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

Document Type : Research/Original/Regular Article

Authors

1 Associate Professor, Department of Water Engineering, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran

2 PhD student, Department of Water Engineering, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran

3 Ph.D. Student., Department of Water Engineering, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran

4 PhD student in Water Science and Engineering, Faculty of Agriculture and Natural Resources, Mohaghegh Ardabili University, Ardabil, Iran

5 Professor, Department of Water Engineering and and Member of Water Management Research Center, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran

Abstract

InField-based measurements rely on direct records of irrigation water depth, cultivated area, and actual harvested yield (Table 3), thereby reflecting localized agronomic management such as crop rotation, irrigation frequency, and fertilization practices. For example, field Q, which consistently showed the highest water productivity, followed a canola–maize rotation—a practice widely recognized to improve soil health and enhance nutrient and water uptake. Such agronomic details are rarely captured in remote sensing–based models like WaPOR. Conversely, WaPOR relies on medium-resolution satellite imagery and bio-physical modeling, which inherently apply spatial and temporal averaging. While this ensures regional consistency and enables large-scale assessments, it often overlooks farm-level management heterogeneity, leading to underestimation of actual water productivity. The discrepancy may also be exacerbated by differences in evapotranspiration estimation techniques, the use of generalized crop coefficients, and the static nature of some WaPOR input layers. Notably, temporal trends of field-based GBWP and NBWP values remained relatively stable across the five-year period, while WaPOR-derived values exhibited a more variable and increasing trend. This divergence could result from annual updates in WaPOR algorithms or climatic changes influencing satellite-based evapotranspiration estimates. plot P, a uniform irrigation depth of 55.24 mm per 10-day period appears adequate and well-aligned with crop water requirements during early development (vegetative and rapid leaf expansion stages, mid-June to early July). This is supported by high ETIa (41.97 mm) and Water Stress Coefficients (WSC) values (>1.5), which resulted in a favorable GBWP of 1.97 kg/m³ in 2020. However, as the season progressed into July–August (tasseling and ear formation), crop water demand gradually declined, yet the irrigation rate remained unchanged. With evapotranspiration (ETc) slightly dropping and day temperatures rising (above 24.5 °C), this resulted in marginal over-irrigation during late reproductive stages, possibly increasing non-beneficial losses and contributing to a GBWP drop in 2021 to 1.50 kg/m³ despite consistent irrigation. In contrast, plot Q received only 23.47 mm of irrigation per 10 days—sufficient for early growth but inadequate during mid-to-late season, especially during the reproductive phase when ETc surpassed 50 mm. This under-irrigation, combined with elevated temperatures (~25 °C in July 2021), likely limited photosynthetic efficiency and biomass accumulation. As a result, ETIa dropped below 20 mm in several decades, and GBWP declined to 1.54 kg/m³ in 2021, while NBWP followed a slower recovery trend despite improved weather conditions in subsequent years. Plot R, irrigated with 26.83 mm per 10-day period, exhibited similar constraints. While this amount may have met early-season requirements, it failed to match peak ETc demands during tasseling and grain-filling stages (July–August), which coincided with hot and dry weather. Consequently, actual crop water uptake (ETIa) remained suboptimal, particularly in 2021, where NBWP dropped to its minimum (2.12 kg/m³), indicating acute water stress. Recovery in GBWP and NBWP was observed in 2023, likely due to enhanced rainfall (60 mm) and moderate temperatures (~23 °C), which helped mitigate irrigation shortfalls.

A key observation is that none of the plots implemented stage-specific irrigation. Fixed irrigation rates across all decades ignored the bell-shaped curve of crop water demand, leading to inefficiencies—over-irrigation during physiological maturity (e.g., September) and under-irrigation during peak demand periods (mid-season). The absence of flexible scheduling likely suppressed yield potential and water productivity, especially under heat stress conditions where crops require tightly controlled moisture regimes to maintain stomatal function and assimilate production.

This study conducted a comprehensive comparative analysis of Net and Gross Biomass Water Productivity (NBWP and GBWP) across three agricultural fields (P, Q, and R) over five growing seasons (2020–2024), incorporating both ground-based measurements and WaPOR remote sensing estimates. The findings reveal clear inter-annual and spatial variability in water productivity, closely influenced by irrigation scheduling, rainfall patterns, temperature fluctuations, and crop management practices such as rotation. While NBWP showed a consistent upward trend in all fields—especially in Field Q, where advanced irrigation techniques and a canola–maize rotation contributed to sustained gains—GBWP was more sensitive to climatic extremes and non-optimized water use. The year 2021 emerged as a critical turning point marked by simultaneous declines in both GBWP and NBWP due to limited rainfall and elevated temperatures. Conversely, 2023 presented optimal climatic conditions, leading to productivity recovery, particularly in Fields Q and R. The comparison between WaPOR estimates and field-derived data highlighted a significant water productivity gap, with satellite-derived GBWP and NBWP values consistently underestimating actual productivity by up to 50% or more. This discrepancy is primarily attributed to the coarse spatial resolution, static model assumptions, and inability of WaPOR to capture localized agronomic nuances, such as stage-specific irrigation or soil fertility variations. Nonetheless, WaPOR’s consistent structure offers valuable insights for regional-scale assessments and long-term monitoring. Moreover, the analysis of decade-wise irrigation depth emphasized the limitations of uniform irrigation scheduling. Fixed irrigation rates failed to meet dynamic crop water requirements, leading to either over-irrigation in late-season stages or water stress during peak demand phases (tasseling and grain filling), especially under high-temperature conditions. These mismatches likely suppressed both biomass production and water use efficiency. In conclusion, this study underlines the critical need for integrated irrigation scheduling, climate-adaptive management, and field-calibrated remote sensing approaches to bridge the productivity gap and enhance sustainable water use. Future strategies should prioritize the adoption of precision irrigation technologies and stage-based water allocation to improve both the accuracy of water productivity assessments and the resilience of agroecosystems in semi-arid regions such as Moghan.

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Main Subjects

References

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Water and Soil Management and Modelling
Volume 5, Issue 4
November 2025
Pages 174-190

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  • Receive Date: 29 July 2025
  • Revise Date: 11 September 2025
  • Accept Date: 19 October 2025

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