2014
DOI: 10.5194/hess-18-575-2014
|View full text |Cite
|
Sign up to set email alerts
|

When does higher spatial resolution rainfall information improve streamflow simulation? An evaluation using 3620 flood events

Abstract: Abstract. Precipitation is the key factor controlling the highfrequency hydrological response in catchments, and streamflow simulation is thus dependent on the way rainfall is represented in a hydrological model. A characteristic that distinguishes distributed from lumped models is the ability to explicitly represent the spatial variability of precipitation. Although the literature on this topic is abundant, the results are contrasting and sometimes contradictory. This paper investigates the impact of spatial … Show more

Help me understand this report
View preprint versions

Search citation statements

Order By: Relevance

Paper Sections

Select...
4
1

Citation Types

13
150
0

Year Published

2015
2015
2021
2021

Publication Types

Select...
8

Relationship

0
8

Authors

Journals

citations
Cited by 185 publications
(163 citation statements)
references
References 86 publications
13
150
0
Order By: Relevance
“…This is a characteristic of hydroclimatic conditions in this region northeast of the Appalachians, as confirmed for instance by Zhou et al (2017). Similar results were found by Lobligeois et al (2014), who analyzed spatial variability of storm events associated with the largest 20 flood events in 181 basins in France. They showed that spatial rainfall variability was strongly dependent on hydroclimatic regions, with high variability occurring in the Mediterranean area, associated with summer convective storms, and low variability over much of the northern and western regions of France.…”
Section: Spatial Rainfall Variability and Fractional Basin Coveragesupporting
confidence: 71%
See 2 more Smart Citations
“…This is a characteristic of hydroclimatic conditions in this region northeast of the Appalachians, as confirmed for instance by Zhou et al (2017). Similar results were found by Lobligeois et al (2014), who analyzed spatial variability of storm events associated with the largest 20 flood events in 181 basins in France. They showed that spatial rainfall variability was strongly dependent on hydroclimatic regions, with high variability occurring in the Mediterranean area, associated with summer convective storms, and low variability over much of the northern and western regions of France.…”
Section: Spatial Rainfall Variability and Fractional Basin Coveragesupporting
confidence: 71%
“…Morin et al (2006) found that the sensitivity of flood response (in terms of flood peak magnitude and peak timing) to spatial rainfall variability increased with storm intensity, which they attributed to high flow velocities during intense storms. Similar results were found by Lobligeois et al (2014), who analyzed the influence of spatial rainfall variability on hydrological response in 181 catchments in France based on spatial rainfall variability, storm position and catchment-scale storm velocity indices. They found that flow simulations by hydrological models benefited from spatially distributed rainfall input for large catchments and strongly spatially distributed rainfall fields.…”
Section: Introductionsupporting
confidence: 67%
See 1 more Smart Citation
“…In the French Mediterranean region, streamflow simulation accuracy and dynamics can be significantly enhanced when exploiting information from rainfall at higher spatial resolution (Lobligeois et al 2014;Patil et al 2014;Braud et al 2014). Therefore, analyses to characterize the spatial variability of flood-risk rainfall will contribute to the understanding of flash flood processes.…”
Section: Introductionmentioning
confidence: 99%
“…Reed et al, 2004;Breuer et al, 2009;Smith et al, 2012;Lobligeois et al, 2014;Maxwell et al, 2015;Vansteenkiste et al, 2014), there is surprisingly little fruitful exchange between the different modelling communities who start their model development from the two contrasting endpoints in the resolution-complexity continuum. Models at the lowresolution and low-complexity end of the continuum are criticized for lacking a robust physical or theoretical basis and for their inability to meaningfully represent spatial patterns (e.g.…”
Section: Introductionmentioning
confidence: 99%