Simulation of Groundwater Balance Using Integrated Surface and Groundwater SWAT-MODFLOW-NWT Model (Case Study: Mahabad Plain)

Document Type : Research Article

Authors

• O. Raja ¹
• M. Parsinejad ²
• M. Tajrishi ³

¹ Ph.D. candidate, Department of Irrigation and Reclamation Engineering, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran

² Associate Professor, Department of Irrigation and Reclamation Engineering, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran

³ Professor, Department of Civil Engineering, Sharif University of Technology, Tehran, Iran

https://doi.org/10.22067/jsw.2022.74890.1138

Abstract

Introduction
 Surface and groundwater conjunctively interact at different spatial or temporal scales within a plain. In many plain, surface and groundwater resources are used in combination in agriculture. Therefore, it is important to accurately predict the components of groundwater and surface water balance. Despite the rapid expansion of numerical models over the past two decades, there is still a need for comprehensive and integrated assessment of surface and groundwater components. In particular, the interconnection of both surface and groundwater models is important to connect both surface and groundwater, especially the water balance in the unsaturated root zone. In this study the effect of water recharge due to deep percolation from simultaneous supply of irrigation water from surface and groundwater sources, and rainfall from the SWAT model were used to simulate groundwater balance using the combined MDOFLOW-NWT model.
Materials and Methods
 In this study, the effect of recharge values obtained from the SWAT model was analyzed to simulate the fluctuation of water table, and groundwater balance components using the integrated model of MODFLOW-NWT model in the Mahabad plain. One of the important steps in quantifying the impact of irrigation management, and the change in land-use on the surface and groundwater balance was the simulated recharge due to the deep percolation of rainfall and irrigation water. This was done by the SWAT model, and was used as the boundary condition to the MODFLOW-NWT model. Calibration and validation of groundwater model were also done by trial-and-error and automatic PEST methods. The simulation period was performed for 10 years from the hydrological year of 2009-2010 to 2018-2019, from which 6 and 4 years were used as the period for calibration and validation were from 2009-2010 to 2014-2015 and 2015-2016 to 2018-2019, respectively. Groundwater balance components are naturally different for different years. Therefore, the study was conducted for dry, wet, and normal years. Hydraulic conductivity and specific yield were the used as initial calibration parameters in the MODFLOW-NWT model.
Results and Discussion
 The results showed a higher hydraulic conductivity and specific yield values for the aquifer was in the southern, central, and northeastern areas of the plain, and the lowest values were in the northern and near the outlet of the plain. After the calibration process, the results showed that an average, 9% of rainfall, and 36% of irrigated water percolate to the aquifer. These observations were confirmed based on a satisfactory and acceptable estimate of the water table level of the model for both calibration and validation periods. The statistical RMSE criteria for calibration and validation periods were 0.35 and 0.34 m, respectively. Also, the results of R² and NSE criteria were estimated as 0.94 and 0.91 for the calibration period, and 0.93 and 0.89 for the validation period, which indicates that the model was properly calibrated and was well able to simulate groundwater level. The groundwater hydrographs developed from piezometers’ readings, show that the recharge values estimated by the SWAT model, considering the change in land use and irrigation management across the plain, were able to properly simulate groundwater level across the aquifer. Specifically, the studies showed a continuous drop in groundwater level created in the southern and southwestern regions of the aquifer (piezometers of Fakhrighah, Gorg tapeh, and Serah Haji Khosh) due to the presence of high-consumption crops such as apple and alfalfa, and the higher number of operation wells.
Conclusion
The results of this study showed that the recharge values obtained from the calibrated SWAT model was crucial parameters for proper simulation of groundwater, and can significantly improve the model results. The results of the main components of the groundwater balance for different years showed that the amount of recharge due to the infiltration of rainfall, and irrigation were different for each year. Also, interactions between surface and groundwater resources vary from about 30 to 50 million cubic meters between years, indicating a significant interaction between the water resources. In general, the SWAT-MODFLOW-NWT model can be used as a practical tool for proper management of surface and groundwater resources under different management scenarios.

Keywords

• Mahabad plain
• MODFLOW-NWT
• Recharge Component
• SWAT
• Water table

20.1001.1.20084757.1401.36.1.3.5

Main Subjects

• Irrigation

References

1. Abedi Koupai J., and Golabchian M. 2015. Estimation of Hydrodynamic Parameters of Groundwater Resources in Kouhpayeh- Segzi Watershed Using MODFLOW. Water and Soil Science19(2): 281-293. (In Persian with English abstract) DOI: 18869/acadpub.jstnar.19.72.24.
2. Abiye T., Masindi K., Mengistu H., and Demlie M. 2018. Understanding the groundwater level fluctuations for better management of groundwater resource: a case in the Johannesburg region. Groundwater for Sustainable Development 7: 1–7. https://doi.org/10.1016/j.gsd.2018.02.004.
3. Aliyari F., Bailey R.T., Tasdighi A., Dozier A., Arabi M., and Zeiler K. 2019. Coupled SWAT-MODFLOW model for large-scale mixed agro-urban river basins. Environmental Modelling and Software 115: 200-210. https://doi.org/10.1016/j.envsoft.2019.02.014.
4. Arumí J.L., Rivera D., Holzapfel E., Boochs P., Billib M., and Fernald A. 2009. Effect of the irrigation canal network on surface and groundwater interactions in the lower valley of the Cachapoal river, Chile [Efecto de la red de canales de riego en las interacciones de agua superficial y subterránea en la parte baja del valle del Río Cachapoal, Chile]. Chilean Journal of Agricultural Research 69(1): 12-20. http://dx.doi.org/10.4067/S0718-58392009000100002.
5. Bailey R.T., Wible T.C., Arabi M., Records R.M., and Ditty J. 2016. Assessing regional-scale spatio-temporal patterns of groundwater–surface water interactions using a coupled SWAT-MODFLOW model. Hydrological Processes 30: 4420–4433. https://doi.org/10.1002/hyp.10933.
6. Barazzuoli P., Nocchi M., Rigati R., and Salleolini M. 2008. A conceptual and numerical model for groundwater management: a case study on a coastal aquifer in southern Tuscany, Italy. Hydrogeology Journal 16: 1557–1576. DOI: 1007/s10040-008-0324-z.
7. Bedekar V., Niswonger R.G., Kipp K., Panday S., and Tonkin M. 2012. Approaches to the simulation of unconfined flow and perched groundwater flow in MODFLOW. Ground Water 187–198. https://doi.org/10.1111/j.1745-6584.2011.00829.x.
8. Bejranonda W., Koontanakulvong S., and Koch M. 2007. Surface and Groundwater Dynamic Interactions in the Upper Great Chao Phraya Plain of Thailand: Semi-Coupling of SWAT and MODFLOW; Groundwater and Ecosystems, IAH Selected Papers on Hydrogeolgy; International Association of Hydrology: Goring, UK: 17–21.
9. Chitsazan M., and Kashkuli H.A. 2002. Groundwater modeling and solving hydrogeological problems. translation, Shahid Chamran University Press, Ahvaz. (In Persian)
10. Chitsazan M., Nozarparvar L., Nedri A., and Farhadimanesh M. 2016. Evaluation of hydraulic relationship between Lore Andimeshk plain aquifer and Dez river using MODFLOW model. Journal of Advanced Applied Geology 17: 36-23. (In Persian with English abstract) DOI: 22055/AAG.2015.11822
11. Chu J., Zhang C., and Zhou H. 2010. Study on interface and frame structure of SWAT and MODFLOW models coupling. Geophysical Research Abstracts, V12, EGU2010-4559. DOI: 11820/dlkxjz.2011.03.012
12. Chunn D., Faramarzi M., Smerdon B., and Alessi D.S. 2019. Application of an integrated SWAT–MODFLOW Model to evaluate potential impacts of climate change and water withdrawals on groundwater–surface water interactions in West-Central Alberta. Water 11(1): https://doi.org/10.3390/w11010110.
13. Davis S.N., and De Wiest R.J.M. 1996. Hydrogeology. New York, Wiley.
14. Doherty J., Brebber L., and Whyte P. 1994. PEST: Model-independent parameter estimation. Watermark Computing, Corinda, Australia 122: 336.
15. Dowlatabadi S., and Zomorodian S.A. 2016. Conjunctive simulation of surface water and groundwater using SWAT and MODFLOW in Firoozabad watershed. KSCE Journal of Civil Engineering 20(1): 485-496. DOI: 1007/s12205-015-0354-8.
16. Dowlatabadi S., and Zomorodian  S.M.A. 2015. Utilization of recharge values derived from SWAT model in mathematical model of MODFLOW to simulate groundwater flow of Firoozabad plain. Water and Soil Science 19(1): 337-348. (In Persian with English abstract). DOI: 18869/acadpub.jstnar.19.71.337.
17. Hamzehkhani H. 2015. Groundwater modeling to investigate the effectiveness of aquifer on surface flows by applying different exploitation policies using remote sensing technology (case study: Miandoab plain). M.Sc. Thesis, Sharif University of Technology, 175 p. (In Persian)
18. Izady A., Davary K., Alizadeh A., Ghahraman B., Sadeghi M., and Moghaddamnia A. 2012. Application of "panel-data" modeling to predict groundwater levels in the Neishaboor plain, Iran. Hydrogeology Journal 20(3): 435-447. https://doi.org/10.1007/s10040-011-0814-2.
19. Kardan Moghaddam H., Banihabib M.E., and Javadi S. 2018. Quantitative sustainability analysis of the aquifer system (case study: south Khorasan-birjand aquifer). Journal of Water and Soil 31(6): 1587-1601. (In Persian with English abstract) DOI: 22067/JSW.V31I6.66959.
20. Kim N.W., Chung I.M., Won Y.S., and Arnold J.G. 2008. Development and application of the integrated SWAT–MODFLOW model. Journal of Hydrology 356(1-2): 1-16. https://doi.org/10.1016/j.jhydrol.2008.02.024.
21. Koohestani N., Meftah halaghi M., and Dehghani A. 2013. Numerical simulation of groundwater level using MODFLOW software (a case study: Narmab watershed, Golestan province). International Journal of Advanced Biological and Biomedical Research 1(8): 858-873.
22. Kouchakzadeh M.H., and Nasiri F.  2015. Evaluation of the efficiency of using surface water simulation results to improve the accuracy of groundwater simulation in Silakhor shallow aquifer located in Lorestan province (Iran). Modares Civil Engineering Journal14(3): 129-138. (In Persian with English abstract). http://mcej.modares.ac.ir/article-16-865-en.html.
23. McDonald M.G., and Harbaugh A.W. 1988. A modular three-dimensional finite-difference ground-water flow model. Techniques of Water Resources Investigations, Book 6. Reston, Virginia: U.S. Geological Survey. https://doi.org/10.3133/twri06A1.
24. McKee T.B., Doesken N.J., and Kleist J. 1995. Drought monitoring with Multiple Time scales. In: Proceeding of the 9th Conference on Applied Climatology. Dallas, TX: American Meteorological Society 233-236.
25. Mojtahedi A., Almasi R., and Dadashzadeh M. 2018. The evaluation of the impact of the anthropogenic factors on Lake Urmia crisis using remote sensing and GIS. Journal of Civil and Environmental Engineering University of Tabriz48(2): 59-70. (In Persian with English abstract)
26. Mosase E., Ahiablame L., Park S., and Bailey R. 2019. Modelling potential groundwater recharge in the Limpopo River basin with SWAT-MODFLOW. Groundwater for Sustainable Development 9: 100260. https://doi.org/10.1016/j.gsd.2019.100260.
27. Nair S.S., King K.W., Witter J.D., Sohngen B.L., and Fausey N.R. 2011. Importance of crop yield in calibrating watershed water quality simulation tools. Journal American Water Resource Associate (JAWRA) 47(6): 1285–1297. https://doi.org/10.1111/j.1752-1688.2011.00570.x.
28. Nalbantis I., and Tsakiris G. 2009. Assessment of hydrological drought revisited. Water Resource Management 23: 881-897. https://doi.org/10.1007/s11269-008-9305-1.
29. Nasseri A. 2019. Comparison of fourteen methods of time series to analyze and predict ground water changes in Marand plain (north of Urmia Lake). Iranian Journal of Irrigation and Drainage13(1): 58-68. (In Persian with English abstract)
30. Nasseri H.R., and Adinehvand R., and Salavitabar A. 2014. The use of system dynamics in behavioral prediction and safe yield determination of Tabriz plain, Quarterly Journal of Science Kharazmi University13(4): 937. (In Persian) URL: http://jsci.khu.ac.ir/article-1-1644-fa.html
31. Nayyeri H. 2015. Morphological analysis of Mahabad river channeled the impact of dam construction, Journal of Applied Researches in Geographical Sciences15(37): 155-178. (In Persian with English abstract) DOI: 1001.1.22287736.1394.15.37.8.6
32. Niswonger R.G., Panday S., and Ibaraki M. 2011. MODFLOW-NWT, A newton formulation for MODFLOW-2005: USGS Survey Techniques and Methods 6–A37. https://doi.org/10.3133/tm6A37.
33. Palma H.C., and Bentley L.R. 2007. A regional-scale groundwater flow model for the Leon-Chinandega aquifer, Nicaragua. Hydrogeology Journal 15: 1457–1472. https://doi.org/10.1007/s10040-007-0197-6.
34. Park S., and Bailey R.T. 2017. SWAT-MODFLOW Tutorial—Documentation for Preparing Model Simulations; Department of Civil and Environmental Engineering, Colorado State University: Fort Collins, CO, USA; 56p. https://doi.org/10.1111/1752-1688.12502.
35. Raja O., Parsinejad M., and Tajrishi M. 2021. Multipurpose calibration of SWAT model in estimating runoff, evapotranspiration, and crop yield (a case study: Mahabad plain). Iran-Water Resources Research 17(4): 11-34. (In Persian with English abstract) DOI:  1001.1.17352347.1400.17.4.1.8.
36. Karimipour A.R., and RakhshandehrooR. 2011. Sensitivity analysis for hydraulic behavior of Shiraz plain aquifer using PMWIN, Journal of Water and Wastewater22(78): 102. (In Persian with English abstract)
37. Rezaei Moghaddam M.H., Rahimpour T., and Nakhostinrouhi M. 2016. Potential Detection of the Groundwater Resources Using Analytic Network Process in Geographic Information System (Case Study: Basins Leading to Tabriz Plain). Iranian Journal of Eco Hydrology3(3): 379-389. (In Persian with English abstract). DOI: 22059/IJE.2016.60026.
38. Saadatpour A., Alizadeh A., Ziaei A.N., and Izady A. 2019. Integrated Surface and Groundwater Flow Modeling in Neishaboor Watershed with SWAT-MODFLOW. Journal of Water and Soil33(4): 521-536. (In Persian with English abstract) DOI: 22067/JSW.V0I0.74658.
39. Saberimehr S., Asghari Moghaddam A., and Nadiri A. 2017. Modeling Groundwater Flow and Salinity Intrusion at Shabestar Plain Aquifer Using GMS Software Model, Quaternery Journal of Iran 3(9): 41-50. (In Persian). https://dx.doi.org/10.22059/ijswr.2021.331850.669093.
40. Sadat Hamraz B., Akbarpour A., and Pourreza Bilondi M.  2016. Assessment of parameter uncertainty of MODFLOW model using GLUE method (Case study: Birjand plain). Water and Soil Conservation22(6): 61-79. (In Persian with English abstract). DOI: 1001.1.23222069.1394.22.6.4.6.
41. Scanlon B.R., Keese K.E., Flint A.L., Flint L.E., Gaye C.B., Edmunds W.M., and Simmers I. .2006. Global synthesis of groundwater recharge in semiarid and arid regions. An International Journal 20(15): 3335–3370. https://doi.org/10.1002/hyp.6335.
42. Semiromi M.T., and Koch M. 2019. Analysis of spatio-temporal variability of surface–groundwater interactions in the Gharehsoo river basin, Iran, using a coupled SWAT-MODFLOW model. Environmental Earth Sciences 78(6): 201. https://doi.org/10.1007/s12665-019-8206-3.
43. Sibanda T., Nonner J.C., and Uhlenbrook S. 2009. Comparison of groundwater recharge estimation methods for the semi-arid Nyamandhlovu area, Zimbabwe. Hydrogeology Journal 17: 1427–1441. https://doi.org/10.1007/s10040-009-0445-z.
44. Sophocleous M., and PerkinsP. 2000. Methodology and application of combined watershed and ground water models in Kansas. Journal of Hydrology 236(3–4): 185–201. https://doi.org/10.1016/S0022-1694(00)00293-6.
45. SophocleousA. 2005. Groundwater recharge and sustainability in the High Plains aquifer in Kansas, USA. Hydrogeology Journal 13(2): 351–365. https://doi.org/10.1007/s10040-004-0385-6.
46. Sun H., and Cornish P.S. 2005. Estimating shallow groundwater recharge in the headwaters of the Liverpool Plains using SWAT. Hydrological Processes 19(3): 795–807. https://doi.org/10.1002/hyp.5617.
47. Taheri Tizro A., and Kamali M.  2019. Groundwater modeling by MODFLOW model in Toyerkan aquifer and evaluation of hydrogeological state under present and future conditions. Water Engineering 12(40): 89-104. (In Persian with English abstract) DOI: 1001.1.20086377.1398.12.40.8.4.
48. Tigkas D., Vangelis H., and Tsakiris G. 2015. DrinC: a software for drought analysis based on drought indices. Earth Science Informatics 8(3): 697-709. https://doi.org/10.1007/s12145-014-0178-y.
49. Valizadegan E., and Yazdanpanah S. 2018. Quantitative model of optimal conjunctive use of Mahabad plain's surface and underground water resources, Amirkabir Journal of Civil Engineering50(4): 631-640. (In Persian with English abstract) DOI: 22060/CEEJ.2017.12739.5266.
50. Vicente-Serrano S.M., López-Moreno J.I., Drummond A., Gimeno L., Nieto R., Morán-Tejeda E., Lorenzo-Lacruz J., Beguería S., and Zabalza J. 2011. Effects of warming processes on droughts and water resources in the NW Iberian Peninsula (1930-2006). Climate Research 48: 203–212. https://doi.org/10.3354/cr01002.
51. Water Consulting Engineers and Sustainable Development. 2014. Update studies of water resources balance of study areas of Urmia Lake catchment area, report of water resources balance of Mahabad study area, 81 p. (In Persian)
52. Wei X., and Bailey R.T. 2019. Assessment of system responses in intensively irrigated stream–aquifer systems using SWAT-MODFLOW. Water 11(8): 1576. https://doi.org/10.3390/w11081576.
53. Wei X., Bailey R.T., Records R.M., Wible T.C., and Arabi M. 2018. Comprehensive simulation of nitrate transport in coupled surface-subsurface hydrologic systems using the linked SWAT-MODFLOW-RT3D model. Environmental Modelling and Software 122: 1-10. https://doi.org/10.1016/j.envsoft.2018.06.012.
54. Wheater H.S. 2010. Hydrological processes, groundwater recharge and surface-water/groundwater interactions in arid and semi-arid areas. Groundwater Modeling in Arid and Semi-Arid Areas, 1st ed. Howard S. Wheater, Simon A. Mathias and Xin Li. Published by Cambridge University Press, 5-37. https://doi.org/10.1017/CBO9780511760280.003.
55. Xu Y., and Beekman H.E. 2003. Groundwater recharge estimation in southern Africa. UNESCO IHP UNESCO Paris, 92-9220-000-3. https://doi.org/10.1007/s10040-018-1898-8.