SIMULATING DEEP PERCOLATION IN FLOOD-IRRIGATED MATURE PECAN ORCHARDS WITH RZWQM2

摘要

The timing and amount of irrigation water are critical to the optimum production of pecans in semi-arid, irrigated agriculture systems. However, few tools are available to managers for measuring or estimating water use compared to deep percolation (DP) below the root zone. The RZWQM2 model was compared to the daily water balance method at two flood-irrigated mature pecan orchards, with different soil textures and depths to water table, in the lower Rio Grande Valley near Las Cruces, New Mexico, to characterize: (I) DP below the upper 100 cm soil profile, and (2) the effects of DP on water table levels. At site I (sandy loam) and site 2 (silty clay loam), comparisons between measured and simulated soil water contents at different soil depths during March to December in 2009 and 2010 demonstrated that RZWQM2 generally provided satisfactory predictions of soil water dynamics but consistently undepredicted soil water content after irrigation. Total estimated and simulated DP at site I were 489.1 and 445.2 mm in 2009, and 541.5 and 465.8 mm in 2010, respectively. Thus, at site 1, 25% to 29% of the applied water percolated below the root zone, but the model underpredicted these values by 3 to 4 percentage points. In contrast, total estimated DP at site 2 was 37% and 35% of the total water, and again the model underpredicted by 4 to 5 percentage points. Water table levels at site I were affected by DP following irrigation events. This was likely related to the relatively shallow water table and the highly permeable sandy loam soil in the upper layers. Nevertheless, the root zone water balance at site I did not appear to be influenced by the water table since downward hydraulic fluxes were predominant below 40 cm depth and soil water content remained constant at 160 cm depth. In contrast, the deeper water table at site 2 was not influenced by DP. Calibration and validation of RZWQM2 with field data at pecan orchards with different soil textures and water table depths allow managers to use the model to address water management issues to minimize DP while optimizing pecan production.