Hydraulic and hydrologic uncertainty in analysis of irrigation delivery system performance

Uncertainties in parameters that represent properties and boundary conditions have been largely ignored in the design, management and evaluation of irrigation-water-delivery systems. Disregarding parametric uncertainty may have significant effects on the assessment of overall system performance. This study identifies and describes uncertainties derived from spatial variability, temporal variability, and measurement error in system parameters. A stochastic simulation model incorporates selected hydraulic and hydrologic parameters as random variables in predicting the performance of an irrigation-water-delivery system. The developed model is applied to a hypothetical canal network representative of field conditions and results are compared to a deterministic solution which employs mean values of the parameters. System performance was assessed by statistical analysis of predicted performance measures for adequacy, efficiency, dependability and equity of water delivery. Analysis is conduced to investigate the sensitivity of the relative variability in system performance to the relative variability in the random hydraulic and hydrologic parameters.; The developed methodology combines a model of steady spatially-varied canal network flow with statistical models that generate possible realizations of the random hydraulic and hydrologic parameters. Monte Carlo simulation is used to study the response of system performance for successive realizations of the random parameters.; Expected values of the performance measures obtained from stochastic simulation differed from the values predicted in deterministic simulation. The difference, however, was small for the particular conditions considered in the case study. The main advantage of the stochastic methodology was the estimation of coefficients of variation, {dollar}CVsbomega,{dollar} which indicated the relative variability associated with the anticipated system performance. Results showed that sensitivity to the relative variability in Manning Hydraulic resistance, channel bed slope and irrigation application efficiency was low; sensitivity to the relative variability in upstream water supply level was moderate to high; and sensitivity to the relative variability in channel cross-section geometry and potential crop evapotranspiration was high.; The results obtained, though limited, provide insight into the stochastic nature of irrigation canal network flows and indicate the comparative value of data describing the statistical space-time variability of selected parameters. Such information is valuable to system analysts in ascribing notions of risk, reliability and confidence to system design, management and evaluation decisions.