Evaluating probability of agricultural drought risk using diffusion theory (Case Study: Shazand, Khomein, and Saveh Plains)

Document Type : Research Article


Department of Environment Science and Engineering, Arak University, Arak, Iran



According to the predictions outlined in global warming models, Iran, especially the plains of the central plateau, has been dealing with increasing temperatures and decreasing rainfall. These changes have had harmful effects on agricultural production and the overall sustainability of agriculture and the environment due to ongoing drought conditions. This study utilizes a model to estimate the risk of agricultural drought based on the principles of information diffusion theory. The goal is to assess the likelihood of agricultural drought occurring in the plains of Shazand, Khomein, and Saveh. By using agricultural data and meteorological information, three main aspects were taken into consideration: the susceptibility of environments prone to disasters, the ability to withstand risk, and the collective exposure to risk. To measure the risk of agricultural drought, three indicators were selected: the vulnerability of the area to drought, the percentage of abnormal rainfall, and the frequency of disaster occurrences. The results of the investigation revealed that the assessments of risk, when viewed from the perspective of disaster-prone environments, hazards, and the population exposed to risk, were significantly elevated. Concerning the susceptibility of disaster-prone environments, the examined plains show a concentrated range between severe and extremely severe sensitivities, with values ranging from 0.6 to 0.9. When considering the precariousness of the risk, these regions are facing a notably high level of vulnerability to drought. In evaluating the overall risk, the incidence of drought-related disasters in these areas exceeds 0.5 on the scale. Consequently, the associated probability of such risks materializing is estimated at intervals of approximately 4.8, 3.2, and 1.2 years for the Shazand, Khomein, and Saveh plains, respectively.


Main Subjects

[1]. Pachauri RK. Intergovernmental panel on climate change (IPCC): Keynote address. Environmental Science and Pollution Research, 2007, 9:436-438.
[2]. Hong ZH, Dihua CA, Heling WA, Yang YA, Runyuan WA, Kai ZH, Yue QI, Funian ZH, Fei CH, Ping YU, Xing WA. Progress and prospect on impact of drought disaster on food security and its countermeasures. Journal of Arid Meteorology. 2023, 41(2):187.
[3]. Potop V, Türkott L, Kožnarová V, Možný M. Drought episodes in the Czech Republic and their potential effects in agriculture. Theoretical and applied climatology. 2010, 99:373-88.
[4]. Luo D, Ye L, Sun D. Risk evaluation of agricultural drought disaster using a grey cloud clustering model in Henan province, China. International Journal of Disaster Risk Reduction. 2020, 1;49:101759.
[5]. Xu K, Xu X, Li A, Yang D. Assessing agricultural drought disaster risk in Chengde city using stochastic method. Transactions of the Chinese Society of Agricultural Engineering. 2013, 29(14):139-46.
[6]. Ailian CH, Sijian ZH, Yuxia ZH, Wei SU. Application Scenarios and Research Progress of Remote Sensing Technology in Plant Income Insurance. Smart Agriculture. 2022, 30;4(1):57.
[7]. Hirabayashi Y, Mahendran R, Koirala S, Konoshima L, Yamazaki D, Watanabe S, Kim H, Kanae S. Global flood risk under climate change. Nature climate change. 2013 Sep;3(9):816-21.
[8]. Ward PJ, Jongman B, Weiland FS, Bouwman A, van Beek R, Bierkens MF, Ligtvoet W, Winsemius HC. Assessing flood risk at the global scale: model setup, results, and sensitivity. Environmental research letters. 2013, 8(4):044019.
[9]. Ward PJ, Jongman B, Kummu M, Dettinger MD, Sperna Weiland FC, Winsemius HC. Strong influence of El Niño Southern Oscillation on flood risk around the world. Proceedings of the National Academy of Sciences. 2014,111(44):15659-64.
[10]. Peduzzi P, Chatenoux B, Dao H, De Bono A, Herold C, Kossin J, Mouton F, Nordbeck O. Global trends in tropical cyclone risk. Nature climate change. 2012, 2(4):289-94.
[11]. Garschagen M, Doshi D, Reith J, Hagenlocher M. Global patterns of disaster and climate risk—an analysis of the consistency of leading index-based assessments and their results. Climatic Change. 2021, 169(1-2):11.
[12]. Meza I, Siebert S, Döll P, Kusche J, Herbert C, Eyshi Rezaei E, Nouri H, Gerdener H, Popat E, Frischen J, Naumann G. Global-scale drought risk assessment for agricultural systems. Natural Hazards and Earth System Sciences. 2020, 20(2):695-712.
[13]. Koks EE, Rozenberg J, Zorn C, Tariverdi M, Vousdoukas M, Fraser SA, Hall JW, Hallegatte S. A global multi-hazard risk analysis of road and railway infrastructure assets. Nature communications. 2019, 10(1):2677.
[14]. Deubelli TM, Mechler R. Perspectives on transformational change in climate risk management and adaptation. Environmental Research Letters. 2021, 16(5):053002.
[15]. Yuan X, Wood EF. Multimodel seasonal forecasting of global drought onset. Geophysical Research Letters. 2013, 40(18):4900-5.
[16]. Geng G, Wu J, Wang Q, Lei T, He B, Li X, Mo X, Luo H, Zhou H, Liu D. Agricultural drought hazard analysis during 1980–2008: a global perspective. International Journal of Climatology. 2016, 36(1):389-99.
[17]. Spinoni J, Barbosa P, Bucchignani E, Cassano J, Cavazos T, Christensen JH, Christensen OB, Coppola E, Evans J, Geyer B, Giorgi F. Future global meteorological drought hot spots: a study based on CORDEX data. Journal of Climate. 2020, 33(9):3635-61.
[18]. Hao Z, AghaKouchak A, Nakhjiri N, Farahmand A. Global integrated drought monitoring and prediction system. Scientific data. 2014, 1(1):1-0.
[19]. Carrão H, Naumann G, Barbosa P. Global projections of drought hazard in a warming climate: a prime for disaster risk management. Climate dynamics. 2018, 50(5-6):2137-55.
[20]. Vogt JV, Naumann G, Masante D, Spinoni J, Cammalleri C, Erian W, Pischke F, Pulwarty R, Barbosa P. Drought risk assessment and management: A conceptual framework.
[21]. Pachauri RK, Allen MR, Barros VR, Broome J, Cramer W, Christ R, Church JA, Clarke L, Dahe Q, Dasgupta P, Dubash NK. Climate change 2014: synthesis report. Contribution of Working Groups I, II and III to the fifth assessment report of the Intergovernmental Panel on Climate Change. Ipcc; 2014.
[22]. Carrão H, Naumann G, Barbosa P. Mapping global patterns of drought risk: An empirical framework based on sub-national estimates of hazard, exposure and vulnerability. Global Environmental Change. 2016, 39:108-24.
[23]. Hagenlocher M, Meza I, Anderson CC, Min A, Renaud FG, Walz Y, Siebert S, Sebesvari Z. Drought vulnerability and risk assessments: state of the art, persistent gaps, and research agenda. Environmental Research Letters. 2019, 14(8):083002.
[24]. Kloos J, Renaud FG. Overview of ecosystem-based approaches to drought risk reduction targeting small-scale farmers in Sub-Saharan Africa. Ecosystem-Based Disaster Risk Reduction and Adaptation in Practice. 2016:199-226.
[25]. Heydari F, Sharafi S, Mohammadi Ghaleni M. The relationship between drought indicators and greenhouse gas emissions in Iran's agricultural sector. Iranian Journal of Irrigation & Drainage, 2023, 17(2): 261-275 [Persian].
[26]. Bockstaller C, Guichard L, Makowski D, Aveline A, Girardin P, Plantureux S. Agri-environmental indicators to assess cropping and farming systems. A review. Agronomy for sustainable development. 2008, 8:139-49.
[27]. Mancinelli R, Marinari S, Di Felice V, Savin MC, Campiglia E. Soil property, CO2 emission and aridity index as agroecological indicators to assess the mineralization of cover crop green manure in a Mediterranean environment. Ecological indicators. 2013, 34:31-40.
[28]. Zhang L, Qin R, Chai N, Wei H, Yang Y, Wang Y, Li FM, Zhang F. Optimum fertilizer application rate to ensure yield and decrease greenhouse gas emissions in rain-fed agriculture system of the Loess Plateau. Science of The Total Environment. 2022, 823:153762.
[29]. Guan X, Zang Y, Meng Y, Liu Y, Lv H, Yan D. Study on spatiotemporal distribution characteristics of flood and drought disaster impacts on agriculture in China. International Journal of Disaster Risk Reduction. 2021, 64:102504.
[30]. Sharafi S, Mohammadi Ghaleni M. Enhancing drought monitoring and prediction in diverse climates by using composite drought indices. Stochastic Environmental Research and Risk Assessment, 2023, 37(9): 41-55.
[31]. Sharafi S. Predicting Iran’s future agro-climate variability and coherence using zonation? based PCA. Italian Journal of Agrometeorology. 2022(2):17-30.
[32]. Sharafi S, Kazemi A, Amiri Z. Estimating energy consumption and GHG emissions in crop production: A machine learning approach. Journal of Cleaner Production. 2023, 408:137242.
[33]. Sharafi S, Nahvinia MJ, Salehi F. Assessing water footprints (WFPs) of agricultural products across arid regions: insights and implications for sustainable farming. Journal of Water, 2023, 15(3): 14-29.
[34]. Sharafi S, Nahvinia MJ, Salehi Arjmand H, Akbari, M. Determining the pattern of optimal cultivation of agricultural products in the plains of Central Province (Case study: Shazand, Saveh and Khomein plains). Final Report. 2022; 479 pp.
[35]. Liu Y, Liu L, Xu D, Zhang S. Risk assessment of flood and drought in major grain-producing areas based on information diffusion theory. Transactions of the Chinese Society of Agricultural Engineering. 2010, 26(8):1-7.
[36]. Huang CF, Zhang JX, Liu J. Applications of fuzzy information optimization technology. Information and Control-Shenyang, 2004, 33(1):61-6.
[37]. Shi P, Ye T, Wang Y, Zhou T, Xu W, Du J, Wang JA, Li N, Huang C, Liu L, Chen B. Disaster risk science: A geographical perspective and a research framework. International Journal of Disaster Risk Science. 2020, 11:426-40.
[38]. Pei W, Fu Q, Liu D, Li T, Cheng K, Cui S. A novel method for agricultural drought risk assessment. Water Resources Management. 2019, 3:2033-47.
[39]. Roy P, Pal SC, Chakrabortty R, Chowdhuri I, Saha A, Shit M. Climate change and groundwater overdraft impacts on agricultural drought in India: Vulnerability assessment, food security measures and policy recommendation. Science of The Total Environment. 2022, 849:157850.
[40]. Marengo JA, Galdos MV, Challinor A, Cunha AP, Marin FR, Vianna MD, Alvala RC, Alves LM, Moraes OL, Bender F. Drought in Northeast Brazil: A review of agricultural and policy adaptation options for food security. Climate Resilience and Sustainability. 2022, 1(1):e17.
[41]. Savari M, Damaneh HE, Damaneh HE. Drought vulnerability assessment: Solution for risk alleviation and drought management among Iranian farmers. International Journal of Disaster Risk Reduction. 2022, 67:102654.
[42]. FAOSTAT. Food and Agriculture Organization of the United Nations. Rome. 2019.
[43]. Awan AB, Khan MN, Zubair M, Bellos E. Commercial parabolic trough CSP plants: Research trends and technological advancements. Solar Energy. 2020, 211:1422-58.
[44]. Shahnazari A, Liu F, Andersen MN, Jacobsen SE, Jensen CR. Effects of partial root-zone drying on yield, tuber size and water use efficiency in potato under field conditions. Field Crops Research. 2007, 100(1):117-24.
[45]. Luedeling E, Kunz A, Blanke MM. Identification of chilling and heat requirements of cherry trees—a statistical approach. International Journal of Biometeorology. 2013, 57:679-89.
[46]. Hernandez EA, Uddameri V. Standardized precipitation evaporation index (SPEI)-based drought assessment in semi-arid south Texas. Environmental Earth Sciences. 2014, 471:2491-501.
[47]. Sharafi S, Ghaleni MM. Spatial assessment of drought features over different climates and seasons across Iran. Theoretical and Applied Climatology. 2022, 1:1-7.
[48]. Nam WH, Hayes MJ, Svoboda MD, Tadesse T, Wilhite DA. Drought hazard assessment in the context of climate change for South Korea. Agricultural Water Management. 2015, 160:106-17.
[49]. Kim H, Park J, Yoo J, Kim TW. Assessment of drought hazard, vulnerability, and risk: A case study for administrative districts in South Korea. Journal of Hydro-environment Research. 2015, 9(1):28-35.
[50]. Murthy CS, Laxman B, Sai MS. Geospatial analysis of agricultural drought vulnerability using a composite index based on exposure, sensitivity and adaptive capacity. International journal of disaster risk reduction. 2015, 12:163-71.
[51]. Zhang D, Wang G, Zhou H. Assessment on agricultural drought risk based on variable fuzzy sets model. Chinese Geographical Science. 2011, 21:167-75.
[52]. Hoque MA, Pradhan B, Ahmed N, Sohel MS. Agricultural drought risk assessment of Northern New South Wales, Australia using geospatial techniques. Science of the Total Environment. 2021 Feb 20;756:143600.
[53]. Wang Z, Huang L, Yin L, Wang Z, Zheng D. Evaluation of sustainable and analysis of influencing factors for agriculture sector: Evidence from Jiangsu Province, China. Frontiers in Environmental Science. 2022, 10:836002.
[54]. Mohammed S, Alsafadi K, Enaruvbe GO, Bashir B, Elbeltagi A, Széles A, Alsalman A, Harsanyi E. Assessing the impacts of agricultural drought (SPI/SPEI) on maize and wheat yields across Hungary. Scientific Reports. 2022, 12(1):8838.
[55]. Sharafi S, Ghaleni MM, Sadeghi S. Spatial and temporal analysis of drought in various climates across Iran using the Standardized Precipitation Index (SPI). Arabian Journal of Geosciences. 2022, 15(14):1279.
[56]. Tabari H, Nikbakht J, Hosseinzadeh Talaee P. Hydrological drought assessment in Northwestern Iran based on streamflow drought index (SDI). Water resources management. 2013, 27:137-51.
[57]. Manzoni S, Porporato A. Soil carbon and nitrogen mineralization: Theory and models across scales. Soil Biology and Biochemistry. 2009, 41(7):1355-79.
[58]. Kabba BS, Aulakh MS. Climatic conditions and crop‐residue quality differentially affect N, P, and S mineralization in soils with contrasting P status. Journal of Plant Nutrition and soil science. 2004, 167(5):596-601.
[59]. Naumann G, Carrão H, Barbosa P. Indicators of social vulnerability to drought. Chapter 6 In Drought: Science and Policy, Part II: Vulnerability, risk and policy, 111-125.
[60]. Hagenlocher M, Meza I, Anderson CC, Min A, Renaud FG, Walz Y, Siebert S, Sebesvari Z. Drought vulnerability and risk assessments: state of the art, persistent gaps, and research agenda. Environmental Research Letters. 2019, 14(8):083002.
[61]. Yang P, Zhang S, Xia J, Chen Y, Zhang Y, Cai W, Wang W, Wang H, Luo X, Chen X. Risk assessment of water resource shortages in the Aksu River basin of northwest China under climate change. Journal of Environmental Management. 2022, 305:114394.
[62]. Yue GU, Jia-hong LI, Qi-jin HE, Ruo-chen LI, Xin-yuan MI, Zhi-heng QI. Risk probability of heat injury during summer maize flowering period in North China Plain based on information diffusion theory. Chinese Journal of Agrometeorology. 2021, 42(07):606.