Abstract
Tecomella undulata is an important indigenous tree species found in the hot desert areas of Rajasthan State in India. Data from 22 sample plots were used to model the dominant height growth of T. undulata. Four algebraic difference form equations were compared to select the best model. Autocorrelation was modeled as a first-order autoregressive process. The models were evaluated based on qualitative and quantitative criteria. The Payandeh and Wang's model, which is a base-age invariant polymorphic equation derived as a constrained version of the Chapman–Richards function, produced the best results. With this model, site index can be explicitly determined through direct evaluation of the functions and there is no need for iterative numerical evaluation methods. The model is applicable regardless of the choice of rotation age. The Payandeh and Wang's model is recommended for site classification and dominant height prediction in T. undulata stands in the hot desert of Rajasthan State in India.
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