A grid‐based approach for simulating stream temperature
A grid‐based approach for simulating stream temperature
复制标题
一种基于网格的流温度模拟方法
DOI：
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发表时间：
2012
期刊：
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通讯作者：
J. Yearsley
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文献类型：
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作者：
J. Yearsley
基于网格的系统在环境分析的许多领域都有广泛的应用。在这项研究中，这一概念是适应的宏观水文模型，可变入渗能力（维克），与计算效率和准确的水温模型集成的建模。水文模型已应用于0.0625° ~ 1.0°尺度的多个流域。水温模型使用半拉格朗日数值方案来求解对流河流系统中热能平衡的一维时变方程，已在太平洋西北部的分段河流系统中应用和测试。在以前的工作中描述的水温模型的状态空间结构扩展到包括不确定性的传播。模型结果侧重于概念验证，通过比较测试流域研究的统计数据与使用过程模型或统计模型估计水温的其他研究的结果。本研究的结果与使用数据驱动统计模型的选定案例研究的结果相比，具有优势。水温确定性过程模型的结果通常优于基于网格的方法，特别是对于那些从特定地点开发的模型，数据密集型研究。基于网格的系统的结果中的偏差归因于水力特性的不均匀性和估计水源温度的方法。
Applications of grid‐based systems are widespread in many areas of environmental analysis. In this study, the concept is adapted to the modeling of water temperature by integrating a macroscale hydrologic model, variable infiltration capacity (VIC), with a computationally efficient and accurate water temperature model. The hydrologic model has been applied to many river basins at scales from 0.0625° to 1.0°. The water temperature model, which uses a semi‐Lagrangian numerical scheme to solve the one‐dimensional, time‐dependent equations for thermal energy balance in advective river systems, has been applied and tested on segmented river systems in the Pacific Northwest. The state‐space structure of the water temperature model described in previous work is extended to include propagation of uncertainty. Model results focus on proof of concept by comparing statistics from a study of a test basin with results from other studies that have used either process models or statistical models to estimate water temperature. The results from this study compared favorably with those of selected case studies using data‐driven statistical models. The results for deterministic process models of water temperature were generally better than the grid‐based method, particularly for those models developed from site‐specific, data‐intensive studies. Biases in the results from the grid‐based system are attributed to heterogeneity in hydraulic characteristics and the method of estimating headwater temperatures.