C
Christopher Thompson
Researcher at University of Queensland
Publications - 46
Citations - 1155
Christopher Thompson is an academic researcher from University of Queensland. The author has contributed to research in topics: Floodplain & Flood myth. The author has an hindex of 17, co-authored 46 publications receiving 999 citations. Previous affiliations of Christopher Thompson include London School of Economics and Political Science & Australian Defence Force Academy.
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Geomorphic effects, flood power, and channel competence of a catastrophic flood in confined and unconfined reaches of the upper Lockyer valley, southeast Queensland, Australia
TL;DR: In this paper, a multitemporal LiDAR-derived DEM of Difference (DoD) is used to quantify morphological change in two study reaches with contrasting valley settings (confined and unconfined).
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The use of multi temporal LiDAR to assess basin-scale erosion and deposition following the catastrophic January 2011 Lockyer flood, SE Queensland, Australia
Jacky Croke,Peter Todd,Christopher Thompson,Christopher Thompson,Fiona Watson,Robert Denham,Giri Khanal +6 more
TL;DR: In this paper, the authors presented an assessment of the basin-scale spatial patterns of erosion, deposition, and net morphological change that resulted from a catastrophic flood event in the Lockyer Creek catchment of SE Queensland (SEQ) in January 2011.
Quantifying different riverbank erosion processesduring an extreme flood event
TL;DR: In this paper, the authors demonstrate how multi-temporal LiDAR and high-resolution aerial imagery can be used to determine processes and volumes of riverbank erosion at a catchment scale.
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Channel-floodplain connectivity during an extreme flood event : implications for sediment erosion, deposition, and delivery
TL;DR: In this article, high-resolution aerial photographs and multi-temporal LiDAR digital elevation models (DEMs) coupled with hydrological modeling are used to assess both the nature of hydrologic and sedimentological connectivity and their dominant controls.
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Epistemic Landscapes, Optimal Search, and the Division of Cognitive Labor
TL;DR: Weisberg and Muldoon as mentioned in this paper argue that a search strategy that deliberately seeks novel research approaches need not be optimal, and they generalize the epistemic landscape model, showing that one should be skeptical about the benefits of social learning in epistemically complex environments.