4.7 Article

Position paper: Sensitivity analysis of spatially distributed environmental models- a pragmatic framework for the exploration of uncertainty sources

期刊

ENVIRONMENTAL MODELLING & SOFTWARE
卷 134, 期 -, 页码 -

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.envsoft.2020.104857

关键词

Sensitivity analysis; Spatially distributed environmental model; Uncertainty; SWAT; Environmental modeling

资金

  1. Key Project of NSF of China [41930648]
  2. NSF for Excellent Young Scholars of China [41622108]
  3. National Key Research and Development Program of China [2017YFB0503500]
  4. Australian Government Research Training Program (AGRTP) Scholarship
  5. ANU Hilda-John Endowment Fund
  6. Priority Academic Program Development of Jiangsu Higher Education Institutions [164320H116]

向作者/读者索取更多资源

Sensitivity analysis (SA) has been used to evaluate the behavior and quality of environmental models by estimating the contributions of potential uncertainty sources to quantities of interest (QoI) in the model output. Although there is an increasing literature on applying SA in environmental modeling, a pragmatic and specific framework for spatially distributed environmental models (SD-EMs) is lacking and remains a challenge. This article reviews the SA literature for the purposes of providing a step-by-step pragmatic framework to guide SA, with an emphasis on addressing potential uncertainty sources related to spatial datasets and the consequent impact on model predictive uncertainty in SD-EMs. The framework includes: identifying potential uncertainty sources; selecting appropriate SA methods and QoI in prediction according to SA purposes and SD-EM properties; propagating perturbations of the selected potential uncertainty sources by considering the spatial structure; and verifying the SA measures based on post-processing. The proposed framework was applied to a SWAT (Soil and Water Assessment Tool) application to demonstrate the sensitivities of the selected QoI to spatial inputs, including both raster and vector datasets for example, DEM and meteorological information and SWAT (sub) model parameters. The framework should benefit SA users not only in environmental modeling areas but in other modeling domains such as those embraced by geographical information system communities.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据