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在可扩展和可重复的云实现数字地下水建模的改进
Martin Roth1, Jared Grove1, Andy Davis1
1Geomega, 2585 Central Avenue, Boulder, CO, 80301.
Ground water
|February 2, 2026
概括
云计算显著加速了地下水的建模. 本研究介绍了一个可扩展的,开源的云架构,用于并行PEST++和MODFLOW-6模拟,展示了近乎完美的性能扩展和降低项目成本.
科学领域:
- 环境科学环境科学
- 计算式水文地质学
- 云计算应用程序 云计算应用程序
背景情况:
- 地下水建模越来越依赖于需要并行处理的计算密集型方法.
- 对于MODFLOW和PEST的现有云解决方案缺乏全面的审查,特别是在开源和可扩展的实现方面.
- 计算负担和资源可访问性限制了复杂的地下水模拟.
研究的目的:
- 开发和评估一个基础设施为代码架构,用于在云上并行执行地下水模型.
- 通过使用开源工具来展示MODFLOW和PEST++的可重复和高效的基于云的解决方案.
- 评估云实现的地下水建模的可扩展性和性能.
主要方法:
- 使用了Docker容器和开源软件,用于基于云的并行PEST++执行.
- 使用亚马逊网络服务和Terraform进行云基础设施部署和监控.
- 使用公开可用的MODFLOW-6模型评估并行性能,比较本地和云执行.
主要成果:
- 实现了基于云的地下水模型运行的近乎完美的缩放,与本地运行 (每个代理12秒) 相比,每个模型的时间增加最小 (0.02秒).
- 证明了高效并行执行多达200个并发模型在云中运行.
- 通过使用开发的云基础设施,成功校准了咨询地下水模型,加速了项目的完成.
结论:
- 拟议的云架构为复杂的地下水建模任务提供了一个可扩展,具有成本效益和高效的解决方案.
- 基础设施即代码原则使得平行地下水模拟在云端的简单和可重复部署成为可能.
- 云计算为克服现代地下水建模中的计算局限性提供了一个强大的平台.
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