Multi-objective optimization of rice irrigation modes using ACOP-Rice model and historical meteorological data

Current rice production in China is associated with low rainfall use efficiency. In order to increase rainfall use efficiency and develop simple water-saving irrigation modes that could be readily implemented by farmers, a new multi-objective optimization framework for irrigation modes of paddy rice was developed, based on a modified version of the AquaCrop model called ACOP-Rice model. The optimization focused on the water level at which irrigation was triggered for five growth periods and the irrigation frequency, rainfall use efficiency and yield were optimized. The procedure was tested on nine rice production cases in China for which over 60 years of historical meteorological data and irrigation guidelines were available. Analysis of the weather data showed that rainfall distribution varied greatly between the different locations and growth periods. The results obtained by following the current guidelines were compared to three optimal solutions that corresponded to minimum number of irrigation events, maximum rainfall use efficiency and “balanced” performance in which equal attention was given to rainfall use efficiency and irrigation frequency, respectively. Overall, the optimization led to lowering the water depth at which irrigation was triggered. The optimal water level after irrigation varied between the different cases, depending on the combined effects of rainfall distribution, operation constraints and length of growth period. Compared to the current guidelines, the optimized irrigation modes reduced the proportion of drainage caused by rainfall after irrigation. For optimal solutions with minimum number of irrigation events, maximum rainfall use efficiency and “balanced” performance, the number of irrigation events was reduced by 57 %, 18 % and 44 % on average (9.4, 3.0 and 7.4 fewer irrigation events per year) while on average rainfall use efficiency improved by 5 %, 19 % and 17 % without significant yield loss.