摘要：The structure of global lithosphere is very important to the scientific researches of tectonic movement, geodynamic process, mantle convection, resource exploration, and disaster prevention and reduction. Three-dimensional (3D) spatial modelling and visualization is an effective tool for lithosphere researches. However, both the isoline/profile methods and the Euclidean-based 3D modelling methods cannot meet the requirement of real 3D modeling of global lithosphere, whereas the recently developed global 3D grid methods have some defects on grid design, such as grid shrinkage, overlapping, non-orthogonality, and nonlatitude-longitude consistency. In this paper, Spheroid Degenerated-Octree Grid (SDOG), a non-overlapping, non-shrinking, orthogonal, latitude-longitude consistent grid in the spheroidal manifold space, was chosen as the basic grid for global lithosphere 3D modeling and visualization. The SDOG-based methods of spatial representation and modelling of lithosphere were proposed. A multi-scale model of lithosphere was designed, and the multi-scale modeling and multi-mode visualization were realized at the full advantages of SDOG in multi-hierarchical and multi-resolution and the properties of lithosphere in multi-semantic. It shows that (1) the SDOG-based method has not only overcome the defects of the current global 3D grid, but also reflected the spherical features of lithosphere more realistically and naturally than the traditional methods, providing a novel solution for global modeling, numeric simulating, and data sharing of lithosphere; and (2) more detailed plates division, more precise geo-layer structure, plates boarder and surface concave-convex, and more rich lithosphere properties are revealed as the scale-model moves on.

摘要：Hydrologiska Byrans Vattenbalansavdeling(HBV) Light model was used to evaluate the performance of the model in response to climate change in the snowy and glaciated catchment area of Hunza River Basin. The study aimed to understand the temporal variation of streamflow of Hunza River and its contribution to Indus River System(IRS). HBV model performed fairly well both during calibration(R2=0.87, Reff=0.85, PBIAS=-0.36) and validation(R2=0.86, Reff=0.83, PBIAS=-13.58) periods on daily time scale in the Hunza River Basin. Model performed better on monthly time scale with slightly underestimated low flows period during bothcalibration(R2=0.94, Reff=0.88, PBIAS=0.47) and validation(R2=0.92, Reff=0.85, PBIAS=15.83) periods. Simulated streamflow analysis from 1995-2010 unveiled that the average percentage contribution of snow, rain and glacier melt to the streamflow of Hunza River is about 16.5%, 19.4% and 64% respectively. In addition, the HBV-Light model performance was also evaluated for prediction of future streamflow in the Hunza River using future projected data of three General Circulation Model(GCMs) i.e. BCC-CSM1.1, CanESM2, and MIROCESM under RCP2.6, 4.5 and 8.5 and predictions were made over three time periods, 2010-2039, 2040-2069 and 2070-2099, using 1980-2010 as the control period. Overall projected climate results reveal that temperature and precipitation are the most sensitiveparameters to the streamflow of Hunza River. MIROC-ESM predicted the highest increase in the future streamflow of the Hunza River due to increase in temperature and precipitation under RCP4.5 and 8.5 scenarios from 2010-2099 while predicted slight increase in the streamflow under RCP2.6 during the start and end of the 21 th century. However, BCCCSM1.1 predicted decrease in the streamflow under RCP8.5 due to decrease in temperature and precipitation from 2010-2099. However, Can ESM2 predicted 22%-88% increase in the streamflow under RCP4.5 from 2010-2099. The results of this study could