共 2 条
Assemblages of geomorphic units: A building block approach to analysis and interpretation of river character, behaviour, condition and recovery
被引:40
|作者:
Fryirs, Kirstie
[1
]
Brierley, Gary
[2
]
机构:
[1] Macquarie Univ, Dept Earth & Environm Sci, Sydney, NSW, Australia
[2] Univ Auckland, Sch Environm, Auckland, New Zealand
关键词:
hydromorphology;
landform;
morphodynamics;
river management;
stream process;
CHANNEL MORPHOLOGY;
FLUVIAL LANDFORMS;
BRITISH-COLUMBIA;
SQUAMISH RIVER;
CLASSIFICATION;
MOUNTAIN;
STREAM;
CATCHMENT;
FORMS;
SEDIMENTOLOGY;
D O I:
10.1002/esp.5264
中图分类号:
P9 [自然地理学];
学科分类号:
0705 ;
070501 ;
摘要:
A geomorphic unit is a landform that has been created and reworked by a particular set of earth surface processes. Each geomorphic unit has a particular morphology and sediment properties. Characteristic assemblages and patterns of geomorphic units reflect the use of available energy at any particular location in the landscape. In river systems the mix and balance of erosional and depositional processes creates characteristic, and sometimes distinctive, patterns of geomorphic units at the reach scale. As geomorphic units make up all parts of every valley bottom, the analysis of geomorphic units provides a universal resource with which to undertake systematic geomorphic analysis of river systems. In the first instance, this tool helps to interpret river morphodynamics. Particular process-form associations determine what type of geomorphic unit is found where, how it is formed and/or reworked, and if/how that unit is related to adjacent units in the channel and/or floodplain. From this, particular assemblages of geomorphic units can be used to identify and map reach boundaries along a river course. Each reach has a particular set of process-form relationships that determine (and/or reflect) the range of behaviour and the capacity for adjustment of that section of river. Framed in a catchment context and in relation to evolutionary trajectory, interpretation of geomorphic unit assemblages, and how they change over time, informs analysis of river condition and the potential for geomorphic recovery of each reach. A scaffolding framework to conduct such analyses and interpretations provides an important bridge between expert manual analysis and machine learning analysis using big data, allowing for the identification and interpretation of the distinctive traits of each and every river system.
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页码:92 / 108
页数:17
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