Effective Rainfall Estimates for St. Augustinegrass Lawns under Varying Irrigation Programs

Prediction of effective rainfall, rainfall which contributes to the plant available water content, for lawns remains a challenge despite its critical role in accurately estimating a soil water balance and irrigation water requirement. The objective of this research was to validate simple runoff models for estimating effective rainfall on St. Augustinegrass [Stenotaphrum secundatum (Walter) Kuntze 'Raleigh'] turf managed under varying irrigation strategies. A field experiment was conducted at Texas A&M Urban Landscape Runoff Facility in College Station, TX, USA. Effective rainfall during the irrigation season was approximately 16% of measured rainfall but varied with rainfall depth and irrigation management. Methods which accounted for initial abstraction and subsequent rainfall independently were more accurate than simple coefficient models which only accounted for runoff as a percentage of daily rainfall depth. In general, St. Augustinegrass lawns can abstract 12.5 mm of water before rainfall becomes ineffective (runs off). These findings suggest accurate estimates of effective rainfall can be achieved using readily-available methods such as the SCS Curve Number model with adjustments for irrigation management strategy. Implementing more accurate effective rainfall estimates may reduce irrigation applied without decreasing turf quality.