Journal
JOURNAL OF HYDROLOGY
Volume 523, Issue -, Pages 739-757Publisher
ELSEVIER
DOI: 10.1016/j.jhydrol.2015.02.013
Keywords
Global method; Hydrological model; Parameter optimization; Sensitivity analysis; Uncertainty analysis
Funding
- National Natural Science Foundation of China [41330854]
- Postgraduate Dissertation Foundation of Nanjing Hydraulic Research Institute [LB51302]
- National Basic Research Program of China (973 Program) [2010CB951103, 2015CB452701]
- Los Almas National Laboratory LDRD program
Ask authors/readers for more resources
Sensitivity analysis (SA) aims to identify the key parameters that affect model performance and it plays important roles in model parameterization, calibration, optimization, and uncertainty quantification. However, the increasing complexity of hydrological models means that a large number of parameters need to be estimated. To better understand how these complex models work, efficient SA methods should be applied before the application of hydrological modeling. This study provides a comprehensive review of global SA methods in the field of hydrological modeling. The common definitions of SA and the typical categories of SA methods are described. A wide variety of global SA methods have been introduced to provide a more efficient evaluation framework for hydrological modeling. We review, analyze, and categorize research into global SA methods and their applications, with an emphasis on the research accomplished in the hydrological modeling field. The advantages and disadvantages are also discussed and summarized. An application framework and the typical practical steps involved in SA for hydrological modeling are outlined. Further discussions cover several important and often overlooked topics, including the relationship between parameter identification, uncertainty analysis, and optimization in hydrological modeling, how to deal with correlated parameters, and time-varying SA. Finally, some conclusions and guidance recommendations on SA in hydrological modeling are provided, as well as a list of important future research directions that may facilitate more robust analyses when assessing hydrological modeling performance. (C) 2015 Elsevier B.V. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available