Abstract

The FAO-56 crop coefficient (Kc) approach is widely used for making irrigation decisions. Allen and Pereira (2009) extended this approach by developing a method for estimating Kc using a density coefficient (Kd), which is estimated from the fraction of ground covered by vegetation and plant height. In this study we evaluated this method using detailed measurements of transpiration (T), evapotranspiration (ET), soil attributes, weather, and tree physiological variables in 12 apple (Malus domestica Borkh.) orchards in the Western Cape Province of South Africa. Mid-summer canopy cover of the orchards was less than 20 % in young non-bearing and exceeded 60 % in mature full-bearing orchards. Data were collected over three growing seasons (October 2014 to May 2017) in orchards planted to the Golden Delicious/Reinders®, Cripps Pink, Cripps Red, and Rosy Glow apple cultivars. The original Allen and Pereira (A&P) method significantly overestimated the basal crop coefficients (Kcb) by on average 47 % in mature and 103 % in young orchards, respectively. However, improved Kcb estimates were obtained by adjusting the ratio of the resistances (i.e. rl /100) in the A&P method, where rl is the mean leaf resistance and 100 s/m is the typical resistance for annual crops. We defined a resistance parameter “α” for apple orchards which is equivalent to the bulk canopy resistance of a well-watered tree. Replacing rl /100 with rl /α, and using the measured mean rl and other biophysical measurements to solve the A&P equation for α gave a value ∼ 37 s/m. The improved Kcb values were used to derive the orchard Kc taking into account the contribution of cover crops whose transpiration was measured using miniature stem heat balance sap flow gauges. The seasonal total transpiration (T) estimated as T = Kcb x ETo, where ETo is the reference ET closely matched the measured values with a RMSE (root of the mean square error) of ∼ ±16 mm. Therefore, using the mean canopy resistance which is representative of apple trees in the A&P method has the potential to accurately predict both the crop coefficients and water use of apple orchards from planting until full bearing age.

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