A large-scale hydrological model (MIKE HYDRO) was established for the purpose of sustainable agricultural water management in the main stem Tarim River, located in northwest China. In this arid region, agricultural water consumption and allocation management are crucial to address the conflicts among irrigation water users from upstream to downstream. The results of model calibration indicated a close correlation between simulated and observed values. Scenarios with the change on irrigation strategies and land use distributions were investigated. Irrigation scenarios revealed that the available irrigation water has significant and varying effects on the yields of different crops. Irrigation water saving could reach up to 40% in the water-saving irrigation scenario. Land use scenarios illustrated that an increase of farmland area in the lower reach gravely aggravated the water deficit, while a decrease of farmland in the upper reaches resulted in considerable benefits for all sub-catchments. A substitution of crops was also investigated, which demonstrated the potential for saving considerable amounts of irrigation water in upper and middle reaches. Overall, the results of this study provide a scientific basis for decision-making on agricultural water consumption and allocation in the study area.
The Coupled Model Intercomparison Project Phase 5 (CMIP5) provides data, which is widely used to assess global and regional climate change. In this study, we evaluated the ability of 37 global climate models (GCMs) of CMIP5 to simulate historical precipitation in Central Asia (CA). The relative root mean square error (RRMSE), spatial correlation coefficient, and Kling-Gupta efficiency (KGE) were used as criteria for evaluation. The precipitation simulation results of GCMs were compared with the Climatic Research Unit (CRU) precipitation in 1986–2005. Most models show a variety of precipitation simulation capabilities both spatially and temporally, whereas the top six models were identified as having good performance in CA, including HadCM3, MIROC5, MPI-ESM-LR, MPI-ESM-P, CMCC-CM, and CMCC-CMS. As the GCMs have large uncertainties in the prediction of future precipitation, it is difficult to find the best model to predict future precipitation in CA. Multi-Model Ensemble (MME) results can give a good simulation of precipitation, and are superior to individual models.
Drought has become an important threat to industrial and agricultural production and human activities in Central Asia. Using the Standardized Precipitation Evapotranspiration Index (SPEI), we explored the spatial and temporal patterns of dry and wet changes in Central Asia from 1930–2014. The Mann-Kendall trend test and empirical orthogonal function analysis were used to analyze the characteristics of drought in the interannual and seasonal scales. The results showed that the interannual SPEI index in Central Asia presented a distinct phased feature, in the late 1930s, 1970s and 1990s, three consecutive periods of drought occurred. Seasonal SPEI presented different characteristics, with no obvious drying trends in spring and summer. Autumn and winter showed a wet trend. While an obviously wetting tendency has been detected for the winter season, it started in the mid-1950s. Spatially, drought frequency is 42.87% over the entire region of Central Asia from 1930 to 2014. Kyrgyzstan and Tajikistan are wet relative to other countries in Central Asia, with the frequency of drought occurring at 41.6% and 41.9%, respectively; lower than the average frequency of drought in Central Asia. The average frequency of drought in Kazakhstan is 43.1%. Droughts frequently occur in the central and southern parts of Kazakhstan, with the frequency of drought reaching 46.76%. Droughts hardly occur in eastern of Kazakhstan, as well as in the northeastern region. Turkmenistan and Uzbekistan are the two driest countries in Central Asia, especially in the desert region. The frequency of drought was 50.68% and 47.64% respectively.
Recent studies of soil carbon cycle in arid and semi-arid ecosystems demonstrated that there exists an abiotic CO2 absorption by saline-alkali soils (Aa) at desert ecosystems and suggested potential contributions of CO2 dissolution beneath deserts to the terrestrial ecosystems carbon balance. However, the overall importance of such soil CO2 uptake is still undetermined and its implications to the groundwater environment remain unaddressed. In this manuscript, a simple method is proposed for the direct computation of Aa from the total soil CO2 flux (Fa) as well as for the evaluation of Aa importance to Fa. An artificial soil-groundwater system was employed to investigate the implications to groundwater environment and it was found that soil CO2 uptake in deserts can contribute a possible influence on the evolution of the groundwater environment, providing that the absorbed CO2 largely remained in the soil-groundwater system.