Estimating water productivity of center-pivot irrigation systems using the WaPOR (Case study: Moghan plain)

AziziMobaser, Javanshir; Heydari Ali Kamar, Mahsa; Amirzadeh, Arash; Kohan, Mohammad Reza; Rasoulzadeh, Ali; Raoof, Majid; Ramezani Moghadam, Javad

doi:10.22098/mmws.2025.17934.1635

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	Estimating water productivity of center-pivot irrigation systems using the WaPOR (Case study: Moghan plain)
مدل سازی و مدیریت آب و خاک
مقاله 11، دوره 5، شماره 4، 1404، صفحه 174-190 اصل مقاله (1.43 M)
نوع مقاله: پژوهشی
شناسه دیجیتال (DOI): 10.22098/mmws.2025.17934.1635
نویسندگان
Javanshir AziziMobaser^* ¹؛ Mahsa Heydari Ali Kamar²؛ Arash Amirzadeh³؛ Mohammad Reza Kohan⁴؛ Ali Rasoulzadeh⁵؛ Majid Raoof⁵؛ Javad Ramezani Moghadam¹
¹Associate Professor, Department of Water Engineering, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran
²PhD student, Department of Water Engineering, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran
³Ph.D. Student., Department of Water Engineering, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran
⁴PhD student in Water Science and Engineering, Faculty of Agriculture and Natural Resources, Mohaghegh Ardabili University, Ardabil, Iran
⁵Professor, Department of Water Engineering and and Member of Water Management Research Center, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran
چکیده
Water productivity is essential for sustainable agriculture, especially in semi-arid regions with limited water resources. This study evaluates Net Biomass Water Productivity (NBWP) and Gross Biomass Water Productivity (GBWP) in three agricultural fields (P, Q, and R) cultivating silage maize under center pivot irrigation from 2020 to 2024. Ground measurements of irrigation depth, crop yield, and evapotranspiration, combined with temperature and precipitation data, were analyzed to understand temporal variations and the impact of environmental and management factors. Results showed a consistent increase in NBWP across all fields, with Field Q achieving the highest gain (39%), likely due to advanced irrigation techniques and better adaptation to climatic conditions. GBWP, however, fluctuated more significantly, with declines in 2021 coinciding with severe drought and elevated temperatures, highlighting maize sensitivity to water and heat stress. Field R was most affected during this period, reflecting the importance of targeted drought mitigation. Comparison between field data and WaPOR satellite-based estimates revealed systematic underestimation by the portal, attributed to its coarse spatial resolution and inability to capture localized agronomic practices, such as crop rotation and irrigation scheduling. The study also identified uniform irrigation rates applied throughout the crop cycle, ignoring the dynamic water demands during different growth stages. This led to over-irrigation during maturity and under-irrigation during critical reproductive phases, exacerbating water stress under high temperatures. The findings emphasize the necessity of integrating precise field measurements with remote sensing data for accurate water productivity assessment. Implementing stage-specific irrigation management can optimize water use efficiency and maintain crop biomass production under varying climatic conditions. This research provides valuable insights for improving irrigation strategies and water resource management, contributing to agricultural resilience in water-scarce semi-arid environments facing climate variability.
کلیدواژه‌ها
Water Efficiency؛ Remote Sensing؛ GBWP؛ NBWP؛ Evapotranspiration

مراجع
References Abdiaghdam Laromi, F. , Rasoulzade, A. , Ghavidel, A. , Torabi Giglou, M. and Azizi Mobaser, J. (2023). Effects of Using Agricultural Drainage Water on Chemical, Biological, and Physical Properties of Soil and Yield of Tomato in Moghan Plain, Iran. Irrigation Sciences and Engineering, 46(4), 13-27. doi: 10.22055/jise.2023.39612.2011 Akhavan, K. , Abbassi, N. , kheiry Ghoujeh biglou, M. and Ahmadpari, H. (2021). Investigation on Conveyance Efficiency and Operation Issues of Precast Concrete Channels (Canalette) in Moghan Irrigation Network. Irrigation and Drainage Structures Engineering Research, 22(83), 21-42. doi: 10.22092/idser.2021.354260.1470 Akhavan Giglou, A., Ebrahimi, M., & Ghanbari, A. (2023). Evaluation of water productivity for major crops under semi-arid climate in the Moghan plain. Agricultural Water Management, 285, 108342. doi: 10.1016/j.agwat.2023.108342 Al-Bakri, J. T., D’Urso, G., Calera, A., Abdalhaq, E., Altarawneh, M., & Margane, A. (2022). Remote sensing for agricultural water management in Jordan. Remote Sensing, 15(1), 235. doi: 10.3390/rs15010235 Allen, R.G., Pereira, L.S., Raes, D., & Smith, M. (1998). Crop evapotranspiration - Guidelines for computing crop water requirements. FAO Irrigation and drainage paper 56. FAO, Rome, Italy. Angus, J. F., & Van Herwaarden, A. F. (2001). Increasing water use and water use efficiency in dryland wheat. Agronomy Journal, 93(2), 290-298. doi: 10.2134/agronj2001.932290x Bastiaanssen, W. G. M., Cheema, M. J. M., Immerzeel, W. W., Miltenburg, I. J., & Pelgrum, H. J. W. R. R. (2012). Surface energy balance and actual evapotranspiration of the transboundary Indus Basin estimated from satellite measurements and the ETLook model. Water Resources Research, 48(11). doi: 10.1029/2011WR010482 Bastiaanssen, W.G.M., Allen, R.G., Droogers, P., D'Urso, G., Steduto, P., 2007. Twenty-five years modeling irrigated and drained soils: State of the art. Agricultural Water Management 92, 111-125. doi: 10.1016/j.agwat.2007.05.013 Blatchford, M. L., Mannaerts, C. M., Zeng, Y., Nouri, H., & Karimi, P. (2020). Status of accuracy in remotely sensed and in-situ agricultural water productivity estimates: A review. Remote Sensing of Environment, 234, 111413. doi: 10.1016/j.rse.2019.111413 Blatchford, M., M. Mannaerts, C., Zeng, Y., Nouri, H., & Karimi, P. (2020). Influence of spatial resolution on remote sensing-based irrigation performance assessment using WaPOR data. Remote sensing, 12(18), 2949.‏ doi: 10.3390/rs12182949 Burt, C.M., Clemmens, A.J., Strelkoff, T.S., Solomon, K.H., Bliesner, R.D., Hardy, L.A., Howell, T.A., Eisenhauer, D.E., 1997. Irrigation performance measures: Efficiency and uniformity. Journal of Irrigation and Drainage Engineering 123, 423-442. doi: 10.1061/(ASCE)0733-9437(1997)123:6(423) Chiraz, M. C., Olfa, M. A. R. R. A. K. C. H. I., & Hamadi, H. A. B. A. I. E. B. (2022). Remote sensing and soil moisture data for water productivity determination. Agricultural Water Management, 263, 107482. doi: 10.1016/j.agwat.2022.107482 Choopan, Y., & Emami, S. (2020). An approach to reduce water consumption by optimizing and determining of crop cultivation pattern using meta-heuristic algorithms: A case study on Moghan plain. Journal of Applied Research in Water and Wastewater, 7(1), 48-56. doi: 10.22126/arww.2020.4076.1119 Choudhury, I., & Bhattacharya, B. (2018). An assessment of satellite-based agricultural water productivity over the Indian region. International Journal of Remote Sensing, 39(8), 2294–2311. doi: 10.1080/01431161.2017.1421792 Chukalla, A. D., Mul, M., van Halsema, G., van der Zaag, P., & Uyttendaele, T. (2022). Systematic framework for accuracy assessment of water productivity estimates from remote sensing products. Agricultural Water Management, 265, 107539. doi: 10.1016/j.agwat.2022.107539 Chukalla, A. D., van der Zaag, P., van Halsema, G., & Mul, M. (2023). Calibration and validation of evapotranspiration and biomass production in irrigated agriculture from remote sensing in the WaPOR database. Agricultural Water Management, 278, 108102. doi: 10.1016/j.agwat.2023.108102 Chukalla, A.D., Mul, M., van Halsema, G., van der Zaag, P., Uyttendaele, T., 2020. Exploring temporal variations of spatial differences in water productivity using FAO WaPOR data. Agricultural Water Management 241, 106852. doi: doi.org/10.1080/01431161.2017.1421792 Dinpashoh, Y., & Allahverdipour, P. (2025). Monitoring and predicting changes in reference evapotranspiration in the Moghan Plain according to CMIP6 of IPCC. Environment and Water Engineering, 11(1), 47-56. doi: 10.22034/ewe.2024.466037.1947 Fakhar, M. S., & Kaviani, A. (2024). Estimation of water consumption volume and water efficiency in irrigated and rainfed agriculture based on the WaPOR database in Iran. Journal of Water and Climate Change, 15(6), 2731-2752. doi: 10.2166/wcc.2024.655 FAO, 2018. WaPOR: The FAO portal to monitor Water Productivity through Open access of Remotely sensed derived data, Database User Manual Version 1.0. FAO, Rome. FAO, 2020. The State of Food and Agriculture 2020: Overcoming water challenges in agriculture. Rome. FAO. (2016a). Water accounting and auditing: A sourcebook. FAO Water Reports 43. Rome, Italy. FAO. (2020). WaPOR V2.0: The FAO portal to monitor Water Productivity through Open access of Remotely sensed derived data - Methodology. Rome, Italy. FAO. (2020a). WaPOR: The FAO portal to monitor Water Productivity through Open access of Remotely sensed derived data, Version 3. Food and Agriculture Organization of the United Nations. https://wapor.apps.fao.org FAO. (2020b). WaPOR V3 quality assessment - Technical report on the data quality of the WaPOR FAO database version 3. Rome. doi: 10.4060/cb3268en FAO. (2020c). WaPOR V3 methodology document - Technical specifications of the WaPOR database version 3. Rome. doi: 10.4060/cb2720en FAO. (2022). WaPOR V3 validation report - Analysis of the quality of remotely sensed data products in the WaPOR database version 3. Rome. doi: 10.4060/cb9721en Farahza, M., Bakhshandehmehr, L., & Shakiba, M. (2020). Impact of advanced irrigation systems on physical and economic water productivity in Moghan plain. Journal of Water and Soil, 34(4), 987–1000. doi: 10.22067/jsw.2020.43587 Feng, K., & Hubacek, K. (2015). A multi-region input–output analysis of global virtual water flows. In Handbook of research methods and applications in environmental studies (pp. 225-246). Edward Elgar Publishing. Franco, R. A., Hernandez, F. B., Teixeira, A. H. D. C., Leivas, J. F., Coaguila, D. N., & Neale, C. M. (2016, October). Water productivity mapping using Landsat 8 satellite together with weather stations. In Remote Sensing for Agriculture, Ecosystems, and Hydrology XVIII (Vol. 9998, pp. 482-493). SPIE. doi: 10.1117/12.2242003 Hanjra, M.A., Qureshi, M.E., 2010. Global water crisis and future food security in an era of climate change. Food Policy 35, 365-377. doi: 10.1016/j.foodpol.2010.05.006 Hoekstra, A.Y., Mekonnen, M.M., 2012. The water footprint of humanity. Proceedings of the National Academy of Sciences 109, 3232-3237. doi: 10.1073/pnas.1109936109 Irmak, S., Odhiambo, L.O., Kranz, W.L., Eisenhauer, D.E., 2011. Irrigation efficiency and uniformity, and crop water use efficiency. University of Nebraska-Lincoln Extension, EC732. Jägermeyr, J., Gerten, D., Heinke, J., Schaphoff, S., Kummu, M., Lucht, W., 2016. Water savings potentials of irrigation systems: Global simulation of processes and linkages. Hydrology and Earth System Sciences 20, 953-973. doi: 10.5194/hess-19-3073-2015 Karimi, P., Bastiaanssen, W.G.M., Molden, D., 2013. Water accounting plus (WA+) – a water accounting procedure for complex river basins based on satellite measurements. Hydrology and Earth System Sciences 17, 2459-2472. doi: 10.5194/hess-17-2459-2013 Kijne, J.W., Barker, R., & Molden, D. (2003). Water productivity in agriculture: Limits and opportunities for improvement. CABI Publishing, Wallingford, UK. doi: 10.1079/9780851996691.0000 Lamm, F.R., Aiken, R.M., Kheira, A.A.A., 2012. Corn yield and water use characteristics as affected by tillage, plant density, and irrigation. Transactions of the ASABE 55, 709-720. McCarthy, A.C., Hancock, N.H., Raine, S.R., 2014. Development and simulation of sensor-based irrigation control strategies for cotton using the VARIwise simulation framework. Computers and Electronics in Agriculture 101, 148-162. doi: 10.1016/j.compag.2013.12.014 Molden, D., Oweis, T., Steduto, P., Bindraban, P., Hanjra, M.A., & Kijne, J. (2010). Improving agricultural water productivity: Between optimism and caution. Agricultural Water Management, 97(4), 528-535. doi: 10.1016/j.agwat.2009.03.023 Mukandiwa, B., Gumindoga, W., Rwasoka, D. T., & Chikwiramakomo, L. (2025). Estimating Crop Water Productivity Using Remote Sensing Data at Plot Scale in an Irrigation System: The Case of Chisumbanje and Ratelshoek Estate. In Enhancing Water and Food Security Through Improved Agricultural Water Productivity: New Knowledge, Innovations and Applications (pp. 139-163). Singapore: Springer Nature Singapore. doi: 10.1007/978-981-96-1848-4 Mul, M., & Bastiaanssen, W. G. M. (2019). WaPOR quality assessment: Technical report on the data quality of the WaPOR FAO database version 1.0. FAO, Rome. doi: 10.4060/ca4895en Mul, M., Karimi, P., Coerver, H. M., Pareeth, S., Hunink, J. E., & Kaune, A. (2021). Water productivity from local to basin scale: Methodology and analysis using the WaPOR database. Agricultural Water Management, 253, 106908. doi: 10.1016/j.agwat.2021.106908 Nazari, B., Liaghat, A., Akbari, M. R., & Keshavarz, M. (2018). Irrigation water management in Iran: Implications for water use efficiency improvement. Agricultural Water Management, 204, 53-64. doi: 10.1016/j.agwat.2018.06.003 O'Brien, D.M., Lamm, F.R., Stone, L.R., Rogers, D.H., 2010. Corn yields and profitability for low-capacity irrigation systems. Applied Engineering in Agriculture 27, 1013-1020. Parchami-Araghi, A., Shirani, A. H., & Nazemi, A. (2022). Water productivity of soybean under different irrigation scenarios in Moghan irrigation district. Iranian Journal of Soil and Water Research, 53(3), 583–595. doi: 10.22067/jsw.2022.70389.1041 Patil, P., Biradar, C., Atassi, L., Moussadek, R., Kharrat, M., Singh, M., ... & Agrawal, S. K. (2015, July). Mapping and monitoring of food legumes and dryland cereal production systems. In 2015 Fourth International Conference on Agro-Geoinformatics (Agro-geoinformatics) (pp. 407-413). IEEE.‏ doi: 10.1109/Agro-Geoinformatics.2015.7248158 Patil, V. C., Al-Gaadi, K. A., Madugundu, R., Tola, E. H., Marey, S., Aldosari, A., ... & Gowda, P. H. (2014). Assessing agricultural water productivity in desert farming system of Saudi Arabia. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8(1), 284-297. doi: 10.1109/JSTARS.2014.2320592 Pelgrum, H., Miltenburg, I., Cheema, M., Klaasse, A., & Bastiaanssen, W. (2012, September). ETLook a novel continental evapotranspiration algorithm. In Remote Sensing and Hydrology Symposium, Jackson Hole, Wyoming, USA (Vol. 1085, p. 1087). Perry, C., 2011. Accounting for water use: Terminology and implications for saving water and increasing production. Agricultural Water Management 98, 1840-1846. doi: 10.1016/j.agwat.2010.10.002 Platonov, A., Thenkabail, P. S., Biradar, C. M., Cai, X., Gumma, M., Dheeravath, V., … Isaev, S. (2008). Water productivity mapping (WPM) using landsat ETM+ data for the irrigated croplands of the Syrdarya river basin in Central Asia. Sensors, 8(12), 8156–8180. doi: 10.3390/s8128156 Safi, C., Pareeth, S., Yalew, S., van der Zaag, P., & Mul, M. (2024). Estimating agricultural water productivity using remote sensing derived data. Modeling Earth Systems and Environment, 10(1), 1203-1213. doi: 10.1007/s40808-023-01841-z Seijger, C., Chukalla, A., Bremer, K., Borghuis, G., Christoforidou, M., Mul, M., ... & van Halsema, G. (2023). Agronomic analysis of WaPOR applications: Confirming conservative biomass water productivity in inherent and climatological variance of WaPOR data outputs. Agricultural Systems, 211, 103712. doi: 10.1016/j.agsy.2023.103712 Singh, P., Sehgal, V. K., Dhakar, R., Neale, C. M., Goncalves, I. Z., Rani, A., ... & Dubey, S. K. (2024). Estimation of ET and crop water productivity in a semi-arid region using a large aperture scintillometer and remote sensing-based SETMI model. Water, 16(3), 422. doi: 10.3390/w16030422 Steduto, P., Hsiao, T.C., & Fereres, E. (2007). On the conservative behavior of biomass water productivity. Irrigation Science, 25(3), 189-207. doi: 10.1007/s00271-007-0064-1 Steduto, P., Hsiao, T.C., Fereres, E., Raes, D., 2012. Crop yield response to water. FAO Irrigation and Drainage Paper No. 66. FAO, Rome. Torres-Cobo, L. E. (2024). Estrategias para el uso sostenible del agua en la agricultura. Horizon Nexus Journal, 2(4), 1-14. doi: 10.70881/hnj/v2/n4/40 Trout, T.J., DeJonge, K.C., 2017. Water productivity of maize in the US high plains. Irrigation Science 35, 251-266. doi: 10.1007/s00271-017-0540-1 United Nations Environment Programme (UNEP). (2021). Adaptation Gap Report 2021: The Gathering Storm – Adapting to climate change in a post-pandemic world. Nairobi: UNEP. van Halsema, G.E., Vincent, L., 2012. Efficiency and productivity terms for water management: A matter of contextual relativism versus general absolutism. Agricultural Water Management 108, 9-15. doi: 10.1016/j.agwat.2011.05.016 Veysi, S., Galehban, E., Nouri, M., Mallah, S., & Nouri, H. (2024). Comprehensive framework for interpretation of WaPOR water productivity. Heliyon, 10(16). doi: Wang, D., & Alimohammadi, N. (2012). Responses of annual runoff, evaporation, and storage change to climate variability at the watershed scale. Water Resources Research, 48(5). doi: 10.1029/2011WR011444 World Bank. (2022). Water security for all: The urgent need for climate-resilient water resources. Washington, DC: World Bank. Yari, A., Madramootoo, C.A., Woods, S.A., Adamchuk, V.I., 2017. Performance evaluation of constant versus variable rate irrigation. Irrigation and Drainage, 66, 501-509. doi: 10.1002/ird.2131 Zheng, H., Bian, Q., Yin, Y., Ying, H., Yang, Q., & Cui, Z. (2018). Closing water productivity gaps to achieve food and water security for a global maize supply. Scientific reports, 8(1), 14762. doi: 10.1038/s41598-018-32964-4 Zwart, S.J., Bastiaanssen, W.G.M., 2004. Review of measured crop water productivity values for irrigated wheat, rice, cotton and maize. Agricultural Water Management, 69, 115-133. doi: 10.1016/j.agwat.2004.04.007
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Estimating water productivity of center-pivot irrigation systems using the WaPOR (Case study: Moghan plain)