Effective Precipitation Models in Irrigation Planning: Validation and Comparison Using the SWAT Method

Accurate estimation of effective precipitation (P_eff) - the portion of rainfall stored in soil and utilized by plants - is fundamental for sustainable irrigation planning and soil water management. Despite its critical role in agricultural water use efficiency, existing P_eff calculation methods often lack regional specificity and validation against physical soil-water processes. This study evaluates the performance of two widely-used precipitation estimation methods (CROPWAT and Dependable Rain FAO/AGLW) against detailed soil water balance calculations from the Soil and Water Assessment Tool (SWAT) in the Ceyhan Basin, Türkiye.

Our SWAT model incorporated local soil characteristics, topography, and climate data to simulate soil-water dynamics and establish a benchmark for P_eff estimation. The comparative analysis revealed distinct seasonal patterns in method accuracy. The CROPWAT method showed strong agreement with SWAT results during the May-November, with deviations of only 4-14% in the autumn months. However, it significantly overestimated P_eff during winter months (December-April) by 30-35%. Conversely, the Dependable Rain method performed optimally during winter, with deviations of 6-12% in December-January, but showed substantial inaccuracies (>70%) during January-September, improving only during periods of higher effective precipitation.

These findings demonstrate that current P_eff estimation methods have complementary strengths in different seasons, suggesting the need for a more nuanced, season-specific approach to irrigation planning. The substantial variations in method accuracy highlight the importance of considering local soil conditions and seasonal climate patterns in irrigation system design. Our results indicate that effective irrigation planning requires carefully selecting P_eff estimation methods based on growing season characteristics and local soil-water dynamics.

This study contributes to improving irrigation water management by providing quantitative evidence for the limitations of current P_eff estimation methods and emphasizing the need for regionally calibrated approaches. These insights are particularly relevant for semi-arid regions where efficient use of rainfall in agriculture is crucial for sustainable water resource management.