Determining Optimized Depth of Wells in a Catchment Considering Climate Change and Water Resources Management (Case Study: Khash watershed)

Subject Areas : Agricultural Economics Research

Ebrahim Zeraati ¹ (Master of water resource management, University of Sistan and Baluchestan, Zahedan, Iran.)
ُSamira Zeinodini ² (Phd student of Water resource management, University of Sistan and Baluchestan, Zahedan, Iran.)
Bahareh Pirzadeh ³ (Assistant Professor of Civil Engineering, University of Sistan and Baluchestan, Zahedan, Iran.)
Seyed Arman Hashemi Monfared ⁴ (Associate Professor of Civil Engineering, University of Sistan and Baluchestan, Zahedan, Iran.)

Received: 2019-05-08 Accepted : 2021-10-11 Published : 2022-01-21

Keywords: Climate Change, Groundwater, WEAP Model, Water resources management, optimum depth of wells,

Abstract :

Introduction: Utilization of aqueducts and excavations is one of the most common methods of using groundwater.
Every year, level of groundwater is lowered too much and its flow rate decreases. In the study area (Khash), the water deficit is negative and the annual water level decreases and it is considered as the main source of water supply in the region. By continuing the existing conditions, one of the solutions is well extension for water supply. In this research, the optimal depth of wells was determined from 2014 to 2044, so that there was no need for rehabilitation of wells until the target year.
Materials and Methods: To study the effect of climate change, rainfall data was generated by using the LARS-WG model under the MPEH5  model and A1B scenario. its ability Confirmed with to R2, 94/94 capability .Finally, eight scenarios were defined in the WEAP model and the conditions of region were simulated and the depth of optimum floor was calculated for three wells. The results showed that if the existing conditions continue until 2044, 54.88 percent of the water stored in the aquifer will be empty and the average level of groundwater Decreases 13.67 m
Findings: The best scenario is the S8 scenario, which in this scenario the largest reduction of water stored in the aquifer occurs in 2036  and it is 10.55% of the initial volume, and the average water level is 1.67 m horizontally.
Conclusion: S8 scenario has the least reduction in water stored in the aquifer. In this scenario, the water stored at the end of 2044 is 93.29%, during which time, 6.71% of the stored water will be reduced. The average discharge is constant but costs increase, so discharge has no effect on reducing or increasing costs. Therefore, only the depth of floor and head pumps are the only factors that will have a greater impact on cost changes.

References:

1. Arnell NW. Global warming, river flows and water resources. John Wiley & Sons Ltd; 1996.  http://www.cabdirect.org/cabdirect/abstract/19971903551


2. Mitchell TD. Pattern scaling: an examination of the accuracy of the technique for describing future climates. Climatic change. 2003 Oct; 60(3):217-42.

        [DOI.org/10.1023/A:1026035305597]

3. Johnson GL, Hanson CL, Hardegree SP, Ballard EB. Stochastic weather simulation: Overview and analysis of two commonly used models. Journal of Applied Meteorology and Climatology. 1996 Oct; 35(10):1878-96.

        [DOI.org/10.1175/1520-0450(1996) 035< 1878:SWSOAA>2.0.CO;2]

4. Semenov MA, Barrow EM, Lars-Wg A. A stochastic weather generator for use in climate impact studies. User Man Herts UK. 2002 Aug.


5. Alizadeh, H., and Zahraei, B. Comparison of statistical downscaling models in simulation of the daily rainfall. The 16th Conference of Iran Geophysics. 2014. 128-132.) In Persian).


6. Mousavi RS, Ahmadizadeh M, Marofi S. A multi-GCM assessment of the climate change impact on the hydrology and hydropower potential of a semi-arid basin (A Case Study of the Dez Dam Basin, Iran). Water. 2018 Oct; 10(10):1458.

       [DOI.org/10.3390/w10101458]

7. Baghanam AH, Nourani V, Sheikhbabaei A, Seifi AJ. Statistical downscaling and projection of future temperature change for Tabriz city, Iran. InIOP Conference Series: Earth and Environmental Science 2020 Jun 1 (Vol. 491, No. 1, p. 012009). IOP Publishing. https://iopscience.iop.org/article/10.1088/1755-1315/491/1/012009/meta

8. Sechi GM, Sulis A. Intercomparison of generic simulation models for water resource systems. In International Congress on Environmental Modelling and Software Modeling for Environment’s Sake, Fifth Biennial Meeting, Ottawa, Canada,  2010; 8: 15.

https://scholarsarchive.byu.edu/iemssconference/2010/all/474/

9. Movahed Atar, F., Samadi, H. Evaluation of Zayanderud dam operation during drought period by using weap model. Irrigation and Water Engineering, 2014; 4(2): 18-28. (In Persian)

http://www.waterjournal.ir/article_70873.html?lang=en

10. Mourad KA, Alshihabi O. Assessment of future Syrian water resources supply and demand by the WEAP model. Hydrological Sciences Journal. 2016 Jan 25;61(2):393-401.

[DOI.org/10.1080/02626667.2014.999779]

11. Mousavi S. N. Gholami M. Determine the most profitable optimal depth of the agricultural water wells for sustainable management of the Sidan-Farooq plain aquifer. Journal of Water Resources Engineering, 2012.5:99-109. (In Persian)


12. Gholami Z., Ibrahimian H., Noory H. Determining economic depth of agricultural well in sprinkler irrigated farms in Qazvin plain. Iranian Journal of Soil and Water Research, 2017; 48(2): 441-449.

     [DOI .org/10.22059/ijswr.2017.62660]

9. Movahed Atar, F., Samadi, H. Evaluation of Zayanderud dam operation during drought period by using weap model. Irrigation and Water Engineering, 2014; 4(2): 18-28. (In Persian)

http://www.waterjournal.ir/article_70873.html?lang=en

10. Mourad KA, Alshihabi O. Assessment of future Syrian water resources supply and demand by the WEAP model. Hydrological Sciences Journal. 2016 Jan 25;61(2):393-401. [Doi.org/10.1080/02626667.2014.999779]


11. Mousavi S. N. Gholami M. Determine the most profitable optimal depth of the agricultural water wells for sustainable management of the Sidan-Farooq plain aquifer. Journal of Water Resources Engineering, 2012.5:99-109. (In Persian)


12. Gholami Z., Ibrahimian H., Noory H. Determining economic depth of agricultural well in sprinkler irrigated farms in Qazvin plain. Iranian Journal of Soil and Water Research, 2017; 48(2): 441-449.

13. Sangab Zagros Consulting Engineers. Report on the extension of the ban on Khash plain and its integration with Poshtkouh Plain. Ministry of Energy, Regional Water Company of Sistan and Baluchestan Province. 2014.  (In Persian)

14. Sieber J, Purkey D. WEAP tutorial. Stockholm Environment Institute. 2008.

15. Safari, H., Navaeenia, B., Sharifi, M. Determination of Optimal Depth for Well Extension Using a Nonlinear Programming Model. Journal of Water and Wastewater; Ab va Fazilab 2005; 15(3): 35-41. (In Persian)

16. Office of Technical Affairs and Compilation of Criteria for Management and Planning Organization. Circular of well’s head. 2017. (In Persian)

17. Mehta VK, Haden VR, Joyce BA, Purkey DR, Jackson LE. Irrigation demand and supply, given projections of climate and land-use change, in Yolo County, California. Agricultural water management. 2013 Jan 31;117:70-82.

       [DOI.org/10.1016/j.agwat.2012.10.021]

18. Hosseini M., Ebrahimi N.GH., Mohammadi, E.,  Makrian Z. Quantitative assessment of extractable
water resources in agriculture and natural resources. Economic Evaluation of Water Resources in Agriculture from a Sectorial
Perspective to an Applied Landscape in Natural Resource Management, 2014. 1-9. (In Persian)