Modeling and Prediction of Groundwater Level in Izadkhast Plain, Fars Province

جغرافیا و مخاطرات محیطی

Article 8, Volume 13, Issue 2 - Serial Number 50, June 2024, Pages 162-185   

Document Type: Research Article

DOI: 10.22067/geoeh.2023.81109.1334

Authors

Maryam Ansari¹; Iraj Jabbari^{* 2}

¹PhD in Geomorphology, Razi University, Kermanshah, Iran

²Associate Professor in Geomorphology, Razi University, Kermanshah, Iran

Abstract

Given the limited underground water resources in Iran, careful calculation, proper use, regulation, and maintenance of these resources are crucial. One effective approach for managing and exploiting these resources optimally, both now and in the future, is through modeling. This study focuses on the challenges faced by groundwater in the Izadakhat Basin, employing GMS software and MODFLOW code to model and forecast water levels under both steady and unsteady conditions. Three scenarios are considered: continuation of current trends, a 20% decrease in precipitation, and a 20% increase in precipitation. The results indicate that, under current conditions, the water table is projected to drop by 2.786 meters. A 20% decrease in precipitation would increase this decline to 3.77 meters, while a 20% increase in precipitation would reduce the drop to 1.77 meters. In other words, the water level fluctuates by about 1 meter with a 20% change in precipitation. Over the three-year period studied (2015–2017), the first scenario suggests a steady decline of 2.786 meters every three years if current conditions persist. These findings highlight the importance of surface water storage in the region to replenish groundwater levels. Moreover, the analysis underscores the significant impact of human activity on both the quantity and quality of groundwater resources in the study area, emphasizing the need for improved resource management.

Keywords

Undergroundwater level flactuations; Groundwater level fluctuation; Groundwater resource management; Aquifer; MODFLOW code; Izadkhast plain; Iran

References

Abbasnouvinpour, E., Karimi, F., & Rezaie, H. (2022). The Prediction of Groundwater Level in Ghorve Plain Using MODFLOW Model in Different Scenarios of LARS-WG Climate Change. Water and Soil Science, 32(4), 61-73. [In Persian] https://doi.org/10.22034/ws.2021.30465.2197

Afruzi, A., & Zare Abyaneh, H. (2017). Groundwater Level Modeling and Forecasting Using the Time Series Models (Case Study: The Plains of Hamadan Province). Journal of Watershed Management Research. 8(15), 102-111. [In Persian] https://doi.org/10.29252/jwmr.8.15.102

Akhoni Pourhosseini F., Asadi, E. (2017). Bayesian networks, Gamma Test, Groundwater level, Model Least Squares Support Vector Machine, Plain Ardebil. Iranian Journal of Watershed Management Science and Engineering; 11 (36), 33-42. [In Persian]  http://dorl.net/dor/20.1001.1.20089554.1396.11.36.7.9

Ansari, M., Jabbari, I. & Sargordi, F. (2023). The Effect of Water Resources on Spatial and Temporal Change of Soil Salinity in Izdkhast Playa, Fars Province Iran. Environmental Monitoring and Assessment. 195(63), 1-15. https://doi.org/10.1007/s10661-022-10678-5

Ansari, M., & Jabbari, I. (2023). Investigating spatial and temporal changes in the quality underground water sources in the Izadkhash basin .Physical Geography Quarterly, 15(60) ,1-16. [In Persian]  https://dorl.net/dor/20.1001.1.20085656.1402.16.60.3.2

Ansari, M., Jabbari, I., & Sargordi, F. (2021)a. Spatial Modelling of Water Quality Parameters Based on Geological Formations. Hydrogeomorphology, 8(26), 117- 137.  [In Persian]    https:/ /doi.org/10.22034/hyd.2021.44081.1571

Ansari, M., Jabbari, I., & Sargordi, F. (2021)b. Use of Morphometric Indicators to Identify the Source of Salinity in Playa (Case Study Izadkhast Playa Fars Province). Quantitative Geomorphological Research, 10(3), 134-156. [In Persian]  https://www.geomorphologyjournal.ir/article_141043.html

Atayizadeh, S., Chit Sazan, M. (2018). Investigating the Impact of Drought on the Quantitative Reduction of Underground Water in Maidaoud Plain Using a Mathematical Model. The second national conference on the effects of drought and its management solutions. Isfahan Agricultural and Natural Resources Research Center and Isfahan Governorate's Unforeseen Events Headquarters. Isfahan. [In Persian]

Chidepudi, S.K.R., Massei, N., Massei, A., Henriot, A., Allier, D., Baulon, L. (2023). A Wavelet-Assisted Deep Learning Approach for Simulating Groundwater Levels Affected by Low-Frequency Variability. Science of the Total Environment. 865. https://doi.org/10.1016/j.scitotenv.2022.161035

Heydari, A., & Jabbari, I. (2022). Simulation of Marvdasht Groundwater Level and Investigation of Forecast Scenarios Using MODFLOW Mathematical Code. Hydrogeomorphology, 8(29), 172-149. [In Persian] https://dorl.net/dor/20.1001.1.23833254.1400.8.29.8.3

Jovanovic, N. Z., Israel, S., Tredoux, G., Soltau, L., Le Maitre, D., Rusinga, F., Rozanov, A., van der Merwe, N., (2009). Nitrogen dynamics in land cleared of alien vegetation (Acacia saligna) and impacts on groundwater at Riverlands Nature Reserve (Western Cape, South Africa). Water SA, 35(1), 37-44. https://doi.org/10.4314/wsa.v35i1.76653

Kamali Ardakani, E., Bemani Kharanagh, A., Hayatzadeh, M., & Toshsi, G. (2019). Investigation of modeling techniques in studies related to changes in underground water.The first international conference and the fourth national conference on protection of natural resources and environment. Mohaghegh Ardabili University, Faculty of Agriculture and Natural Resources, Ardabil. [In Persian]

Katibeh, H., & Hafezi, S. (2005). Application of Modflow in Groundwater Management and Evaluation of Artificial Recharge Project of Ab-Barik Aquifer (Bam). Journal of Water and Wastewater, 15(2), 45-58. [In Persian]

Knotters, M., & Bierkens, M. F. (2001). Predicting water Table Depths in Space and Time using a Regionalised Time Series Model. Geoderma, 103(1-2), 51–77. https://doi.org/10.1016/S0016-7061(01)00069-6  

Kushwaha, R. K., Pandit, M. K., Goyal, T., (2009). MODFLOW Based Groundwater Resource Evaluation and Prediction in Mendha Sub-basin, NE Rajasthan, Journal geological society of India, 74, 449–458. https://doi.org/10.1007/s12594-009-0154-1

Mackay, J. D., Jackson, C. R. & Wang, L. (2014). A Lumped Conceptual Model to Simulate Groundwater Level Time-series. Environmental Modelling & Software, 61, 229-245. https://doi.org/10.1016/j.envsoft.2014.06.003 

Masoumi, F., Najjar-Ghabel, S., & Safarzadeh, A. (2021). Automatic Calibration of Groundwater Simulation Model (MODFLOW) by Indeterministic SUFI-II Algorithm. Amirkabir Journalof Civil Engineering, 53(4), 1507-1524.  https://doi.org/10.22060/ceej.2019.16990.6426          

McDonald, M. G., Harbaugh, A. W. (1988). A Modular Three-Dimensional Finite Difference Groundwater Flow Model. In: Techniques of Water-Resources Investigations, Book 6, U.S. Geological Survey, 588.  https://doi.org/10.3133/twri06A1

Mehl, S., Hill, M. C. (2010). Grid-size dependence of Cauchy boundary conditions used to simulate stream-aquifer interactions, Advances in Water Resources, 33(4), 430-442. https://doi.org/10.1016/j.advwatres.2010.01.008

Mirzaei, A., & Nazemi, A. (2011).  Water Table Elevation Prediction in the Shabestar Plain Using the Artificial Intelligence Techniques. Water Resources Engineering, 4(8), 1-10. https://dorl.net/dor/20.1001.1.20086377.1390.4.8.1.7

Mondal, N. C., Singh. V. S. (2009). Mass transport modeling of an industrial belt using visual MODFLOW and MODPATH: A case study.  Journal of Geography and Regional Planning 2(1), 001-019. https://doi.org/10.5897/JGRP.9000103

Pande, C.B., Moharir, K.N., Singh, S.K.,  Elbeltagi, A.,  Bao Pham, Q., Panneerselvam, B.,  Varade, A.M.,  Kouadri, S.  (2022). Groundwater Flow Modeling in the Basaltic Hard Rock Area of Maharashtra, India. Applied Water Science, 12(12) 1-14. https://doi.org/10.1007/s13201-021-01525-y

Parameswari, K., Mudgal, B. V. (2015). Assessment of Contaminant Migration in an Unconfined Aquifer Around an Open Dumping Yard: Perungudi a Case Study. Environmental Earth Sciences,74(7),6111-6122. https://doi.org/10.1007/s12665-015-4634-x

Patil, N.S., Chetan, N.L., Nataraja, M., Sutharb, S. (2020). Climate Change Scenarios and its Effect on Groundwater Level in the Hiranyakeshi Watershed. Groundwater for Sustainable Development, 10. https://doi.org/10.1016/j.gsd.2019.100323

Porhaghi, A., Akhondali, A., Radmanesh, F., & Mirzaee, S. (2014). Manage the Groundwater Sources Exploration of the Nourabad Plain in the Drought Conditions with MODFLOW Modeling. Irrigation Sciences and Engineering, 37(2), 71-82. [In Persian] https://dorl.net/dor/20.1001.1.25885952.1393.37.2.7.7

Rahmawati, N., Vuillaume, J.F.  & Purnama, I.L.S. (2013). Salt Intrusion in Coastal and Lowland Areas of Semarang City, Journal of Hydrology, 494, 146-159. https://doi.org/ 10.1016/j.jhydrol.2013.04.031

Rajabi, K., Nikbakht Shahbazi, A., Fathian, H., & Zohrabi, N. (2021). Izeh Plain Subsidence Modeling Using MODFLOW Mathematical Code, Iran-Water Resources Research, 16(4), 112-126. https://dorl.net/dor/20.1001.1.17352347.1399.16.4.8.8

Rashvand, M., Li, J., Liu, Y. (2019). Coupled Stress-Dependent Groundwater Flow-Deformation Model to Predict Land Subsidence in Basins with Highly Compressible Deposits. Hydrology, 6(3), 78. https://doi.org/10.3390/hydrology6030078

Rayne, T. W., Bradbury, K., Muldoon, M. (2001). Report: Delineation of Capture Zones for Municipal Wells in Fractured Dolomite, Sturgeon Bay, Wisconsin, USA, Hydrogeology Journal, 9, 432–450. https://doi.org/10.1007/s100400100154

Shakoor, M., Khan, Z. M., Farid, H. U., Ahmad, F., Arshad, M., Qamar, U., Ahmad, R., & Sultan, M. (2018). Development of Groundwater Flow Model (MODFLOW) to Simulate the Escalating Groundwater Pumping in the Punjab, Pakistan. Pakistan Journal of Agricultural Sciences, 55(3), 635-644. https://doi.org/10.21162/PAKJAS/18.4909

Shakya, C. M., Bhattacharjya, R. K., Dadhich, S. (2022). Groundwater Level Prediction with Machine Learning for the Vidisha District, a Semi-Arid Region of Central India, Groundwater for Sustainable Development, 19. https://doi.org/10.1016/j.gsd.2022.100825

Tao, H., Hameed, M.M., Marhoon, H.A., Zounemat-Kermani, M., Heddam, S., Kim, S., et al. (2022). Groundwater Level Prediction Using Machine Learning Models: A Comprehensive Review, Neurocomputing, 489, 271-308. https://doi.org/10.1016/j.neucom.2022.03.014

Wang, S., Shao, J., Song, X., Zhang, Y., Huo, Z. & Zhou, X. (2008). Application of MODFLOW and geographical information system to groundwater flow simulation in North plain, China. Environmental Geological, 55, 1449-1462. https://doi.org/10.1007/s00254-007-1095-x

Yanxun, S., Yuan, F., Hui, Q., Xuedi, Zh. )2011(. Research and Application of Groundwater Numerical Simulation-A Case Study in Balasu Water Source. Procedia Environmental Sciences, 8,146–152. http://dx.doi.org/10.1016/j.proenv.2011.10.024