Climate information; Drought; Early warning system; Environmental risk; Response capacity; Drought management; Early warning systems; Farming activities; Management strategies; Random sampling method; Smart agricultures; Environmental Engineering; Environmental Chemistry; Waste Management and Disposal; Pollution
Abstract :
[en] Drought is a persistent, sluggish natural disaster in developing countries that has generated a financial burden and an unstable climate. Farmers should adopt early warning systems (EWS) in their strategies for monitoring drought to reduce its serious consequences. However, farmers in developing countries are reluctant to use EWS as their management strategies. Hence, the aim of this study was to investigate the decision of farmers to use climate knowledge through the model of farming activity in Kermanshah Township, Iran. A surveyor questionnaire was used to gather data from 370 wheat farmers using random sampling methods in multi-stage clusters. Results revealed that the decision to use climate information is affected by personal factors, attitude towards climate information, objectives of using climate information, and external/physical farming factors. The result of this study has implications for drought management practitioners. To be specific, the results can aid policymakers to design early alert programs to minimize the risk of drought and thus move from conventional to climate smart agriculture.
Disciplines :
Agriculture & agronomy
Author, co-author :
Sharafi, Lida; Department of Agricultural Extension & Education, Razi University, Kermanshah, Iran
Zarafshani, Kiumars; Department of Agricultural Extension & Education, Razi University, Kermanshah, Iran. Electronic address: zarafshani2000@yahoo.com
Keshavarz, Marzieh; Department of Agriculture, Payame Noor University, Tehran, Iran
Azadi, Hossein ; Université de Liège - ULiège > TERRA Research Centre > Modélisation et développement ; Department of Geography, Ghent University, Ghent, Belgium, Faculty of Environmental Sciences, Czech University of Life Sciences Prague, Prague, Czech Republic
Van Passel, Steven; Department of Engineering Management, University of Antwerp, Antwerp, Belgium
Language :
English
Title :
Farmers' decision to use drought early warning system in developing countries.
Ajzen, I., The theory of planned behavior. Organ. Behav. Hum. Decis. Process. 50 (1991), 179–211.
Alarcon, P., Wieland, B., Mateus, A.L.P., Dewberry, C., Pig farmers’ perceptions, attitudes, influences and management of information in the decision-making process for disease control. Prev. Vet. Med. 116 (2014), 223–242.
Ali, J., Kumar, S., Information and communication technologies (ICTs) and farmers’ decision-making across the agricultural supply chain. Int. J. Inf. Manag. 31:2 (2011), 149–159.
Aliyari, H., Kholghi, M., Zahedi, S., Momeni, M., Providing decision support system in groundwater resources management for the purpose of sustainable development. Journal of Water Supply: Research and Technology - AQUA 67:5 (2018), 423–437.
Ansari, N., Rezaei-Moghaddam, K., Fatemi, M., Experts’ viewpoints of agricultural Jihad Centerstoward the agricultural extension new approach in Fars province. European journal of natural and. Sociol. Sci. 8:3 (2019), 399–410.
Bai, Y., Deng, X., Zhang, Y., Wang, C., Liu, Y., Does climate adaptation of vulnerable households to extreme events benefit livestock production?. J. Clean. Prod. 210 (2019), 358–365.
Basher, R., Global early warning systems for natural hazards: systematic and people-centred. Philos. Trans. R. Soc. A. 364 (2006), 2167–2182.
Buurman, J., Dahm, R., Goedbloed, A., Monitoring and early warning systems for droughrs: lessons from floods, Water Cooperation Initiative Symposium, 17 Octobr 2014, Hanoi, Vietnam, 1–12. 2014.
Byrne, K.A., Silasi-Mansat, C.D., Worthy, D.A., Who chokes under pressure? The big five personality traits and decision-making under pressure. Pers. Individ. Differ. 74 (2015), 22–28.
Chang, F.J., Huang, C.W., Cheng, S.T., Chang, L.S., Conservation of groundwater from over-exploitation—scientific analyses for groundwater resources management. Sci. Total Environ. 598 (2017), 828–838.
Chen, Y., Zhang, J., Zhou, A., et al. Modeling and analysis of mining subsidence disaster chains based on stochastic petri nets. Nat. Hazards 92 (2018), 19–41.
Choularton, R.J., Krishnamurthy, P.K., How accurate is food security early warning?. Evaluation of FEWS NET accuracy in Ethiopia. Food Sec. 11 (2019), 333–344.
Das, P.K., Das, P.K., Midya, S.K., Raj, U., Dadhwal, V.K., 2019. Fore-warning of early season agricultural drought condition over Indian region – a fractional wetness approach. Geocarto International, 35(6).
Davis, F.D., Bagozzi, R.P., Warshav, P.R., User acceptance of computer technology: a comparison of two theoretical models. Manag. Sci. 35:8 (1989), 982–1003.
de Souza Machado, A.A., Horton, A.A., Davis, T., Maaß, S., Microplastics and Their Effects on Soil Function as a Life-supporting System. 2020, The Handbook of Environmental Chemistry. Springer, Berlin, Heidelberg, In.
Ellis-Iversen, J., Cook, A.J., Watson, E., et al. Perceptions, circumstances and motivators that influence implementation of zoonotic control programs on cattle farms. Prev. Vet. Med. 93 (2010), 276–285.
Feng, X., Liu, M., Huo, X., Ma, W., What motivates Farmers’ adaptation to climate change? The case of apple farmers of Shaanxi in China. Sustainability. 9:4 (2017), 1–15.
Gasson, R., Goals and values of farmers. J. Agric. Econ. 24:3 (1973), 521–542.
Gilmor, D.A., Behavioral studies in agriculture: goals, values, and enterprise choice. Ir. J. Agric. Econ. Rural. Sociol. 2 (1986), 19–33.
Grossi, M., 2017. California's Biggest Drought Success Story Came With a High Cost. Water Deeply. Accessed August 3, 2018.
Hirsh, J.B., Morisano, D., Peterson, J.B., Delay discounting: interactions between personality and cognitive ability. J. Res. Pers. 42:6 (2008), 1646–1650.
Horita, F.E.A., de Albuquerque, J.P., Marchezini, V., Understanding the decision-making process in disaster risk monitoring and early-warning: a case study within a control room in Brazil. Int. J. Disast. Risk. Re. 28 (2018), 22–31.
Hou, L., Huang, J., Wang, J., Early warning information, farmers’ perceptions of, and adaptations to drought in China. Clim. Chang. 141 (2017), 197–212.
Hu, Q., PytlikZillig, L., Lynne, G., Tomkins, A., et al. Global semi-arid climate change over last 60 years. Clim. Dyn. 45:3–4 (2016), 1131–1150.
Hurlbert, M.A., Gupta, J., Verrest, H., A comparison of drought instruments and livelihood capitals. Clim. Dev. 11:10 (2019), 863–872.
IPCC., 2014. Summary for policymakers. In: Edenhofer, O., Pichs-Madruga, R., Sokona, Y., Farahani, E., Kadner, S., Seyboth, K., Adler, A., Baum, I., Brunner, S., Eickemeier, P., Kriemann, B., Savolainen, J., Schlömer, S., von Stechow, C., Zwickel, T., and Minx, J.C., Eds.), Climate Change 2014: Mitigation of Climate Change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
Karali, E., Rounsevell, M.D.A., Doherty, R., Integrating the diversity of farmers’ decisions into studies of rural land-use change. Procedia Environ. Sci. 4 (2011), 136–145.
Keshavarz, M., Karami, E., Farmers’ decision making process under drought. J. Arid Environ. 108 (2014), 43–56.
Keshavarz, M., Karami, E., Vanclay, F., The social experience of drought in rural Iran. Land Use Policy 30:1 (2013), 120–129.
Khanian, M., Serpoush, B., Gheitarani, Balance between place attachment and migration based on subjective adaptive capacity in response to climate change: the case of Famenin County in Western Iran. Clim. Dev. 11:1 (2019), 69–82.
Kusunose, Y., Mahmood, R., Imperfect forecasts and decision making in agriculture. Agric. Syst. 146 (2016), 103–110.
Lal, P., Pimentel, D., Soil erosion: a carbon sink or source?. Science 319 (2008), 1040–1041.
Li, X., Yang, Y., Liu, Y., et al. Impacts and effects of government regulation on farmers’ responses to drought: a case study of North China Plain. J. Geogr. Sci. 27 (2017), 1481–1498.
Lillemets, J., Viira, A.H., 2019. Rural development in the common agricultural policy: correlations at regional level. 8th EAAE PhD Workshop, June 10–12, 2019, Uppsala, Sweden 296798, European Association of Agricultural Economists.
Liu, C., Guo, L., Ye, L., et al. A review of advances in China's flash flood early-warning system. Nat. Hazards 92 (2018), 619–634.
Mafi-Gholami, D., Zenner, E.K., Jaafari, A., Ward, R.D., Modeling multi-decadal mangrove leaf area index in response to drought along the semi-arid southern coasts of Iran. Sci. Total Environ. 656 (2019), 1326–1336.
Matere, J., Simpkin, P., Angerer, J., et al. Predictive livestock early warning system (PLEWS): monitoring forage condition and implications for animal production in Kenya. Weather. Clim., 27, 2019.
McCrea, R., Dalgleish, L., Coventry, W., Encouraging use of seasonal climate forecasts by farmers. Int. J. Climatol. 25:8 (2005), 1127–1137.
Mehta, V., Knutson, C.L., Rosenberg, N., et al. Decadal climate information needs of stakeholders for decision support in water and agriculture production sectors: a case study in the Missouri River basin. Weather Clim Soc. 5:1 (2013), 27–42.
Miyan, M.A., Droughts in Asian least developed countries: vulnerability and sustainability. Weather. Clim. 7 (2015), 8–23.
Momeni, M., Zakeri, Z., Esfandiari, M., et al. Comparative analysis of agricultural water pricing between Azarbaijan provinces in Iran and the state of California in the US: a hydro-economic approach. Agric. Water Manag., 233, 2019, 105724.
Nuñez, R., Drought early warning system (EWS) for the Dominican Republic. International Hydroinformatics Conference. March, 11, 2020, 2020.
O'Kane, H., Ferguson, E., Kaler, J., Green, L., Associations between sheep farmer attitudes, beliefs, emotions and personality, and their barriers to uptake of best practice: the example of footrot. Prev. Vet. Med. 139 (2017), 123–133.
Pendergrass, A.G., Meehl, G.A., Pulwarty, R., et al. Flash droughts present a new challenge for subseasonal-to-seasonal prediction. Nat. Clim. Chang. 10 (2020), 191–199.
Pulwarty, R., Sivakumar, M.V.K., Information systems in a changing climate: early warnings and drought risk management. Weather. Clim. 3 (2014), 14–21.
Rehman, F., Muhammad, S., Ashraf, I., et al. Effect of farmers’ socioeconomic characteristics on access to agricultural information: Emprical evidence from Pakistan. J. Anim. Plant Sci. 23:1 (2013), 324–329.
Rembold, F., Meroni, M., et al. ASAP: a new global early warning system to detect anomaly hot spots of agricultural production for food security analysis. Agric. Syst. 168 (2019), 247–257.
Rezaei-Moghaddam, K., Fatemi, M., Strategies for improvement of agricultural extension new approach of Iran. Iran Agricultural Extension and Education Journal, 5(2), 2020.
Rovero, F., Ahumada, J., The tropical ecology, assessment and monitoring (TEAM) network: an early warning system for tropical rain forests. Sci The Tot Environ 574 (2017), 914–923.
Sajjad Kabir, S.M., 2016. Research design. In book: Basic Guidelines for Research: An Introductory Approach for All Disciplines, Edition: First, Chapter: 6, Publisher: Book Zone Publication, Chittagong-4203, Bangladesh, pp.111-169.
Sarstedt, M., Ringle, C. M., and Hair, J. F., 2017. Partial least squares structural equation modeling. Springer international publishing AG 2017, C. Homburg et al. (eds), Handbook of Market Research.
Sayuti, R., Karyadi, W., Yasin, I., Abawi, Y., Factors affecting the use of climate forecasts in agriculture: a case study of Lombok Island, Indonesia, (ed). Australian Centre for International Agricultural Research (ACIAR) Technical Reports No. 59 (2004), 15–21.
Shamano, N., 2010. Investigation Into the Disaster Risk Reduction (DRR) Efforts in Gutu District (Zimbabwe): A Focus on Drought Early Warning Systems. Master dissertation. University of the Free State.
Sharafi, L., Modeling Drought Early Warning System in Kermanshah Township. 2017, Razi University, Iran, Ph. D. dissertation in Agricultural Development.
Sharafi, L., Zarafshani, K., Keshavarz, M., Azadi, H., Van Passel, S., Analyzing the production and information diffusion mechanism of drought early warning system (DEWS) in Kermanshah township. J. Rural Res. 10:4 (2020), 740–753.
Sharafi, L., Zarafshani, K., Keshavarz, M., Azadi, H., Van Passel, S., Drought risk assessment: towards drought early warning system and sustainable environment in Western Iran. Ecol. Indic., 114, 2020, 106276.
Sharifzadeh, M., Zamani, Gh., Karami, E., Some determining factors of weather information use in Farmers’ decision making. Iranian. J. Agric. Econ. Devel. Res. 2-41:4 (2011), 541–555.
Sharifzadeh, M., Zamani, G.H., Khalili, D., Karami, E., Agricultural climate information use: an application of the planned behaviour theory. J. Agr. Sci. Tech-Iran. 14:3 (2012), 479–492.
Su, Y., Yue-qi, Y., Dynamic early warning of regional atmospheric environmental carrying capacity. Sci. Total Environ., 714, 2020.
Taylor, S., Todd, P., Decomposition and crossover effects in the theory of planned behavior: a study of consumer adoption intentions, Int. J. Res. Mark. 12:2 (1995), 137–155.
Tulare County. 2017. Drought Effects Status Updates. Accessed July 2, 2018.
UNISDR, UNISDR Terminology on Disaster Risk Reduction. 2009, Strategy for Disaster Reduction, The United Nations International.
Vyas, S.S., Bhattacharya, B.K., Agricultural drought early warning from geostationary meteorological satellites: concept and demonstration over semi-arid tract in India. Environ. Monit. Assess., 192, 2020, 311.
Wang, J., Yang, Y., Huang, J., Chen, K., Information provision, policy support, and farmers’ adaptive responses against drought: an empirical study in the North China Plain. Ecol. Model. 318 (2015), 275–282.
Wang, L., Zhou, Y., Lei, X., Zhou, Y., Bi, H., Mao, X. Zhong, 2020. Predominant factors of disaster caused by tropical cyclones in South China coast and implications for early warning systems. Sci. Total Environ. 726.
Wei, W., Chen, L., Fu, B., Chen, J., Water erosion response to rainfall and land use in different drought-level years in aloess hilly area of China. Catena 81 (2010), 24–31.
Wicklung, E., and Raum, L., 2006. Early warning systems in the context of disaster risk management. Available at: Http://archiv.rural-development.de/fileadmin/rural-development/volltexte/2006/02/ELR–dt–23-25.pdf.
Wilhite, D. A., and Svoboda, M. D., 2000. Drought early warning systems in the context of drought preparedness and mitigation. Drought Early Warning Systems in the Context of Drought Preparedness and Mitigation, Proceedings of an Expert Group Meeting Held in Lisbon, Portugal, 5–7 September 2000. Geneva, Switzerland: World Meteorological Organization. 1–21.
Wilhite, D.A., Sivakumar, M.V.K., Pulwarty, R., Managing drought risk in a changing climate: the role of national drought policy. Weather. Clim. 3 (2014), 4–13.
Willock, J., Deary, I.J., McGregor, M., et al. Farmers’ attitudes, objectives, behaviors, and personality traits: the Edinburgh study of decision making on farms. J. Vocat. Behav. 54:1 (1999), 5–36.
Zhang, F., Chen, Y., Zhang, J., Guo, E., Wang, R., Li, D., Dynamic drought risk assessment for maize based on crop simulation model and multi-source drought indices. J. Clean. Prod. 233 (2019), 100–114.