Earthquake forecasting models play a vital role in earthquake occurrence assessment. Despite improved availability of seismic and geodetic data and processing techniques to produce high‐resolution catalogs and deformation history, the implementation of earthquake forecasting models with seismic and geodetic data remains a challenge. In this study, we utilize seismicity and Global Navigation Satellite Systems (GNSS) data to propose time‐independent grid‐based regional earthquake likelihood models for southeastern Tibetan plateau (RELM‐TibetSE). First, we solve the GNSS velocity field and strain rates from 1999 to 2017, deriving geodetic moment rates and introducing empirical correction coefficients to balance them with historical seismic moment rate. Subsequently, we employ a truncated Gutenberg–Richter law and Poisson process to calculate time‐independent probabilities for M ≥ 6 earthquakes in 0.2° × 0.2° cells. The grid‐based forecasting models indicate that the 30‐year probability for M ≥ 6 earthquakes exceeds 1% in more than one‐third of the entire study area, highlighting prominently higher earthquake occurrence in these regions. Probability distribution exhibits significant spatial variations. Finally, the predictive performance of the forecasting models is validated based on historical seismicity. The validation indicates that all RELM‐TibetSE exhibit good predictive capability relative to a spatially uniform model. The RELM‐TibetSE incorporating principal strain rates outperforms those involving maximum shear strain rate in forecasting seismicity. And the differences in forecasting performance between the RELM‐TibetSE accounting for spatially varied seismogenic thickness and rigidity and those with uniform thickness and rigidity are not significant. The forecasting models also exhibit better predictive performance for seismic source areas than for epicenters. Moreover, the optimal model highlights zones with higher earthquake occurrence, including the zones about 50 km wide across the Ninglang fault, the zones across the southwestern segment of the Lijiang–Xiaojinhe fault, the China–Myanmar borderland north of the Nantinghe fault, and so on. Therefore, it is justified to conduct multidisciplinary rigorous observations to capture the potential nucleation process of future large earthquakes in these zones.

中文翻译：

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利用 GNSS 应变率和地震活动对青藏高原东南部 M ≥ 6.0 级地震进行时间无关网格预报模型

地震预报模型在地震发生评估中发挥着至关重要的作用。尽管地震和大地测量数据的可用性以及生成高分辨率目录和变形历史的处理技术有所提高，但利用地震和大地测量数据实施地震预测模型仍然是一个挑战。在本研究中，我们利用地震活动性和全球导航卫星系统（GNSS）数据提出了青藏高原东南部基于时间独立网格的区域地震可能性模型（RELM-TibetSE）。首先，我们求解 1999 年至 2017 年的 GNSS 速度场和应变率，推导大地矩率并引入经验校正系数以将其与历史地震矩率进行平衡。随后，我们采用截断的古腾堡-里希特定律和泊松过程来计算 0.2° × 0.2° 单元中 M ≥ 6 次地震的与时​​间无关的概率。基于网格的预测模型表明，在整个研究区超过三分之一的地区，30年发生M级≥6级地震的概率超过1%，突出表明这些地区的地震发生率明显较高。概率分布表现出显着的空间变化。最后，基于历史地震活动验证了预测模型的预测性能。验证表明，所有 RELM-TibetSE 相对于空间均匀模型都表现出良好的预测能力。在预测地震活动方面，包含主应变率的 RELM-TibetSE 优于包含最大剪应变率的 RELM-TibetSE。并且考虑空间变化的发震厚度和刚度的RELM-TibetSE与具有均匀厚度和刚度的RELM-TibetSE的预报性能差异并不显着。预测模型对震源区的预测性能也优于对震中的预测性能。此外，优化模型还突出了地震高发区，包括宁蒗断裂带约50 km宽的区域、丽江—小金河断裂带西南段、南亭河断裂带以北的中缅边境地区等。在。因此，有理由进行多学科严格观测，以捕捉这些地区未来大地震的潜在成核过程。