برآورد تغذیه آب‌زیرزمینی با استفاده از روش نوسانات سطح ایستابی و شبیه‌سازی جریان در ناحیه غیراشباع (آبخوان مرودشت، استان فارس، ایران)

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه مهندسی و مدیریت آب، دانشگاه تربیت مدرس، تهران، ایران.

2 دانشکده مهندسی، دانشگاه بریتیش کلمبیای شمالی، بریتیش کلمبیا، کانادا.

10.22059/jwim.2025.399355.1246

چکیده

تغذیه منابع آب‌زیرزمینی در آبخوان مرودشت با استفاده از دو روش نوسانات سطح ایستابی و روش شبیه‌سازی جریان در ناحیه غیراشباع با مدل HYDRUS-1D برآورد شد. برآورد تغذیه در روش اول با استفاده از داده‌های تغییرات تراز و آبدهی ویژه و در روش دوم با داده‌های ویژگی‌ و مشخصات هیدرولیکی ستون خاک غیراشباع انجام شد. میانگین تغذیه محاسبه‌شده برای کل محدوده با مدل HYDRUS-1D برابر با 33/291 میلیون مترمکعب و با روش نوسانات سطح ایستابی برابر با 68/204 میلیون مترمکعب به‌دست آمد که اختلافی معادل 7/29 درصد را نشان می‌دهد. علت این اختلاف را می‌توان به تفاوت در اصول و فرضیات پایه‌ای دو روش نسبت داد، به‌طوری‌که مدل HYDRUS-1D با حل معادله ریچاردز و درنظرگرفتن پارامترهای هیدرولیکی خاک و شرایط مرزی، فرایند نفوذ و تغذیه را در ناحیه غیراشباع به‌صورت دینامیکی شبیه‌سازی می‌کند، درحالی‌که روش نوسانات سطح ایستابی با اتکا به تغییرات تراز آب‌زیرزمینی و ذخیره‌سازی آن، تغذیه را به‌صورت غیرمستقیم و نسبت به دقت مشاهدات سطح آب‌زیرزمینی و آبدهی ویژه برآورد می‌نماید. نقشه‌های پهنه‌بندی نشان دادند که الگوی مکانی تغذیه منابع آب‌زیرزمینی در هر دو روش مشابه است. بررسی زمان تأخیر نفوذ آب در ناحیه غیراشباع نشان داد که این زمان در محدوده موردمطالعه بسته به بافت خاک و ضخامت ناحیه غیراشباع بین 30 تا 730 روز متغیر است. پیشنهاد می‌شود که در صورت وجود داده‌های لازم، روش‌های مختلف برای بررسی و ارزیابی تغذیه منابع آب‌زیرزمینی برای یک محدوده مورد استفاده قرار گیرد تا با تخمین و درک بهتر و دقیق‌تر این پارامتر مهم به مدیریت پایدار و استفاده از بهینه از منابع آب‌زیرزمینی دست یافت.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Estimation of groundwater recharge using water table fluctuation method and unsaturated zone flow simulation (Marvdasht aquifer, Fars province, Iran)

نویسندگان [English]

  • Mohammad Ghaffari-Sola 1
  • Hamed Ketabchi 1
  • Davood Mahmoodzadeh 2
1 Department of Water Engineering and Management, Tarbiat Modares University, Tehran, Iran.
2 School of Engineering, University of Northern British Columbia, British Columbia, Canada.
چکیده [English]

Groundwater recharge in the Marvdasht aquifer was estimated using two approaches: the water table fluctuation (WTF) method and unsaturated zone flow simulation with the HYDRUS-1D model. In the first approach, recharge was calculated based on variations in groundwater level and specific yield, whereas in the second approach, it was estimated using soil column hydraulic properties within the unsaturated zone. The average recharge for the entire study area was estimated at 291.33 million cubic meters using HYDRUS-1D and 204.68 million cubic meters using the WTF method, indicating a difference of 29.7%. This discrepancy can be attributed to the fundamental differences in the assumptions underlying the two approaches. HYDRUS-1D simulates infiltration and recharge dynamically by solving Richards’ equation and considering the soil hydraulic parameters and boundary conditions, while the WTF method indirectly estimates recharge based on groundwater level fluctuations and specific yield, and is therefore sensitive to the accuracy of these observations. Zonation maps revealed that both methods produced similar spatial recharge patterns. Moreover, analysis of water infiltration delay through the unsaturated zone indicated that the lag time varied between 30 and 730 days, depending on soil texture and the thickness of the unsaturated zone. It is recommended that, where data availability permits, multiple methods be applied to assess groundwater recharge, thereby obtaining more reliable estimates of this critical parameter and supporting sustainable management and optimal utilization of groundwater resources.

کلیدواژه‌ها [English]

  • Marvdasht aquifer
  • Groundwater recharge estimation
  • Unsaturated zone flow simulation
  • Water table fluctuation method

مراجع

  1. Addisie, M. B. (2022). Groundwater recharge estimation using water table fluctuation and empirical methods. H2Open Journal, 5(3), 457–468. https://doi.org/10.2166/h2oj.2022.026
  2. Arjmand Sharif, M., & Jafari, H. (2021). Estimation of Groundwater Recharge Lag Time in Mashhad-Chenaran Aquifer Using Cross-Correlation Method. Water and Soil, 35(4), 489-504. doi: 10.22067/jsw.2021.70672.1058. (In Persion).
  3. Cai, Z., & Ofterdinger, U. (2016). Analysis of groundwater-level response to rainfall and estimation of annual recharge in fractured hard rock aquifers, NW Ireland. Journal of Hydrology, 535, 71–84. https://doi.org/10.1016/j.jhydrol.2016.01.066
  4. Chae, G. T., Yun, S. T., Kim, D. S., Kim, K. H., & Joo, Y. (2010). Time-series analysis of three years of groundwater level data (Seoul, South Korea) to characterize urban groundwater recharge. Quarterly Journal of Engineering Geology and Hydrogeology, 43(1), 117–127. https://doi.org/10.1144/1470-9236/07-056
  5. Dandekar, A. T., Singh, D. K., Sarangi, A., & Singh, A. K. (2018). Modelling vadose zone processes for assessing groundwater recharge in semi-arid region. Current Science, 114(3), 608–618. https://doi.org/10.18520/cs/v114/i03/608-618
  6. De Silva, C. (2015). Simulation of Potential Groundwater Recharge from the Jaffna Peninsula of Sri Lanka using HYDRUS-1D Model. OUSL Journal, 7. https://doi.org/10.4038/ouslj.v7i0.7307
  7. Du, Q., & Ross, M. (2024). Timescale of Groundwater Recharge in High Percolation Coastal Plain Soils. Water (Switzerland), 16(10). https://doi.org/10.3390/w16101320
  8. Fijani, E., Meysami, S., & Mozafari, M. (2023). 'Evaluation of Potential and the Amounts of Groundwater Recharge in the Garmsar Plain Aquifer Using Water Table Fluctuations and Piscopo Methods', Ferdowsi Civil Engineering, 36(1), pp. 1-18. doi: 10.22067/jfcei.2022.77818.1169. (In Persion).
  9. Ghaffari-Sola, M., Ketabchi, H., & Mahmoodzadeh, D. (2025). 'Groundwater withdrawal management measures using a finite difference mathematical model: A case study of Marvdasht aquifer in Fars province', Iranian Journal of Soil and Water Research, 56(6), 1265-1288. doi: 10.22059/ijswr.2025.390956.669888. (In Persion).
  10. Ghafari, H., Rasoulzadeh, A., Raoof, M., & Esmeali, A. (2018). 'Estimation of Natural Groundwater Recharge using WTF Method (Case Study: Ardabil Plain Aquifer)', Journal of Civil and Environmental Engineering, 48(90), pp. 43-52. doi: 10.22034/ceej.2018.7576. (In Persion).
  11. Grismer, M. (2013). Estimating agricultural deep drainage lag times to groundwater: Application to Antelope Valley, California, USA. Hydrological Processes, 27, 378–393. https://doi.org/10.1002/hyp.9249
  12. Healy, R.W. (2010). Estimating groundwater recharge. Cambridge University Press. https://doi.org/10.1017/CBO9780511780745
  13. Healy, R. W., & Cook, P. G. (2002). Using groundwater levels to estimate recharge. Hydrogeology Journal, 10(1), 91–109. https://doi.org/10.1007/s10040-001-0178-0
  14. Hung Vu, V., & Merkel, B. J. (2019). Estimating groundwater recharge for Hanoi, Vietnam. Science of the Total Environment, 651, 1047–1057. https://doi.org/10.1016/j.scitotenv.2018.09.225
  15. Jie, F., Fei, L., Li, S., Hao, K., Liu, L., & Li, J. (2022). Journal of Hydrology : Regional Studies Quantitative effects of vadose zone thickness on delayed recharge of groundwater for an irrigation district in an arid area of Northwest China. Journal of Hydrology: Regional Studies, 40(February), 101022. https://doi.org/10.1016/j.ejrh.2022.101022
  16. Labrecque, G., Chesnaux, R., & Boucher, M. A. (2020). Water-table fluctuation method for assessing aquifer recharge: application to Canadian aquifers and comparison with other methods. Hydrogeology Journal, 28(2), 521–533. https://doi.org/10.1007/s10040-019-02073-1
  17. Larijani, S., Noori, H., & Ebrahimian, H. (2017). Estimating Groundwater Recharge by HYDRUS-1D Model (Case Study: Hashtgerd). Iranian Journal of Irrigation & Drainage, 11(4), 572-585. (In Persion).
  18. Mali, S. S., Scobie, M., Schmidt, E., Okwany, R. O., Kumar, A., Islam, A., & Bhatt, B. P. (2021). Modelling vadose zone flows and groundwater dynamics of alluvial aquifers in Eastern Gangetic Plains of India: evaluating the effects of agricultural intensification. Environmental Earth Sciences, 80(18). https://doi.org/10.1007/s12665-021-09915-w
  19. Min, L., Shen, Y., & Pei, H. (2015). Estimating groundwater recharge using deep vadose zone data under typical irrigated cropland in the piedmont region of the North China Plain Estimating groundwater recharge using deep vadose zone data under typical irrigated cropland in the piedmont regio. May 2019. https://doi.org/10.1016/j.jhydrol.2015.04.064
  20. Nogueira, G. E. H., & Gonçalves, R. D. (2022). Groundwater recharge in phreatic aquifers, a case study: modeling unsaturated zone and recharge rates of the Rio Claro Aquifer using Hydrus-1D. Holos Environment, 21(3), 402–422. https://doi.org/10.14295/holos.v21i3.12455
  21. Nazarieh, F., Ansari, H., Ziaei, A. N., Izady, A., Davari, K., & Brunner, P. (2018). Spatial and temporal dynamics of deep percolation, lag time and recharge in an irrigated semi-arid region. Hydrogeology Journal, 26(7), 2507–2520. https://doi.org/10.1007/s10040-018-1789-z
  22. Nugraha, G. U., Lubis, R. F., Bakti, H., & Hartanto, P. (2021). Groundwater Recharge Estimation Using Water Budget and Water Table Fluctuation Method in the Jakarta Groundwater Basin, 1(1), 25–38. https://doi.org/10.51835/iagij.2021.1.1.12
  23. Rassam, D., Šimůnek, J., Mallants, D., & van Genuchten, M. T. (2018). The HYDRUS-1D software package for simulating the movement of water, heat, and multiple solutes in variably-saturated media: Tutorial, version 1.00. In CSIRO Land and Water, Australia (Issue July).
  24. Scheiffele, L. M., Munz, M., Francke, T., Baroni, G., & Sascha, E. (2024). Enhancing hectare-scale groundwater recharge estimation by integrating data from cosmic-ray neutron sensing into soil hydrological modelling cosmic-ray neutron sensing into soil hydrological modelling Key Points.
  25. Seeboonruang, U. (2015). An application of time-lag regression technique for assessment of groundwater fluctuations in a regulated river basin: a case study in Northeastern Thailand. Environmental Earth Sciences, 73(10), 6511–6523. https://doi.org/10.1007/s12665-014-3872-7
  26. Šimůnek, J., M. Šejna, G. Brunetti, and M. Th. van Genuchten, The HYDRUS Software Package for Simulating One-, Two-, and Three-Dimensional Movement of Water, Heat, and Multiple Solutes in Variably-Saturated Porous Media, Technical Manual I, Hydrus 1D, Version 5.x, PC Progress, Prague, Czech Republic, 334 pp., 2022.
  27. Simunek Jirka, J., Šejna, M., Saito, H., Sakai, M., & Van Genuchten, M. (2013). The Hydrus-1D Software Package for Simulating the Movement of Water, Heat, and Multiple Solutes in Variably Saturated Media, Version 4.17, HYDRUS Software Series 3, Department of Environmental Sciences, University of California Riverside, Riverside, Calif. USA.
  28. Xue, D., Dai, H., Liu, Y., Liu, Y., Zhang, L., & Lv, W. (2022). Interaction Simulation of Vadose Zone Water and Groundwater in Cele Oasis: Assessment of the Impact of Agricultural Intensification, Northwestern China. Agriculture (Switzerland), 12(5). https://doi.org/10.3390/agriculture12050641
مدیریت آب و آبیاری
دوره 15، شماره 3
آذر 1404
صفحه 585-605

فایل ها

هم رسانی

ارجاع به این مقاله

آمار