Data · dataset · 2026
Reply on RC1 [* Cross-Reference *]
Listed in LORE
Abstract.
Description
We still lack substantial understanding on how landscape characteristics shape the storage and release of water at the catchment scale. Here we use 13 years of fortnightly precipitation and streamflow δ18O measurements together with hydrometeorological data from 12 nested catchments (0.5 to 247.5 km2) in the Alzette River basin (Luxembourg) to study bedrock geology and landcover controls on streamflow generation.
Streamflow responses to precipitation were highly variable. Runoff coefficients were typically higher in catchments dominated by less permeable bedrock (i.e. marls and claystones, Rc = 0.43 to 0.52) than in catchments with a high fraction of permeable bedrock (i.e. sandstones and conglomerates, Rc = 0.19 to 0.40). The fraction of new water (Fnew, water younger than ~16 days in this study) determined via ensemble hydrograph separation was strongly related to differences in bedrock geology.
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Fnew was highest in impermeable bedrock catchments (i.e. with a dominance of marls and claystone, Fnew = 4.5 to 11.9 %), increasing with higher specific daily streamflow (Fnew up to 45 % in one catchment). In catchments with an important fraction of permeable sandstone and conglomerates, high Fnew variability with specific streamflow (Fnew rising to 25 % in one catchment) was also found, despite a damped and delayed hydrograph response to precipitation and low Fnew (means of 1.3 to 2.7 %).
In the weathered bedrock catchments (i.e. dominated by schists and quartzites), rapid infiltration led to large fractions of water that was older than 12 weeks (~80 %) and very small fractions of water younger than two weeks (~3.5 %). Fnew variability with streamflow was near zero, contrasting with the rapid response of the hydrograph to precipitation events. At high specific streamflow, Fnew was also correlated with bedrock geology and certain land use types.
The extensive data set of streamflow δ18O enabled us to link water storage and release to bedrock geology. Such information is key for a better anticipation of water storage and release functions under changing climate conditions, i.e. long dry spells and high-intensity precipitation events. ***This entry has been automatically imported via OpenAlex by LIST harvest scripts. Please refer to doi.org/10.5194/egusphere-2025-1530-ac1 for the original and latest version of the publication***
Links
Where it is published
- Dataverse dataset page lore.list.lu/dataset.xhtml?persistentId=perma%3ALIST.GHAMRR ↗
landing page · from lore list lu
- Persistent identifier lore.list.lu/citation?persistentId=perma%3ALIST.GHAMRR ↗
DOI / persistent id · from lore list lu
Catalogue records · 1
- Dataverse API lore.list.lu/api/datasets/:persistentId/?persistentId=perma%3ALIST.GHAMRR ↗
metadata API · from lore list lu
Topics
- Stated by source
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- From keywords
- Computer Science & AI
Related
- Possibly the same asReply on RC1 [* Cross-Reference *]
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- Possibly the same asReply on RC1 [* Cross-Reference *]
- Possibly the same asReply on RC1 [* Cross-Reference *]
- Possibly the same asReply on RC1 [* Cross-Reference *]
Provenance · 1 source records, 8 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| LORE | perma:LIST.GHAMRR | 4 h ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].dataverse_subject:other | source · lore list lu | connector:lore_list_lu@1.0.0 | /subjects |
| concepts[field].local:field:computer-science-ai | mapping · lore list lu | connector:lore_list_lu@1.0.0 | /subjects |
| created_date | source · lore list lu | connector:lore_list_lu@1.0.0 | |
| description | source · lore list lu | connector:lore_list_lu@1.0.0 | /description |
| publication_date | source · lore list lu | connector:lore_list_lu@1.0.0 | |
| title | source · lore list lu | connector:lore_list_lu@1.0.0 | /name |
| updated_date | source · lore list lu | connector:lore_list_lu@1.0.0 | |
| version_label | source · lore list lu | connector:lore_list_lu@1.0.0 |