Saline groundwater irrigation is an important way to alleviate the shortage of fresh water resources. In order to find a reasonable saline irrigation method for farmland, an irrigation experiment was conducted with fresh water and saline water at the seedling, jointing, heading, and filling stages. The soil salinity, growth, chlorophyll fluorescence, and yield of summer maize were measured. The results showed that alternating fresh and saline water irrigation led to a smaller increase in soil salinity relative to that irrigation with saline water alone. In addition, different sequences of alternating irrigation also significantly affected the accumulation of soil salinity. The maximum quantum yield, effective quantum yield of photochemical energy conversion, photochemical quenching, and non-photochemical quenching varied greatly at the jointing stage and heading stage. Furthermore, the yield of maize that was irrigated with fresh water at the heading stage (8.53 t ha⁻¹) was greater than that at the jointing (7.69 t ha⁻¹) and filling stages (7.45 t ha⁻¹). Therefore, these findings indicate that in areas where fresh water is scarce, priority should be given to the application of fresh water at the heading stages for summer maize irrigation.

The simulation and prediction of the land use changes is generally carried out by cellular automata—Markov (CA-Markov) model, and the generation of suitable maps collection is subjective in the simulation process. In this study, the CA-Markov model was improved by the Boosted Regression Trees (BRT) to simulate land use to make the model objectively. The weight of ten driving factors of the land use changes was analyzed in BRT, in order to produce the suitable maps collection. The accuracy of the model was verified. The outcomes represent a match of over 84% between simulated and actual land use in 2015, and the Kappa coefficient was 0.89, which was satisfactory to approve the calibration process. The land use of Hotan Oasis in 2025 and 2035 were predicted by means of this hybrid model. The area of farmland, built-up land and water body in Hotan Oasis showed an increasing trend, while the area of forestland, grassland and unused land continued to show a decreasing trend in 2025 and 2035. The government needs to formulate measures to improve the utilization rate of water resources to meet the growth of farmland, and need to increase ecological environment protection measures to curb the reduction of grass land and forest land for the ecological health.

Studying the pattern of agricultural water demand under climate change has great significance for the regional water resources management, especially in arid areas. In this study, the future pattern of the irrigation demand in Hotan Oasis in Xinjiang Uygur Autonomous Region in Northwest China, including Hotan City, Hotan County, Moyu County and Luopu County, was assessed based on the general circulation models (GCMs) and the Surface Energy Balance System model (SEBS). Six different scenarios were used based on the GCMs of BCC_CSM1.1, HadGEM2-ES and MIROC-ESM-CHEM under the Representative Concentration Pathway (RCP) 4.5 and RCP 8.5. The results showed that the method integrating the GCMs and SEBS to predict the spatial pattern was useful. The irrigation demand of Hotan Oasis will increase in 2021–2040. The annual irrigation demand of Hotan City is higher, with 923.2 and 936.2 mm/a in 2021–2030 and 2031–2040, respectively. The other three regions (Hotan County, Moyu County and Luopu County) are lower in the six scenarios. The annual irrigation demand showed a spatial pattern of high in the middle, low in the northwest and southeast under the six scenarios in 2021–2040. The study can provide useful suggestions on the water resources allocation in different regions to protect water resources security in arid areas.