View in EDS

Quantitative accuracy assessment of the revised sparse Gash model using distinct time-step climatic parameters

Saved in:
Bibliographic Details
Title: Quantitative accuracy assessment of the revised sparse Gash model using distinct time-step climatic parameters
Authors: Yong Niu, Li Yiran, Chuanjie Zhang
Source: Hydrology Research, Vol 52, Iss 6, Pp 1615-1632 (2021)
Publisher Information: IWA Publishing, 2021.
Publication Year: 2021
Subject Terms: rainfall interception, Composite material, Physical geography, Atmospheric sciences, Hydrological Modeling, 0208 environmental biotechnology, 0207 environmental engineering, Platycladus, 02 engineering and technology, Environmental science, River, lake, and water-supply engineering (General), Range (aeronautics), Meteorology, sensitivity analysis, Storm, Biology, Water Science and Technology, TC401-506, Interception, Climatology, revised sparse gash model, Global and Planetary Change, Ecology, Geography, Global Forest Drought Response and Climate Change, Paleontology, Geology, FOS: Earth and related environmental sciences, 15. Life on land, potential counteracting mechanism, Watershed Simulation, Materials science, GB3-5030, Hydrological Modeling and Water Resource Management, 13. Climate action, FOS: Biological sciences, Environmental Science, Physical Sciences, Global Drought Monitoring and Assessment
Description: Rainfall interception (I) can considerably influence the transport process of water. The revised sparse Gash model (RSGM) is a tool for determining the I, which assumes that the two climate parameters in the model are equal for all storms. However, few studies have provided additional cases to reexamine the correctness of this assumption and investigated the response of I of single storms to the time-step variability in climatic parameters. Hence, rainfall partitioning was measured during the growing season in 2017 for Pinus tabuliformis, Platycladus orientalis, and Acer truncatum in Northern China, and we ran RSGM on an event basis using different time-step climatic parameters (storm-based, monthly, and fixed) to estimate I. In summary, the modeling accuracy of both cumulative I and individual I was enhanced by increasing the time step of the climatic parameters in this study. These positively support the assumption in the RSGM. These results suggest that it is more appropriate to run the RSGM using fixed climate parameters to estimate I for these tree species during the growing season in northern China. Additionally, the assumption in the RSGM should be appealed to be further confirmed across the widest possible range of species, regions, and time scales.
Document Type: Article
Other literature type
Language: English
ISSN: 2224-7955
0029-1277
DOI: 10.2166/nh.2021.085
DOI: 10.60692/31yk4-5f812
DOI: 10.60692/bv1bh-fjg31
Access URL: https://iwaponline.com/hr/article-pdf/52/6/1615/982650/nh0521615.pdf
https://doaj.org/article/11f6e4e148854cf4987db0d9b3f9db49
https://iwaponline.com/hr/article-pdf/doi/10.2166/nh.2021.085/958291/nh2021085.pdf
Rights: CC BY
Accession Number: edsair.doi.dedup.....39f6b56f9bc54e9cb9cf80aede8c6b5e
Database: OpenAIRE
Description
Abstract:Rainfall interception (I) can considerably influence the transport process of water. The revised sparse Gash model (RSGM) is a tool for determining the I, which assumes that the two climate parameters in the model are equal for all storms. However, few studies have provided additional cases to reexamine the correctness of this assumption and investigated the response of I of single storms to the time-step variability in climatic parameters. Hence, rainfall partitioning was measured during the growing season in 2017 for Pinus tabuliformis, Platycladus orientalis, and Acer truncatum in Northern China, and we ran RSGM on an event basis using different time-step climatic parameters (storm-based, monthly, and fixed) to estimate I. In summary, the modeling accuracy of both cumulative I and individual I was enhanced by increasing the time step of the climatic parameters in this study. These positively support the assumption in the RSGM. These results suggest that it is more appropriate to run the RSGM using fixed climate parameters to estimate I for these tree species during the growing season in northern China. Additionally, the assumption in the RSGM should be appealed to be further confirmed across the widest possible range of species, regions, and time scales.
ISSN:22247955
00291277
DOI:10.2166/nh.2021.085