IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v36y2022i14d10.1007_s11269-022-03315-w.html
   My bibliography  Save this article

Determining Groundwater Recharge Rate with a Distributed Model and Remote Sensing Techniques

Author

Listed:
  • M. Babaei

    (Tarbiat Modares University)

  • H. Ketabchi

    (Tarbiat Modares University)

Abstract

Groundwater balance estimation techniques, as important tools for dealing with many hydrological problems, are one of the main issues in water resources management. One of the critical challenges in estimating the groundwater balance components is the uncertainty in the proposed inflow and outflow rates. Groundwater recharge rate varies both spatially and temporally, making direct measurement difficult. In order to reliably estimate the groundwater recharge rate in the groundwater balance equations, the uncertainties in estimation of the other components such as evapotranspiration (ET) should be reduced by estimating them using more accurate techniques such as remote sensing-based methods. The present study applies the WetSpass-M distributed model to the Rafsanjan aquifer in Kerman, Iran. This model has been run for eight years (2009–2016) with monthly time steps. The recorded monthly surface flow data of the hydrometric station is used as the observed data for calibration and validation. ET is also calculated with satellite images of Landsat8 by using SSEB and SEBAL algorithms on a monthly scale in order to evaluate the reliability of the estimated ET by the model. The average rainfall rate during the simulation period is 297.1 MCM/year. The obtained results showed that the average ET and groundwater recharge from rainfall is 185.1 and 102.1 MCM/year, respectively. Although, considering the rainfall rate and irrigation, these numbers are estimated to be 552.3 and 417.2 MCM/year, respectively. Two components of recharge rate and ET constitute large portions of the groundwater balance.

Suggested Citation

  • M. Babaei & H. Ketabchi, 2022. "Determining Groundwater Recharge Rate with a Distributed Model and Remote Sensing Techniques," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(14), pages 5401-5423, November.
    • Handle: RePEc:spr:waterr:v:36:y:2022:i:14:d:10.1007_s11269-022-03315-w
    DOI: 10.1007/s11269-022-03315-w
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11269-022-03315-w
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11269-022-03315-w?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Zwart, Sander J. & Bastiaanssen, Wim G.M., 2007. "SEBAL for detecting spatial variation of water productivity and scope for improvement in eight irrigated wheat systems," Agricultural Water Management, Elsevier, vol. 89(3), pages 287-296, May.
    2. Hydar Ebrahimi & Reza Ghazavi & Haji Karimi, 2016. "Estimation of Groundwater Recharge from the Rainfall and Irrigation in an Arid Environment Using Inverse Modeling Approach and RS," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(6), pages 1939-1951, April.
    3. Vishwakarma, Dinesh Kumar & Pandey, Kusum & Kaur, Arshdeep & Kushwaha, N.L. & Kumar, Rohitashw & Ali, Rawshan & Elbeltagi, Ahmed & Kuriqi, Alban, 2022. "Methods to estimate evapotranspiration in humid and subtropical climate conditions," Agricultural Water Management, Elsevier, vol. 261(C).
    4. Duncan, M.J. & Srinivasan, M.S. & McMillan, H., 2016. "Field measurement of groundwater recharge under irrigation in Canterbury, New Zealand, using drainage lysimeters," Agricultural Water Management, Elsevier, vol. 166(C), pages 17-32.
    5. Bispo, R.C. & Hernandez, F.B.T. & Gonçalves, I.Z. & Neale, C.M.U. & Teixeira, A.H.C., 2022. "Remote sensing based evapotranspiration modeling for sugarcane in Brazil using a hybrid approach," Agricultural Water Management, Elsevier, vol. 271(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Immerzeel, W.W. & Gaur, A. & Zwart, S.J., 2008. "Integrating remote sensing and a process-based hydrological model to evaluate water use and productivity in a south Indian catchment," Agricultural Water Management, Elsevier, vol. 95(1), pages 11-24, January.
    2. Li, Xiaolin & Tong, Ling & Niu, Jun & Kang, Shaozhong & Du, Taisheng & Li, Sien & Ding, Risheng, 2017. "Spatio-temporal distribution of irrigation water productivity and its driving factors for cereal crops in Hexi Corridor, Northwest China," Agricultural Water Management, Elsevier, vol. 179(C), pages 55-63.
    3. Cai, Ximing & Yang, Yi-Chen E. & Ringler, Claudia & Zhao, Jianshi & You, Liangzhi, 2011. "Agricultural water productivity assessment for the Yellow River Basin," Agricultural Water Management, Elsevier, vol. 98(8), pages 1297-1306, May.
    4. Zwart, Sander J. & Bastiaanssen, Wim G.M. & de Fraiture, Charlotte & Molden, David J., 2010. "WATPRO: A remote sensing based model for mapping water productivity of wheat," Agricultural Water Management, Elsevier, vol. 97(10), pages 1628-1636, October.
    5. Xiao, Chunan & Cai, Jiabing & Zhang, Baozhong & Chang, Hongfang & Wei, Zheng, 2023. "Evaluation and verification of two evapotranspiration models based on precision screening and partitioning of field temperature data," Agricultural Water Management, Elsevier, vol. 278(C).
    6. Beyene, Abebech & Cornelis, Wim & Verhoest, Niko E.C. & Tilahun, Seifu & Alamirew, Tena & Adgo, Enyew & De Pue, Jan & Nyssen, Jan, 2018. "Estimating the actual evapotranspiration and deep percolation in irrigated soils of a tropical floodplain, northwest Ethiopia," Agricultural Water Management, Elsevier, vol. 202(C), pages 42-56.
    7. Seijger, Chris & Chukalla, Abebe & Bremer, Karin & Borghuis, Gerlo & Christoforidou, Maria & Mul, Marloes & Hellegers, Petra & van Halsema, Gerardo, 2023. "Agronomic analysis of WaPOR applications: Confirming conservative biomass water productivity in inherent and climatological variance of WaPOR data outputs," Agricultural Systems, Elsevier, vol. 211(C).
    8. Awada, Hassan & Di Prima, Simone & Sirca, Costantino & Giadrossich, Filippo & Marras, Serena & Spano, Donatella & Pirastru, Mario, 2022. "A remote sensing and modeling integrated approach for constructing continuous time series of daily actual evapotranspiration," Agricultural Water Management, Elsevier, vol. 260(C).
    9. Fabiana Natali & Giacomo Branca, 2020. "On positive externalities from irrigated agriculture and their policy implications: An overview," Economia agro-alimentare, FrancoAngeli Editore, vol. 22(2), pages 1-25.
    10. Qiu, Rangjian & Li, Longan & Liu, Chunwei & Wang, Zhenchang & Zhang, Baozhong & Liu, Zhandong, 2022. "Evapotranspiration estimation using a modified crop coefficient model in a rotated rice-winter wheat system," Agricultural Water Management, Elsevier, vol. 264(C).
    11. Graham, Scott L. & Kochendorfer, John & McMillan, Andrew M.S. & Duncan, Maurice J. & Srinivasan, M.S. & Hertzog, Gladys, 2016. "Effects of agricultural management on measurements, prediction, and partitioning of evapotranspiration in irrigated grasslands," Agricultural Water Management, Elsevier, vol. 177(C), pages 340-347.
    12. Dench, William E. & Morgan, Leanne K., 2021. "Unintended consequences to groundwater from improved irrigation efficiency: Lessons from the Hinds-Rangitata Plain, New Zealand," Agricultural Water Management, Elsevier, vol. 245(C).
    13. Malik, Anurag & Jamei, Mehdi & Ali, Mumtaz & Prasad, Ramendra & Karbasi, Masoud & Yaseen, Zaher Mundher, 2022. "Multi-step daily forecasting of reference evapotranspiration for different climates of India: A modern multivariate complementary technique reinforced with ridge regression feature selection," Agricultural Water Management, Elsevier, vol. 272(C).
    14. Abdelaziz M. Okasha & Nehad Deraz & Adel H. Elmetwalli & Salah Elsayed & Mayadah W. Falah & Aitazaz Ahsan Farooque & Zaher Mundher Yaseen, 2022. "Effects of Irrigation Method and Water Flow Rate on Irrigation Performance, Soil Salinity, Yield, and Water Productivity of Cauliflower," Agriculture, MDPI, vol. 12(8), pages 1-18, August.
    15. Li, Zhouyuan & Liu, Xuehua & Ma, Tianxiao & Kejia, De & Zhou, Qingping & Yao, Bingquan & Niu, Tianlin, 2013. "Retrieval of the surface evapotranspiration patterns in the alpine grassland–wetland ecosystem applying SEBAL model in the source region of the Yellow River, China," Ecological Modelling, Elsevier, vol. 270(C), pages 64-75.
    16. C. Dionisio Pérez Blanco & Thomas Thaler, 2015. "Water Flows in the Economy. An Input-output Framework to Assess Water Productivity in the Castile and León Region (Spain)," Working Papers 2015.07, Fondazione Eni Enrico Mattei.
    17. Yousaf, Wasif & Awan, Wakas Karim & Kamran, Muhammad & Ahmad, Sajid Rashid & Bodla, Habib Ullah & Riaz, Mohammad & Umar, Muhammad & Chohan, Khurram, 2021. "A paradigm of GIS and remote sensing for crop water deficit assessment in near real time to improve irrigation distribution plan," Agricultural Water Management, Elsevier, vol. 243(C).
    18. Islam, AFM Tariqul & Islam, AKM Saiful & Islam, GM Tarekul & Bala, Sujit Kumar & Salehin, Mashfiqus & Choudhury, Apurba Kanti & Dey, Nepal C. & Mahboob, M. Golam, 2023. "Simulation of water productivity of wheat in northwestern Bangladesh using multi-satellite data," Agricultural Water Management, Elsevier, vol. 281(C).
    19. Doug J. Booker & Ton H. Snelder, 2023. "Climate change and local anthropogenic activities have altered river flow regimes across Canterbury, New Zealand," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(6), pages 2657-2674, May.
    20. Petra Hellegers & Richard Soppe & Chris Perry & Wim Bastiaanssen, 2010. "Remote Sensing and Economic Indicators for Supporting Water Resources Management Decisions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(11), pages 2419-2436, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:waterr:v:36:y:2022:i:14:d:10.1007_s11269-022-03315-w. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.