Sensitivity Analysis of Furrow-Irrigation Performance Parameters

Abstract

Knowledge of the sensitivity of performance and other related dependent furrow-irrigation parameters, in quantitative terms, to variations in field, design, and management variables can help save a considerable amount of cost, time, and effort spent in field data collection. A univariate analysis, based on the concept of relative sensitivity, was used to quantify the sensitivity of seven dependent irrigation parameters ( E a , E r , R r , D r , U cc , ℓr, and t a ) to 13 variables ( t co , S0 , σ1, σ2, ρ1, ρ2, n , k , a , c , ℓ, q0 , and Z r ). Three different data sets, representative of a wide range of irrigation conditions have been used in the analysis. The response of each dependent parameter to variations in a variable has been evaluated using a zero-inertia model. It was found that no general conclusion can be drawn regarding the relative significance of variables in terms of their effect on each of the dependent parameters, since the interaction between variables is significant enough to weaken or strengthen the effect of changes in a given variable on a dependent parameter. Nevertheless, based on observed relative sensitivity clues, a qualitative categorization of variables into five sensitivity classes, with respect to each dependent parameter, was made.