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Department of Biological and Irrigation Engineering
Dep. of Plants, Soils, and Biometeorology, Utah State Univ., Logan, UT 84321-4820
*Corresponding author (dani{at}tal.agsci.usu.edu).
ABSTRACT
Modeling of water distribution for drip irrigation management under cropped conditions requires information on water uptake patterns by plant roots. Based on experimental data, we propose using Bivariate Gaussian distribution density functions (normal, semilognormal, and lognormal) as parametric models for two-dimensional water uptake intensity patterns under drip irrigation. These models offer (i) a concise representation of large amounts of uptake information; (ii) parameters that may be useful for modeling and comparisons between crops, locations, and management scenarios; (iii) physical and statistical insight into spatial and temporal changes in uptake patterns that may be gained by applying moment analyses for the center of activity location and the spread in uptake intensity about it. Different water uptake patterns associated with four basic plant-dripper configurations (surface and subsurface source, within and between crop rows) were identified and measured in field and greenhouse experiments. Uptake intensity pattern was influenced by the relative positions of the plant and the source and by the presence of no-uptake boundaries (e.g., soil surface) requiring different models based on various forms of the Bivariate Gaussian model (normal, semi-log, and log-log). The proposed models were in good agreement with corn (Zea mays L.) uptake data measured by dense grids of time domain reflectometry probes in large containers and in the field.
Received for publication September 18, 1995.
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