Journal article
Spatial sensitivity of river flooding to changes in climate and land cover through explainable AI
- Abstract:
-
Explaining the spatially variable impacts of flood-generating mechanisms is a longstanding challenge in hydrology, with increasing and decreasing temporal flood trends often found in close regional proximity. Here, we develop a machine learning-informed approach to unravel the drivers of seasonal flood magnitude and explain the spatial variability of their effects in a temperate climate. We employ 11 observed meteorological and land cover (LC) time series variables alongside 8 static catchmen...
Expand abstract
- Publication status:
- Published
- Peer review status:
- Peer reviewed
Actions
Access Document
- Files:
-
-
(Preview, Version of record, pdf, 4.1MB, Terms of use)
-
- Publisher copy:
- 10.1029/2023ef004035
Authors
Bibliographic Details
- Publisher:
- Wiley
- Journal:
- Earth's Future More from this journal
- Volume:
- 12
- Issue:
- 5
- Article number:
- e2023EF004035
- Publication date:
- 2024-04-30
- Acceptance date:
- 2024-03-29
- DOI:
- EISSN:
-
2328-4277
- ISSN:
-
2328-4277
Item Description
- Language:
-
English
- Keywords:
- Pubs id:
-
1994192
- Local pid:
-
pubs:1994192
- Deposit date:
-
2024-05-02
Terms of use
- Copyright holder:
- Slater et al.
- Copyright date:
- 2024
- Rights statement:
- © 2024 The Authors. Earth's Future published by Wiley Periodicals LLC on behalf of American Geophysical Union. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
- Licence:
- CC Attribution (CC BY)
Metrics
If you are the owner of this record, you can report an update to it here: Report update to this record