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Comparative analysis of Vening-Meinesz Moritz isostatic models using the constant and variable crust-mantle density contrast – a case study of Zealandia

机译:使用恒定和可变的地幔幔密度对比对Vening-Meinesz Moritz等静压模型进行比较分析–以西兰西亚为例

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摘要

We compare three different numerical schemes of treating the Moho density contrast in gravimetric inverse problems for finding the Moho depths. The results are validated using the global crustal model CRUST2.0, which is determined based purely on seismic data. Firstly, the gravimetric recovery of the Moho depths is realized by solving Moritz’s generalization of the Vening-Meinesz inverse problem of isostasy while the constant Moho density contrast is adopted. The Pratt-Hayford isostatic model is then facilitated to estimate the variable Moho density contrast. This variable Moho density contrast is subsequently used to determine the Moho depths. Finally, the combined least-squares approach is applied to estimate jointly the Moho depths and density contract based on a priori error model. The EGM2008 global gravity model and the DTM2006.0 global topographic/bathymetric model are used to generate the isostatic gravity anomalies. The comparison of numerical results reveals that the optimal isostatic inverse scheme should take into consideration both the variable depth and density of compensation. This is achieved by applying the combined least-squares approach for a simultaneous estimation of both Moho parameters. We demonstrate that the result obtained using this method has the best agreement with the CRUST2.0 Moho depths. The numerical experiments are conducted at the regional study area of New Zealand’s continental shelf.
机译:我们比较了在重力反问题中处理Moho密度对比的三种不同数值方案,以找到Moho深度。使用全球地壳模型CRUST2.0验证了结果,该模型完全基于地震数据确定。首先,通过采用恒定的Moho密度对比来解决Moritz对等静压的Vening-Meinesz反问题的推广,实现了Moho深度的重量恢复。然后促进Pratt-Hayford等静模型,以估计可变的Moho密度对比。随后使用该可变的Moho密度对比来确定Moho深度。最后,结合最小二乘方法,基于先验误差模型联合估计莫霍面深度和密度收缩。 EGM2008全球重力模型和DTM2006.0全球地形/测深模型用于生成等静重力异常。数值结果的比较表明,最佳等静逆方案应同时考虑可变深度和补偿密度。这是通过应用组合最小二乘法同时估算两个Moho参数来实现的。我们证明使用此方法获得的结果与CRUST2.0 Moho深度具有最佳一致性。数值实验是在新西兰大陆架的区域研究区域进行的。

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