...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of hydrometeorology >Evaluation of the Parameter Sensitivities of a Coupled Land Surface Hydrologic Model at a Critical Zone Observatory
【24h】

Evaluation of the Parameter Sensitivities of a Coupled Land Surface Hydrologic Model at a Critical Zone Observatory

机译：临界区天文台耦合地表水文模型参数敏感性评价

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Land surface models (LSMs) and hydrologic models are parameterized models. The number of involved parameters is often large. Sensitivity analysis (SA) is a key step to understand the complex relationships between parameters and between state variables and parameters. SA is also critical to understand system dynamics and to examine the parameter identifiability. In this paper, parameter SA for a fully coupled, physically based, distributed land surface hydrologic model, namely, the Flux-Penn State Integrated Hydrologic Model (Flux-PIHM), is performed. Multiparameter and single-parameter tests are performed to examine the three dimensions of identifiability: distinguishability, observability, and simplicity. Results show that Flux-PIHM model predictions of discharge, water table depth, soil moisture, land surface temperature, and surface heat fluxes are very sensitive to the selection of parameter values. Parameter uncertainties produce large uncertainties in hydrologic and land surface variable predictions. The van Genuchten parameters a and b and the Zilitinkevich parameter C_(zil) are the most identifiable among the 20 tested parameters. Results indicate that the land surface and the subsurface are closely coupled. Hydrologic parameters have significant influence on land surface simulations.At the same time, land surface parameters have considerable impacts on hydrologic simulations; the evapotranspiration prediction prior to a strong precipitation event is critical for initializing accurate prediction of discharge peaks. Results also show that parameter identifiability depends on seasons and canopy wetness. Parameter identifiability at high and low flow conditions can be extremely different. Complex system dynamics have been revealed during the SA.
机译：陆面模型（LSM）和水文模型是参数化模型。涉及参数的数量通常很大。灵敏度分析（SA）是了解参数之间以及状态变量与参数之间复杂关系的关键步骤。 SA对于了解系统动态和检查参数可识别性也至关重要。本文针对完全耦合的，基于物理的分布式陆面水文模型，即通量—潘恩状态综合水文模型（Flux-PIHM），执行参数SA。执行多参数和单参数测试以检查可识别性的三个维度：可区分性，可观察性和简单性。结果表明，流量，水位深度，土壤湿度，土地表面温度和表面热通量的Flux-PIHM模型预测对参数值的选择非常敏感。参数不确定性在水文和地表变量预测中产生很大的不确定性。 van Genuchten参数a和b以及Zilitinkevich参数C_（zil）在20个测试参数中最可识别。结果表明，陆地表面和地下紧密耦合。水文参数对地表模拟有重要影响。同时，地表参数对水文模拟也有很大影响。在强降水事件之前的蒸散量预测对于初始化排放峰值的准确预测至关重要。结果还表明，参数可识别性取决于季节和冠层湿度。高流量和低流量条件下的参数可识别性可能会大不相同。 SA期间揭示了复杂的系统动态。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号