Modelling and mapping rainfall erosivity in New South Wales, Australia
Xihua Yang A C and Bofu Yu BA New South Wales Office of Environment and Heritage, PO Box 3720, Parramatta, NSW 2150, Australia.
B Griffith School of Engineering, Griffith University, Nathan, Qld 4111, Australia.
C Corresponding author. Email: xihua.yang@environment.nsw.gov.au
Soil Research 53(2) 178-189 https://doi.org/10.1071/SR14188
Submitted: 24 October 2013 Accepted: 2 November 2014 Published: 6 February 2015
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 >0.90. 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.
Additional keywords: GIS, hillslope erosion, mapping, modeling, rainfall erosivity, RUSLE.
References
Angulo-Martínez M, Begueriía S (2009) Estimating rainfall erosivity from daily precipitation records: A comparison among methods using from the EroBasin (NE Spain). Journal of Hydrology 379, 111–121.| Estimating rainfall erosivity from daily precipitation records: A comparison among methods using from the EroBasin (NE Spain).Crossref | GoogleScholarGoogle Scholar |
Bureau of Meteorology (1989) ‘Climate of Australia.’ (AGPS Press: Canberra, ACT)
Bureau of Meteorology (2007) About Climate Statistics: Climate normals. Australian Government Bureau of Meteorology. Available at: www.bom.gov.au/climate/cdo/about/about-stats.shtml (accessed 9 April 2014)
Duan N (1983) Smearing estimates: a non-parametric retransformation method. Journal of the American Statistical Association 78, 605–610.
| Smearing estimates: a non-parametric retransformation method.Crossref | GoogleScholarGoogle Scholar |
Edwards K (1987) ‘Runoff and soil loss studies in NSW.’ Technical Handbook No. 10. (Soil Conservation Service of NSW: Sydney)
Evans JP, Ji F, Lee C, Smith P, Argueso D, Fita L (2014) Design of a regional climate modeling projection ensemble experiment—NARCliM. Geoscientific Model Development 7, 621–629.
| Design of a regional climate modeling projection ensemble experiment—NARCliM.Crossref | GoogleScholarGoogle Scholar |
Gallant JC, Dowling TI, Read AM, Wilson N, Tickle P, Inskeep C (2011) 1 second SRTM derived Digital Elevation Models User Guide. Australian Government, Geoscience Australia. Available at: www.ga.gov.au/metadata-gateway/metadata/record/gcat_72759
Hutchinson MF (1989) A new method for gridding elevation and streamline data with automatic removal of pits. Journal of Hydrology 106, 211–232.
| A new method for gridding elevation and streamline data with automatic removal of pits.Crossref | GoogleScholarGoogle Scholar |
Lal R (1990) ‘Soil erosion in the tropics: Principles and management.’ (McGraw-Hill: New York)
Lu H, Yu B (2002) Spatial and seasonal distribution of rainfall erosivity in Australia. Australian Journal of Soil Research 40, 887–901.
| Spatial and seasonal distribution of rainfall erosivity in Australia.Crossref | GoogleScholarGoogle Scholar |
Lu D, Li G, Valladares GS, Batistell M (2004) Mapping soil erosion risk in Rondonia, Brazilian Amazonia: Using RUSLE, remote sensing and GIS. Land Degradation & Development 15, 499–512.
| Mapping soil erosion risk in Rondonia, Brazilian Amazonia: Using RUSLE, remote sensing and GIS.Crossref | GoogleScholarGoogle Scholar |
Meusburger K, Steel A, Panagos P, Montanarella L, Alewell C (2012) Spatial and temporal variability of rainfall erosivity factor for Switzerland. Hydrology and Earth System Sciences 16, 167–177.
| Spatial and temporal variability of rainfall erosivity factor for Switzerland.Crossref | GoogleScholarGoogle Scholar |
Nash JE, Sutcliffe JV (1970) River flow forecasting through conceptual models, Part 1: A discussion of principles Journal of Hydrology 10, 282–290.
| River flow forecasting through conceptual models, Part 1: A discussion of principlesCrossref | GoogleScholarGoogle Scholar |
Renard KG, Freimund JR (1994) Using monthly precipitation data to estimate the R factor in the revised USLE. Journal of Hydrology 157, 287–306.
| Using monthly precipitation data to estimate the R factor in the revised USLE.Crossref | GoogleScholarGoogle Scholar |
Renard KG, Foster GR, Weesies GA, McCool DK, Yoder DC (1997) ‘Predicting soil erosion by water: a guide to conservation planning with the Revised Universal Soil Loss Equation (RUSLE).’ Agricultural Handbook, Vol. 703. pp. 1–251. (US Department of Agriculture: Washington, DC)
Rosewell CJ (1993) ‘SOILOSS – A program to assist in the selection of management practices to reduce erosion.’ Technical Handbook No. 11. (Soil Conservation Services: Sydney)
Rosewell CJ, Turner JB (1992) Rainfall erosivity in NSW. CaLM Technical Report No. 20, New South Wales Department of Conservation and Land Management, Sydney.
Wischmeier WH, Smith DD (1978) ‘Predicting rainfall erosion losses, a guide to conservation planning.’ Agricultural Handbook, Vol. 537. pp. 58. (US Department of Agriculture, Washington, DC)
Yang X (2014) Deriving RUSLE cover factor from time-series fractional vegetation cover for soil erosion risk monitoring in New South Wales. Soil Research 52, 253–261.
| Deriving RUSLE cover factor from time-series fractional vegetation cover for soil erosion risk monitoring in New South Wales.Crossref | GoogleScholarGoogle Scholar |
Yang X, Leys J (2009) Spatial interpolation of dust concentration using time-series meteorological data and MODIS vegetation index. In ‘The 6th International Symposium on Digital Earth (ISDE6)’. Beijing, China, 9–12 September 2009. (International Society for Digital Earth)
Yang X, Yu B (2014) Predicting rainfall erosivity and hillslope erosion risk over South-east Australia. In ‘20th World Congress of Soil Sciences’. 8–13 June 2014, Jeju, South Korea. (International Union of Soil Sciences)
Yang X, Yu B, Chapman G (2012) Spatial and temporal prediction of rainfall erosivity and its impact on soil erosion in New South Wales. In ‘Soil Science Australia and the New Zealand Society of Soil Science Conference’. 2–7 December 2012, Hobart, Tas. (ASSSI/NZSSS)
Yu B (1995) Long-term variation of rainfall erosivity in Sydney. Weather and Climate 15, 57–66.
Yu B (1998) Rainfall erosivity and its estimation for Australia’s tropics. Australian Journal of Soil Research 36, 143–165.
| Rainfall erosivity and its estimation for Australia’s tropics.Crossref | GoogleScholarGoogle Scholar |
Yu B (1999) A comparison of the R-factor in the universal soil loss equation and revised universal soil loss equation. Transactions of the American Society of Agricultural Engineers 42, 1615–1620.
| A comparison of the R-factor in the universal soil loss equation and revised universal soil loss equation.Crossref | GoogleScholarGoogle Scholar |
Yu B (2003) Precipitation and erosion. In ‘Encyclopaedia of water sciences’. (Eds BA Stewart, T Howell) pp. 214–217. (Marcel Dekker Inc. New York)
Yu B, Neil DT (2000) Empirical catchment-wide rainfall erosivity models for two rivers in the humid tropics of Australia. The Australian Geographer 31, 115–132.
| Empirical catchment-wide rainfall erosivity models for two rivers in the humid tropics of Australia.Crossref | GoogleScholarGoogle Scholar |
Yu B, Rosewell CJ (1996a) An assessment of a daily rainfall erosivity model for New South Wales. Australian Journal of Soil Research 34, 139–152.
| An assessment of a daily rainfall erosivity model for New South Wales.Crossref | GoogleScholarGoogle Scholar |
Yu B, Rosewell CJ (1996b) Rainfall erosivity estimation using daily rainfall amounts for South Australia. Australian Journal of Soil Research 34, 721–733.
| Rainfall erosivity estimation using daily rainfall amounts for South Australia.Crossref | GoogleScholarGoogle Scholar |
Yu B, Rosewell CJ (1996c) A robust estimator of the R-factor for the Universal Soil Loss Equation. Transactions of the American Society of Agricultural Engineers 39, 559–561.
| A robust estimator of the R-factor for the Universal Soil Loss Equation.Crossref | GoogleScholarGoogle Scholar |
Yu B, Rosewell CJ (1997) RECS: A program to calculate the R-factor for the USLE/RUSLE Using BOM/AWS Pluviograph Data. ENS Working Paper 8/98. Griffith University, Nathan, Qld.
