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Salts that accumulate near the soil surface with subsurface drip irrigation (SDI) can hinder the establishment of succeeding direct‐seeded crops. To prevent crop loss or yield reduction, producers rely on sprinklers for germination, which is often expensive and requires added capital inputs. Predicting salt movement and accumulation with SDI will allow producers to anticipate the need for sprinkler irrigation for salt control. The HYDRUS‐2D model was used to model salt accumulation from an SDI system on successive crops of cantaloupe ( Cucumis melo L. ssp. melo var. cantalupensis Naudin) and broccoli ( Brassica oleracea L. var. italica Plenck) with two tape depths (18 and 25 cm), different germination practices (germination with SDI and with sprinklers), and water salinity (1.5 and 2.6 dS m −1 ). Predicted saturated‐paste electrical conductivity (ECe) values from HYDRUS‐2D were significantly correlated with actual ECe data obtained from field experiments ( r 2 = 0.08–0.93). After Season 1, the correlation coefficients were highly variable, with the majority of model ECe values being higher than field data. Season 2 results indicated a much stronger relationship, with R 2 values as high as 0.93. Model predictions for Season 2 showed underprediction of ECe when compared with actual ECe. Relationships between model‐predicted ECe and actual ECe resulted in a slope of nearly 1.0 for all treatments and a y intercept close to −1 dS m −1 A better understanding of the processes that occur at the field scale, such as root growth, root distribution, and plant water uptake, is essential for modeling water and solute transport with SDI. A better characterization of evapotranspiration from SDI is required to accurately model salt accumulation.
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Roberts et al. (2009) studied this question.
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