Simulating Surface Water Allocation and Identifying Systemic Archetype Using Vensim Software: A Case Study of Qorveh Dehgolan's Basin

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10.22052/deej.2021.10.31.61

Abstract

Extended Abstract
Introduction: Modeling the allocation of water resources systems in the world has been considered from different perspectives. One of the most important differences in modeling is between linear and dynamic approaches. The term linear refers to a common approach in modeling with a mechanical conception of events that justifies phenomena with unilateral cause and effect relationships. On the other hand, in the dynamic approach, which is also applied in the present study, the system is first broken down into smaller components, the mutual causal relationships between the components are defined, and finally, the combination of their results determines the system's performance. Together with each other, Causal relationships create a Generic Archetype that helps identify the problems and solve them, which could especially be helpful in water resources management. This study sought to simulate surface water allocation in the agricultural sector of Qorveh Dehgolan's basin, dealing with future problems by identifying generic archetypes.
Materials and Methods: in the study area, drinking water, the water used in industry, and some part of the water used in agriculture are supplied from groundwaters. Thus, the researchers attempted to measure the amount of surface water consumed by the agricultural sector. To this end, first, the model was simulated on an annual scale. Then, after ensuring the model's accuracy, it was implemented on a monthly scale using the Vensim software. Moreover, behavior and condition tests were performed to validate the simulated model, proving the model's high accuracy.
Results: To ensure that the decrease in rainfall does not affect discharge, a comparison of rainfall trends and river discharge was performed in two selected stations, and the results showed that the decrease in river discharge was due to consumption. After that, has been evaluated model in annual scale, we used average values of RMSE and MAE in all stations, results show values equal 0.4 and 0.10 respectively, on the other hand, the test of limit conditions was confirmed high accuracy of the model.
 In the next stage, the average percentage of computational withdrawals was calculated for the annual scale, and the results showed that the maximum and minimum percentages of water consumption are equal to 27.79 and 19.53 for Dehgolan and Golbalagh stations, respectively. These values ​​indicate a deficit equal to 50% of the water requirement throughout the simulation period. Then, simulations were performed on a monthly scale before and after dam activity. Before operating the dams in the region (until 1390), the RMSE and MAE values were calculated as 0.74 and 0.39, respectively, which confirmed the model's efficiency. Then the impact of dams on the region's behavior and the causes of their occurrence was considered. Despite an intense decrease in discharge, the activity of generic archetypes, such as growth limit, failed fixes, and escalation, have expanded the under-cultivation area in all zones from 1390 to 1395, with the HassanKhan under-cultivation zone being expanded by 4.5 times compared to the previous conditions.
 
Discussion & conclusion: Simulating the dams' post-operation performance model shows that the dams' output can be increased up to 2 times in the best case. An increase in growth-limit patterns failed solutions, and escalation has led to the construction of dams in this region to deal with water shortages crisis and to supply more water, and, thus, to the expansion of under-cultivation areas in all zones with the assumption of the existence of adequate water supplies. Therefore, in addition to the critical decrease in Qorveh and Dehgolan aquifers' water level throughout the 1369-1390 period, the region's discharge rate has dropped by 72% compared to its rate at the beginning of the period (from 1390 to 1395), and by 114% compared to the whole study period due to recent extractions, while according to most of the meteorological station, the precipitation rate has not been decreased so critically.
On the other hand, the under-cultivation areas in zones where dams are constructed such as Soral, Sang Siah, and Golbalagh, or under-cultivation areas in areas located downstream of those zones, including Hassan Khan, have been expanded by 2.40, 3.56, 3.93, and 4.5 times compared to the study period's average rate in response to the escalation. As the growth limit and failed solutions have not been applied to these zones yet, this part of the basin has increased the irrigation efficiency from 37% to 45% to maintain the equilibrium. Therefore, considering the observed behaviors, it could be argued that if appropriate measures are not taken to manage water consumption properly, the dams' minimum output and their reservoirs' dryness would be highly expected. 

Keywords

References

1. Alami, M. T., Farzin, S., Ahmadi, M. H. and Aghabalaee, B. (2014). System Dynamics Modeling of Dam and Groundwater for Optimal Water Management (Case study: Golak Dam). Journal of Civil and Environmental Engineering. 44(1):74-87. 2. Amoo, O.T., Nakin, M.D. V., Abayomi, A., Ojoubele, H. o. and Salami, A. W.(2020). System Dynamics Approach for Evaluating Existing and Future Water Allocation Planning Among Confilicting Users. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences.4(3):44-51. 3. Asadzadeh, F., Kaki, M., Shakiba, S. and B. Raei, B. (2016). Impact of Drought on Groundwater Quality and 3-Groundwater Level in Qorveh-Chardoli Plain. Iran-Water Resources Research. 12(3):513-561. 4. Barati, Kh., Abedi Koupai, J., Darvishi, E., Azari, A. and Yousefi, A. (2020). Cropping Pattern Optimization Using System Dynamics Approach and Multi-Objective Mathematical Programming. J. Agr. Sci. Tech. 22(5):1397-1412. 5. Wade, P. and Eslamian, S., (2017). Water Issues from a System Dynamics Perspective, Ch. 25 in Handbook of Drought and Water Scarcity, Vol. 2: Environmental Impacts and Analysis of Drought and Water Scarcity, Ed. by Eslamian S. and Eslamian F., Taylor and Francis, CRC Press, USA, 461-488 6. Fotookian, M.R., Safari. N. and Zarghami. M. (2017). Using System Dynamics Modeling to Develop the Operation Policy for Yamchi Reservoir (Iran) by Applying Optimum Cropping Pattern. Iran-Water Resources Research.13(3):1-16. 7. Ghaderzadeh, H. and karimi, M. (2019). Impacts of Agricultural Water Quota Policy in Groundwater Resources Management in Qorveh-Dehgolan Plain. Agricultural Economics.12(4):73-89. 8. Ghodoosi, M., Morid, S. and Delavar, M. (2013). Comparison of de trending methods for the temperature and precipitations time series. Journal of Agricultural Meteorology.1(2):32-45. 9. Huanhuan, Q., Amy C. Sun, J. L. and Chunmiao, Z. (2012). System dynamics analysis of water supply and demand in the North China Plain. Water Policy 14:214–231. 10. Kadkhodahosseini. M., Shahomammadi. S., Mirabbasi. R. and Nozari. H. (2018). Evaluation of Different Allocation Scenarios for Choghakhor Dam Reservoir Using System Dynamic M. Iran-Watershed Management Science & Engineering. 11(36):23-32. 11. Naseri. H., Ahmadi. M. and Salavitabar. A. (2011). Modeling the utilization of sustainable water resources of Shahrchai Dam (orumieh) by system dynamics method. Iranian Geological Quarterly. 16:97-108. 12. Ojaghlu. H., Mashahir. M. and Razmjo, m. GH. (2017). Monitoring the exploitation of tributaries on reducing the flow of the Ghezel Ozan River (Study Case: Tarom Basin - Khalkhal). 16th Iranian Hydraulic Conference. Faculty of Engineering, Mohaghegh Ardabili University.1-8. 13. Ormsbee, L. and Elshorbagy, A. (2006) Object-oriented modeling approach to surface water quality management, Environmental Modelling & Software.:21:689-698. 14. Paimozd. Sh., Morid. S., Bagheri. A. and Torabi. S.(2011). Inter State water allocation in common basin, using a system dynamics approach:A case study in the Qezel ozan basin. Ph.D. Thesis. Tarbiat Modares University. 15. Park, S. and Sahle, V. and Jung, S. Y. (2015). A System Dynamics Model for the Simulation of the Management of a Water Supply System. 2nd International Conference on Geological and Civil Engineering. 80(8):3641. 16. Report of Agricultural Jihad of Kurdistan Province. (2017). Ministry of Agricultural. 17. Saysel, A. K., Yaman, B. and Yenigun, O. (2002), Environmental sustainability in an agricultural development project: a system dynamics approach. Journal of Environmental Management,64: 247-260. 18. Senge, P. M. (1992). The Fifth Discipline. Random House, Australia, 7th ed. Edition. 19. Simonovic. S. P. (2002). Global water dynamics: Issues for the 21st century. Water Science and Technology, 45(8):53–64. 20. Simonovic, S. P.and Bender, M. J. (1996). Collaborative planning support system: an approach for determining evaluation criteria, Journal of Hydrology, 177(3):237–251. 21. Smith, P. and Ackere, A.V. (2002). A note on the integration of system dynamics and economic models. Journal of economic and control, 26:1–10. 22. Soltani, M. and Alizadeh, A.(2017.)Integrated water resources management at basin scale (IWMsim) using a system dynamics approach. Journal of Soil and Water Resources Protection. 2:69-90 23. Stave, K. A. (2003). A system dynamics model to facilitate public understanding of water management options in Las Vegas, Nevada. International Journal of Environmental Management, 67:303-313. 24. Sterman, J. D. (1994).Learning in and about complex systems. System Dynamics Review, 10(2-3):291–330. 25. Teimoori, M., Mirdamadi, S. M. and Hosseini, S. J. (2018). Modeling of Climate Change Effects on Groundwater Resources: The Application of Dynamic Systems Approach. International Journal of Agricultural Management and Development, 9: 107-118. 26. Yuan, L., He, W., Degefo., D. M., Whan, Zh., Ramsey, T. S and Wu, x.(2021). A system dynamics simulation model for water conflicts in the Zhanghe River Basin, China.International Journal of Water Resources Development. https://doi.org/10.1080/07900627.2021.1873107 27. Vlachos, D., Georgiadis, P. and Iakovou, E. (2007). A system dynamics model for dynamic capacity planning of remanufacturing in closed-loop supply chains. International Journal of Computers and Operations Research, 34:367-394. 28. Water resources planning report.(2011).Ministry of Energy. Iran Water Resources Studies Company.1:1-336. 29. Water resources balance updating studies.(2011). Iran Water Resources Studies Company.5:1-106. 30. Xi. X. and Poha, K. L. (2013). Using system dynamics for sustainable water resources management in Singapore. Procedia Computer Science 16:157 – 166. 31. Xu, Z. X., Takeuchi, K., Ishidaira, H. and Qhang, X. W. (2002). Sustainability analysis for Yellow River water resources using the system dynamics approach. Water Resources Management. 16(3):239–261. 32. Zarghami, M. and Akbariyeh, S. (2012). System dynamics modeling for complex urban water systems: Application to the city of Tabriz, Iran. Resources, Conservation and Recycling. 60:99-106.
Desert Ecosystem Engineering
Volume 10, Issue 31
September 2021
Pages 123-141

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