Understanding the variations of future drought under climate warming can provide the basis for mitigation efforts. This study utilized the standardized precipitation evapotranspiration index (SPEI), empirical mode decomposition (EMD) and empirical orthogonal function analysis (EOF) to predict the spatiotemporal variation of future drought under the representative concentration pathway RCP4.5 and RCP8.5 scenarios within the Mongolian Plateau over the period 2020–2100. The SPEI was computed using temperature and precipitation data generated by the fifth stage of the Coupled Model Intercomparison Project (CMIP5). The results under both the RCP4.5 and RCP8.5 scenarios showed increasing changes in temperature and precipitation. Both scenarios indicated increases in drought, with those under RCP8.5 much more extreme than that under RCP4.5. Under both scenarios, the climate showed an abrupt change to become drier, with the change occurring in 2041 and 2054 for the RCP4.5 and RCP8.5 scenarios, respectively. The results also indicated future drought to be more extreme in Mongolia than in Inner Mongolia. The simulated drought pattern showed an east–west antiphase and a north–south antiphase distribution based on EOF. The frequency of drought was higher under RCP8.5 compared to that under RCP4.5, with the highest frequencies under both scenarios occurring by the end of the 21st century, followed by the mid-21st century and early 21st century. The findings of this research can provide a solid foundation for the prevention, early warning and mitigation of drought disasters within the context of climate change in the Mongolian Plateau.

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Accurate estimation of gross primary productivity (GPP) from the regional to global scale is essential in modeling carbon cycle processes. The recently-developed two-leaf light use efficiency (TL-LUE) model and its revised versions based on different concepts have significantly improved the underlying mechanisms between model assumptions and photosynthetic processing. Yet few studies have compared the advantages of the various two-leaf LUE models for their practical applications. Here, an integrated model referred to as a three-parameter radiation-constrained mountain TL-LUE (RMTL3-LUE), is proposed by combining the radiation scalar of the [radiationconstrained TL-LUE model] and the topographic parameters of the [mountainous TL-LUE model]. In this way, the importance of light intensity and topography on vegetation photosynthesis is integrated. Our calibration and validation of RMTL3-LUE were carried out for 11 ecosystems with in situ eddy covariance measurements around the globe. This indicates that the model can effectively improve the GPP estimates compared to its predecessors. At the landscape scale, RMTL3-LUE can also realistically quantify topographic effects on photosynthesis, with topographic sensitivities of decreasing (increasing) with the slope on the unshaded (shaded) terrain. Furthermore, RMTL3-LUE displays an asymmetric sensitivity to PAR variability, with a low sensitivity to PAR compared to other models under high PAR conditions and a similar sensitivity to PAR in low PARs.Altogether, it is clear that the integration of the merits of multiple TL-LUE models can further improve the photosynthetic processes for various conditions amid more challenges in constructing more complex models.

Risk Analysis and Crisis Response under the Background of the Belt and Road (RAC-18

Global warming has altered the uniformity of precipitation in Inner Mongolia, China, eventually leading to droughts. Further studies are necessary to determine the relationship between the concentration of precipitation and drought.Therefore, we assessed the spatial and temporal characteristics of the precipitation concentration degree (PCD), precipitation concentration period (PCP), and standardized precipitation evapotranspiration index (SPEI) in Inner Mongolia in the past and predict changes in the three indices under different scenarios in the future (2018-2100) using measured model data and Sen's slope and Mann-Kendall trend analysis. The correlation between PCD/PCP and SPEI was explored using Pearson's correlation coefficient. The results showed that the spatial distribution of PCD and PCP in Inner Mongolia exhibited significant east-west differences. The PCD values were 0.42-0.76, with high-value areas in the east. PCD showed a decreasing trend in both historical and future scenarios, indicating an even distribution of precipitation and an increased risk of drought. The PCP values were 190 -226 , with high-value areas mainly in the western region. Except for in the Representative Concentration Pathways RCP4.5 and RCP8.5, PCP values in the historical and RCP2.6 scenarios showed a decreasing trend, indicating an earlier onset of maximum precipitation. SPEI values ranged between −1.23 and 1.17, with all future scenarios showing a decreasing trend and the historical scenario showing an increasing trend. The stations with positive correlation between SPEI and PCD accounted for 89.13, 67.39, 91.3, and 95.65% of Inner Mongolia, while those with positive correlation with PCP accounted for 43.47, 60.87, 56.52, and 4.35%, indicating that the correlation between drought variation and precipitation concentration is strong. These results can help reduce and prevent droughts and floods caused by changes in precipitation patterns and provide a basis for the rational use of water resources for preventing droughts and making relief decisions.