Assessing crop coefficient variability in arid and semi-arid regions: A meta-analytic approach

Context

Accurate determination of crop coefficients (Kc) is crucial for estimating crop water requirements and improving irrigation systems.

Objective

This study critically evaluates engineering methodologies for estimating Kc values for major crops (rice, cotton, maize, and potato) in arid and semi-arid climates.

Methods

Following the PRISMA protocol, 28 studies were selected and categorized by plant type under standard conditions. A meta-analysis approach was applied to evaluate Kc values across different growth stages.

Results

Meta-analysis parameters (Q and H²) indicated notable heterogeneity among studies, while I² and τ² reflected true heterogeneity and variance, respectively. The p-value (<0.05) confirms the statistical significance of this heterogeneity. The findings emphasize the importance of considering local factors- such as irrigation methods and crop cultivar variations—to enhance the reliability of Kc values. Moreover, discrepancies in estimated water requirements using local Kc versus revised FAO-56 Kc values (e.g., −65 % to +35 % for initial cotton growth and −34.2 % to −18.4 % for late-season potato growth) suggest that employing revised FAO-56 Kc values without considering local factors, such as crop cultivar, can lead to significant estimation errors.

Conclusions

This study identifies key gaps in current methodologies and reveals significant heterogeneity across studies in similar climatic conditions. The most notable issue is the overestimation of crop water requirements when using revised FAO-56 crop coefficients, which leads to increased applied water volumes without improving crop yield. Future research should focus on developing advanced Kc measurement techniques to improve crop water requirement estimates and meet critical engineering needs in water resource management.