IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i12p5618-d1681965.html
   My bibliography  Save this article

Estimation of Groundwater Abstractions from Irrigation Wells in Mediterranean Agriculture: An Ensemble Approach Integrating Remote Sensing, Soil Water Balance, and Spatial Analysis

Author

Listed:
  • Luís Catarino

    (Instituto Superior de Agronomia, University of Lisbon, Tapada da Ajuda, 1349-017 Lisbon, Portugal)

  • João Rolim

    (A LEAF-Linking Landscape, Environment, Agriculture and Food-Research Center, Associated Laboratory TERRA, Instituto Superior de Agronomia, School of Agriculture, University of Lisbon, Tapada da Ajuda, 1349-017 Lisbon, Portugal)

  • Paula Paredes

    (A LEAF-Linking Landscape, Environment, Agriculture and Food-Research Center, Associated Laboratory TERRA, Instituto Superior de Agronomia, School of Agriculture, University of Lisbon, Tapada da Ajuda, 1349-017 Lisbon, Portugal)

  • Maria do Rosário Cameira

    (A LEAF-Linking Landscape, Environment, Agriculture and Food-Research Center, Associated Laboratory TERRA, Instituto Superior de Agronomia, School of Agriculture, University of Lisbon, Tapada da Ajuda, 1349-017 Lisbon, Portugal)

Abstract

This study presents a robust methodology for the indirect estimation of groundwater abstraction for irrigation at the scale of individual wells, addressing a key gap in data-scarce agricultural settings. The approach combines NDVI time series, crop water requirement modelling, and spatial analysis of irrigation systems within a GIS environment. A soil water balance model was applied to Homogeneous Units of Analysis, and irrigation requirements were estimated using an ensemble approach accounting for key sources of uncertainty related to phenology detection, soil moisture at sowing (%SAW), and irrigation system efficiency. A spatial linkage algorithm was developed to associate individual wells with the irrigated areas they supply. Sensitivity analysis demonstrated that 10% increases in %SAW resulted in abstraction reductions of up to 1.98%, while 10% increases in irrigation efficiency reduced abstractions by an average of 6.48%. These findings support the inclusion of both parameters in the ensemble, generating eight abstraction estimates per well. Values ranged from 33,000 to 115,000 m 3 for the 2023 season. Validation against flowmeter data confirmed the method’s reliability, with an R 2 of 0.918 and an RMSE equivalent to 9.3% of the mean observations. This approach offers an accurate, spatially explicit estimation of groundwater abstractions without requiring direct metering and offers a transferable, cost-effective tool to improve groundwater accounting and governance in regions with limited monitoring infrastructure.

Suggested Citation

  • Luís Catarino & João Rolim & Paula Paredes & Maria do Rosário Cameira, 2025. "Estimation of Groundwater Abstractions from Irrigation Wells in Mediterranean Agriculture: An Ensemble Approach Integrating Remote Sensing, Soil Water Balance, and Spatial Analysis," Sustainability, MDPI, vol. 17(12), pages 1-26, June.
  • Handle: RePEc:gam:jsusta:v:17:y:2025:i:12:p:5618-:d:1681965
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/12/5618/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/17/12/5618/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jolijn Engelenburg & Rosa Hueting & Sjoerd Rijpkema & Adriaan J. Teuling & Remko Uijlenhoet & Fulco Ludwig, 2018. "Impact of Changes in Groundwater Extractions and Climate Change on Groundwater-Dependent Ecosystems in a Complex Hydrogeological Setting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(1), pages 259-272, January.
    2. Yifru, Bisrat Ayalew & Lee, Seoro & Bak, Sangjoon & Bae, Joo Hyun & Shin, Hyungjin & Lim, Kyoung Jae, 2024. "Estimating exploitable groundwater for agricultural use under environmental flow constraints using an integrated SWAT-MODFLOW model," Agricultural Water Management, Elsevier, vol. 303(C).
    3. Pereira, L.S. & Paredes, P. & López-Urrea, R. & Hunsaker, D.J. & Mota, M. & Mohammadi Shad, Z., 2021. "Standard single and basal crop coefficients for vegetable crops, an update of FAO56 crop water requirements approach," Agricultural Water Management, Elsevier, vol. 243(C).
    4. Li, He & Miao, Qingfeng & Shi, Haibin & Li, Xianyue & Zhang, Shengwei & Zhang, Fengxia & Bu, Huailiang & Wang, Pei & Yang, Lin & Wang, Yali & Du, Heng & Wang, Tong & Feng, Weiying, 2024. "Remote sensing monitoring of irrigated area in the non-growth season and of water consumption analysis in a large-scale irrigation district," Agricultural Water Management, Elsevier, vol. 303(C).
    5. Dhungel, Ramesh & Aiken, Robert & Lin, Xiaomao & Kenyon, Shannon & Colaizzi, Paul D. & Luhman, Ray & Baumhardt, R. Louis & O’Brien, Dan & Kutikoff, Seth & Brauer, David K., 2020. "Restricted water allocations: Landscape-scale energy balance simulations and adjustments in agricultural water applications," Agricultural Water Management, Elsevier, vol. 227(C).
    6. Serra, J. & Paredes, P. & Cordovil, CMdS & Cruz, S. & Hutchings, NJ & Cameira, MR, 2023. "Is irrigation water an overlooked source of nitrogen in agriculture?," Agricultural Water Management, Elsevier, vol. 278(C).
    7. Zipper, Sam & Kastens, Jude & Foster, Timothy & Wilson, Blake B. & Melton, Forrest & Grinstead, Ashley & Deines, Jillian M. & Butler, James J. & Marston, Landon T., 2024. "Estimating irrigation water use from remotely sensed evapotranspiration data: Accuracy and uncertainties at field, water right, and regional scales," Agricultural Water Management, Elsevier, vol. 303(C).
    8. Hunink, Johannes E. & Contreras, Sergio & Soto-García, Mariano & Martin-Gorriz, Bernardo & Martinez-Álvarez, Victoriano & Baille, Alain, 2015. "Estimating groundwater use patterns of perennial and seasonal crops in a Mediterranean irrigation scheme, using remote sensing," Agricultural Water Management, Elsevier, vol. 162(C), pages 47-56.
    9. Pereira, L.S. & Paredes, P. & Hunsaker, D.J. & López-Urrea, R. & Mohammadi Shad, Z., 2021. "Standard single and basal crop coefficients for field crops. Updates and advances to the FAO56 crop water requirements method," Agricultural Water Management, Elsevier, vol. 243(C).
    10. French, Andrew N. & Sanchez, Charles A. & Wirth, Troy & Scott, Andrew & Shields, John W. & Bautista, Eduardo & Saber, Mazin N. & Wisniewski, Elzbieta & Gohardoust, Mohammadreza R., 2023. "Remote sensing of evapotranspiration for irrigated crops at Yuma, Arizona, USA," Agricultural Water Management, Elsevier, vol. 290(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. Darouich, Hanaa & Karfoul, Razan & Ramos, Tiago B. & Moustafa, Ali & Shaheen, Baraa & Pereira, Luis S., 2021. "Crop water requirements and crop coefficients for jute mallow (Corchorus olitorius L.) using the SIMDualKc model and assessing irrigation strategies for the Syrian Akkar region," Agricultural Water Management, Elsevier, vol. 255(C).
    2. Pereira, L.S. & Paredes, P. & Melton, F. & Johnson, L. & Mota, M. & Wang, T., 2021. "Prediction of crop coefficients from fraction of ground cover and height: Practical application to vegetable, field and fruit crops with focus on parameterization," Agricultural Water Management, Elsevier, vol. 252(C).
    3. Ebtessam A. Youssef & Marwa M. Abdelbaset & Osama M. Dewedar & José Miguel Molina-Martínez & Ahmed F. El-Shafie, 2023. "Crop Coefficient Estimation and Effect of Abscisic Acid on Red Cabbage Plants ( Brassica oleracea var. Capitata) under Water-Stress Conditions," Agriculture, MDPI, vol. 13(3), pages 1-16, March.
    4. Serra, J. & Paredes, P. & Cordovil, CMdS & Cruz, S. & Hutchings, NJ & Cameira, MR, 2023. "Is irrigation water an overlooked source of nitrogen in agriculture?," Agricultural Water Management, Elsevier, vol. 278(C).
    5. 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).
    6. Paredes, Paula & Trigo, Isabel & de Bruin, Henk & Simões, Nuno & Pereira, Luis S., 2021. "Daily grass reference evapotranspiration with Meteosat Second Generation shortwave radiation and reference ET products," Agricultural Water Management, Elsevier, vol. 248(C).
    7. Tamimi, Mansoor Al & Green, Steve & Hammami, Zied & Ammar, Khalil & Ketbi, Mouza Al & Al-Shrouf, Ali M. & Dawoud, Mohamed & Kennedy, Lesley & Clothier, Brent, 2022. "Evapotranspiration and crop coefficients using lysimeter measurements for food crops in the hyper-arid United Arab Emirates," Agricultural Water Management, Elsevier, vol. 272(C).
    8. Qin, Shujing & Li, Sien & Cheng, Lei & Zhang, Lu & Qiu, Rangjian & Liu, Pan & Xi, Haiyang, 2023. "Partitioning evapotranspiration in partially mulched interplanted croplands by improving the Shuttleworth-Wallace model," Agricultural Water Management, Elsevier, vol. 276(C).
    9. Zhao, Xiaole & Mak-Mensah, Erastus & Zhao, Wucheng & Wang, Qi & Zhou, Xujiao & Zhang, Dengkui & Zhu, Jinhui & Qi, Wenjia & Liu, Qinglin & Li, Xiaoling & Li, Xuchun & Liu, Bing, 2024. "Optimized ridge-furrow technology with biochar amendment for alfalfa yield enhancement and soil erosion reduction based on a structural equation model on sloping land," Agricultural Water Management, Elsevier, vol. 298(C).
    10. McNamara, Ian & Flörke, Martina & Uschan, Thorben & Baez-Villanueva, Oscar M. & Herrmann, Frank, 2024. "Estimates of irrigation requirements throughout Germany under varying climatic conditions," Agricultural Water Management, Elsevier, vol. 291(C).
    11. Martínez-Romero, A. & López-Urrea, R. & Montoya, F. & Pardo, J.J. & Domínguez, A., 2021. "Optimization of irrigation scheduling for barley crop, combining AquaCrop and MOPECO models to simulate various water-deficit regimes," Agricultural Water Management, Elsevier, vol. 258(C).
    12. Mashabatu, Munashe & Ntshidi, Zanele & Dzikiti, Sebinasi & Jovanovic, Nebojsa & Dube, Timothy & Taylor, Nicky J., 2023. "Deriving crop coefficients for evergreen and deciduous fruit orchards in South Africa using the fraction of vegetation cover and tree height data," Agricultural Water Management, Elsevier, vol. 286(C).
    13. Yuanzhen Zhang & Guofang Wang & Lingzhi Li & Mingjing Huang, 2025. "A Monitoring Method for Agricultural Soil Moisture Using Wireless Sensors and the Biswas Model," Agriculture, MDPI, vol. 15(3), pages 1-18, February.
    14. He, Rui & He, Min & Xu, Haidong & Zhang, Kun & Zhang, Mingcai & Ren, Dan & Li, Zhaohu & Zhou, Yuyi & Duan, Liusheng, 2023. "A novel plant growth regulator brazide improved maize water productivity in the arid region of Northwest China," Agricultural Water Management, Elsevier, vol. 287(C).
    15. Ramos, Tiago B. & Darouich, Hanaa & Oliveira, Ana R. & Farzamian, Mohammad & Monteiro, Tomás & Castanheira, Nádia & Paz, Ana & Gonçalves, Maria C. & Pereira, Luís S., 2023. "Water use and soil water balance of Mediterranean tree crops assessed with the SIMDualKc model in orchards of southern Portugal," Agricultural Water Management, Elsevier, vol. 279(C).
    16. Ahmed, A.A. Masrur & Wang, Quan J. & Western, Andrew W. & Graham, Tristan D.J. & Wu, Wenyan, 2024. "Monthly disaggregation of annual irrigation water demand in the southern Murray Darling Basin," Agricultural Water Management, Elsevier, vol. 302(C).
    17. Liebhard, Gunther & Klik, Andreas & Neugschwandtner, Reinhard W. & Nolz, Reinhard, 2022. "Effects of tillage systems on soil water distribution, crop development, and evaporation and transpiration rates of soybean," Agricultural Water Management, Elsevier, vol. 269(C).
    18. Chia, Min Yan & Huang, Yuk Feng & Koo, Chai Hoon, 2022. "Resolving data-hungry nature of machine learning reference evapotranspiration estimating models using inter-model ensembles with various data management schemes," Agricultural Water Management, Elsevier, vol. 261(C).
    19. Gu, Ruidan & He, Huaxiang & Chen, He & Tian, Jiake, 2025. "Study on hierarchical regulation of crop irrigation threshold under severe drought conditions," Agricultural Water Management, Elsevier, vol. 307(C).
    20. Rallo, G. & Paço, T.A. & Paredes, P. & Puig-Sirera, À. & Massai, R. & Provenzano, G. & Pereira, L.S., 2021. "Updated single and dual crop coefficients for tree and vine fruit crops," Agricultural Water Management, Elsevier, vol. 250(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:gam:jsusta:v:17:y:2025:i:12:p:5618-:d:1681965. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.