Abstract:
Abstract: Pivot sprinkler irrigation is efficient and able to improve irrigation uniformity and water conservation, especially in arid and semi-arid regions in northwest China. The motor to move the sprinkler machine is one of the key components of the machine. Most methods available for calculating the power demand to move the sprinkler system is empirical and lack of scientific basis, despite its importance in sprinkler application and improving work efficiency. To bridge this gap, we investigated the dependence of this resistance on soil water content and soil bulk density via their impact on soil cohesion modulus, internal friction modulus, sinkage-exponent, cohesion and internal friction angle. We tested a loess soil and a Lou soil, two common soils in arid and semi-arid regions in northwest China. In the experiment, the soil were first air-dried and the deigned soil water content was achieved by evenly spraying a volume of water, calculated based on the water content, over the arid-dry soil followed by a thorough mixture to ensure homogeneity. Binary quadratic general rotation combination tests were then carried out. The change in the five soil mechanical parameters with water content and bulk density were calculated based on results obtained from plate-subsidence test and direct-shear box test, from which we calculated the variation of the resistance with moisture content and bulk density of the soils. Regression models linking each of the five mechanical parameters to moisture and bulk density were established and were used to configure the motor of the sprinkler machine. We verified the models against field tests conducted at Yangling and Yulin in Shannxi province. In the test, we measured the soil moisture and bulk density at 0, 50 and 100 m from the edge of the tested plot. The results showed that the cohesion modulus, internal friction modulus, sinkage-exponent, cohesion and internal friction angle of both soils changed significantly with both soil moisture and bulk density (P<0.05). With water content and bulk density increasing, the cohesion modulus of the loess soil decreased monotonically, while of the Lou soil increased first followed by a decrease. We also found that, as soil moisture and bulk density increased, the internal friction modulus of both soils decreased, and their sinkage-exponent decreased first followed by an increase. The regression model fitted the experimental results of both soils well. In particular, the regression model was quadratic for the cohesion modulus and sinkage-exponent, and linear for the internal friction modulus, cohesion and internal friction angle. The motor in the sprinkler machine configured from the regression model meet the power demand, with its rotating speed and torque for moving the sprinkling machine being 500 W, 2.6 N·m and 1800 r/min for the loess soil, and 400 W, 2.2 N·m and 1800 r/min for the Lou soil. Compared to the measurement, the maximum relative error of the calculated power demand for the Lou soil and loess soil was 6.43% and 7.73%, respectively, proving the accuracy of the model. Our results provide a basis for configuring the power of the motor to move sprinkling machine over different soils in field.