Abbott, B. N. and J. Perry Mapping very poor condition grazed landscapes at a regional
scale - A remote sensing approach.
http://www.southwestnrm.org.au/information/downloads/Abbot_paper.pdf
Alexander, D., Ed. (2000). Hydrographic procedures for water quality sampling.
Brisbane, Queensland Department of Natural Resources and Mines.
Argent, R., R. Grayson, G. Podger, J. Rahmann, S. Seaton and J.-M. Perraud, Eds.
(2005). E2 - A Flexible Framework for Catchment Modelling. MODSIM 2005
International Congress on Modelling and Simulation, Modelling and Simulation Society
of Australia and New Zealand.http://www.mssanz.org.au/modsim05/papers/argent.pdf
Basin, G., B. Abbott and V. Chewings (2008). Validating a Remotely Sensed Index of
Landscape Leakiness in the Burdekin Dry Tropics, Qld. National Research Flagships:
Water for a Healthy Country, Reef Catchment Systems Project
39.http://www.csiro.au/files/files/plqh.pdf
Brodie, J., L. McKergow, I. Prosser, M. Furnas, A. Hughes and H. H (2003). Sources of
sediment and nutrient exports to the Great Barreir Reef World Heritage Area. ACTFR
Report. Townsville: 191.
Carroll, C., L. Merton and P. Burger (2000). "Impact of vegetative cover and slope on
runoff, erosion, and water quality for field plots on a range of soil and spoil materials on
central Queensland coal mines." Australian Journal of Soil Research 38: 313-27.
Carter, J. (2000). Aussie GRASS:Australian grassland and rangeland assessment by
spatial simulation. Applications of seasonal climate forecasting in agricultural and
natural ecosystems: the Australian experience. G. Hammer, N. Nicholls and C. Mitchell.
Dordrecht, Boston, Kluwer Academic Publishers: 469.
Chiew, F. and T. Mcmahon (1993). "Assessing the adequacy of catchment streamflow
yield estimates." Australian Journal of Soil Research 31(5): 665680.http://www.publish.csiro.au/paper/SR9930665
Rainfall-runoff models are frequently used by hydrologists to estimate runoff from
rainfall and climate data, with the model adequacy assessed by comparing the
level of agreement between flows simulated by the model and the recorded
flows. This paper describes simple methods (visual plots, statistical parameters
and dimensionless coefficients) which are commonly used to compare estimated
and recorded streamflow time series and discusses their advantages and
limitations. Results of a survey conducted to ascertain the required quality of flow
estimates before they are considered to be satisfactory, as well as to identify
preferred methods used by hydrologists in Australia to determine the adequacy
of streamflow estimates, are also discussed in this paper. Information from the
survey is also used to suggest objective criteria based on dimensionless
coefficients that can be used as guides in assessing the adequacy of flows
estimated by rainfall-runoff models. In particular, the coefficient of efficiency is a
very useful indicator in assessing model adequacy.
De Vries, C., T. Danaher and P. Scarth (2004). "Calibration of multiple landsat sensors
based on pseudo-invariant target sites in Western Queensland, Australia." International
Geoscience and Remote Sensing Symposium (IGARSS): 3729-3732.
Freebairn, D. and G. Wockner (1986). "A study of soil erosion on vertisols of the eastern
Darling Downs, Queensland .I. Effects of surface conditions on soil movement within
Contour Bay catchments." Australian Journal of Soil Research 24(2): 135158.http://www.publish.csiro.au/paper/SR9860135
Effects of soil surface conditions on runoff and soil loss were studied on two
major cracking clay soils of the Darling Downs, Queensland. Techniques used to
measure soil loss between field contour bays under natural rainfall are described,
and the results from 10 contour bay catchments (66 plot years) are presented.
Soil movement was separated into rill, interrill, suspended sediment and channel
deposition. Two slope lengths were considered (60 and 35 m), and interrill
erosion appeared to be the major source of soil loss. Runoff and sediment
concentration were both inversely related to surface cover and total soil
movement was greatly reduced by surface cover. In an annual winter-wheat,
summer-fallow system, removal of stubble resulted in soil movement of 29-62 t
ha-1 year-1. Retention of stubble (stubble mulching) reduced soil movement to
less than 5 t ha-1 year-1. Greater than 75% of the variance in soil movement
from single events was explained by surface cover and peak runoff rate. Surface
cover is a measure of the surface area protected from soil detachment and
entrainment. Peak runoff rate describes the amount of energy or stream power
available for detachment and entrainment.
Freebairn, D. and G. Wockner (1986). "A study of soil erosion on vertisols of the eastern
Darling Downs, Queensland .II. The effect of soil, rainfall, and flow conditions on
suspended sediment losses." Australian Journal of Soil Research 24(2): 159172.http://www.publish.csiro.au/paper/SR9860159
Runoff water was sampled as it discharged through weirs installed at the outlet of
1 ha contour bay catchments. Cover, rainfall intensity, and soil tilth were
important factors determining the concentration of suspended sediment in runoff.
Mean delivery ratios for a grey clay, and a black earth, were 0.19 and 0.13
respectively. Contour banks reduced sediment loads reaching the bottom of
slopes by at least six-fold. Three methods of calculation of total sediment loss
were assessed. It was found that a flow-weighted mean of rising stage samples,
and the arithmetic mean of sequential samples, were adequate in most cases for
determining sediment losses. However, sequential samples weighted for
discharge between samples were necessary for reliable measurements,
especially during complex events.
Hamilton, J. S., C. R. Chilcott and D. B. Savage (2008). "Contemporary livestock
carrying capacities for pastoral properties in Northern Australia: a methodology for
integrating objective data on pasture growth and condition." Australian Journal of
Experimental Agriculture 48(7): 735-740.http://www.publish.csiro.au/paper/EA08035
Stocking rate is often the most important and manageable factor influencing the
profitability and environmental sustainability of pastoral properties. Methods for
determining carrying capacity, and therefore stocking rate, include subjective
approaches based on land manager experience, long-term ‘benchmark’
stocking rates and techniques using computer-aided predictions of pasture
growth. This paper presents a new approach for objectively calculating shortterm livestock carrying capacities of pastoral properties by integrating remotely
sensed ground cover assessments as a proxy for land condition. The study
region was three commercial pastoral properties in the north Australian pastoral
region (above 26°S). Two properties were situated in the Victoria River District
of the Northern Territory and a third in the Kimberley region of Western Australia.
Annual pasture growth was estimated using GRASP, a deterministic, pointbased, native pasture model developed for semiarid and tropical grasslands,
which was calibrated for the different land types in the study region. Carrying
capacity estimates were further refined by investigating trends in landscape
cover change between years using data from satellite imagery assessment.
These tools have been shown to be useful for inferring land condition and
pasture growth within these regions of northern Australia but had not been
integrated before this study. This study developed an approach for inferring
rangeland pasture condition and applying it to refine short-term carrying
capacities, thus aiding decision making. The approach developed in this study is
considered to be more applicable for commercial land management than
currently available methods for determining carrying capacities on pastoral
properties in northern Australia.
Hassett, R., H. Wood, J. Carter and T. Danaher (2002). "A field method for statewide
ground-truthing of a spatial pasture model." Australian Journal of Experimental
Agriculture 40: 1069-1079.
Karfs, R., C. Chilcott and P. Scarth (2007). Land monitoring information for grazing
management. NABRUC Conference.
Monitoring grazing land condition in Australian
rangelands is complex because of vast areas
and difficulties in quantifying condition variables consistently over time and space. Yet
condition is a
significant factor in setting stock carrying capacities that are appropriate for profitable
and sustainable
grazing enterprises. In this paper we propose an integrated grazing land monitoring
framework. We
discuss the components necessary of a monitoring system and a delivery approach for
using system
outputs in property-scale decision-making. Time-series remote sensing data is the key
component for
interpreting land condition in a spatially continuous manner. Combined with site
assessments, the
local experiences of land managers and systems analysis, our ability to monitor with
respect to climate
variability is greatly improved. However, the benefits of the monitoring system are not
fully realised if
system outputs are not used in grazing management. A delivery approach where
consideration is given
to profitability and sustainability across the whole grazing enterprise is needed. Those
land managers
equipped with better monitoring information can optimise the use of pastures through
proactive
management suited to prevailing and predicted land condition, thus, contribute towards
the goal of
reaching environmental outcomes set for the broader catchments and regions.
Loch, R. J., B. K. Slater and C. Devoil (1998). "Soil erodibility (<i>K</i>_m)
values for some Australian soils." Australian Journal of Soil Research 36(6): 10451056.http://www.publish.csiro.au/paper/S97081
This paper reports calculated soil erodibility (K_m) values for the
universal soil loss equation (USLE) for a range of surface soils, and for some
subsoils. The calculation of erodibility values was based on laboratory
measurements of water-stable sizes at the soil surface following wetting by rain
and on the wet density of coarse sediment. Also included are erodibility data
derived from field studies of erosion for 5 soils from New South Wales and
Queensland. The erodibility values obtained indicate reasonable consistency in
erodibility values for Vertosols and Ferrosols, but considerable variation in the
erodibility of soils lower in clay.</p> <p>Soil factors best correlated with the
calculated K_m factors were identified, and the potential to use such
information to estimate K_m factors was evaluated.</p>
Peel, M. C., F. H. Chiew, A. W. Western and T. A. McMahon (2000). Extension of
Unimpaired Monthly Streamflow Data and Regionalisation of Parameter Values to
Estimate Streamflow in Ungauged Catchments.
This project is carried out by the
Centre for Environmental Applied Hydrology at the University of
Melbourne as part of the National Land and Water Resources Audit Project 1 in Theme
1 (Water
Availability). The objectives of the project are to extend unimpaired streamflow data for
stations
throughout Australia and to relate the model parameters to measurable catchment
characteristics. The
long time series of streamflow data are important for both research and management of
Australia’s
hydrological and ecological systems.
A simple conceptual daily rainfall-runoff model, SIMHYD, is used to extend the
streamflow data. The
model estimates streamflow from daily rainfall and areal potential evapotranspiration
data. The
parameters in the model are first calibrated against the available historical streamflow
data. The
optimised parameter values are then used to estimate monthly streamflow from 19011998.
The modelling is carried out on 331 catchments across Australia, most of them located
in the more
populated and important agricultural areas in eastern and south-east Australia. These
catchments are
unimpaired, have at least 10 years of streamflow data and catchment areas between 50
km2 and 2000
km2.
The model calibration and cross-validation analyses carried out in this project indicate
that SIMHYD
can estimate monthly streamflow satisfactorily for most of the catchments. The
streamflow simulations
are considered to be good in 111 catchments, satisfactory in 123 catchments, passable
in 52 catchments
and poor in 45 catchments. The streamflow data are only extended for catchments with
simulations
that are considered passable or better.
The main outcome of this project is therefore time series of estimated monthly
streamflow data
from 1901-1998 for 286 catchments in Australia.
The relationship between the optimised model parameter values and climate, relief and
soil
characteristics are also investigated. The results indicate that there is a high statistical
significance
between some of the model parameters and the catchment characteristics. There
relationships will be
explored further in a more detailed analysis with a view to developing relationships
between model
parameters and catchment characteristics that can be used in ungauged catchments.
Perraud, J.-M., S. Seaton, J. Rahmann, G. Davis, R. Argent and P. GD, Eds. (2005).
The architecture of the E2 catchment modelling framework. MODSIM 2005 International
Congress on Modelling and Simulation, Modelling and Simulation Society of Australia
and New Zealand.http://www.mssanz.org.au/modsim05/papers/perraud.pdf
QLUMP - Queensland Land-Use Mapping Program (2004). Land-use mappingmethodology.
Queensland Department of Natural Resources and Water (2008). Water Quality
Modelling for the Great Barrier Reef Catchment and Lagoon - a compilation of modelling
activities undertaken during 2002-2008, June 2008. Report for the Reef Water Quality
Partnership. Brisbane: 125.
Queensland Department of the Environment and Resource Management (2009). the
SILO Data Drill.http://www.longpaddock.qld.gov.au/silo/
Rowland, T. and M. Calvert (2000). Land use management mapping for the MurrayDarling Basin - Phase 1 Queensland Pilot Study. St
George.http://www.nrw.qld.gov.au/science/lump/pdf/st_george_rep.pdf
A methodology for land use management mapping for the Murray-Darling Basin
was
assessed. A pilot study of land use mapping was conducted across the St George
1:100,000 mapsheet in southwest Queensland. The use of a combination of
remotely sensed satellite imagery, datasets containing land use information, field
verification and expert local knowledge was evaluated.
Satellite imagery and datasets containing land use information were interpreted
using image processing software in a GIS and land use type polygons identified.
These were assigned land use classes according to a modified version of the Baxter
& Russell land use classification (Bureau of Rural Sciences and State agencies,
1999) and a draft land use map (as at 1997) produced. This was field verified by
visual inspection and expert local knowledge from land extension and protection
officers as well as land managers. The draft map was updated using field data
followed by final editing and quality assurance checks.
Although no independent validation of the final dataset was conducted, thorough
checking of virtually all land use polygons resulted in an estimated accuracy of 90%
or better.
Improved efficiency could be gained by using as much locally available data as
possible both in the initial interpretation and field verification stages. Land use
classifications must be robust and sufficiently flexible to accommodate modifications
to class descriptors as well as addition and removal of classes according to local
mapping requirements. Independent validation is essential for a meaningful and
useful land use dataset.
Scanlan, J., A. Pressland and D. Myles (1996). "Run-Off and Soil Movement on MidSlopes in North-East Queensland [Australia] Grazed Woodlands." The Rangeland
Journal 18(1): 33-46.http://www.publish.csiro.au/paper/RJ9960033
Run-off, bedload and sediment concentration data were collected over a fiveyear period from unbounded catchments in grazed and exclosed pastures in
woodlands. Cover varied from 4% during drought conditions to almost 100% in
exclosed areas after above-average rainfall. High bedload soil loss, sediment
concentration and run-off percentages were associated with low cover (&lt;30%).
Run-off as a percentage of rainfall increased linearly with rainfall intensity;
decreased linearly with cover; decreased slightly as soil moisture status declined;
and reached a maximum at intermediate rainfall events. Interactions between
these factors were observed. Run-off was up to 30% of rainfall in moderate
rainfall events (30-40 mm) where maximum rainfall intensity over any 15 minute
period (I15) exceeded 70 mm/h. When soil moisture status was high, mean runoff exceeded 30% for 40-80 mm rainfall events. For all rainfall event sizes, run-off
exceeded 20% where I15 exceeded 60 mm/h. Cover had very little effect on runoff when rainfall intensity was low (I15&lt;20 mm/h), soil water deficit was low
(&lt;10 mm) or when rainfall events were &gt;75 mm or &lt;10 mm. Bedload plus
suspended sediment loads ranged from negligible to 1000 kg/ha/a, depending
principally on cover. Soil movement from areas with &gt;40-50% cover was very
low. Pastures dominated by Bothriochloa pertusa (a stoloniferous, naturalised
grass) had lower run-off and lower rates of soil movement than pastures
dominated by Heteropogon contortus (a native tussocky perennial grass) when
compared at the same level of cover. Differences between grazed and exclosed
areas could be attributed solely to differences in cover.
Scarth, P., M. Byrne, T. Danaher, B. Henry, R. Hassett, J. Carter and P. Timmers
(2006). State of the paddock: monitoring condition and trend in groundcover across
Queensland. Proceedings of the 13th Australasian Remote Sensing Conference.
Canberra.
The proposed State Rural Leasehold Land Strategy (SRLLS) is a potential
major driver for vegetation condition assessment across Queensland. Pastoral leases
cover 85 million ha and within the next 5 years, 60% of these will be up for renewal.
Since three quarters of Queensland has a woody foliage cover of less than 20%,
methods of monitoring the extent of groundcover (or conversely, bare ground) are
required. Monitoring of groundcover is important since it is linked to indicators of soil
loss, biodiversity, and pasture production. In some parts of the state, the achievement of
gains in production has been matched by improvements in environmental condition
indicators, however, in other parts of the state the environmental condition has declined.
Many interlinked and usually compounding factors have caused this, some outside, and
some within, the control of the state’s lessees. By building on the world-class SLATS
archive of more than 1500 Landsat TM and ETM scenes covering the state with annual
coverage or better from 1987, this project will deliver information on the condition and
trend of groundcover over the past 20 years at better than paddock scale. By linking
these results with climate and pasture growth models, the impacts and ramifications of
management decisions on condition indicators can be assessed. This paper will discuss
some of the challenges in deriving a robust product that is applicable across the range
of cover types encountered in Queensland, and presents some preliminary condition
and trend products.
Schmidt, M. (2008). Statewide Landcover and Trees Study (SLATS) 2008 Ground
Cover Index (GCI), Landsat
SLATS Scene Series, Queensland Government, Department of Natural Resources and
Water.
Scott N. Wilkinson, W. J. Y., Ron C. DeRose, (2006). "Regionalizing mean annual flow
and daily flow variability for basin-scale sediment and nutrient modelling." Hydrological
Processes 20(13): 2769-2786.http://dx.doi.org/10.1002/hyp.6070
River discharges vary strongly through time and space, and quantifying this
variability is fundamental to understanding and modelling river processes. The
river basin is increasingly being used as the unit for natural resource planning
and management; to facilitate this, basin-scale models of material supply and
transport are being developed. For many basin-scale planning activities, detailed
rainfall-runoff modelling is neither necessary nor tractable, and models that
capture spatial patterns of material supply and transport averaged over decades
are sufficient. Nevertheless, the data to describe the spatial variability of river
discharge across large basins for use in such models are often limited, and
hence models to predict river discharge at the basin scale are required. We
describe models for predicting mean annual flow and a non-dimensional
measure of daily flow variability for every river reach within a drainage network.
The models use sparse river gauging data, modelled grid surfaces of mean
annual rainfall and mean annual potential evapotranspiration, and a network
accumulation algorithm. We demonstrate the parameterization and application of
the models using data for the Murrumbidgee basin, in southeast Australia, and
describe the use of these predictions in modelling sediment transport through the
river network. The regionalizations described contain less uncertainty, and are
more sensitive to observed spatial variations in runoff, than regionalizations
based on catchment area and rainfall alone. Copyright © 2006 John Wiley &
Sons, Ltd.
Searle, R. (2005). Modelling of runoff, sediment and nutrient loads for the Marooch
River catchment using EMSS. Technical Report, Cooperative Research Centre for
Catchment Hydrology: 71.http://www.catchment.crc.org.au/pdfs/technical200508.pdf
Smith, D. M. and D. M. Brough (2006). Modelling the land surface : a report on the
creation of digital elevation models for high priority regions of Queensland / D.M. Smith
and D.M. Brough. [Brisbane] :: v, 19, 29 p. :.
Stone, G., G. Fraser, P. O'Reagain, P. Timmers and J. Bushell "A new methodology for
the calculation of pasture utilisation for grazing
lands."http://www.longpaddock.qld.gov.au/AboutUs/Publications/HiddenArea/Stone_pap
er.pdf
Pasture utilisation is a term used to describe the estimation of animal intake of
pasture dry matter
expressed as a proportion of either pasture growth per season or nominated period.
The calculation has
been used for purposes of evaluating animal production and grazing pressure impacts
on the pasture
resource, including the flow-on effects to runoff and soil loss. Pasture utilisation is a
unifying concept
across grazing trials (McKeon and Rickert 1984) and hence there has been increasing
interest from
rangeland scientists, policy makers and the grazing industry to determine optimal
pasture utilisation
across a range of land types for the purpose of improving rangeland management.
Information from the Wambiana grazing trial at Charters Towers was used to model
‘potential’ pasture
growth, and provide estimations of animal intake and pasture utilisation. This analysis
was performed
on a paddock-by-paddock basis for each draft of steers (annual grazing period) from
1997 to 2007.
The GRASP model (McKeon and Rickert 1984) was used to produce daily pasture
simulations from
SWIFTSYNpD data (Day and Philp 1997) collected at the trial and the QuikIntake
spreadsheet model
(McLennan and Poppi 2004) was used to calculate feed intake. Liveweight of steers and
pasture dry
matter digestibility (DMD) were interpolated to daily values using a linear interpolation
function in an
MS EXCEL spreadsheet. The resultant time-series include accumulated pasture growth,
feed intake,
pasture digestibility and pasture utilisation. The information presented in the time-series
provides a
valuable summary of management outcomes and is used to compare differing grazing
strategies across
land types for both production and sustainability issues.
Timmers, P., B. Zhang, G. Stone, K. Day and A. Panjkov "Forage - A Web-based
framework for generating and distributing decision support information for sustainable
grazing land
management.".http://www.longpaddock.qld.gov.au/AboutUs/Publications/HiddenArea/Ti
mmers_paper.pdf
FORAGE is a web-based facility which provides information relating to climate and
pasture condition
at user-specified locations. The system receives requests from web pages, processes those
requests
and generates the requested information which is then emailed back to the user.
FORAGE currently offers: a) a Rainfall and Pasture Report; b) a Ground Cover Report; and c)
products based on satellite imagery of ground cover. The Rainfall and Pasture Report provides
30year time series of: interpolated annual rainfall; model-simulated annual pasture growth; pasture
biomass (i.e. total standing dry matter); and pasture-litter cover. The Ground Cover Report
provides
time-series (~ 20 years) of pasture ground cover derived both from model calculations and
satellite
imagery. The satellite imagery products are sourced from the QNRW Statewide Landcover And
Trees
Study (SLATS) project (http://www.nrw.qld.gov.au/slats/).
FORAGE is currently used by a range of clients such as government agencies, extension
officers and
land managers to assess climate risk and land condition and to support their decision making in
sustainable natural resource management.
Titmarsh G, G. Lochhead, L. Bradley, P. Thorburn, K. Burrage, A. Rudder, A. Cameron
and D. Gramshaw (2002). Land management to reduce nutrient movement from
catchments. Final Report Project D5028, Murray-Darling Basin Commission.
Titmarsh, G. and L. Larkin (2007). Condamine Catchment Water Erosion Monitoring.
Canberra, National Land & Water Resources
Audit.http://products.lwa.gov.au/files/pn21620.pdf
Waters, D. (2006). Application of the EMSS water quality model for the Queensland
Murray Darling Catchment - Assessing the impacts of on-ground works. Technical
Report of the Water Quality State-level Investment Project. Brisbane, Queensland
Department of Natural Resources and Water:
52.http://www.wqonline.info/Documents/Report_EMSS_QMDC.pdf
To help build regional capacity in the use and application of Environmental Management
Support Systems modelling for the Condamine region, a number of maps and input layers
have been produced.
Waters, D. and R. Packett (2007). Sediment and nutrient generation rates for
Queensland rural catchments – an event monitoring program to improve water quality
modelling. 5th Australian Stream Management Conference. Australian rivers: making a
difference, Charles Sturt University, Thurgoona, New South
Wales.http://www.wqonline.info/Documents/ConfPaper_ASM_waters.pdf
Improving water quality model parameterisation and validation is dependent on
having locally relevant
sediment and nutrient data. Appropriate parameterisation is becoming increasingly
important as Natural
Resource Management (NRM) Groups use such models to quantify any change in
water quality as a result of
on-ground works. Water quality data sets for model parameterisation and validation are
limited in rural
catchments across Queensland. A sampling program was undertaken over four years,
across four catchments
in Queensland to collect sediment and nutrient storm runoff event data to improve
model parameterisation
and validation. Event mean concentrations (EMC) for sediment and phosphorus were
higher than those
reported in the literature. Total suspended solids (TSS) event concentrations ranged
from 141 - 2,720 with a
median TSS EMC of 785 mg/l. Total phosphorus (TP) and total nitrogen (TN)
concentrations ranged from
0.07 – 2.4 mg/l and 1.0 – 5.7 mg/l respectively. The data suggest that sediment and
phosphorus values for
rural catchments in Queensland may be higher than typical values reported in literature.
This work provides
new EMC values for a range of Queensland’s rural catchments. The data will improve
water quality model
parameterisation, calibration and validation. NRM groups using the data will have
greater confidence in
model outputs when quantifying the benefits of investment or prioritising funding for onground works.
Waters, D. and P. Webb, Eds. (2007). The Application of the E2 Water Quality Model
for Regional NRM Planning. MODSIM 2007 International Congress on Modelling and
Simulation, Modelling and Simulation Society of Australia and New
Zealand.http://www.mssanz.org.au/modsim07/papers/15_s37/TheApplicationofThe_s37
_Waters_.pdf