HR: 1340h
AN: H53G-1518    [Abstracts]
TI: Using Electrical Resistance Sensors for High Resolution Monitoring of Channel Network Expansion
AU: * Goulsbra, C
EM: claire.goulsbra@postgrad.manchester.ac.uk
AF: Geography, The University of Manchester, Geography, School of Environment and Development, The University of Manchester, Oxford Road, Manchester, M13 9PL, United Kingdom
AU: Lindsay, J
EM: john.lindsay@manchester.ac.uk
AF: Geography, The University of Manchester, Geography, School of Environment and Development, The University of Manchester, Oxford Road, Manchester, M13 9PL, United Kingdom
AU: Evans, M
EM: martin.evans@manchester.ac.uk
AF: Geography, The University of Manchester, Geography, School of Environment and Development, The University of Manchester, Oxford Road, Manchester, M13 9PL, United Kingdom
AB: It has long been recognized that the volume of water in a channel network can vary greatly over single storm events. This increase in drainage network volume may be expressed as changes in stream stage, an increase in the wetted perimeter as streams expand laterally onto their floodplains and an increase in the flowing length of channels as the stream head migrates upstream into ephemeral portions of the channel network. Monitoring the increase in the flowing length of channels over entire catchments is tremendously difficult. However, it has been found that Electrical Resistance (ER) sensors can used to detect the presence or absence of stream flow at any point in a stream network. During flow conditions, there is a continuous circuit between the sensor electrodes, so the measured electrical conductivity is high. When there is no flow, the circuit is broken and conductivity is low. This enables a binary level flow/no flow distinction to be made. These sensors are robust and inexpensive with on-board data loggers. As such they can facilitate distributed measurements at fine spatial and temporal resolutions. Therefore, extensive instrument networks could be installed to monitor the spatial pattern of stream network expansion and contraction within an entire catchment. This could enhance our understanding of hydrological response to rainfall and the controls governing runoff generation. Dynamic-extent drainage networks could eventually replace the static networks currently used in runoff, erosion, sediment, and pollution transport models with potentially significant improvements to prediction accuracy. This paper presents results from an extensive sensor network established to monitor stream network expansion and contraction in a peatland catchment in the South Pennines, UK, over the autumn of 2007.
DE: 1804 Catchment
DE: 1848 Monitoring networks
DE: 1856 River channels (0483, 0744)
SC: Hydrology [H]
MN: 2007 Fall Meeting