Biobjective Optimization for Efficient Irrigation under Fuzzy Uncertainty
Publication: Journal of Irrigation and Drainage Engineering
Volume 142, Issue 8
Abstract
A biobjective programming model is developed with fuzzy inputs in response to the complexity of conflicting objectives and uncertainties in irrigation water allocation systems. The model is capable of increasing agricultural water productivity and meanwhile reducing irrigation water shortage, compromising the concerns of both agricultural decision makers and farmers. Moreover, the developed model adequately considers the fuzzy uncertainties in parameters, constraints, and objective functions. The potential of the developed model is shown by applying to a real case study in northwest China. Results show alternative decisions for irrigation water allocation under different flow levels, and indicate that the effectiveness of the trading program is explicitly affected by uncertainties expressed as fuzziness. Comparison with a commonly used model for irrigation water allocation demonstrates the feasibility and applicability of the developed model, which is helpful for the development of water-saving high-efficiency agriculture.
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Acknowledgments
This research was supported by the Ph.D. Programs Foundation of Ministry of Education of China (No. 20130008110021), National High Technology Research and Development Program of China (863 Program) (No. 2013AA102904), and International Science & Technology Cooperation Program of China (2013DFG70990).
References
Allen, R. G., Pereira, L. A., and Smith, M. (1998). “Crop evapotranspiration—Gudelines for computing crop water requirements.”, Food and Agricultural Organization of the United Nations (FAO), Rome.
Ashofteh, P-S., Haddad, O. B., Akbari-Alashti, H., and Mariño, A. M. (2015). “Determination of irrigation allocation policy under climate change by genetic programming.” J. Irrig. Drain. Eng., 141(4), 04014059.
Cao, X. C., Wu, P. T., Wang, Y. B., and Zhao, X. N. (2014). “Temporal and spatial variation and correlativity of water productivity indexes in irrigated land of China.” Adv. Water Sci., 25(2), 268–274 (in Chinese with English abstract).
Etedali, H. R., Liaghat, A., Parsinejad, M., Tavakkoli, A. R., Haddad, O. B., Etedail, M. R. (2013). “Water allocation optimization for supplementary irrigation in rained lands to increase total income case study: Upstream Karkheh River basin.” Irrig. Drain., 62(1), 74–83.
Fasakhodi, A. A., Nouri, S. H., and Amini, M. (2010). “Water resources sustainability and optimal cropping pattern in farming systems: A multi-objective fractional goal programming approach.” Water Resour. Manage., 24(15), 4639–4657.
Griffin, R. C. (2006). Water resources economics: The analysis of scarcity, policies, and projects, MIT Press Books, Cambridge, MA.
Guo, P., Chen, X. L., Li, M., and Li, J. B. (2014). “Fuzzy chance-constrained linear fractional programming approach for optimal water allocation.” Stochastic Environ. Res. Risk Assess., 28(6), 1601–1612.
Han, Y., Huang, Y.-F., Wang, G.-Q., and Maqsood, I. (2011). “A multi-objective linear programming model with interval parameters for water resources allocation in Dalian City.” Water Resour. Manage., 25(2), 449–463.
Huang, Y., Li, Y. P., Chen, X., and Ma, Y. G. (2012). “Optimization of the irrigation water resources for agricultural sustainability in Tarim River Basin, China.” Agric. Water Manage., 107, 74–85.
Kang, S. Z., and Cai, H. J. (1996). Agricultural water management, China Agricultural Press, Beijing (in Chinese).
Lalehzari, R., Nasab, S. B., Moazed, H., and Haghighi, A. (2015). “Multiobjective management of water allocation to sustainable irrigation planning and optimal cropping pattern.” J. Irrig. Drain. Eng., 05015008.
Li, M., Guo, P. (2014). “A multi-objective optimal allocation model for irrigation water resources multiple uncertainties.” Appl. Math. Modell., 38(19–20), 4897–4911.
Li, Z., Huang, G. H., Zhang, Y. M., and Li, Y. P. (2013). “Inexact two-stage stochastic credibility constrained programming for water quality management.” Resour. Conserv. Recycl., 73, 122–132.
Liu, J., Li, Y. P., and Huang, G. H. (2013). “Mathematical modeling for water quality management under interval and fuzzy uncertainties.” J. Appl. Math., 14.
Liu, S. Q., Liu, J. X., and Zhu, X. C. (2010). “Discussion on method for evaluation of field water-saving level.” Water Resour. Hydropower Eng., 41(2), 60–64 (in Chinese with English abstract).
Miao, G. Y., Huang, W. W., Li, Y. P., and Yang, Z. F. (2014). “Planning water resources systems under uncertainty using an interval-fuzzy de novo programming method.” J. Environ. Inform., 24(1), 11–23.
Morankar, D. V., Raju, S. K., and Kumar, D. N. (2013). “Integrated sustainable irrigation planning with multiobjective fuzzy optimization approach.” Water Resour. Manage., 27(11), 3981–4004.
Norry, H., Liaghat, A., Parsinejad, M, and Haddad, O. (2012). “Optimizing irrigation water allocation and multicrop planning using discrete PSO algorithm.” J. Irrig. Drain. Eng., 437–444.
Parsinejad, M., Yazdi, A. B., Araghinejad, S., Nejadhashemi, A. P., and Tabrizi, M. S. (2013). “Optimal water allocation in irrigation networks based on real time climate data.” Agric. Water Manage., 117(31), 1–8.
Perera, K. C., Western, A. W., Nawarathna, B., and George, B. (2014). “Forecasting daily reference evapotranspiration for Australia using numerical weather prediction outputs.” Agric. Forest Meteorol., 194(15), 50–63.
Raju, K. S., and Kumar, D. N. (2000). “Irrigation planning of SRI RAM SAGAR project using multi objective fuzzy linear programming.” ISH J. Hydraul. Eng., 6(1), 55–63.
Regulwar, D. G., and Gurav, J. B. (2011). “Irrigation planning under uncertainty—A multi objective fuzzy linear programming approach.” Water Resour. Manage., 25(5), 1387–1416.
Sahoo, B., Lohani, A. K., and Sahu, R. K. (2006). “Fuzzy multiobjective and linear programming based management models for optimal land-water-crop system planning.” Water Resour. Manage., 20(6), 931–948.
Sasikumar, K., and Mujumdar, P. P. (1998). “Fuzzy optimization model for water quality management of a river system.” J. Water Resour. Plann. Manage., 79–88.
Singh, A. (2012). “Optimal allocation of resources for the maximization of net agricultural return.” J. Irrig. Drain. Eng., 830–836.
Singh, A. (2014). “Irrigation planning and management through optimization modelling.” Water Resour. Manage., 28(1), 1–14.
Tanaka, H., and Lee, H. (1998). “Interval regression analysis by quadratic programming approach.” IEEE Trans. Fuzzy Syst., 6(4), 473–481.
Xu, T. Y., and Qin, X. S. (2014). “Integrating decision analysis with fuzzy programming: Application in urban water distribution system operation.” J. Water Resour. Plann. Manage., 638–648.
Xu, Y., Huang, G. H., Cheng, G. H., Liu, Y., and Li, Y. F. (2014). “A two-stage fuzzy chance-constrained model for solid waste allocation planning.” J. Environ. Inform., 24(2), 101–110.
Yang, G. Q., and Guo, P. (2015). “Optimization of the irrigation water resources for Shijin irrigation district in north China.” Agric. Water Manage., 158, 82–98.
Zhan, D. J., and Ye, S. Z. (2000). Engineering hydrology, China Water & Power Press, Beijing.
Zhang, X. D., Huang, G. H., and Nie, X. H. (2011). “Possibilistic stochastic water management model for agricultural nonpoint source pollution.” J. Water Resour. Plann. Manage., 101–112.
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© 2016 American Society of Civil Engineers.
History
Received: Nov 23, 2015
Accepted: Jan 26, 2016
Published online: Apr 7, 2016
Published in print: Aug 1, 2016
Discussion open until: Sep 7, 2016
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