SENSITIVITY ANALYSIS OF FURROW-IRRIGATION PERFORMANCE PARAMETERS

Knowledge of the sensitivity of performance and other related dependen t furrow-irrigation parameters, in quantitative terms, to variations i n field, design, and management variables can help save a considerable amount of cost, time, and effort spent in field data collection. A un ivariate analysis, based on the concept of relative sensitivity, was u sed to quantify the sensitivity of seven dependent irrigation paramete rs (E(a), E(r), R(r), D-r, U-cc, l(r), and t(a)) to 13 variables (t(co ), S-0, sigma(1), sigma(2), rho(1), rho(2), n, k, a, c, l, q(0), and Z (r)). Three different data sets, representative of a wide range of irr igation, conditions have been used in the analysis. The response of ea ch dependent parameter to variations in a variable has been evaluated using a zero-inertia model. It was found that no general conclusion ca n be drawn regarding the relative significance of variables in terms o f their effect on each of the dependent parameters, since the interact ion between variables is significant enough to weaken or strengthen th e effect of changes in a given variable on a dependent parameter. Neve rtheless, based on observed relative sensitivity clues, a qualitative categorization of variables into five sensitivity classes, with respec t to each dependent parameter, was made.