Cyber-enabled autocalibration of hydrologic models to support Open Science
Cyber-enabled autocalibration of hydrologic models to support Open Science
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DOI：
10.1016/j.envsoft.2022.105561
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发表时间：
2022-10
期刊：
影响因子：
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通讯作者：
M. Rajib;I. L. Kim;M. Ercan;V. Merwade;Lan Zhao;C. Song;Kuan-Hung Lin
中科院分区：
文献类型：
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作者：
M. Rajib;I. L. Kim;M. Ercan;V. Merwade;Lan Zhao;C. Song;Kuan-Hung Lin
模型的自动校准（autocalibration）是水文科学中的标准实践。然而，水文建模人员在执行自动校准时，花费大量时间进行数据预处理，编码和运行模拟，而不是专注于科学问题。如本文所述，这种低效率源于：（i）平台依赖性，（ii）有限的计算资源，（iii）有限的编程素养，（iv）有限的模型结构和源代码素养，以及（v）在所谓的自动校准过程中缺乏数据模型互操作性。通过扩展和增强现有的基于网络的建模平台SWATShare，开发的土壤和水资源评估工具（SWAT）水文模型，本文展示了一个可推广的途径，使自动校准效率通过网络基础设施（CI）的解决方案。SWATShare是一个在线共享和可视化SWAT模型、模型结果和元数据的协作平台。本文介绍了前端和后端体系结构的SWATShare，使有效的SWAT模型自动校准在网络上。此外，本文还展示了三个实施案例研究，以验证自动校准的工作流程和结果。这些实施的结果表明，SWATShare自动校准可以产生流量过程线和参数，是常用的离线SWATCUP校准输出相媲美。在某些情况下，来自SWATShare校准的参数值比来自SWATCUP的参数值更具物理相关性。虽然本文中的讨论是在SWAT和SWATShare的背景下，这里提出的概念和技术设计可以作为一个开放科学的蓝图，类似的CI启用其他水文模型的发展，更重要的是，在地球系统科学的其他领域。
Automatic calibration (autocalibration) of models is a standard practice in hydrologic sciences. However, hydrologic modelers, while performing autocalibrations, spend considerable amount of time in data pre-processing, coding, and running simulations rather than focusing on science questions. Such inefficiency, as this paper outlines, stems from: (i) platform dependence, (ii) limited computational resource, (iii) limited programming literacy, (iv) limited model structure and source code literacy, and (v) lack of data-model interoperability in the so-called autocalibration process. By expanding and enhancing an existing web-based modeling platform SWATShare, developed for the Soil and Water Assessment Tool (SWAT) hydrologic model, this paper demonstrates a generalizable pathway to making autocalibration efficient via cyberinfrastructure (CI) solutions. SWATShare is a collaborative platform for sharing and visualization of SWAT models, model results, and metadata online. This paper describes the front and back end architectures of SWATShare for enabling efficient SWAT model autocalibration on the web. In addition, this paper also demonstrates three implementation case studies to validate the autocalibration workflow and results. Results from these implementations show that SWATShare autocalibration can produce streamflow hydrograph and parameters that are comparable with commonly used offline SWATCUP calibration outputs. In some instances, the parameter values from SWATShare calibration are more physically relevant than those from SWATCUP. Although the discussion in this paper is in the context of SWAT and SWATShare, the conceptual and technical design presented here can be used as an Open Science blueprint for similar CI-enabled developments in other hydrologic models, and more importantly, in other domains of Earth system sciences.