As indicated in Table 17 the current data strongly indicates that targeting gully erosion continues to be a high priority for a majority of the BBB sub-catchments . Drawing on the work of Bartley and others ( Section 4.3 ) and Brooks and others ( Section 5.1 ), the key learnings for prioritising landscape remediation can be synthesised into a summary for future investment in the BBB , with extension of these learnings to other locations . This summary draws on the findings from the collaborative work between the NESP Tropical Water Quality Hub projects and the LDC Project to prepare a NESP Synthesis product on the lessons for gully management . It was prepared by Andrew Brooks and Rebecca Bartley and is available
here on the NESP Tropical Water Quality Hub website .
Whilst there are likely thousands of gullies in the BBB catchment area , it is now very clear that the population of gullies is highly skewed , with a relatively small proportion of the gullies contributing a large proportion of the erosion and , therefore , sediment runoff to the GBR . Gully mapping and characterisation shows that there are distinct differences between alluvial and colluvial ( or hillslope gullies ) in terms of their sediment yield and morphological characteristics . Brooks et al . ( 2021 ) highlighted that 6 % of all gullies are contributing 30 % of the BBB fine sediment yield .
There are three primary features of gullies that determine whether rehabilitation will deliver a cost-effective return on investment :
1 . Rate of erosion – gullies that are active and have a high rate of fine sediment generation .
2 . Position in the landscape - includes factors such as distance to the end of the catchment , rainfall patterns and sediment delivery ratio which may be affected by soil type , slope and trapping mechanisms such as dams .
3 . Opportunities for efficiencies – rehabilitation of a large number of densely situated gully features may prove to be viable through ‘ clustering ’ of efforts .
Semi-automated mapping and analysis techniques using LiDAR have been developed to comprehensively assess the extent and characteristics of gullies as distinct from ephemeral streams . These techniques are critical in guiding selection of priority sites for rehabilitation and could be consistently applied across the GBR catchments , and at least in the highest sediment generation areas .
The most ‘ active ’ gullies are those delivering both large fine sediment loads and high specific yields ( i . e ., sediment load per unit area ). Gully activity requires an understanding of historic erosion rates and is conventionally assessed in 4 ways :
1 . Using remote sensing techniques e . g ., multiple historical air photo images , or LiDAR data which provides 3D representation of gully topography and allows gully erosion to be calculated over periods of years to decades
2 . Where gullies have been mapped from LiDAR data , the sediment yield can also be determined by combining the gully volume with the reconstruction of the Prior Land Surface and an estimate of the gully initiation date which can be determined from back extrapolating the gully growth time series determined from aerial photos .
3 . On ground site assessment using quantitative survey methods ( e . g ., terrestrial LiDAR ; ground survey ).
4 . Measurement of the water quality exiting the gully , i . e ., this is typically employed for measuring preand post-treatment water quality – after a site is identified using methods 1-3 above .
The current ideal method for quantitatively assessing gully activity rates at a regional scale is to use a Digital Elevation Model ( DEM ) of Difference ( DoD ) analysis from repeat airborne LiDAR surveys some years apart ( ideally 5 to 10 years apart ). However , at present the availability of repeat airborne LiDAR data is spatially limited . As an alternative to the DoD approach , a Potential Active Erosion ( PAE ) metric was developed to
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