Improving Water Productivity Through Deficit Irrigation Using the SALTMED Model

Document Type : Research Paper

Authors

Department of Irrigation and Reclamation Engineering, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran.

Abstract

Increasing water demand due to population growth and climate change has led to the depletion of agricultural water resources in water-scarce regions. Accordingly, a field experiment was conducted over two consecutive seasons (2022 and 2023) at the Medicinal Plants Research Center, Islamic Azad University, Shahr-e Qods Branch. The objective of this study was to evaluate the effects of surface drip irrigation (SDI) and partial root zone drying (PRD), combined with three irrigation treatments (100%, 75%, and 55% of crop evapotranspiration), on lentil yield, and to assess the SALTMED model's performance in simulating soil moisture, total dry matter, and yield. Although the highest yields were obtained under full irrigation (100% ETc), no significant difference was observed between the 100% and 75% treatments. This suggests that a 25% reduction in water use can be achieved without compromising yield. Yield and water productivity under PRD were slightly higher than those under SDI, as PRD maintained soil moisture in the root zone for a longer period without exposing the crop to water stress. The SALTMED model accurately simulated soil moisture, total dry matter, yield, and water use efficiency. Therefore, it can serve as a valuable tool for crop, water, and land management under Iran's climatic conditions.

Keywords

Main Subjects

Introduction

Water scarcity is one of the major challenges facing agriculture today. This study evaluated the effects of surface drip irrigation (SDI) and partial root-zone drying (PRD) under different irrigation levels (100%, 75%, and 55% of crop evapotranspiration) on lentil growth, yield, and water productivity. The SALTMED model was used to simulate soil moisture, dry matter, and yield. Results aimed to identify a water-saving, cost-effective irrigation strategy suitable for drought-prone regions.

Material and methods

Field experiments were conducted during the 2022 and 2023 growing seasons at the research farm of Islamic Azad University, Shahre Ghods Branch, under a hot and dry climate. Soil samples were collected to 60 cm depth, and irrigation treatments were applied using surface drip and partial root-zone drying methods with three irrigation levels (100%, 75%, and 55% of crop water requirement) in a randomized complete block design. Meteorological data were recorded by a nearby weather station and ET₀ was calculated using the FAO Penman-Monteith equation. Lentil was sown in mid-September and harvested in early December. Soil moisture was measured using calibrated EnviroSCAN sensors, and crop yield and water productivity were assessed. Irrigation scheduling was based on a 3-day interval using climatic data, soil properties, and FAO recommendations for effective rainfall and leaching requirements. The SALTMED model was calibrated using observed soil moisture, dry matter, and yield under full irrigation, then validated using remaining treatments. Model performance was evaluated using R², RMSE, NRMSE, NSE, and CRM indices. Statistical analysis was conducted using SPSS and Duncan's test.

Result and Discussion

A strong correlation was observed between measured and simulated soil moisture in both 0.00–0.25 m and 0.25–0.50 m layers under full irrigation with surface drip and PRD methods, with simulated values closely matching the observed data. A high agreement was observed between measured and simulated soil moisture in both 0–25 cm and 25–50 cm layers under surface drip and partial root-zone drying irrigation. The minimal variation in soil moisture was attributed to frequent irrigation events that maintained high moisture levels in the root zone. Statistical performance indicators confirmed the model's accuracy and calibration quality, indicating its suitability for validation and application in soil water dynamics modeling under different irrigation strategies. Yield and total dry matter were successfully calibrated in both surface drip and PRD systems by adjusting crop growth parameters, showing strong agreement between observed and simulated values. Model validation for other treatments confirmed its accuracy, with good alignment between simulated and measured soil moisture, yield, and biomass. Soil moisture was lower in the upper layer due to surface evaporation, and PRD maintained higher moisture levels than surface drip across both seasons, likely due to reduced wetted area and lower evaporation losses. Statistical indices confirmed a strong correlation between observed and simulated soil moisture across all irrigation treatments and soil layers under both surface drip and PRD systems. The validation results demonstrated the model’s reliability and effectiveness in simulating soil water content under different irrigation methods. The irrigation system and water treatment levels had consistent effects on lentil yield and total dry matter in both seasons. The highest values were observed under full irrigation, while the lowest occurred under severe deficit irrigation in both surface drip and PRD systems. Yield and biomass reductions were mainly due to soil moisture deficiency, which limited photosynthesis and overall plant performance. In the 2022 and 2023 growing seasons, the model showed a strong correlation between observed and simulated yield and total dry matter under full irrigation for both surface drip and PRD systems, with minimal deviations. Across all irrigation treatments, simulated values closely matched observed data, indicating high model accuracy. Statistical indicators confirmed excellent agreement and low error rates, placing the model's performance in yield and biomass simulation within a highly reliable range. Water productivity, defined as crop yield per unit of irrigation water, showed similar trends across two seasons. The highest water productivity occurred under deficit irrigation treatments, with the partial root-zone drying method outperforming surface drip irrigation. Statistical analyses confirmed a strong correlation between observed and simulated water productivity, with low error margins and good model efficiency. Overall, the SALTMED model accurately simulated soil moisture, yield, dry matter, and water productivity for lentil under different irrigation levels in both irrigation systems.

Conclusion

The highest yield was obtained under the 100% crop water requirement treatment. However, the difference in yield between the 100% and 75% treatments was not statistically significant, indicating that irrigation with 75% of the plant’s water requirement does not impose significant water stress on lentil. Therefore, a 25% reduction in irrigation water can be achieved without a notable decline in yield. In the 2022–2023 growing season, partial root-zone drying (PRD) irrigation increased yield by 11.743%, 13.76%, and 15.55% compared to surface drip irrigation for the 100%, 75%, and 55% water requirement treatments, respectively, with an average increase of 13.59%. In the second season, PRD irrigation resulted in 10.47%, 13.80%, and 15.43% higher yields under the same treatments, averaging 13.05% higher than surface drip irrigation. Overall, across both years, PRD improved yield by an average of 13.32%. Water productivity under PRD was also higher, as water remained longer in the root zone, reducing moisture stress and enhancing yield. In the first season, water productivity in PRD improved by 11.59%, 13.74%, and 15.59% for the 100%, 75%, and 55% treatments, respectively, with a mean increase of 13.75%. In the second season, it increased by 10.49%, 13.65%, and 15.61%, respectively, with an average improvement of 13.61%. Over both years, water productivity under PRD was 13.68% higher than under surface drip irrigation. Although PRD slightly outperformed surface drip in yield and water productivity, the main benefit lies in saving 25% of irrigation water by applying 75% of the crop water requirement. The SALTMED model accurately simulated soil moisture, dry matter production, and yield under all three treatments and both irrigation systems. It proved effective for predicting crop growth, yield, and water productivity under various scenarios, with minimal differences between observed and simulated data. The highest water productivity occurred under the 55% treatment, followed by the 75% and 100% treatments.

Author Contributions

Conceptualization, M.A. and A.N.GH.; methodology, M.A. and A.N.GH.; software, M.A. and A.N.GH.; validation, M.A. and A.N.GH.; formal analysis, M.A. and A.N.GH.; investigation, M.A. and A.N.GH.; resources, M.A. and A.N.GH.; data curation, M.A.; writing-original draft preparation, M.A. and A.N.GH.; writing-review and editing, M.A. and A.N.GH.; visualization, M.A. and A.N.GH.; supervision, M.A. and A.N.GH.; project administration, M.A. and A.N.GH.; funding acquisition, M.A. and A.N.GH. All authors have read and agreed to the published version of the manuscript.

Data Availability Statement

Data is available on reasonable request from the authors.

Acknowledgements

The authors would like to thank the reviewers and editor for their critical comments that helped to improve the paper

Ethical considerations

The authors avoided data fabrication, falsification, plagiarism, and misconduct.

Conflict of interest

The author declares no conflict of interest.

 

References

Abd El-Mageed, T.A., Semida, W.M. and Abd El-Wahed, M.H. (2016). Effect of mulching on plant water status, soil salinity and yield of squash under summer-fall deficit irrigation in salt affected soil. Agricultural Water Management, 173, 1–12
Abd El-Wahed, M.H., Baker, G.A., Ali, M.M. and Abd El-Fattah, F. A. (2017). Effect of drip deficit irrigation and soil mulching on growth of common bean plant, water use efficiency and soil salinity. Scientia Horticulturae, 225, 235–242.
Abdelraouf, R.E. and Ragab, R. (2018). Applying Partial Root Drying drip irrigation in presence of organic mulching. Is that the best irrigation practice for arid regions? Field and Modelling Study Using SALTMED model. Irrigation and Drainage, 67, 491–507.
Abdelraouf, R.E., El Habbasha, S.F., Taha, M.H. and Refaie, K.M. (2013). Effect of irrigation water requirements and fertigation levels on growth, yield and water use efficiency in wheat. Middle-East Journal of Scientific Research, 16(4), 441–450.
Adu, M. O., Yawson, D. O., Armah, F. A., Asare, P. A., & Frimpong, K. A. (2018). Meta-analysis of crop yields of full deficit and partial root-zone drying irrigation. Agricultural Water Management, 197, 79–90.
Afzal, M., Battilani, A., Solimando, D. and Ragab, R. (2016). Improving water resources management using different irrigation strategies and water qualities: Field and modelling study. Agricultural Water Management, 176, 40–54.
Allen R, Pereira L, Raes D, Smith M. (1998). Crop evapotranspiration. FAO Irrigation and drainage paper No. 56. Food and Agriculture Organization of the United Nations. Rome, Italy.
Al-Omran, A., Louki, I., Alkhasha, A., Abd ElWahed, M.H., & Obadi, A. (2020). Water saving and yield of potatoes under partial root zone drying drip irrigation technique: field and modelling study using SALTMED model in Saudi Arabia. Agronomy, 10(12). doi:10.3390/agronomy10121997
Cosi c, M., Stricˇevic, R., Djurovic, N., Moravcˇevic, D., Pavlovic, M. and Todorovic, M. (2017). Predicting biomass and yield of sweet pepper grown with and without plastic film mulching under different water supply and weather conditions. Agricultural Water Management, 188, 91–100.
Duncan, D.B. (1955) Multiple range and multiple F. tests. Biometrics, 11, 1–42.
El-Metwally, I., Abdelraouf, R.E., Ahmed, M., Mounzer, O., Alarcón, J. and Abdelhamid, M. (2015). Response of wheat (Triticum aestivum L.) crop and broad-leaved weeds to different water requirements and weed management in sandy soils. Agriculture, 61(1), 22–32.
El-Noemani, A.A., Aboamera, M.A.H. and Dewedar, O.M. (2015a). Determination of crop coefficient for bean (Phaseolus vulgaris L.) plants under drip irrigation system. International Journal of ChemTech Research, 8(12), 203–214.
El-Noemani, A.A., Aboellil, A.A.A. and Dewedar, O.M. (2015b). Influence of irrigation systems and water treatments on growth, yield, quality and water use efficiency of bean (Phaseolus vulgaris L.) plants. International Journal of ChemTech Research, 8(12), 248–258.
El-Shafie, A.F., Osama, M.A., Hussein, M.M., El-Gindy, A.M. and Ragab, R. (2017). Predicting soil moisture distribution, dry matter, water productivity and potato yield under a modified gated pipe irrigation system: SALTMED model application using fieldexperimental data. Agricultural Water Management, 184, 221–233.
English, M.J, Musick, J.T., Murty, V.V.N., 1990. Deficit irrigation. In: Management of farm irrigation systems (Hoffman, G.J., Howell, T.A., and Solomon, K.H., Editors). ASAE Monograph no. 9. American Society of Agricultural Engineers publisher, 1020p.
FAOSTAT. 2020. Crops and livestock products. [Available online at https://www.fao.org/faostat/en/#data/QCL].
Food and Agriculture Organization of the United Nations (FAO). (2019). FAOSTAT Statistical Database. Rome, Italy. http://www.fao.org/faostat/en/#data (accessed March 2019).
Gardner, W.H. (1986) Water content. In: Methods of Soil Analysis: Part 1—Physical and Mineralogical Methods. Madison, WI: Soil Science Society of America, American Society of Agronomy.pp. 493–544.
Gee, G.W. and Bauder, J.W. (1986) Particle-size analysis 1. In: Methods of Soil Analysis: Part 1—Physical and Mineralogical Methods. Madison, WI: Soil Science Society of America, American Society of Agronomy. pp. 383–411.
Gençoglan, C., Altunbey, H. and Gençoglan, S. (2006) Response of green bean (P. vulgaris L.) to subsurface drip irrigation and partial rootzone-drying irrigation. Agricultural Water Management, 84(3), 274–280.
Gholipoor M, Sinclair TR, Raza MAS, Loffler C, Cooper M, Messina CD (2013) Maize hybrid variability for transpiration decrease with progressive soil drying. J Agron Crop Sci 199:23–29
Golabi, M., Albaji. M. and Naseri, A. A. (2013). The Feasibility application of drainage water on irrigation and drainage networks covered by Karkhe and Shavoor Exploitation Company using SALTMED model. Journal of Iran Water Research, 12(7), 111-119. (In Farsi)
Hasan, M. K., Sarkar, M. A. R., & Hossain, M. S. (2024). Impact of drought and heat stress on photosynthetic efficiency and yield of lentil (Lens culinaris Medik.) genotypes. Frontiers in Plant Science, 15, Article 1403922.
Hirich, A., Choukr-Allah, R., Ragab, R., Jacobsen, S.-E., El Youssfi, L. and El Omari, H. (2012) The SALTMED model calibration and validation using field data from Morocco. Journal of Materials and Environmental Sciences, 3(2), 342–359.
Iqbal R, Raza MAS, Valipour M, Saleem MF, Zaheer MS, Ahmad S, Nazar MA (2020)
Potential agricultural and environmental benefits of mulches-a review. Bull Natl Res Cent 44:1–16
Jabro J, Leib B, Jabro A (2005) Estimating soil water content using site specific calibration of capacitance measurements from Sentek EnviroSCAN systems. Appl Eng Agric 21:393–399
James, L.G. (1988) Principles of farm irrigation system design, Vol. 73. Washington, USA: John Willey & sons. Inc., Washington State University. pp. 152–153 350–351.
Kader MA, Singha A, Begum MA, Jewel A, Khan FH, Khan NI (2019) Mulching as water-saving technique in dry-land agriculture. Bull Nat Res Cent 43:1–6.
Katerji, N., Hoorn, J.W., Hamdy, A. and Mastrorlli, M. (2003). Salinity effect on crop development and yield, analysis of salt tolerance according to several classification methods. Journal of agricultural water management. 62, 37-66.
Kaya, Ç.I., Yazar, A. and Sezen, S.M. (2015) SALTMED model performance on simulation of soil moisture and crop yield for quinoa irrigated using different irrigation systems, irrigation strategies and water qualities in Turkey. Agriculture and Agricultural Science Procedia, 4, 108–118.
Klute, A. and Dirksen, C. (1986) Hydraulic conductivity and diffusivity: laboratory methods. In: Methods of Soil Analysis: Part 1—Physical and Mineralogical Methods. Madison, WI: Soil Science Society of America, American Society of Agronomy. city, USA. pp. 687–734.
Malash, N., Abdel Gawad, G., Arslan, A. and Ghaibeh, A. (2005a) A holistic generic integrated approach for irrigation, crop and field management: 1. The SALTMED model and its calibration using field data from Egypt and Syria. Agricultural Water Management, 78(1–2), 67–88.
Malash, N., Gawad, G.A., Arslan, A. and Ghaibeh, A. (2005b) A holistic generic integrated approach for irrigation, crop and field management: 2. The SALTMED model validation using field data of five growing seasons from Egypt and Syria. Agricultural Water Management, 78(1–2), 89–107.
Marwa, M.A., Abdelraouf, R.E., Wahba, S.A., El-Bagouri, K.F. and El-Gindy, A.G. (2017). Scheduling Irrigation using automatic tensiometers for pea crop. Agricultural Engineering International: CIGR Journal, Special issue, 174–183.
Marwa, M.A., El-Shafie, A.F., Dewedar, O.M., Molina-Martinez, J. M. and Ragab, R. (2020). Predicting the water requirement, soil moisture distribution, yield, water productivity of peas and impact of climate change using SALTMED model. Plant Archives, 20(1), 3673–3689.
Ministry of Jihad-e-Agriculture, (2023). Office of agriculture statistics analysis and information. Availabe at web (https://biamar.maj.ir/ManagementReport/powerbi/DataBank/AgriBiReport?rs:embe =true).
Nash, J. E. & Sutcliffe, J. V. (1970) River flow forecasting through conceptual models. Part I—A discussion of principles. J. Hydrol. 27(3), 282–290.     
Pulvento, C., Riccardi, M., Lavini, A., D'andria, R. and Ragab, R. (2013). SALTMED model to simulate yield and dry matter for quinoa crop and soil moisture content under different irrigation strategies in south Italy. Irrigation and Drainage, 62(2), 229–238.
Ragab R. (2020). A special issue combines 17 research papers on SALTMED model. ‘SALTMED Publications in Irrigation and Drainage. Virtual Issues First published: 20 May 2020 Last updated: 20 May 2020. Wiley on line Library’.
Ragab, R. (2002). A holistic generic integrated approach for irrigation, crop and field management: the SALTMED model. Environmental Modelling & Software, 17(4), 345–361.
Ragab, R. (2015) Integrated Management tool for water, crop, soil and N-Fertilizers: The SALTMED model. Irrigation and Drainage, 64(1), 1–12
Ragab, R., Battilani, A., Matovic, G., Stikic, R., Psarras, G. and Chartzoulakis, K. (2015) SALTMED model as an integrated management tool for water, crop, soil and N-fertilizer water management strategies and productivity: field and simulation study. Irrigation and Drainage, 64(1), 13–28.
Ragab, R., Evans, J.G., Battilani, A. and Solimando, D. (2017). Towards accurate estimation of crop water requirement without the crop coefficient: New approach using modern technologies. Irrigation and Drainage, 66, 469–477.
Ragab, R., Malash, N., Gawad, G.A., Arslan, A. and Ghaibeh, A. (2005a). A holistic generic integrated approach for irrigation, crop and field management: 1. The SALTMED model and its calibration using field data from Egypt and Syria. Agricultural Water Management, 78(1), 67–88.
Ragab, R., Malash, N., Gawad, G.A., Arslan, A. and Ghaibeh, A. (2005b) A holistic generic integrated approach for irrigation, crop and field management: 2. The SALTMED model validation using field data of five growing seasons from Egyptand Syria. Agricultural Water Management, 78(1), 89–107.
Raza, M. A., Ahmad, S., Saleem, M. F., Khan, I. H., Iqbal, R. … Ali, M. (2017). Physiological and biochemical assisted screening of wheat varieties under partial rhizosphere drying. Plant Physiology & Biochemistry: PPB / Societe Francaise de Physiologie Vegetale, 116, 150–166. 
Schahbazian N, Iran-Nejad H (2006). The effects of different mulch types and irrigation intervals on cotton yield. Die Boden 57:765–766
Sentek (2001) Calibration of sentek pty ltd soil moisture sensors. A report published by Sentek Pty Ltd, Stepney, p 60
Sezen, S.M., Yazar, A., Akyildiz, A., Dasgan, H.Y. and Gencel, B. (2008). Yield and quality response of drip irrigated green beans under full and deficit irrigation. Scientia Horticulturae, 117(2), 95–102.
Sezen, S.M., Yazar, A., Canbolat, M., Eker, S. and Çelikel, G. (2005) Effect of drip irrigation management on yield and quality of field grown green beans. Agricultural Water Management, 71 (3), 243–255. https://doi.org/10.1016/J.AGWAT.2004.09.004
Tawfik RS, El-Mouhamady ABA (2019). Molecular genetic studies on abiotic stress
resistance in sorghum entries through using half diallel analysis and inter simple sequence repeat (ISSR) markers. Bull Natl Res Cent 43:117
Wahba, S.A., El-Gindy, A.M., El-Bagouri, K.F. and Marwa, M.A. (2016) Response of green peas to Irrigation automatic scheduling and potassium fertigation. International Journal of ChemTech Research, 9(3), 228–237.
Wilhite, D. A., & Buchanan-Smith, M. (2005). Drought as hazard: understanding the natural and social context. Drought and water crises: Science, technology, and management issues, 3, 29.
Youssef, E.A., El-Baset, M.M.A., El-Shafie, A.F. and Hussien, M.M. (2018). The applications of water deficiency levels and ascorbic acid foliar on growth parameters and yield of summer squash plant (Cucurbita pepo L.). Agricultural Engineering International: CIGR Journal, 19(5), 147–158.
Iranian Journal of Soil and Water Research
Volume 56, Issue 8
November 2025
Pages 2137-2162

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