areas. Third conference on water resources management, Tabriz, Iranian association of water resources science and engineering, Tabriz University. 2008. (In Persian).
[28]. Dima W. Nazer A, Amaury Tilmant B, Ziad Mimi C, Maarten A. Siebel B, Pieter Vander Zaag B. E, Huub J. Gijzen d. Optimizing irrigation water use in the West Bank, Palestine. Agricultural Water Management. 2010; 97: 339-345.
[29]. Sadati S, Speelman S, Sabouhi M, Gitizadeh M, Ghahraman B. Optimal irrigation water allocation using a genetic algorithm under various weather conditions. Water. 2014; 6(10): 3068–3084.
[30]. Mohammadrezapour O, Yoosefdoost I, Ebrahimi M. Cuckoo optimization algorithm in optimal water allocation and crop planning under various weather conditions (case study: Qazvin plain, Iran). Neural Computing and Applications. 2017; 31(1): 1879–1892.
[31]. Meftah Halaghi M, Ghorbani Kh, Keramatzadeh A, Salarijazi M. Application of game theory to determining optimal harvesting of water resources and determination of optimal cropp pattern (Case study: Gharesu basin). Iranian Journal of Water and Soil Conservation. 2021; 27(5): 69- 87. (In Persian).
[32]. Abedinpour A. A, Jabbarzadeh A, Yahyaei M. A multi-objective mathematical modeling for optimization of crop planning problem under Z-number uncertainty. Iranian Journal of Water and Soil Conservation. 2019; 25(5): 1- 24. (In Persian).
[33]. Georgiou P. E, Papamichail D. M. Optimization model of an irrigation reservoir for water allocation and crop planning under various weather conditions. Irrigation Science. 2008; 26(6): 487–504.
[34]. Nazarifar M. H, Salari A, Momeni R.. Development of a nonlinear programming model for determination of optimal cropping pattern based on deficit irrigation scenarios. Iranian journal of soil and water research. 2018; 49(5): 1055- 1070. (In Persian).
[35]. Anonymous. Water resources balance of
Gavkhuni basin study area to Blue water. Isfahan eegional water corporation, Office of basic water resources studies. 2010. (In Persian)
[36]. Anonymous. The plain is the most critical slope of Frieden in terms of water resources depletion. Iran Islamic Republic News Agency. 2014. (In Persian)
[37]. Yoosefdoost A, Yoosefdoost I, Asghari H, Sadeghian M. Comparison of HadCM3, CSIRO Mk3 and GFDL CM2.1 in prediction the climate change in Taleghan river basin. American Journal of Civil Engineering and Architecture. 2018. 6(3):93-100.
[38]. Yoosefdoost I, Siuki A. K, Mohammadrezapour O, Tabari H. Evaluating performance of four statistical downscaling models (SDSM) of precipitation and temperature data under the fifth assessment report of the intergovernmental panel on climate change (IPCC) scenarios. Journal of Climate Research. 2021. 45: 43- 66. (In Persian).
[39].Yoosefdoost I, Mohammadrezapour O, Ebrahimi M. Applying genetic algorithms in determining optimal cropping pattern in different weather conditions in qazvin plain. Iranian journal of water research in agriculture. 2016. 30(3): 317- 331. (In Persian).
 [40]. Jensen M. E. Chapter 1: Water defecits and plant groth. ,New York, USA: In: Plants, Water consumption by agricultural. 1968. 22 P.
Iranian journal of Ecohydrology
Volume 9, Issue 1
April 2022
Pages 227-242

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History

  • Receive Date: 14 September 2021
  • Revise Date: 26 February 2022
  • Accept Date: 26 February 2022

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