Study On Crop-Water Relationship And Availability Of Field Irrigation Water Based On SWAP Model Simulation In Arid Area

Crop-water relationship and availability of field irrigation water based on SWAP model simulation were studied in two areas of a largest-sized irrigation district-Hetao Irrigation District in the western arid area of China respectively according to its unique characteristics of hydrology and water resources so as to provide a theoretical basis and technical support for its water-saving transformation and agricultural sustainable development. The results can also be applied to other areas with similar natural and agricultural conditions. The study will contribute to the improvement of water-saving irrigation theory and the implementation of water-saving measures as well as agricultural sustainable development of China.The physical meaning of sensitive index for six worldwide representative models of crop response to water (Stewart a, Jensen, Minhas, Blank, Stewart band Singh) was analyzed based on multi-variable linear regression theory and was verified by a case study. Results show that sensitivity of drop increases as the absolute value of sensitive index become larger for all the 6 models. The sensitive index obtained by least-squared method sometimes can not be scientifically explained in terms of crop physiology. The phenomenon is related to the statistical distribution of experiment data in addition to the number of experiment treatment and water deficit level. When the data is not in normal or logarithmic normal distribution, the least-squared method is not applicable to obtaining the sensitive index. Because the models are all empirical ones established based on deficit experiment, the application of them should be limited above the low soil moisture of the water deficit experiment according to statistical theory, otherwise the prediction of crop yield by the models may produce considerable error .In order to establish relationship between crop yield and water use, a deficit irrigation experiment was conducted each for 3 main crops- spring wheat, maize and sunflower in Hetao Irrigation District. According to the manner of possible water shortage in future, the water deficit treatment was designed with controlled water application method (reduce water application with irrigation date remaining unchanged according to the irrigation schedule in use) which is more suitable to the irrigation management of the local area. The relationship between crop yield and water use of spring wheat and maize was studied using the data respectively. The results show that crop yields of spring wheat and maize hold an roughly good linear relationship with seasonal evapotranspirations respectively. Statistical analysis shows that Minhas model is capable to express therelationship of crop yields of spring wheat and maize with their evapotranspirations at different growth stages accurately. The sensitivity indices at different growth stages of the two models differ significantly, which indicates that the time of occurrence of water deficit has a great influence on the reduction of the yield of spring wheat an maize. The evapotranspirations of spring wheat for the field deficit irrigation experiment were calculated using the agro-hydrological simulation model SWAP 2.0. Comparison show the SWAP 2.0 is an attractive and effective tool to obtain evapotranspiration for the study of relationship between crop yield and water use.A model of crop response to water based on BP neural network for spring wheat was developed using deficit irrigation experiment data. Analysis of simulation results of the model shows that the model is able to express correctly the relation between the yield and water use of spring wheat and this method has some unique merit. The comparison with Minhas model, which fits well the experiment data, indicated that the spring wheat's sensibility to water expressed by these two models is identical and their results of yield prediction agree with each other for same water application. It can be concluded that the BP neural network is a new method suitable to simulate the crop response to water.A eval...