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A terrain-following grid transform and preconditioner for parallel, large-scale,integrated hydrologic modeling

机译:用于并行,大规模,综合水文建模的地形跟踪网格变换和预处理器

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摘要

A terrain-following grid formulation (TFG) is presented for simulation of coupled variably-saturated subsurface and surface water flow. The TFG is introduced into the integrated hydrologic model, ParFlow, which uses an implicit, Newton Krylov solution technique. The analytical Jacobian is also formulated and presented and both the diagonal and non-symmetric terms are used to precondition the Krylov linear system. The new formulation is verified against an orthogonal stencil and is shown to provide increased accuracy at lower lateral spatial discretization for hillslope simulations. Using TFG, efficient scaling to a large number of processors (16,384) and a large domain size (8.1 Billion unknowns) is shown. This demonstrates the applicability of this formulation to high-resolution, large-spatial extent hydrology applications where topographic effects are important. Furthermore, cases where the analytical Jacobian is used for the Newton iteration and as a non-symmetric preconditioner for the linear system are shown to have faster computation times and better scaling. This demonstrates the importance of solver efficiency in parallel scaling through the use of an appropriate preconditioner.
机译:提出了一种地形跟踪网格公式(TFG),用于模拟可变饱和地下和地表水流的耦合。 TFG被引入到集成水文模型ParFlow中,该模型使用隐式牛顿Krylov解决方案技术。解析雅可比行列式也被提出和表示,对角线和非对称项都用于预处理Krylov线性系统。该新配方已针对正交模板进行了验证,并显示可在较低的横向空间离散化条件下为坡度模拟提供更高的精度。使用TFG,可以有效地扩展到大量处理器(16,384)和大域大小(81亿未知数)。这证明了该制剂对地形效应很重要的高分辨率,大空间范围水文学应用的适用性。此外,使用解析雅可比行列式进行牛顿迭代并作为线性系统的非对称前置条件的情况显示具有更快的计算时间和更好的缩放比例。这证明了通过使用适当的预处理器,在并行缩放中求解器效率的重要性。

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