Modeling Irrigation Management For Water Conservation By DSSAT Model In The Heihe River Watershed

Water resource is a precious, unique resource that is essential for both human well-being and the maintenance of ecosystem services. With the rapid development of society and expansion of population, along with the frequent occurrence of extreme climate events, water shortage problem around the world is becoming increasingly severe. Water is essential for agricultural production, and the shortage of water would lead to grain reduction, which would result in the threat to national food security. Inland region of Northwestern China is far away from sea, with scarce precipitation, high evaporation, and faces chronical water shortage problems. Located between the Qilian Mountain in the south and the Alashan Plain in the north, the Hexi Corridor is an important grain production base, but the precipitation here is scarce, with the annual precipitation ranging between 100 and 250 mm, while the annual evaporation reaches 1,200 mm. In this region, agriculture cannot exist without irrigation. Efficient irrigation and water uses are important to sustainable development and management of water resources in the region. The irrigation method commonly adopted locally is flooding irrigation, which leads to a large amount of deep percolation and wasteful evaporation, and low irrigation water use efficiency. Overconsumption of the water resources by the middle oases has caused a number of social instability and environmental problems downstream.This paper applied DSSAT-maize v4.5 to explore optimal irrigation strategies for maize under different climatic conditions, and to improve the water use efficiency in the Northwest China. The study area is the Yingke Irrigation District, a typical irrigation district in the middle reach oasis of the Heihe River Watershed. The DSSAT model was first calibrated and validated based on the yield and phenological phases as well as soil water content data from 2006-2008 to evaluate its applicability to the study area. DSSAT was then used to simulate the growth of maize under scenarios of different planting dates and irrigation schedules to obtain the optimal planting dates and key irrigation periods. Subsequently, based on the precipitation data during 1971-2010 from the Zhangye Meteorological Station, we use the P III frequency curve method to define different climatic years: p=25% as wet year, p=50% as normal year, and p=75% as dry year. Next 15 simulations under different irrigation scenarios were conducted to obtain the appropriate irrigation amount at different climatic years. Finally, the water saving potential was further evaluated by comparing the current irrigation water quota with the optimal irrigation water use in the study area. The main findings from the research are as follows:Firstly, for the crop yield, phenological phases and soil water content, good agreements were achieved between the simulated and observed data in both the calibration and validation periods. In the calibration period, the simulated maize phenological phases differed by two days of the observed phases, and n RMSE for grain yield was 6.00%. In the validation period, the values of nRMSE of yield were 4.95% in 2006 and 2.96% in 2008, respectively, the RMSE for soil water content ranged from 0.118 to 0.046. The results indicated that DSSAT model is applicable to the Yingke Irrigation District, and it can accurately simulate the soil water dynamics.Secondly, for the four planting dates, difference in the average yield between the April 5 and April 20 planting dates was relatively small, and the yield of April 5 was the highest, while the yields of May 5 and May 20 planting dates were less than the previous planting dates. We can conclude that in the Yingke Irrigation District, the best planting dates range from early April to mid-April.Thirdly, different irrigation treatments were conducted to explore the key irrigation period. The irrigation treatments consisted of irrigation schedules based on different phenological stages(Emergence, Jointing, Tassel, Grain filling, Maturity) with various irrigation levels. The average yield at all four planting dates reached the high point first at the treatment 11, which was the combination of jointing and tassel. After that, with the increasing number of irrigation times and volume, the yield increment was relatively small. Thus irrigation at jointing and tassel stages seems optimal and economic.Fourthly, the optimal irrigation amount varied over different climatic years, for 1989, the dry year, the optimal irrigation was 480 mm, for 1992 the normal year, the optimal irrigation was 420 mm, slightly less than the 1989 irrigation amount, while for 1972, the wet year, the optimal irrigation amount was the least, just 100 mm.Fifthly, the annual precipitation showed a 5-year cycle, consisting of two wet years, two dry years and one normal year. The simulations show that, 1,580 mm/ha was needed in a 5-year precipitation cycle to assure the high yield if the proposed optimal irrigation schedule was performed. The current irrigation water quota locally is 6,900 m3/ha per year, that is 34,500 m3/ha for a 5-year precipitation cycle. Therefore 18,700 m3/ha water could be saved over a 5-year precipitation cycle if the optimal irrigation scheduling was implemented.