assessing impacts of weighting indicators on optimum performance of irrigation canals

abstract icssdom is a mathematical synthetic model that was written with fortran77 and in which used sa simulation annealing algorithm like an internal loop in basic structure of icss hydrodynamic simulation model. this model presented by mohseni movahed in 1381. this model is able assess current performance and present optimal operation considering downstream requirement of turnout in real conditions and actual constrains of canal system. for performance optimization of irrigation, canals must be chosen a complete spectrum of indicators and optimized them in an objective function with utilization of optimization method. in this model, necessary actions are considered in order to appoint the relative value of indicators and also is noticed to it’s effectiveness in optimization process with sensitivity analysis. another problem created after choosing appropriate indicators, is the lack of a standard and quantitative method for appointing their relative value. using model, mohseni movahed (1381), mohseni (1384) and norozpour (1387) have assessed e1r1, e1r5 and e1l4 canals of dez networks respectively. in these researches, the most appropriate weighting coefficient of indicators is appointed to performance optimization of irrigation canals and applied method for mentioned coefficient is an origin basic mathematical and logical process, which doesn’t depend on any professional judgment. although, hydraulic conditions in these canals are different, they show similar results. according to the results in all three cases, while the weighting coefficient of indicators is noticed as a direct proportion of difference between ideal and presented performance, the improvement percent is better than other conditions. the other important and new results of this research are such as: determination of the suitable composition of sa optimization algorithm parameters and presentation a method and general vision in order to appoint the appropriate extent of kdiv parameter relative to length of random steps in sa optimization algorithm. these results that earn after different and spreading testes of sensitivity analysis can summarize volume of testes and also can be applied as a confident criterion in future researches.