ORCID Profile
0000-0001-7266-4197
Current Organisation
Griffith University
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Soil And Water Sciences Not Elsewhere Classified | Land Capability And Soil Degradation | Soil Sciences | Surfacewater Hydrology
Other | Land and water management | Rehabilitation of degraded farmland |
Publisher: Springer Science and Business Media LLC
Date: 13-04-2017
Publisher: CSIRO Publishing
Date: 1998
DOI: 10.1071/S97025
Abstract: Pluviograph data at 6-min intervals for 41 sites in the tropics of Australia were used to compute the rainfall and runoff factor (R-factor) for the Revised Universal Soil Loss Equation (RUSLE), and a daily rainfall erosivity model was validated for these tropical sites. Mean annual rainfall varies from about 300 mm at Jervois (015602) to about 4000 at Tully (032042). The corresponding R-factor ranges from 1080 to 33500 MJ·mm/(ha ·h·year). For these tropical sites, both rainfall and rainfall erosivity are highly seasonal with a single peak in February mostly. Summer months (November–April) typically contribute about 80% of annual rainfall and about 90% of the R-factor. The daily erosivity model performed better for the tropical sites with a marked wet season in summer in comparison to model performance in temperate regions of Australia where peak rainfall and peak rainfall erosivity may occur in different seasons. A set of regional parameters depending on seasonal rainfall was developed so that the R-factor and its seasonal distribution can be estimated for sites without pluviograph data. The prediction error using the regional parameter values is about 20% for the R-factor and 1% for its monthly distribution for these tropical sites.
Publisher: Elsevier BV
Date: 06-2022
Publisher: Elsevier BV
Date: 10-2016
Publisher: IEEE
Date: 07-2016
Publisher: CSIRO Publishing
Date: 2009
DOI: 10.1071/SR09032
Abstract: The time-controlled rotational grazing (TC grazing) has become popular in Australia and elsewhere in the world to provide graziers and ranchers with improved productivity over traditional practices. However, this grazing system, which involves short periods of intensive grazing, has raised concerns about sustainability and environmental impacts on water and soil resources, and ecosystem health generally. A runoff experiment at the catchment scale was established on the grazing property ‘Currajong’ in the south-east region of Queensland, Australia, to investigate the effects of continuous and TC grazing on runoff and sediment generation from 2001 to 2006. Sediment loss was reduced significantly under TC grazing compared with continuous grazing irrespective of the size of runoff events. This effect was more pronounced in the catchments with soils of gentler slopes and greater depths. The reduction in soil erosion was achieved despite the fact that the increase in ground cover under TC grazing had little effect on runoff coefficient or runoff depth. Decrease in runoff in relation to the increase in surface cover only occurred for small events, whereas for large rainfall events, runoff generated irrespective of the level of ground cover. This study showed that ground cover is a key driver in reducing sediment concentration, resulting in a significantly lower sediment loss under TC grazing. In the study area a minimum of 70% of surface cover as a threshold appeared to be needed to efficiently protect the soil surface from erosive forces of rain and runoff and to control soil erosion. The results also indicate that TC grazing has a superior capability to produce and maintain a higher level of ground cover (up to 90%) than continuous grazing (up to 65%). The long rest periods in TC grazing are seen as the major contributor to soil and pasture recovery after intensive defoliations by grazing animals, leading to an increase in above-ground organic material and thus surface cover over time.
Publisher: Elsevier BV
Date: 08-2007
Publisher: Springer Science and Business Media LLC
Date: 17-11-2022
Publisher: Copernicus GmbH
Date: 17-02-2022
Abstract: Abstract. Rainfall erosivity quantifies the effect of rainfall and runoff on the rate of soil loss. Maps of rainfall erosivity are needed for erosion assessment using the Universal Soil Loss Equation (USLE) and its successors. To improve erosivity maps that are currently available, hourly and daily rainfall data from 2381 stations for the period 1951–2018 were used to generate new R-factor and 1-in-10-year event EI30 maps for mainland China (available at 0.12275/bnu.clicia.rainfallerosivity.CN.001 Yue et al., 2020b). One-minute rainfall data from 62 stations, of which 18 had a record length 29 years, were used to compute the “true” rainfall erosivity against which the new R-factor and 1-in-10-year EI30 maps were assessed to quantify the improvement over the existing maps through cross-validation. The results showed that (1) existing maps underestimated erosivity for most of the south-eastern part of China and overestimated for most of the western region (2) the new R-factor map generated in this study had a median absolute relative error of 16 % for the western region, compared to 162 % for the existing map, and 18 % for the rest of China. The new 1-in-10-year EI30 map had a median absolute relative error of 14 % for the central and eastern regions of China, compared to 21 % for the existing map (map accuracy was not evaluated for the western region where the 1 min data were limited) (3) the R-factor map was improved mainly for the western region, because of an increase in the number of stations from 87 to 150 and temporal resolution from daily to hourly (4) the benefit of increased station density for erosivity mapping is limited once the station density reached about 1 station per 10 000 km2.
Publisher: American Society of Civil Engineers (ASCE)
Date: 02-2017
Publisher: Institution of Engineering and Technology (IET)
Date: 1967
DOI: 10.1049/EL:19670193
Publisher: Wiley
Date: 11-1992
Publisher: Springer Science and Business Media LLC
Date: 03-06-2016
Publisher: Elsevier BV
Date: 07-2006
Publisher: IWA Publishing
Date: 02-2007
DOI: 10.2166/WST.2007.113
Abstract: Observed reductions in pollutant concentrations through stormwater treatment devices commonly display the characteristic form of exponential decay, in which the rate of decrease of pollutant concentration with distance is proportional to the concentration. The observation of an apparently irreducible or background pollutant concentration, C*, in many devices has led to development of the two-parameter “k-C*” model. It is known that this model is too simplistic because the parameters k and C* are not constant but can vary greatly with pollutant concentration and hydraulic conditions. This paper presents an alternative exponential decay model for filtration of particulate pollutants, which is based on simple mathematical descriptions of key removal processes. The model delivers a process-based method for estimating the exponential decay constant. Moreover, the need to specify a background concentration is eliminated. To test the theory, the model is applied to the removal of clay and silica particles from horizontal flow through an experimental gravel trench. Particle concentrations were measured at nine locations along a 7.2 m long flume. The model agrees very well with the observed change in suspended solids concentration for the two pollutant materials and the range of flow rates tested. A single model parameter, notionally representing the “stickiness” of pollutant particles, is required for different pollutant materials.
Publisher: CSIRO Publishing
Date: 1996
DOI: 10.1071/SR9960721
Abstract: The rainfall erosivity model relating storm erosivity to daily rainfall amounts was tested for 4 sites in South Australia where seasonal rainfall erosivity is generally out of phase with seasonal rainfall because of the predominant winter rainfall. The model worked reasonably well, with the coefficient of efficiency varying from 0.54 to 0.77, and the average discrepancy between actual and estimated monthly distribution was no more than 3%. The model performance in the winter rainfall area is similar to that in the uniform and summer rainfall areas. A set of regional parameter values estimated using a combined dataset is recommended for other sites in the agricultural and viticultural areas of South Australia where the mean annual rainfall ranges from 300 to 500 mm. The R-factor and its seasonal distribution were estimated for 99 sites in South Australia using long-term daily rainfall data. The R-factor varies mostly between 250 and 500 MJ . mm/(ha . h . year). Rainfall erosivity peaks in winter in the southern part of the western agricultural area and the south-east corner of the State, while it peaks in summer in the inland area east of the South Flinders and Mount Lofty Ranges.
Publisher: American Society of Civil Engineers (ASCE)
Date: 11-1998
Publisher: American Geophysical Union (AGU)
Date: 05-2023
DOI: 10.1029/2022WR033625
Abstract: Predicting catchment stormflow responses after tropical deforestation remains difficult. We used 5‐min rainfall and storm runoff data for 30 events to calibrate the Green–Ampt (GA) and the Spatially Variable Infiltration (SVI) models and predict runoff responses for a small, degraded grassland catchment on Leyte Island (the Philippines), where infiltration‐excess overland flow (IOF) is considered the dominant runoff process. SVI replicated in idual stormflow hydrographs better than GA, particularly for events with small runoff responses or multiple peaks. Calibrated parameter values of the SVI model (i.e., spatially averaged maximum infiltration capacity, I m and initial abstraction, F 0 ) varied markedly between events, but were statistically significant and negatively correlated with (mid‐slope) soil moisture content at 10 cm (SWC 10 )—as did the “catchment‐wide effective” hydraulic conductivity ( K e ) of the GA model. Using SWC 10 ‐based estimates of F 0 and I m in SVI yielded satisfactory to good simulations for 11 out of 17 events with runoff coefficients ≥15%, but failed to reproduce the hydrographs for events with very small runoff amounts (0.25–1 mm) and low runoff coefficients (3%–6%). The median field‐measured near‐surface K sat (2 mm hr −1 ) was distinctly lower than the median I m (32 mm hr −1 ) and, to a lesser extent, K e (∼8 mm hr −1 ), suggesting an underestimation of the spatially averaged K sat by the field measurements. Application of SVI is expected to give the most realistic results for situations where IOF is dominant, that is, where surface conditions are degraded and rainfall intensities high.
Publisher: Wiley
Date: 02-12-2019
DOI: 10.1002/JOC.6382
Publisher: Elsevier BV
Date: 04-2004
Publisher: CSIRO Publishing
Date: 2015
DOI: 10.1071/SR14188
Abstract: Considerable seasonal and inter-annual changes exist in rainfall amount and intensity in New South Wales (NSW), Australia. These changes are expected to have significant effect on rainfall erosivity and soil erosion by water, but the magnitude of the impact is not well quantified because of the non-linear and dynamic nature of the relationship between rainfall amount and rainfall erosivity. The primary aim of this study was to model spatial and temporal variations in rainfall erosivity and impacts on hillslope erosion across NSW. We developed a daily rainfall erosivity model for NSW to calculate monthly and annual rainfall erosivity values by using gridded daily rainfall data for a continuous 53-year period including a baseline period (1961–90) and a recent period (2000–12). Model parameters were improved based on their geographic locations and elevations to be truly geo-referenced and representative of the regional relationships. Monthly and annual hillslope erosion risk for the same periods was estimated with the Revised Universal Soil Loss Equation. We produced finer scale (100-m) maps of rainfall erosivity and hillslope erosion through spatial interpolation techniques, and implemented the calculation of rainfall erosivity and hillslope erosion in a geographic information system by using automated scripts so that it is fast, repeatable and portable. The modelled rainfall erosivity values were compared with pluviograph calculations and previous studies, and the Nash–Sutcliffe coefficient of efficiency is .90. Outcomes from this study provide not only baseline information but also continuous estimates of rainfall erosivity and hillslope erosions allowing better monitoring and mitigation of hillslope erosion risk in NSW.
Publisher: Wiley
Date: 11-10-2023
DOI: 10.1002/ESP.5714
Publisher: Elsevier BV
Date: 09-2023
Publisher: American Geophysical Union (AGU)
Date: 09-2016
DOI: 10.1002/2016WR019046
Publisher: Wiley
Date: 03-1999
DOI: 10.1002/(SICI)1096-9837(199903)24:3<233::AID-ESP949>3.0.CO;2-T
Publisher: Elsevier BV
Date: 11-2016
Publisher: American Society of Civil Engineers (ASCE)
Date: 11-2012
Publisher: CSIRO Publishing
Date: 04-10-2021
DOI: 10.1071/SR21030
Abstract: Land clearing for cropping and grazing has increased runoff and sediment yield in Central Queensland. The Brigalow Catchment Study (BCS), was established to determine the effect of land clearing on water balance, soils, and productivity, and consisted of three catchments: brigalow forest, cropping, and grazing. Factors responsible for changes in and models for predicting sediment yield have not been assessed. Objectives of this study are to identify climatic, hydrological, and ground cover factors responsible for the increased sediment yield and to assess suitable models for sediment yield prediction. Runoff and sediment yield data from 1988 to 2018 were used to assess the Revised Universal Soil Loss Equation (RUSLE) and the Modified USLE (MUSLE) to predict the sediment yield in brigalow catchments. Common events among the three catchments and events for all catchment pairs were assessed. The sediment yield was approximately 44% higher for cropping and 4% higher for grazing than that from the forested catchment. The runoff amount (Q) and peak runoff rate (Qp) were major variables that could explain most of the increased sediment yield over time. A comparison for each catchment pair showed that sediment yield was 801 kg ha−1 or 37% higher for cropping and 28 kg ha−1 or 2% higher for grazing than for the forested catchment. Regression analysis for three different treatments (seven common events) and for different storm events (15 for forested, 40 for cropping, and 20 for grazing) showed that Q and Qp were best correlated with sediment yield in comparison with variations in ground cover. The high coefficient of determination (R2 0.60) provided support for using the MUSLE model, based on both Q and Qp, instead of the RUSLE, and Q and Qp were the most important factors for improving sediment yield predictions from BCS catchments.
Publisher: Elsevier BV
Date: 02-2019
Publisher: Cambridge University Press
Date: 13-01-2005
Publisher: Elsevier BV
Date: 09-2003
Publisher: American Meteorological Society
Date: 07-2017
Abstract: Global climate models (GCMs) are usually used for future climate projections. Model output from GCMs needs to be downscaled and stochastic weather generators such as Climate Generator (CLIGEN) are tools to downscale GCM output and to produce synthetic weather sequences that are statistically similar to the observed weather data. Two methods of adjusting CLIGEN parameters were developed to reproduce precipitation sequences for southeastern Australia (SEA), where significant changes in annual precipitation had occurred, and for southwestern Western Australia (SWWA), where the precipitation has shown a significant decreasing trend since the 1920s. The adjustment methods have been validated using observed precipitation data for these regions. However, CLIGEN outputs ultimately will be used as input to other simulation models. The objective of this research was to further validate the methods of CLIGEN parameter adjustment using conceptual hydrological models to simulate streamflow and to compare the streamflow using observed and CLIGEN-generated precipitation data. Six precipitation sites from SEA and SWWA were selected and synthetic time series of daily precipitation were generated for these sites. Conceptual hydrological models, namely, the Australian Water Balance Model and SimHyd, were used for flow simulation and were calibrated using recorded daily streamflow data from six gauging stations in SEA and SWWA. Both monthly and annual streamflow show statistically similar patterns using observed and CLIGEN-generated precipitation data. The adjustment methods for CLIGEN parameters are further validated and can be used to reproduce the significant changes, both abrupt and gradually decreasing, in streamflow for these two climatically contrasting regions of Australia.
Publisher: American Geophysical Union (AGU)
Date: 02-2016
DOI: 10.1002/2015WR017766
Publisher: American Geophysical Union (AGU)
Date: 03-1987
Publisher: Elsevier BV
Date: 05-2007
Publisher: American Geophysical Union
Date: 1995
DOI: 10.1029/GM089P0113
Publisher: American Society of Agricultural and Biological Engineers (ASABE)
Date: 1999
DOI: 10.13031/2013.13327
Publisher: American Society of Civil Engineers (ASCE)
Date: 06-2015
Publisher: CSIRO Publishing
Date: 1997
DOI: 10.1071/S97002
Abstract: In recent years, a number of physically based models have been developed for soil loss predictions. GUEST is one such model based on fundamental physical principles and the current understanding of water erosion processes. GUEST is mainly used to determine a soil erodibility parameter. To apply the model in a predictive mode, the model is simplified in a physically meaningful manner for flow-driven erosion processes, and 2 essential hydrologic variables are identified, namely total runoff amount and an effective runoff rate. These variables are required to determine soil loss for in idual runoff events. A simple water balance model was developed and used to predict runoff amount from rainfall amount. The efficiency of this runoff amount model in prediction was over 90% using field data. A 1-parameter regression model (r2 ~ 0·9) for the effective runoff rate was also established which uses peak rainfall intensity in addition to rainfall and runoff amounts. The prediction of peak rainfall intensity for a given rainfall amount and storm type was also sought. The field data were from Goomboorian, near Gympie, in south-east Queensland and these data were used to test and validate both models. Results overall are satisfactory and the approach adopted is promising. A framework for soil loss prediction is established within which in idual parts can be further refined and improved.
Publisher: Elsevier BV
Date: 12-2020
Publisher: MDPI AG
Date: 27-10-2021
DOI: 10.3390/APP112110044
Abstract: Total imperviousness (residential and non-residential) increases with population growth in many regions around the world. Population density has been used to predict the total imperviousness in large areas, although population size was only closely related to residential imperviousness. In this study, population density together with land use data for 154 suburbs in Southeast Queensland (SEQ) of Australia were used to develop a new model for total imperviousness estimation. Total imperviousness was extracted through linear spectral mixing analysis (LSMA) using Landsat 8 OLI/TIRS, and then separated into residential and non-residential areas based on land use data for each suburb. Regression models were developed between population density and total imperviousness, and population density and residential imperviousness. Results show that (1) LSMA approach could retrieve imperviousness accurately (RMSE 10%), (2) linear regression models could be used to estimate both total imperviousness and residential imperviousness better than nonlinear regression models, and (3) correlation between population density and residential imperviousness was higher (R2 = 0.77) than that between population density and total imperviousness (R2 = 0.52) (4) the new model was used to predict the total imperiousness based on population density projections to 2057 for three potential urban development areas in SEQ. This research allows accurate prediction of the total impervious area from population density and service area per capital for other regions in the world.
Publisher: Informa UK Limited
Date: 2000
Publisher: Elsevier BV
Date: 11-2003
Publisher: Elsevier BV
Date: 11-2019
Publisher: Elsevier BV
Date: 03-2014
Publisher: Informa UK Limited
Date: 05-07-2013
Publisher: Informa UK Limited
Date: 02-1999
Publisher: Springer Science and Business Media LLC
Date: 11-05-2011
Publisher: Wiley
Date: 2003
DOI: 10.1002/ESP.1001
Publisher: Copernicus GmbH
Date: 23-06-2021
DOI: 10.5194/ESSD-13-2945-2021
Abstract: Abstract. The stochastic weather generator CLIGEN can simulate long-term weather sequences as input to WEPP for erosion predictions. Its use, however, has been somewhat restricted by limited observations at high spatial–temporal resolutions. Long-term daily temperature, daily, and hourly precipitation data from 2405 stations and daily solar radiation from 130 stations distributed across mainland China were collected to develop the most critical set of site-specific parameter values for CLIGEN. Ordinary kriging (OK) and universal kriging (UK) with auxiliary covariables, i.e., longitude, latitude, elevation, and the mean annual rainfall, were used to interpolate parameter values into a 10 km×10 km grid, and the interpolation accuracy was evaluated based on the leave-one-out cross-validation. Results showed that UK generally outperformed OK. The root mean square error between UK-interpolated and observed temperature-related parameters was ≤0.88 ∘C (1.58 ∘F). The Nash–Sutcliffe efficiency coefficient for precipitation- and solar-radiation-related parameters was ≥0.87, except for the skewness coefficient of daily precipitation, which was 0.78. In addition, CLIGEN-simulated daily weather sequences using UK-interpolated and observed parameters showed consistent statistics and frequency distributions. The mean absolute discrepancy between the two sequences for temperature was .51 ∘C, and the mean absolute relative discrepancy for solar radiation, precipitation amount, duration, and maximum 30 min intensity was % in terms of the mean and standard deviation. These CLIGEN parameter values at 10 km resolution would meet the minimum data requirements for WEPP application throughout mainland China. The dataset is available at clicia.bnu.edu.cn/data/cligen.html (last access: 20 May 2021) and 0.12275/bnu.clicia.CLIGEN.CN.gridinput.001 (Wang et al., 2020).
Publisher: American Society of Agricultural and Biological Engineers (ASABE)
Date: 1996
DOI: 10.13031/2013.27535
Publisher: Springer Science and Business Media LLC
Date: 23-06-2017
DOI: 10.1038/S41598-017-04282-8
Abstract: The exposure of the Earth’s surface to the energetic input of rainfall is one of the key factors controlling water erosion. While water erosion is identified as the most serious cause of soil degradation globally, global patterns of rainfall erosivity remain poorly quantified and estimates have large uncertainties. This h ers the implementation of effective soil degradation mitigation and restoration strategies. Quantifying rainfall erosivity is challenging as it requires high temporal resolution( min) and high fidelity rainfall recordings. We present the results of an extensive global data collection effort whereby we estimated rainfall erosivity for 3,625 stations covering 63 countries. This first ever Global Rainfall Erosivity Database was used to develop a global erosivity map at 30 arc-seconds(~1 km) based on a Gaussian Process Regression(GPR). Globally, the mean rainfall erosivity was estimated to be 2,190 MJ mm ha −1 h −1 yr −1 , with the highest values in South America and the Caribbean countries, Central east Africa and South east Asia. The lowest values are mainly found in Canada, the Russian Federation, Northern Europe, Northern Africa and the Middle East. The tropical climate zone has the highest mean rainfall erosivity followed by the temperate whereas the lowest mean was estimated in the cold climate zone.
Publisher: University of Chicago Press
Date: 12-2019
DOI: 10.1086/706040
Publisher: CSIRO Publishing
Date: 2001
DOI: 10.1071/SR00091
Abstract: It is important to use historical data to test physically based runoff and soil erosion prediction models as well as the method to estimate model parameters. WEPP (Water Erosion Prediction Project) was validated for bare fallow and annual wheat treatments at Gunnedah, New South Wales, Australia. Wheat stubble was either burned or mulched. Climate, soil, management, and runoff and soil loss data were collected for the period 1980–87 for 3 bare fallow plots, and 1950–74 for 10 annual wheat plots. Three slope lengths from 21 to 62 m were established for the treatment with stubble burned. Slope steepness varied from 8% to 9% at the site. Effective saturated hydraulic conductivity and soil erodibility parameters were estimated from measured soil properties. No further calibration of these parameters was attempted in order to assess the true potential of the model for runoff and soil loss predictions. WEPP worked well for the bare fallow plots with prediction efficiency of 0.97 for event runoff and soil losses. WEPP generally over-predicted the runoff, and consequently, the soil loss for annual wheat treatments for the site. WEPP was able to predict the effect of slope length on sediment concentration and soil loss for the site. CLIGEN, which provides the continuous climate input to WEPP, was found to produce adequately the mean daily rainfall, but produced higher than expected peak rainfall intensity, resulting in higher runoff and soil loss for all treatments.
Publisher: CSIRO Publishing
Date: 2000
DOI: 10.1071/SR99104
Abstract: Monthly runoff and soil loss simulated by WEPP (Water Erosion Prediction Project) were compared with field observations on a pineapple farm in south-east Queensland for a 3-year period. The soil at the site is sandy. Slope length and steepness are 36m and 5.5%, respectively. Three treatments, namely bare, farmers’ conventional practice, and mulching of the furrows, were used. Infiltration and erodibility parameters were determined using WEPP-recommended equations and measurable soil properties. These parameters were also calibrated using the runoff and soil loss data for the bare plot only. Apart from the soil loss prediction for the mulching treatment, for which WEPP did not perform well, the average coefficient of efficiency in runoff and soil loss predictions was –0.02 using soil property-based parameter values and 0.66 using calibrated parameter values. The corresponding r 2 values are 0.57 and 0.81, respectively. On the whole, WEPP is able to reproduce the trend and variations in runoff and soil loss among different treatments for the site. Parameter values based on measurable soil properties would greatly under-estimate the runoff and soil loss for the site. Thus, use of WEPP outside its US database requires calibration with locally obtained data. It was also found that WEPP does not seem to model effectively the situation where there is considerable flow impediment with the furrows covered with mulch. We are unable to reject WEPP because the statistical performance indicators are reasonable for the site, and because the model is so complex that it is nearly impossible to pinpoint the source of discrepancy and articulate the model deficiency on physical grounds.
Publisher: Elsevier BV
Date: 06-2014
Publisher: Elsevier BV
Date: 10-2018
Publisher: Elsevier BV
Date: 06-2008
Publisher: Springer Science and Business Media LLC
Date: 12-07-2007
Publisher: American Society of Agricultural and Biological Engineers (ASABE)
Date: 1998
DOI: 10.13031/2013.17233
Publisher: CSIRO Publishing
Date: 1999
DOI: 10.1071/S98040
Abstract: When physically based erosion models such as GUEST are used to determine soil erodibility parameters or to predict the rate of soil loss, data on runoff rates, as distinct from event runoff amount, are often needed. Data on runoff rates, however, are not widely available. This paper describes methods that can be used to overcome this lack of data on runoff rates. These methods require only rainfall rates and runoff amounts, which are usually available for sites set up primarily to test and validate the USLE technology. In addition, the paper summarises the data requirements for the erosion model GUEST and application procedures. In the accompanying paper, these methods are applied to 4 experimental sites in the ASIALAND Network.
Publisher: Elsevier BV
Date: 09-2022
Publisher: Informa UK Limited
Date: 20-08-2015
Publisher: Informa UK Limited
Date: 25-02-2010
Publisher: CSIRO Publishing
Date: 2020
DOI: 10.1071/RJ19082
Abstract: Considering the degree of spatial and temporal variation of groundcover in grazing land, it is desirable to use a simple and robust model to represent the spatial variation in cover in order to quantify its effect on runoff and soil loss. The purpose of the study was to test whether a two-parameter beta (β) distribution could be used to characterise cover variation in space at the sub-catchment scale. Twenty sub-catchments (area range 35.8–231km2) in the Burnett–Mary region, Queensland, were randomly selected. Thirty raster layers of groundcover at 30-m resolution were prepared for these 20 sub-catchments with the average cover for the 30 layers ranging from 24% to 91%. Three methods were used to test the appropriateness of the β distribution for characterising the cover variation in space: (i) visual goodness-of-fit assessment and Kolmogorov–Smirnov (K-S) test (ii) the fractional area with cover ≤53% and (iii) estimated runoff amount for a given rainfall amount for the area with cover ≤53%. The K-S test on 30×100 s les of groundcover showed that the hypothesis of β distribution for groundcover could not be rejected at P=0.05 for 97.5% of the cases. A comparison of the observed and β distributions in terms of the fractional area with cover ≤53% showed that the discrepancy was ≤8% for the 30 layers considered. A comparison in terms of the estimated runoff showed that results using the observed cover distribution and the β distribution were highly correlated (R2 range 0.91–0.98 Nash–Sutcliffe efficiency measure range 0.88–0.99). The mean absolute error of estimated runoff ranged from 0.98 to 8.10mm and the error relative to the mean was 4–16%. The results indicated that the two-parameter β distribution can be adequately used to characterise the spatial variation of cover and to evaluate the effect of cover on runoff for these predominantly grazing catchments.
Publisher: CSIRO Publishing
Date: 1999
DOI: 10.1071/S98041
Abstract: Runoff rates were estimated from rainfall rates and runoff amounts for 4 experimental sites in China, Malaysia, and Thailand before a physically based erosion model GUEST was used to determine the soil erodibility parameter and evaluate the potential to use the erosion model to predict the amount of soil loss on an event basis. We also examined 3 different ways of determining the soil erodibility parameter for the same storm event using: (i) hydrographs estimated from rainfall intensities and runoff amounts (ii) an effective runoff rate calculated from the hydrograph (iii) an estimate of the effective runoff rate based on a scaling technique involving the peak rainfall intensity and the gross runoff coefficient. All 3 methods can produce consistent soil erodibility parameters for a given runoff event. The calculated soil erodibility for in idual storm events for all sites shows considerable temporal variation and for most sites a decreasing trend over time, as observed elsewhere in the same region. Among the 4 soils examined, the average soil erodibility tends to decrease as the ratio of coarse to fine materials decreases. When the erosion model GUEST is used to predict event soil loss using estimated soil erodibility parameters, an average model efficiency of 0·68 is achieved for the sites tested.
Publisher: Wiley
Date: 2003
Publisher: Elsevier BV
Date: 03-2019
Publisher: Elsevier BV
Date: 06-2005
Publisher: Elsevier BV
Date: 06-2000
Publisher: Elsevier BV
Date: 04-2002
Publisher: IWA Publishing
Date: 08-11-2018
DOI: 10.2166/NH.2017.003
Abstract: Loess Plateau is known for its high rate of soil erosion. Infiltration models are needed to simulate runoff hydrograph for erosion prediction. Rainfall-runoff data at 1-min interval for 33 plot-events in Tuanshangou catchment were used to evaluate three infiltration models: constant infiltration (CI) rate, spatially variable infiltration (VI) rate, and Green–Ampt (GA). Each of the three models has three parameters. The three models performed similarly when calibrated for in idual storms with a Nash–Sutcliffe coefficient (NSC) of efficiency of around 0.76, with better performance for large storm events. For all three models, the total runoff amount is well simulated while the modelled peak runoff rate is systematically smaller by about 30%. The variation in the initial infiltration amount is smaller than that in other infiltration parameters. For ungauged events, averaged parameter values were used to predict runoff hydrographs, and the results showed a decrease in model performance with the average NSC reduced to 0.47. One advantage in using the spatially VI model is that the simulated runoff is least sensitive to changes in model parameters compared with the other two models, as a 10% variation in parameter values would lead to 5% variations on average in the simulated runoff for VI, while around 8.6% for the other two.
Publisher: Elsevier BV
Date: 03-2015
Publisher: Wiley
Date: 06-12-2018
DOI: 10.1002/IRD.2197
Publisher: Elsevier BV
Date: 05-2018
Publisher: Wiley
Date: 06-05-2023
DOI: 10.1002/ESP.5611
Abstract: Dust storms are regarded as global natural hazards, adversely impacting the climate, economy, and human health. As a dry continent, Australia is extensively impacted by dust storm activity, particularly in dry seasons. Located in the Mallee region and 600 km downwind of the Lake Eyre Basin, Mildura is one of the most vulnerable regional cities to dust storms. Rapid development of agriculture in the Mildura region removed natural vegetation and increased the frequency of dust storms in the 20th century. To better understand the factors and processes that affect dust storm activity in Mildura, a seasonal predictive model for dust event days was developed in the early 1990s. This was based on an empirical relationship between seasonal rainfall in preceding autumn and summer dust event days (the most active dust season in Mildura). In this study, this model was applied for a further 24‐year period (from 1990 to 2013) to test model validity for forecasting dust activity. Results show that the r 2 was 0.13 and the root mean square error was 5.33 days in the ‘forecast’ mode, which indicates poorer model performance than that for the original calibration period (1960–1989). All large ‘forecast’ errors occurred in the 1990s. Winter rainfall was identified as the main climate factor for overprediction. The effect of the preceding winter rainfall on summer dust event occurrence was found to increase with the ratio of winter rainfall over autumn rainfall for the whole period of 1960–2013. An updated dust prediction model for 1960–2013 was constructed based on preceding autumn and winter rainfall. Autumn rainfall was used as the predictor when the ratio of winter and autumn rainfall was no more than 3.1 otherwise, winter rainfall was used. This was a marked improvement in model performance with an r 2 value of 0.37 to that of 0.26 for the original model performance for the period as a whole (1960–2013).
Publisher: American Geophysical Union (AGU)
Date: 28-07-2014
DOI: 10.1002/2014GL060741
Publisher: Wiley
Date: 2005
DOI: 10.1002/ASL.95
Publisher: Elsevier BV
Date: 10-2009
Publisher: Elsevier BV
Date: 02-2022
Publisher: Copernicus GmbH
Date: 12-06-2015
DOI: 10.5194/PIAHS-371-109-2015
Abstract: Abstract. Most hydrological models use continuous daily precipitation and potential evapotranspiration for streamflow estimation. With the projected increase in mean surface temperature, hydrological processes are set to intensify irrespective of the underlying changes to the mean precipitation. The effect of an increase in rainfall intensity on the long-term water balance is, however, not adequately accounted for in the commonly used hydrological models. This study follows from a previous comparative analysis of a non-stationary daily series of stream flow of a forested watershed (River Rimbaud) in the French Alps (area = 1.478 km2) (1966–2006). Non-stationarity in the recorded stream flow occurred as a result of a severe wild fire in 1990. Two daily models (AWBM and SimHyd) were initially calibrated for each of three distinct phases in relation to the well documented land disturbance. At the daily and monthly time scales, both models performed satisfactorily with the Nash–Sutcliffe coefficient of efficiency (NSE) varying from 0.77 to 0.92. When aggregated to the annual time scale, both models underestimated the flow by about 22% with a reduced NSE at about 0.71. Exploratory data analysis was undertaken to relate daily peak hourly rainfall intensity to the discrepancy between the observed and modelled daily runoff amount. Preliminary results show that the effect of peak hourly rainfall intensity on runoff prediction is insignificant, and model performance is unlikely to improve when peak daily precipitation is included. Trend analysis indicated that the large decrease of precipitation when daily precipitation amount exceeded 10–20 mm may have contributed greatly to the decrease in stream flow of this forested watershed.
Publisher: Wiley
Date: 22-12-2010
Publisher: Elsevier BV
Date: 04-2019
DOI: 10.1016/J.SCITOTENV.2018.12.310
Abstract: The bio ersity value of river-oxbow lake systems in high plateau peatland has been little recognized, and there are many gaps in our understanding of their ecology. In this study, we investigated the river-oxbow lake system of the Bai River basin, the main tributary of the Yellow River Source in the Zoige wetland from 2015 to 2016, in attempt to show how the environmental variations, especially hydrological connectivity and macrophyte biomass in the river-oxbow lake system influenced macroinvertebrates. Habitat patches were investigated in 11 river cross-sections and 18 oxbow lakes in the Bai River basin. Through hierarchical clustering and non-metric multidimensional scaling, four main types of habitats were identified in the river-oxbow lake system in the plateau: sand-bed river, cobble-bed river, sparse-macrophyte oxbow lake, and luxuriant-macrophyte oxbow lake. The luxuriant-macrophyte oxbows were characterized by high dissolved oxygen concentrations, alkalinity, and higher macroinvertebrate richness, density, biomass, and the Improved Shannon-Wiener Index in comparison to the other habitat types. Additionally, influential patterns of environmental variables on macroinvertebrates were analyzed using redundancy analysis. Lasso regression models were established to describe how macroinvertebrate density responded to macrophyte biomass and other variables, and how macrophyte biomass responded to hydrological connectivity and oxbow size. It was revealed that reduced hydrological connectivity and reduced oxbow size played important roles in increasing the biomass of submerged macrophyte, and dense macrophyte was directly responsible for the high bio ersity of macroinvertebrates. Different from the commonly believed unimodal influential pattern that medium hydrological connectivity supports the highest bio ersity in oxbow lakes reported in previous studies, macroinvertebrates in the high plateau river-oxbow lake systems benefited from low connectivity and reduced size. Oxbow lakes, especially those covered with luxuriant macrophytes, ersified the macroinvertebrate assemblages and enhanced primary consumer biomass at the regional scale.
Publisher: Elsevier BV
Date: 10-2019
Publisher: CSIRO Publishing
Date: 2002
DOI: 10.1071/SR01117
Abstract: Spatially distributed rainfall erosivity and its seasonal distribution are needed to use the revised universal soil loss equation (RUSLE) for erosion risk assessment at large scale. An erosivity model and 20-year daily rainfall data at 0.05° resolution were used to predict the R-factor and its monthly distribution for RUSLE in Australia. Predicted R-factor values were compared with those previously calculated using pluviograph data for 132 sites around Australia. The daily erosivity model was further evaluated for 43 sites where long-term pluviograph data were available. Predicted and calculated monthly distributions of the R-factor were compared for these 43 sites. For the 132 sites where R-factor values were compiled from previous investigations, the model efficiency was 0.81 with root mean squared error (rmse) of 1832 MJ.mm/(ha.h.year), or 47.5% of the mean for the 132 sites. For the additional 43 sites, the coefficient of efficiency was 0.93 with a 12.7 mm rainfall threshold, and 0.94 when all storms were included in the calculations. The rmse was 908 MJ.mm/(ha.h.year), or 28.6% of the mean for the 43 sites with a zero rainfall threshold. The prediction error for monthly distribution of the R-factor was 2.3% with a zero threshold and 2.5% with 12.7�mm threshold. This and previous studies have shown that the daily rainfall erosivity model can be used to accurately predict the R-factor and its seasonal distribution in Australia. Digital maps were produced showing the spatial and seasonal distribution of the R-factor at 0.05° resolution in Australia. These maps have been used to assess rill and sheet erosion rate at the continental scale.
Publisher: Wiley
Date: 18-10-2020
DOI: 10.1002/LDR.3778
Abstract: The sediment transport capacity plays a pivotal role in erosion research, and is usually predicted using hydraulic variables. The transport capacity and hydraulic variables are affected by vegetation cover. Our understanding of the effect of vegetation cover, including the size, density, and arrangement of vegetation stems, on the relationship between the sediment transport capacity and hydraulic variables were rather limited. The objectives of this study were to investigate the effect vegetation stem cover on the relationship between hydraulic variables and the sediment transport capacity and to derive an equation for predicting the sediment transport capacity in the presence of vegetation cover. Five data sets from 288 flume experiments with a wide range of discharge (0.25–2 × 10 −3 m 3 s −1 ), slope (8.8–42.3%), median sediment diameter (0.11–1.16 × 10 −3 m), stem cover (0–30%), stem diameter (2–36 mm), and stem arrangement (bead, tessellation, zigzag, random, and banding) were compiled for this study. Extensive regression analysis has shown that the sediment transport capacity could be expressed as a power function of flow velocity, shear stress, stream power, or unit stream power. Predictors of the sediment transport capacity were ranked from the unit stream power as the strongest, followed by the stream power, flow velocity, and the shear stress. Vegetation stem cover had no apparent and direct effect on the relationship between hydraulic variables and the sediment transport capacity so long as the unit stream power or stream power was used as its predictor. Vegetation cover became a significant factor only when the shear stress was used to predict the sediment transport capacity. Finally, a new equation involving the slope gradient, flow velocity, and median sediment diameter in a nondimensional form was shown to be a superior predictor of the sediment transport capacity with the Nash–Sutcliffe coefficient of efficiency of 0.92. The product of slope and flow velocity, that is, the unit stream power, captures the effect of vegetation stem cover and surface roughness and was shown to be an effective predictor of the transport capacity in the presence of vegetation cover.
Publisher: American Meteorological Society
Date: 08-0928
Abstract: Karst landforms cover 7%–12% of the Earth’s continental area and provide water resources for 25% of the global population. Climate, particularly frequent climate extremes, may greatly affect the annual runoff, especially in climate-sensitive regions such as a karst area of southwest China. Knowledge of the linkage between climate and runoff is urgently needed for smart water resources management. This study therefore selected five catchments that have different carbonized rock coverage (from 11% to 64%) to detect the dominant climatic variables driving changes in annual runoff for the period of 1957–2011 in southwest China. Because climatic variables are highly codependent, a partial least squares regression (PLSR) was used to elucidate the linkages between runoff and 17 climatic variables. Results indicated that the dominant climatic factors driving annual runoff are annual total precipitation, rainy days, heavy precipitation amount, heavy precipitation days, rainstorm amount, and rainstorm days. These six factors are generally used to represent extreme climatic events, and hence it may demonstrate that annual runoff is highly linked to precipitation extremes in this region. The PLSR approach presented in this study is beneficial and novel, as it enables the elimination of codependency among the variables and facilitates a more unbiased view of the contribution of the changes in climatic variables to the changes in runoff. As a practical and simple tool, the PLSR approach is thus recommended for application to a variety of other catchments.
Publisher: Public Library of Science (PLoS)
Date: 28-03-2018
Publisher: Wiley
Date: 09-2000
Publisher: American Meteorological Society
Date: 08-2013
Abstract: It is generally assumed that rainfall intensity will increase with temperature increase, irrespective of the underlying changes to the average rainfall. This study documents and investigates long-term trends in rainfall intensities, annual rainfall, and mean maximum and minimum temperatures using the Mann–Kendall trend test for nine sites in eastern Australia. Relationships between rainfall intensities at various durations and 1) annual rainfall and 2) the mean maximum and minimum temperatures were investigated. The results showed that the mean minimum temperature has increased significantly at eight out of the nine sites in eastern Australia. Changes in annual rainfall are likely to be associated with changes in rainfall intensity at the long duration of 48 h. Overall, changes in rainfall intensity at short durations (& h) positively correlate with changes in the mean maximum temperature, but there is no significant correlation with the mean minimum temperature and annual rainfall. Additionally, changes in rainfall intensity at longer durations (≥1 h) positively correlate with changes in the mean annual rainfall, but not with either mean maximum or minimum temperatures for the nine sites investigated.
Publisher: American Society of Agricultural and Biological Engineers (ASABE)
Date: 17-02-2016
Publisher: MDPI AG
Date: 06-06-2023
Abstract: Temporal variability of rainfall is extreme in the rangelands of northern Australia and occurs at annual, decadal, and even longer timescales. To maintain long-term productivity of the rangelands of northern Australia under highly variable rainfall conditions, suitable land management practices are assessed using rangeland biophysical models, e.g., GRASP (GRASs Production). The daily maxima of the 15 min rainfall intensity (I15) are used to predict runoff and moisture retention in the model. The performance of rangeland biophysical models heavily relies on the I15 estimates. As the number of pluviograph stations is very limited in northern Australian rangelands, an empirical I15 model (Fraser) was developed using readily available daily climate variables, i.e., daily rainfall total, daily diurnal temperature range, and daily minimum temperature. The aim of this study is to estimate I15 from daily rainfall totals using a well-established disaggregation scheme coupled with the Bartlett–Lewis rectangular pulse (BLRP) model. In the absence of pluviograph data, the BLRP models (RBL-E and RBL-G) were calibrated with the precipitation statistics estimated using the Integrated Multi-satellitE Retrievals for GPM (global precipitation measurement) (IMERG 30 min, 0.1° resolution) precipitation product. The Fraser, RBL-E, and RBL-G models were assessed using 1 min pluviograph data at a single test site in Darwin. The results indicated that all three models tended to underestimate the observed I15, while a serious underestimation was observed for RBL-E and RBL-G. The underestimation by the Fraser, RBL-E, and RBL-G models consisted of 23%, 38%, and 50% on average, respectively. Furthermore, the Fraser model represented 29% of the variation in observed I15, whereas RBL-E and RBL-G represented only 7% and 11% of the variation, respectively. A comparison of RBL-E and RBL-G suggested that the difference in the spatial scales of IMERG and pluviograph data needs to be addressed to improve the performance of RBL-E and RBL-G. Overall, the findings of this study demonstrate that the BLRP model calibrated with IMERG statistics has the potential for estimating I15 for the GRASP biophysical model once the scale difference between IMERG and point rainfall data is addressed.
Publisher: CSIRO Publishing
Date: 2008
DOI: 10.1071/SR07220
Abstract: Grazing by livestock has a great influence on soil characteristics with major effects on soil carbon and nitrogen cycling in grazing lands. Grazing practices affect soil properties in different ways depending on the prescribed stocking rate and grazing periods. The new grazing system of short, intensive grazing followed by a long period of rest, referred to as time-controlled grazing (TC grazing), has become popular among many graziers in Australia and elsewhere. However, little research has been carried out on the impacts of this grazing system on the physical and chemical health of the soil. To address this issue, a comprehensive field study was carried out on a sheep-grazing property in the south-eastern region of Queensland, Australia, where the 2 grazing systems of continuous and TC grazing were compared. Results over the period 2001–2006 showed an increase in soil organic carbon and nitrogen in the areas with favourable soil condition compared with continuous grazing. There was also an increase in ground-litter accumulation over time and no compaction in TC grazing. Nitrate and extractable P concentrations were reduced by increased grass growth under TC grazing, which in turn decreased the contamination potential for downstream water bodies. This reduction was much more pronounced on a historical sheep aggregation c , where a large amount of faecal material had been deposited prior to conversion to TC grazing. The smaller size of the paddocks, along with the long rest period provided by TC grazing in this area, are recognised to be the major contributors to both physical and chemical recovery of the soil after each grazing operation.
Publisher: Informa UK Limited
Date: 10-2000
Publisher: Wiley
Date: 09-2007
Publisher: American Society of Agricultural and Biological Engineers (ASABE)
Date: 1999
DOI: 10.13031/2013.13212
Publisher: Elsevier BV
Date: 10-2023
Publisher: American Geophysical Union (AGU)
Date: 11-2017
DOI: 10.1002/2017GB005733
Publisher: American Geophysical Union (AGU)
Date: 05-2015
DOI: 10.1002/2015JG002947
Publisher: Springer Science and Business Media LLC
Date: 10-2016
Publisher: Wiley
Date: 1993
Publisher: Wiley
Date: 22-09-2022
Publisher: Informa UK Limited
Date: 11-1998
Publisher: American Meteorological Society
Date: 05-2020
DOI: 10.1175/EI121.1
Abstract: At the Visayas State College of Agriculture (ViSCA) on the island of Leyte in the Philippines, hydrologic and soil-loss measurements were recorded for 32 erosion events over 3 yr on three 12-m-long bare soil plots with slopes of approximately 50%, 60%, and 70%. Measurements included rainfall and runoff rates at 1-min intervals, total soil lost per event from the plot, rill details when observed after an erosion event, and soil settling-velocity characteristics. Storm events are characterized by high rainfall rates but quite low rates of runoff, because of the consistently high infiltration rate of the stable clay soil (an Oxic Dystropept). Both observation and modeling indicated that overland flow is commonly so shallow that much of the soil surface is likely to be unsubmerged. For the 70% slope plot, half the events recorded mean sediment concentrations from 100 to 570 kg m−3. A somewhat constant hydrologic lag between rainfall and runoff is used to estimate a Manning’s roughness coefficient n of about 0.1 m−1/3 s, a value used to estimate velocity of overland flow. Possible effects of shallow flows and high sediment concentrations on existing erosion theory are investigated theoretically but are found to have only minor effects for the ViSCA dataset. A soil erodibility parameter β was evaluated for the data whenever rilling was recorded following an erosion event. The values of β indicate that, except for events with higher stream powers, other erosion processes in addition to overland flow could have contributed to soil loss from erosion plots in a significant number of events.
Publisher: Informa UK Limited
Date: 2006
Publisher: MDPI AG
Date: 11-09-2018
DOI: 10.3390/INVENTIONS3030066
Abstract: The Microgrids (MGs) are an effective way to deal with the smart grid challenges, including service continuity in the event of a grid interruption, and renewable energy integration. The MGs are compounded by multiple distributed generators (DGs), and the main control goals are load demand sharing and voltage and frequency stability. Important research has been reported to cope with the implementation challenges of the MGs including the power sharing control problem, where the use of cybernetic components such as virtual components, and communication systems is a common characteristic. The use of these cybernetic components to control complex physical systems generates new modeling challenges in order to achieve an adequate balance between complexity and accuracy in the MG model. The standardization problem of the cyber-physical MG models is addressed in this work, using a cyber-physical energy systems (CPES) modeling methodology to build integrated modules, and define the communication architectures that each power sharing control strategy requires in an AC-MG. Based on these modules, the control designer can identify the signals and components that eventually require a time delay analysis, communication requirements evaluation, and cyber-attacks’ prevention strategies. Similarly, the modules of each strategy allow for analyzing the potential advantages and drawbacks of each power sharing control technique from a cyber physical perspective.
Publisher: Springer Science and Business Media LLC
Date: 17-04-2023
Publisher: Springer Science and Business Media LLC
Date: 07-08-2018
DOI: 10.1007/S10661-018-6836-7
Abstract: Soil and water conservation (SWC) measures can be adopted to conserve soil and water and improve soil fertility. The degree to which SWC measures improve soil fertility is affected by the type of SWC measure, soil type, climate, etc. The purpose of this study was to study the effect of the main SWC measures implemented in the Beijing mountain area on soil fertility. Six runoff plots, including a fish pit (fallow) (FPF), fish pit (Platycladus orientalis L. Franco) (FPP), narrow terrace (fallow) (NTF), narrow terrace (Juglans regia L.) (NTJ), tree pan (Juglans regia L.) (TPJ), and fallow land (FL), were established to analyze the differences in soil fertility in the Beijing mountain area. Soil s les were collected in 2005 and 2015 from the six runoff plots. Soil particle size soil total nitrogen (TN), total phosphorous (TP), total potassium (TK), alkali-hydrolysable nitrogen (Ah-N), available P (Av-P), and available K (Av-K) and soil organic matter (SOM) were measured. The soil integrated fertility index (IFI) was calculated. The results showed that the soil nutrient content and IFI significantly decreased from 2005 to 2015 in the FL plot and significantly increased in the five runoff plots with SWC measures. Compared to the other runoff plots with SWC measures, the FPP plot more significantly improved the soil nutrient content and IFI. The TN, Ah-N, Av-K, SOM, and IFI in the FPP plots increased by 98%, 113%, 61%, 69 and 47%, respectively, from 2005 to 2015. The IFI for the FPP, NTJ, and TPJ exceeded the average IFI of the farmland soil in the study region. The results indicated that the combination of engineering practices and vegetative measures effectively improved soil fertility. These results may be helpful for selecting SWC measures, land-use planning and monitoring and assessing soil fertility.
Publisher: Informa UK Limited
Date: 11-1991
Publisher: CSIRO Publishing
Date: 2016
DOI: 10.1071/SR15121
Abstract: In Queensland, Australia, large tracts of native vegetation have been cleared for agriculture, resulting in substantial hydrological changes in the landscape. Australia’s longest-running paired catchment study, the Brigalow Catchment Study (BCS), was established in 1965 to monitor hydrological changes associated with land development, particularly that of the 1960s Land Development Fitzroy Basin Scheme. The BCS has unequivocally shown that developing brigalow (Acacia harpophylla) for cropping or for grazing doubles runoff volume. However, to date little research had been undertaken to quantify the changes in peak runoff rate when brigalow is cleared for cropping or grazing. The present study compared peak runoff rates from three brigalow catchments, two of which were subsequently cleared for cropping and pasture. Prior to land development, average peak runoff rates from the three brigalow scrub catchments were 3.2, 5 and 2mmh–1 for catchments 1 to 3 respectively. After development, these rates increased to 6.6mmh–1 from the brigalow scrub control catchment (catchment 1), 8.3mmh–1 from the cropping catchment (catchment 2) and 5.6mmh–1 from the pasture catchment (catchment 3). Peak runoff rate increased significantly from both the cropping and pasture catchments after adjusting for the underlying variation in peak runoff rate due to climatic variation between the pre- and post-development periods. The average peak runoff rate increased by 5.4mmh–1 (96%) for the cropping catchment and by 2.6mmh–1 (47%) for the pasture catchment. Increases in peak runoff rate were most prevalent in smaller events with an average recurrence interval of less than 2 years under cropping and 4 years under pasture.
Publisher: MDPI AG
Date: 30-06-2023
DOI: 10.3390/LAND12071326
Abstract: Climate and land use changes impact catchment hydrology and water quality (WQ), yet few studies have investigated the amount of land use changes required to meet specific WQ targets under future climate projections. The aim of this study was to determine streamflow and nutrient load responses to future land use change (LUC) and climate change scenarios. We hypothesized that (1) increasing forest coverage would decrease nutrient loads, (2) climate change, with higher temperatures and more intense storms, would lead to increased flow and nutrient loads, and (3) LUC could moderate potential nutrient load increases associated with climate change. We tested these hypotheses with the Soil and Water Assessment Tool (SWAT), which was applied to a lake catchment in New Zealand, where LUC strategies with afforestation are employed to address lake WQ objectives. The model was calibrated from 2002 to 2005 and validated from 2006 to 2010 using measured streamflow (Q) and total nitrogen (TN), total phosphorus (TP), nitrate (NO3-N), and ammonium (NH4-N) concentrations of three streams in the catchment. The model performance across the monitored streams was evaluated using coefficient of determination (R2) and Nash–Sutcliffe efficiency (NSE) metrics to provide a basis for model projections. Future scenarios incorporated LUC and climate change (CC) based on the Representative Concentration Pathway 8.5 and were compared to the baseline streamflow and WQ indicators. Consistent with our hypotheses, Q, TN, and TP loads were predicted to decrease with afforestation. Specifically, afforestation of 1.32 km2 in one of the monitored stream sub-catchments (subbasin 3), or 8.8% of the total lake catchment area, would result in reductions of 11.9, 26.2, and 17.7% in modeled annual mean Q, TN, and TP loads, respectively. Furthermore, when comparing simulations based on baseline and projected climate, reductions of 13.6, 22.8, and 19.5% were observed for Q, TN, and TP loads, respectively. Notably, the combined implementation of LUC and CC further decreased Q, TN, and TP loads by 20.2, 36.7, and 28.5%, respectively. This study provides valuable insights into the utilization of LUC strategies to mitigate nutrient loads in lakes facing water quality challenges, and our findings could serve as a prototype for other lake catchments undergoing LUC. Contrary to our initial hypotheses, we found that higher precipitation and temperatures did not result in increased flow and nutrient loading.
Publisher: American Society of Agricultural and Biological Engineers (ASABE)
Date: 1997
DOI: 10.13031/2013.21388
Publisher: Springer Science and Business Media LLC
Date: 04-10-2023
Publisher: Elsevier BV
Date: 02-2007
Publisher: Wiley
Date: 10-02-2015
DOI: 10.1002/HYP.10435
Publisher: CRC Press
Date: 12-08-2014
DOI: 10.1201/B17133-307
Publisher: Elsevier BV
Date: 10-2020
Publisher: Elsevier BV
Date: 10-2022
Publisher: American Society of Agricultural and Biological Engineers (ASABE)
Date: 16-02-2015
Publisher: Wiley
Date: 09-1991
Publisher: American Society of Civil Engineers (ASCE)
Date: 11-2018
Publisher: MDPI AG
Date: 12-10-2017
DOI: 10.3390/W9100782
Abstract: Inappropriate use of land and poor ecosystem management have accelerated land degradation and reduced the storage capacity of reservoirs. To mitigate the effect of the increased sediment yield, it is important to identify erosion-prone areas in a 287 km2 catchment in Ethiopia. The objectives of this study were to: (1) assess the spatial variability of sediment yield (2) quantify the amount of sediment delivered into the reservoir and (3) prioritize sub-catchments for watershed management using the Soil and Water Assessment Tool (SWAT). The SWAT model was calibrated and validated using SUFI-2, GLUE, ParaSol, and PSO SWAT-CUP optimization algorithms. For most of the SWAT-CUP simulations, the observed and simulated river discharge were not significantly different at the 95% level of confidence (95PPU), and sources of uncertainties were captured by bracketing more than 70% of the observed data. This catchment prioritization study indicated that more than 85% of the sediment was sourced from lowland areas (slope range: 0–8%) and the variation in sediment yield was more sensitive to the land use and soil type prevailing in the area regardless of the terrain slope. Contrary to the perception of the upland as an important source of sediment, the lowland in fact was the most important source of sediment and should be the focus area for improved land management practice to reduce sediment delivery into storage reservoirs. The research also showed that lowland erosion-prone areas are typified by extensive agriculture, which causes significant modification of the landscape. Tillage practice changes the infiltration and runoff characteristics of the land surface and interaction of shallow groundwater table and saturation excess runoff, which in turn affects the delivery of water and sediment to the reservoir and catchment evapotranspiration.
Publisher: IWA Publishing
Date: 18-04-2013
DOI: 10.2166/WCC.2013.138
Abstract: Rainfall intensity–frequency–duration curves are used extensively for storm runoff estimation. It is generally assumed that rainfall intensity would increase with global warming irrespective of the underlying changes to rainfall. This study analyzed rainfall and temperature from six sites in Eastern Australia. Two non-overlapping 30-year periods with the greatest difference in the mean annual rainfall were selected at each of the six sites to test for significant changes in the mean annual temperature and rainfall. Changes in the mean rainfall intensity for different frequencies of occurrence and storm durations for each site were also analyzed. Temperature has increased at all sites, and significantly at five out of the six sites. The mean annual rainfall has significantly changed between the two non-overlapping periods at the sites with the exception of Cairns (latitude – 16.87° south). The changes in rainfall intensity for longer durations (≥1 h) positively correlate with changes in the mean annual rainfall. There is evidence to suggest that the 6 min rainfall intensity would increase irrespective of the changes in the mean annual rainfall.
Publisher: American Society of Civil Engineers (ASCE)
Date: 08-2015
Publisher: Elsevier BV
Date: 11-2020
Publisher: American Society of Civil Engineers (ASCE)
Date: 06-2015
Publisher: American Association for the Advancement of Science (AAAS)
Date: 10-03-2023
Abstract: Increases in concurrent climate extremes in different parts of the world threaten the ecosystem and our society. However, spatial patterns of these extremes and their past and future changes remain unclear. Here, we develop a statistical framework to test for spatial dependence and show widespread dependence of temperature and precipitation extremes in observations and model simulations, with more frequent than expected concurrence of extremes around the world. Historical anthropogenic forcing has strengthened the concurrence of temperature extremes over 56% of 946 global paired regions, particularly in the tropics, but has not yet significantly affected concurrent precipitation extremes during 1901–2020. The future high-emissions pathway of SSP585 will substantially lify the concurrence strength, intensity, and spatial extent for both temperature and precipitation extremes, especially over tropical and boreal regions, while the mitigation pathway of SSP126 can ameliorate the increase in concurrent climate extremes for these high-risk regions. Our findings will inform adaptation strategies to alleviate the impact of future climate extremes.
Publisher: Elsevier BV
Date: 11-2020
Publisher: Informa UK Limited
Date: 22-05-2015
Publisher: International Society for Environmental Information Science (ISEIS)
Date: 2015
Publisher: CSIRO Publishing
Date: 1996
DOI: 10.1071/SR9960139
Abstract: A rainfall erosivity model using daily rainfall amounts to estimate rainfall erosivity was tested for 29 sites in New South Wales to see whether such a model could adequately describe the temporal variation and seasonal distribution of rainfall erosivity. The coefficient of determination varied from 0.57 to 0.97 and the average discrepancy between actual and estimated seasonal distribution was no more than 3%. A set of parameter values for sites without pluviograph data was recommended for New South Wales. With this set of recommended parameter values, the percentage of total variance explained was decreased to 44%–89% for the 29 sites. Large errors, however, can occur when estimating extreme storm erosivity with large return periods. The daily erosivity model could be used for determining the seasonal distribution of rainfall erosivity or for simulating changes to rainfall erosivity as part of climate change impacts assessment.
Publisher: Wiley
Date: 24-05-2014
DOI: 10.1002/ESP.3593
Publisher: Wiley
Date: 12-11-2019
DOI: 10.1002/LDR.3146
Publisher: American Geophysical Union (AGU)
Date: 27-03-2015
DOI: 10.1002/2015GL063511
Publisher: American Meteorological Society
Date: 09-2018
Abstract: Climate Generator (CLIGEN) is a stochastic weather generator that has been widely used to generate daily precipitation and storm patterns for hydrological and erosion prediction models. Rainfall data with measurement intervals ≤ 30 min are required to compute two parameters for generating storm patterns, namely, the cumulative distribution of the time to peak rainfall intensity (TimePk) and the mean daily maximum 30-min rainfall intensity (MX.5P). High-resolution rainfall data, however, are not widely available around the world. One-minute precipitation data for 18 stations in eastern and central China were aggregated into hourly intervals to evaluate methods to optimally prepare TimePk and MX.5P for CLIGEN. Four sets of the two parameters were used to run CLIGEN for comparison: C 0 , using the original 1-min data C 1 , replacing TimePk with those computed with hourly data C 2 , replacing MX.5P with those computed with hourly data with an adjustment factor and C 3 , replacing both parameters with those computed with hourly data, and the MX.5P was adjusted as for C 2 . Results showed that 1) MX.5P computed with hourly data was systematically lower than that computed with the 1-min data, and the bias could be corrected by multiplying by an adjustment factor of 1.40 2) the difference in generated storm patterns between C 0 and C 1 was insignificant and 3) results from C 2 and C 3 agreed well with those generated from C 0 . Hourly precipitation data can be used to prepare CLIGEN input parameter values for generating storm patterns for sites where only hourly data are available.
Publisher: American Society of Civil Engineers (ASCE)
Date: 10-2021
Publisher: American Meteorological Society
Date: 2020
Abstract: Rainfall in the southwest of Western Australia (SWWA) has decreased significantly over recent decades. Previous studies documented this decrease in terms of the change in rainfall depth or decrease in the frequency of rainfall events for selected sites. Although rainfall volume is of vital importance to determine water resources availability for a given region, no study has yet been undertaken to examine the change in rainfall volume in SWWA. The aim of this study is to examine the spatiotemporal changes in rainfall volume and to attribute this change to the changes in wet area and rainfall depth. Gridded daily rainfall data at 0.05° resolution for the period from 1911 to 2018 were used for an area of 265 952 km 2 in SWWA. For the whole region and most zones, rainfall volume decreased, which was mostly due to a decrease in the wet area, despite an increase in the mean rain depth. In the regions near the coast with mean annual rainfall ≥ 600 mm, 84% of the decrease in rainfall volume could be attributed to a decrease in the wet area, whereas the decrease in rainfall depth only played a minor role. The regions near the coast with a higher number of rain days showed a decreasing trend in wet area, and the regions farther inland with a lower number of rain days showed an increasing trend in wet area. On the coast, the rate of decrease in rainfall has been reduced, and heavy rainfall, in fact, has increased over the past 30 years, although there was no concurrent change in the southern annular mode (SAM). This suggests that the relationship between SAM and rainfall could have changed and that other climate drivers could also be responsible for the recent rainfall trend and variations in the coastal regions of SWWA.
Start Date: 2004
End Date: 06-2007
Amount: $158,882.00
Funder: Australian Research Council
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