Have a personal or library account? Click to login

Optimization in Water Resources At Dry Weather Conditions Before and After the Dam Failure By Using Dummy Variable Regression Approach

Open Access
|May 2021

References

  1. Alok, K.P., 2014. Measuring Energy Intensity and Elasticity in India, A DummyVariablea Approach for Unit LevelHouseh. Jindal Journal of Business Research, 3(1&2), pp.77-92.10.1177/2278682116647602
  2. Ashofteh, P.S., Rajaee, T., Golfam, P., 2017. Assessment of Water Resources Development Projects under Conditions of Climate Change Using Efficiency Indexes (EIs). Water Resour Manage, 31, pp.3723-3744.10.1007/s11269-017-1701-y
  3. Christer, N., Catherine, A., Reidy, M.D., 2005. Fragmentation and Flow Regulation of the World’s Large River Systems. Science, 308, pp.405-407.www.sciencemag.org (15 April 2005).10.1126/science.1107887
  4. Christina, T.,Susan, R., 2016. Planning and implementing small dam removals: lessons learned from dam removals across the eastern United States. Water Resource Managment, 2, pp.489–493.10.1007/s40899-016-0062-7
  5. Doorenbos, J., KASSAN, A. H.,1979. Yield response to water. Roma, FAO. 193p.
  6. English, M.J., NUSS, G.S., 1982. Designing for deficit irrigation.Journal of the Irrigation and Drainage Engineering, 08(02), pp91-106.10.1061/JRCEA4.0001386
  7. English, M.J., NUSS, G.S., 1982. Designing for deficit irrigation.Journal of the Irrigation and Drainage Engineering, 08(02), pp91-106.10.1061/JRCEA4.0001386
  8. Frizzone, R.D., Coelho, D., Dourado, N., 1997. Linear Programming Model to Optimize the Water Resource Use in. Irrigation Projects:an Application to the Senator Nilo Coelho. Sci agric Piracicaba, 54, pp.136-148.10.1590/S0103-90161997000300016
  9. Ghahraman, B., Sepaskhah, A.R., 2004. Linear and Non linear optimization model for allocation of limited water supply.Irrig Darin Jornal, 53(3), pp39-34.10.1002/ird.108
  10. Hargreaves, G.H., Samani, Z.A., 1984. Economics considerations on deficit irrigation.Journal of the Irrigation and Drainage Engineering,10(4), pp.343-258.10.1061/(ASCE)0733-9437(1984)110:4(343)
  11. Hasan, S., Mohammad, F.A., 2015. Linear Programming Model to Optimize Water Supply and Cropping Area for Irrigation A Case Study for Kalihati.Global Journal of Researches Engineering: G Industrial Engineering, 15 (2), PP.19-24.
  12. Hassani, N.,Yadollahi, P., Mortazavi, A., 2017. Farmers’ Perception of the Seriousness of the Declining Groundwater Volume and their Reactions to Mitigation of its undesirable Outcomes. Journal Management System, 10 (Issue 34), Page 1-10.
  13. HSPD., 2011. Estimating Economic Consequences for Dam Failure Scenarios. Homeland Security Presidential Directive (HSPD), USA, pp.1-45.
  14. Huai, Z.u., Jiang, H., Zhi, P.W., 2013. Optimizationof reinforcement strategies for dangerous dams considering time-averaged system failure probability and benefit–cost ratio using a life quality index. Natural Hazards, 65, PP.799–817.10.1007/s11069-012-0394-z
  15. Jonkman, S.N., Vrijling, J.K.,Vrouwenvelder, A., 2008. Methods for the estimation of loss of life due to floods: a literature review and a proposal for a new method. Natural Hazards, 3, PP.353–389.10.1007/s11069-008-9227-5
  16. Kassahun, B.,Tena, A., Megersa, O., Dinka, S., 2014. Optimizing Reservoir Operation Policy Using Chance Constraint Nonlinear Programming for Koga Irrigation Dam, Ethiopia. Water Resour. Manag, 28, PP.4957–4961.10.1007/s11269-014-0770-4
  17. Kumar, D.N., Raju, K.S., Ashok, B., 2012. Optimalreservoir operation for irrigation of multiple crops using genetic algorithms. ASCE J Irrig Drain Eng, 132(2), pp.123-129.10.1061/(ASCE)0733-9437(2006)132:2(123)
  18. Michael, L. D., Gary, H.M., 1992. Predicting Loss of Life in Cases of Dam Failure and Flash flood. RiskAnalysk, 13(2),PP193-204.10.1111/j.1539-6924.1993.tb01069.x
  19. Palacios,V. H., 1976. Strategies to improve water management in Mexican irrigation districts: A case study in Sonora. Tucson, 197p. Thesis (Ph.D.) the University of Arizona,USA.
  20. Rao, S.S., 1984. Optimization Theory and Application Second edition. John Wiley and Sons, IEEE,PP1247-1248.
  21. The American Statistician, 2012. Use of Dummy Variables in Testing for Equality Between Sets of Coefficients in linear Regressions: A Generalization. The American Statistician City University of New York, New York, USA. Regressions: A Generalization. The American Statistician City University of New York, New York, USA.
  22. Yavary, G.R., Sashvary, N., 2005. Determining surface and subsurface water productivity in the agriculture sector of Iran. Agriculture Economy &development, 76, pp.167-181.
  23. U.S.Water Resources Council, 2012. Economic and Environmental Principles and Guidelines for Water and Related Land Resources Implementation Studies, U.S. Government Printing Office, Washington, USA.
Language: English
Page range: 61 - 68
Submitted on: Dec 14, 2020
Accepted on: Jan 4, 2021
Published on: May 26, 2021
Published by: University of Oradea, Civil Engineering and Architecture Faculty
In partnership with: Paradigm Publishing Services
Publication frequency: 2 times per year

© 2021 H. A. Torabi, M. Najarchi, H. Mazaheri, R. Jafarinia, M. Izadikhah, published by University of Oradea, Civil Engineering and Architecture Faculty
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.