
%0 Journal Article
%A Tilahun, Ketema 
%A Raes, D. 
%T Sensitivity analysis of optimal irrigation scheduling using a dynamic programming model
%J Australian Journal of Agricultural Research
%D 2002/02/20
%V 53
%N 3
%P 339-346
%K dynamic programming, initial soil moisture; irrigation scheduling, sensitivity stage, yield response factor.
%R https://doi.org/10.1071/AR00143
%U https://www.publish.csiro.au/paper/AR00143 
%X The problem of designing farm irrigation systems is complicated by the fact that the return from a project is a function not only of the design variables, but also of the operation schedules. These operation decisions are not independent, as irrigation applications at any given time period affect the entire set of applications to be made in the future. An optimisation dynamic programming model, CSUDP, was used to analyse the effects of irrigation levels, yield response factors, and initial soil moisture on irrigation scheduling. The CSUDP model requires the following as input data: crop evapotranspiration, rainfall, soil moisture holding capacity, and length of crop sensitivity stages with corresponding yield response factors. Weekly irrigation scheduling, which maximises crop yield, was obtained for a given amount of irrigation water. It has been observed that irrigation scheduling that takes into account crop sensitivity stages reduces irrigation amounts by optimally distributing the irrigation water over the growing season. For some crops, simulation results show that water saving of about 50% resulted in yield reduction of only 25%. By varying yield response factors around the values given in literature, it was observed that increasing the yield response factor of a sensitivity stage decreases relative yield for a given amount of irrigation water. Though residual soil moisture contributed to the crop production under limited irrigation water availability, its effect on irrigation scheduling was found to be limited only to the first 2 sensitivity stages. This information can be of great importance in optimal irrigation water management under limited water conditions. 
