Pulse Brain · Growing Health Evidence Index
Tier 4 — Narrative / commentaryPeer-reviewed

Characterizing Uncertainty of the Hydrologic Impacts of Climate Change

Martyn Clark, Robert L. Wilby, E. D. Gutmann, J. A. Vano, Subhrendu Gangopadhyay, Andrew W. Wood, Hayley J. Fowler, Christel Prudhomme, J. R. Arnold, L. D. Brekke

Current Climate Change Reports · 2016

Read source ↗ All evidence

Summary

This review examines the multiple sources of uncertainty affecting hydrologic climate change impact assessments, as suggested by the authorship and journal focus. The paper characterises how uncertainties from global climate models, regional downscaling techniques, and catchment-scale hydrologic models compound to affect projections of future water availability and extremes. Understanding and communicating these uncertainties is presented as essential for robust water resource planning under climate change.

UK applicability

The methodological framework for uncertainty characterisation has direct relevance to UK hydrologic impact assessments and water resource management planning. Similar uncertainty quantification approaches would apply to UK catchments, though specific climate model ensembles and downscaling methods differ between US and UK contexts.

Key measures

Uncertainty quantification in hydrologic projections; climate model spread; downscaling uncertainty; hydrologic model sensitivity

Outcomes reported

The study characterizes sources and magnitudes of uncertainty in projections of climate change impacts on hydrologic systems. It examines how uncertainties from climate models, downscaling methods, and hydrologic models propagate through impact assessments.

Theme
Climate & resilience
Subject
Climate & greenhouse gas mitigation
Study type
Narrative Review
Study design
Narrative review
Source type
Peer-reviewed study
Status
Published
Geography
United States
System type
Other
DOI
10.1007/s40641-016-0034-x
Catalogue ID
BFmor3gf2d-uivkn1

Topic tags

Pulse AI · ask about this record

Dig deeper with Pulse AI.

Pulse AI has read the whole catalogue. Ask about this record, its theme, or how the findings apply to UK farming and policy — every answer cites the underlying studies.