Role of Knowledge in Water Crisis Management: A Bayesian Network Model Approach

Document Type : Research Paper

Authors

1 MSc Graduated, Department of Agricultural Economics, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman, Iran.

2 Professor, Department of Agricultural Economics, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman, Iran.

3 Assistant Professor, Department of Agricultural Economics, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman, Iran

4 Assistant Professor of Agricultural Economics, Faulty of Agricultural, University of Jiroft, Jiroft, Iran

Abstract

Water is one of the critical natural resources in the world and one of the scarce inputs of the agriculture sector in arid and semi-arid areas, including Iran. Consecutive droughts, lower groundwater levels, and lower water quality are among the concerns of farmers and policymakers in Iran. Therefore, the impacts of various factors, including the knowledge-based economy index, on the water crisis in Iran were investigated. In the present study, the Bayesian Network has been applied for modeling water crisis management in Iran. Therefore, key factors related to water crisis management were identified. The U.N. indicator was used to assess the water crisis. The composite index of the knowledge-based economy was calculated using the Knowledge Assessment Methodology. The results of the U.N. indicator indicated that Iran is in a state of a severe water crisis. The modeling results showed that advances in the knowledge-based economy index could alleviate the water crisis. Also, increased economic growth can exacerbate the water crisis. Sensitivity analysis showed that drought has the most significant impact on the water crisis in Iran. Therefore, planning and policymaking to advance the various components of the knowledge-based economy and moving towards sustainable development can help manage the water crisis in Iran.

Keywords

References

Abbasi, A., Khalili, K., Behmanesh, J., and Shirzad, A. 2019. Drought monitoring and prediction using SPEI index and gene expression programming model in the west of Urmia Lake. Theoretical and Applied Climatology. 138(1-2), 553-567.
Abbasi, F., Abbasi, N., and Tavakoli, A.R. 2017. Water Productivity in Agriculture Sector: Challenges and Prospects. Journal of Water and Sustainable Development. 4(1), 141-144 (In Persian).
Afzal, M.N.I., and Lawrey, R. 2012. Investigating World Bank knowledge assessment methodology (KAM) using data envelopment analysis (DEA): a study in the ASEAN region. Research Journal of Science and IT Management. 1, 33-38.
Aghapour, M., Yazdani, S., and Rafeei, H. 2014. Effective Factors on Pressurized Irrigation Acceptance in Shosh, Andymeshk and Dezful Province. Iranian Journal of Agricultural Economics and Development Research. 44(4), 603-612 (In Persian).  
Ali, A., Rahut, D.B., and Behera, B. 2016. Factors influencing farmers' adoption of energy-based water pumps and impacts on crop productivity and household income in Pakistan. Renewable and Sustainable Energy Reviews. 54, 48-57.
AQUASTAT. 2004. FAO’s Global Water Information System Website. AQUASTAT. http://www.fao.org/nr/water/aquastat/data/query/results.html.
AQUASTAT. 2015. FAO’s Global Water Information System Website. AQUASTAT. http://www.fao.org/nr/water/aquastat/data/query/index.html?lang=en.
AQUASTAT. 2016. FAO’s Global Water Information System Website. AQUASTAT. http://www.fao.org/nr/water/aquastat/data/query/results.html.
Arnaldo Valdés, R., Liang Cheng, S., Gómez Comendador, V., and Sáez Nieto, F. 2018. Application of Bayesian Networks and Information Theory to Estimate the Occurrence of Mid-Air Collisions Based on Accident Precursors. Entropy. 20, 969.
Asadzadeh, A., Mirani, N., Ghazi Khani, F., Esmail Darjani, N., and Honardoust, A. 2017. Investigating the role of employment and education of women on economic growth in Iran: Gravitational search algorithm and Firefly algorithm approach. Women in Development & Politics. 15(3), 359-381 (In Persian).
Ashofteh, A., and Vojdanifard, M. 2015. The possibility of exploitation and utilization of rain water for irrigation in greenhouses Khorasan Razavi. Iranian Journal of Rainwater Catchment Systems. 6, 15-22 (In Persian).
Azizi, F., and Moradi, M. 2018. Calculating the Index and Sub-Indices of Knowledge-Based Economy for Iran (1996- 2014). Journal of Economic Research and Policies. 85, 243-270 (In Persian).
Babran, S., and Honarbakhsh, N. 2008. Water Crisis in in Iran and the World. Scientific Research Journal of Rahbord. 48, 193-212 (In Persian).
Bakhshi Dastjerdi, R.,and Khaki Najafabadi, N. 2011. Examining the Effect of Population on Economic Growth Using Optimal Growth Theory an Application of Genetic Algorithm Iranian Economy (1971-2006). Journal of Economic Research. 94, 1-22 (In Persian).  
Baumann, J., and Kritikos, A.S. 2016. The link between R&D, innovation and productivity: Are micro firms different? Research Policy. 45, 1263-1274 (In Persian).
Bayat, M.A., and Babazadeh, H. 2014. Evaluation of Water Use Productivity Indicators in the Main Agricultural Products of Iran. Journal of Water Sciences Research. 6, 17-29.
Benito, M., and Romera, R. 2011. Improving quality assessment of composite indicators in university rankings: a case study of French and German universities of excellence. Statistics and Econometrics Series. 15, 11-20.
Blitzstein, J.K., and  Hwang, J. 2014. Introduction to probability. Chapman and Hall/CRC.
Craig, C., Feng, S., Gilbertz, S. 2019. Water crisis, drought, and climate change in the southeast United States. Land Use Policy. 88, 104-110.
DeVol, R.C., Klowden, K., and Yeo, B. 2011. State Technology and Science Index 2010: Enduring Lessons for the Intangible Economy. Milken Institute. www.milkeninstitute.org.
Duarte, R., Pinilla, V., and Serrano, A. 2013. Is there an environmental Kuznets curve for water use? A panel smooth transition regression approach. Economic Modelling. 31, 518-527.
Ehsani, M., and Khaledy, H. 2003. Water productivity in agriculture. Iranian National Committee on Irrigation and Drainage (IRNCID) Press (In Persian).
Finne, H., Day, A., Piccaluga, A., Spithoven, A., Walter, P., and Wellen, D. 2011. A Composite Indicator for Knowledge Transfer. Report from the European Commission's Expert Group on Knowledge Transfer Indicators.
Fu, X., Mohnen, P., and Zanello, G. 2018. Innovation and productivity in formal and informal firms in Ghana. Technological Forecasting and Social Change. 131, 315-325.
Ghobadi, S., and Komaijani, A. 2010. Explain the Relationship between Monetary Policy-Currency and Government Debt and its Impact on Inflation and Economic Growth in Iran. Journal of International Economics Studies. 37, 1-21 (In Persian).
Gholi Khani Farahani, N., Hosseini, M., and Najafabadi, M. 2013. Investigating Factors Affecting Adoption of Innovations Related to Advanced Irrigation Systems by Farmers in the Karaj Township. Journal of Agricultural Extension and Education Research. 6(2), 37-48 (In Persian).
Gorji, E., and Alipourian, M. 2011. The Knowledge Economy and the Knowledge Assessment Methodology. Iranian Economic Review. 15(29), 43-72 (In Persian).
Haji-Rahimi, M., Torkmani, J. 2003. Investigating the Role of Agricultural Sector Growth in Iranian Economic Growth Using Path Analysis Method. Agricultural Economics and Development. 11(41-42), 71-89 (In Persian).  
Jalalinasab, M., Motiee, N., and Sadafi Abkenar, S. 2014. The water crisis and its social and economic impacts on agriculture. 2th National Conference on Agriculture Engineering and Management. Environment and Sustainable Natural Resources, Tehran, Iran (In Persian).
Kanpinit, K. 2008. Composite indicators for educational quality management for a master's degree program in educational administration in private higher education institutions in Thailand. Dissertation, Victoria University.
Karimi, M., and Jolaini, M. 2017. Evaluation of Agricultural Water Productivity Indices in Major Field Crops in Mashhad Plain. Water and Sustainable Development. 4(1), 133-138 (In Persian).
Kariminazar, M., Moghaddam, A.R., and Mosaedi, A. 2010. Investigation of Climatic Factors Affecting Occurrence of Drought (Case Study: Zabol Region). Journal of Water and Soil Conservation (Journal of Agricultural Science and Natural Resources). 17(1), 145-158 (In Persian).
Kavakebi, G.H., Mousavi Baygi, M., Mosaedi, A., and Jabbari Nobaghi, M. 2015. Determining of most Effective Factors on drought Using of Panel Data Analyze (Khorasan Razavi Province). Journal of Water and Soil (Agricultural Science and Technology). 28(6), 1298-1310 (In Persian).
Keshavarz, A., and Dehghanisanije, H. 2012. Water productivity index and solutions for future agricultural activities in Iran. Economic Strategy. 1(1), 199-233 (In Persian).
Kharazmi, A., and Dehghani Tafti, A., Mashal, M., Allahdadi, A. 2011. Investigating the water crisis in Iran from the perspective of sustainable development indicators. 1th First National Conference on Strategies for Achieving Sustainable Agriculture, Khuzestan University, Iran (In Persian).
Koohi, S., Azizian, A., and Brocca, L. 2021. Spatiotemporal drought monitoring using bottom-up precipitation dataset (SM2RAIN-ASCAT) over different regions of Iran. Science of The Total Environment. 779, 146535.
Koski, T., and Noble, J. 2011. Bayesian networks: an introduction. vol 924. John Wiley & Sons.
Kurt, S., and Kurt, Ü. 2015. Innovation and labour productivity in BRICS countries: panel causality and co-integration. Procedia-Social and Behavioral Sciences. 195, 1295-1302.
Lam, P-L., Lam, T. 2005. Total factor productivity measures for Hong Kong telephone. Telecommunications Policy. 29(1), 53-68.
Mamitimin, Y., Feike, T., and Doluschitz, R. 2015. Bayesian network modeling to improve water pricing practices in northwest China. Water. 7(10), 5617-5637.
Mitchell, T.M. 1997. Machine Learning. McGraw-Hill.
Mohammadzadeh Asl, N., Seifi Pour, R., and Mehrabian, A. 2017. The Impact of the Return of Research and Development on Economic Growth (Using Regression Quintiles Model). Journal of Economics and Business Research. 8(15), 1-14 (In Persian).
Mokhtari, A., Noory, H., Vazifedoust, M., Palouj, M., Bakhtiari, A., Barikani, E., Afrooz, R.A., Fereydooni, F., Naeni, A.S., Pourshakouri, F., and Badiehneshin, A. 2019. Evaluation of single crop coefficient curves derived from Landsat satellite images for major crops in Iran. Agricultural Water Management. 218, 234-249.
Morris, D.M. 2018. Innovation and productivity among heterogeneous firms. Research Policy. 47(10), 1918-1932.
Murias, P., de Miguel, J.C., and Rodríguez, D. 2008. A composite indicator for university quality assessment: The case of Spanish higher education system. Social Indicators Research. 89(1), 129-146.
Nepomilueva, D. 2017. Water scarcity indexes: water availability to satisfy human needs. Thesis, University of Applied Sciences.
Pearl, J. 1988. Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann Publishers Inc.
Plan and Budget Organization. 2017. https://www.mporg.ir/FileSystem/View/File.aspx? FileId=f4afa150-ee8b-4237-b169-f16f8b2c532b (In Persian).
Popov, E.V., and Kochetkov, D.M. 2019. Developing the Regional Knowledge Economy Index: a Case of Russian Regions. Journal of the Knowledge Economy. 10(4), 1860-1878.
Rosegrant, M.W., Cai, X., and Cline, S.A. 2002. World water and food to 2025: dealing with Scarcity. International Food Policy Research Institute, Washington, D.C.
Rosegrant, M.W., Ringler, C., and Zhu, T. 2009. Water for agriculture: maintaining food security under growing scarcity. Annual Review of Environment and Resources. 34, 205-222.
Roson, R., and Damania, R. 2016. Simulating the macroeconomic impact of future water scarcity: An assessment of alternative scenarios University Ca'Foscari of Venice, Department of Economics Research Paper Series, No 7.
Surendran, U., Anagha, B., Raja, P., Kumar V., Rajan, K., and Jayakumar, M. 2019. Analysis of Drought from Humid, Semi-Arid and Arid Regions of India Using DrinC Model with Different Drought Indices. Water Resources Management. 33(4), 1521-1540.
Taheri, M., Emadzadeh, M., Gholizadeh, M., Tajrishi, M., Ahmadi, M., and Moradi, M. 2019. Investigating the temporal and spatial variations of water consumption in Urmia Lake River Basin considering the climate and anthropogenic effects on the agriculture in the basin. Agricultural Water Management. 213, 782-791.
Xue, J., and Ren, L. 2016. Evaluation of crop water productivity under sprinkler irrigation regime using a distributed agro-hydrological model in an irrigation district of China. Agricultural Water Management. 178, 350-365.
Zhang, F., Guo, S., Liu, X., Wang, Y., Engel, B.A., and Guo, P. 2020. Towards sustainable water management in an arid agricultural region: A multi-level multi-objective stochastic approach. Agricultural Systems. 182, 102848.
Environmental Resources Research
Volume 9, Issue 2
July 2021
Pages 253-266

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