A Generalized Multistep Dynamic (GMD) TOPMODEL
A Generalized Multistep Dynamic (GMD) TOPMODEL
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DOI：
10.1029/2022wr032198
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发表时间：
2023-01
影响因子：
5.4
通讯作者：
Salim Goudarzi;D. Milledge;Joseph Holden
中科院分区：
文献类型：
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作者：
Salim Goudarzi;D. Milledge;Joseph Holden
数值水文学中缺乏常微分方程(ODE)公式，这导致了封闭的自适应时间步长解算器的应用不足；因此，固定(例如，欧拉)时间步长技术尽管存在根本问题，但仍然占据主导地位。在本文中，我们将Dynamic-TopModel重新描述为约束处理的ODE形式，并使用MatLab先进的自适应ODE求解器来求解得到的方程组。为了更广泛的适用性，但基于已有的研究和/或第一原理，我们发展了广义多步动态TOPMODEL，它包括：等值域空间离散，扩散波路径，随深度变化的陆面流速，放宽地下水位与地表平行的假设，幂函数导水率剖面，新的非饱和区通量，以及参考系平差。为了演示该模型，我们将其校准为泥炭流域的案例研究，对于该案例，我们还测试了对空间离散化的敏感性。我们的结果表明：(A)自适应时间推进可以将模型运行时间提高五倍；(B)作为进一步约束所需空间信息的一种方式，额外的等流域离散化层也提高了性能；以及(C)通用的任意地形指数(TI)离散化显著改变了校准的参数。可能需要更客观和物理上受限(例如，自上而下)的方法来进行TI分类。
There is a lack of Ordinary Differential Equation (ODE) formulations in numerical hydrology, contributing to the lack of application of canned adaptive timestep solvers; hence the continued dominance of fixed (e.g., Euler) timestep techniques despite their fundamental problems. In this paper, we reformulate Dynamic‐TOPMODEL into a constraint‐handling ODE form and use MATLAB's advanced adaptive ODE‐solvers to solve the resulting system of equations. For wider applicability, but based on existing research and/or first principles, we developed Generalized Multistep Dynamic TOPMODEL which includes: iso‐basin spatial discretization, diffusion wave routing, depth‐dependent overland flow velocity, relaxing the assumption of water‐table parallelism to the ground surface, a power‐law hydraulic conductivity profile, new unsaturated zone flux, and a reference frame adjustment. To demonstrate the model we calibrate it to a peat catchment case study, for which we also test sensitivity to spatial discretization. Our results suggest that (a) a five‐fold improvement in model runtime can result from adaptive timestepping; (b) the additional iso‐basin discretization layer, as a way to further constrain spatial information where needed, also improves performance; and (c) the common‐practice arbitrary Topographic Index (TI) discretization substantially alters calibrated parameters. More objective and physically constrained (e.g., top‐down) approaches to TI classification may be needed.