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- Title
Prediction of Plant Available Water at Sowing for Winter Wheat in the Southern Great Plains.
- Authors
Lollato, Romulo P.; Patrignani, Andres; Ochsner, Tyson E.; Edwards, Jeffrey T.
- Abstract
Sowing plant available water (PAWs) can impact wheat (Triticum aestivum L.) stand establishment, early crop development, and yield. Consequently, PAWs is an essential input in crop simulation models and its estimation can improve agronomic decisions. Our objective was to identify effective methods to predict PAWs in continuous winter wheat by exploring empirical and mechanistic models based on the preceding 4-mo summer fallow. The mechanistic soil water balance models dual crop coefficient (dual Kc) and simple simulation model (SSM) were calibrated, validated, and tested using soil moisture datasets collected from 2009 to 2013 in Oklahoma totaling 29 site-years. Additionally, PAWs was predicted using empirical nonlinear models based on cumulative fallow precipitation and the soil's plant available water capacity (PAWC). Both the dual Kc and SSM models resulted in normalized root mean squared error (RMSEn) below 12% (20 mm) for the calibration and validation datasets. Modeled PAWs for the prediction dataset was within ±30% of field observations in 67% of the site-years for both dual Kc and SSM models, wiThrMSEn of 27 and 32%. An inverse-exponential and a logarithmic model of PAWs using cumulative fallow precipitation and PAWC boThresulted in RMSEn = 23 and 29% in the calibration and validation datasets. The dual Kc model was slightly superior to empirical models based on nonlinear regression analysis, and was superior to the SSM model. Initializing the dual Kc at the start of the preceding fallow or using empirical relationships allow for acceptable predictions of PAWs, eliminating the need for subjective PAWs values.
- Subjects
WINTER wheat; SOWING; SIMULATION methods &; models; SOIL moisture; STANDARD deviations; REGRESSION analysis
- Publication
Agronomy Journal, 2016, Vol 108, Issue 2, p745
- ISSN
0002-1962
- Publication type
Article
- DOI
10.2134/agronj2015.0433