Consequences of soil map unit uncertainty on environmental risk assessment
T. H. Webb A B and L. R. Lilburne AA Landcare Research, PO Box 69, Lincoln, Canterbury, New Zealand.
B Corresponding author. Email: Webbt@LandcareResearch.co.nz
Australian Journal of Soil Research 43(2) 119-126 https://doi.org/10.1071/SR04055
Submitted: 22 April 2004 Accepted: 3 December 2004 Published: 1 April 2005
Abstract
Soil maps are being applied in modelling of environmental risk at a regional scale. Analysis of soil maps shows that there can be considerable uncertainty in map unit composition with consequent spatial variability in soil properties within map units. Uncertainty of map unit composition arises from a number of factors including map labels that do not reflect the mix of soil types present and imprecise location of map unit boundaries. Usually little, if any, information is supplied as to the extent and magnitude of these uncertainties. In this paper we develop datasets to quantify soil property variability for map units on the Canterbury Plains and use expert knowledge to quantify uncertainty in map unit composition for a small case-study area. We then apply Monte Carlo sampling to the estimated range of soil properties to input soil data into the GLEAMS simulation model to assess the effect of soil variability on nitrate leaching.
The simulation results show that there is considerable uncertainty in leaching from data derived from current soil map units. Even simple map units (map units characterised by a single soil type) have a wide range of potential leaching related to variation in soil profiles within the soil type. When map-unit inclusions were accounted for, variation in leaching risk can increase by 10–30%. Compound map units encompass the range of variability of the named component soils and there is a smaller increase in leaching variability in these units (compared with simple map units) when inclusions are added to the analysis. We discuss the implications of this study to the use of current soil survey data and make recommendations for future soil survey practice. In particular, greater effort is needed on description of the composition and reliability of soil map units.
Additional keywords: nitrate, water quality, simulation models, soil survey, GLEAMS, Monte Carlo.
Acknowledgments
The New Zealand Foundation for Research, Science and Technology, funded this research under contract C09X0017.
Bakhsh A,
Kanwar RS,
Jaynes DB,
Colvin TS, Ahuja LR
(2000) Prediction of NO3-N losses with subsurface drainage water from manured and UAN-fertilized plots using GLEAMS. Transactions of the American Society of Agricultural Engineers 43, 69–77.
Bleecker M,
Degloria SD,
Hutson JL,
Bryant RB, Wagenet RJ
(1995) Mapping atrazine leaching potential with integrated environmental databases and simulation models. Journal of Soil and Water Conservation 50, 388–394.
Bouma J,
van Lanen HAJ,
Breeuwsma A,
Wosten HJM, Kooistra MJ
(1985) Soil survey data needs when studying modern land use problems. Soil Use and Management 2, 125–130.
Brubaker SC, Hallmark CT
(1991) A comparison of statistical methods for evaluating map unit composition. In ‘Spatial variabilities of soils and landforms’. Soil Science Society of America Special Publication 28. pp. 73–88. (Soil Science Society of America: Madison, WI)
Close ME,
Pang L,
Watt JPC,
Vincent KW, Naidu RT
(1998) Leaching of picloram, atrazine and simazine through two New Zealand soils. Geoderma 84, 45–63.
| Crossref | GoogleScholarGoogle Scholar |
Close ME,
Watt JPC, Vincent KW
(1999) Simulation of picloram, atrazine, and simazine transport through two New Zealand soils using LEACHM. Australian Journal of Soil Research 37, 53–74.
Cox JE
(1978) Soils and agriculture of part Paparua County. New Zealand Soil Bureau Bulletin 34, DSIR, Wellington.
Di HJ, Aylmore LAG
(1997) Modeling the probabilities of groundwater contamination by pesticides. Soil Science Society of America Journal 61, 17–23.
Di HJ, Kemp RA
(1989) Variation in soil physical properties between and within morphologically defined series taxonomic units. Australian Journal of Soil Research 27, 259–273.
Fortin M-C, Moon DE
(1999) Errors associated with the use of soil survey data for estimating plant-available water at a regional scale. Agronomy Journal 91, 984–990.
Foussereau X,
Hornsby AG, Brown RB
(1993) Accounting for variability within map units when linking a pesticide fate model to soil survey. Geoderma 60, 257–276.
| Crossref | GoogleScholarGoogle Scholar |
Griffiths E
(1985) Interpretation of soil morphology for assessing moisture movement and storage. New Zealand Soil Bureau Scientific Report 74, DSIR, Wellington.
Hansen S,
Thorsen M,
Pebesma EJ,
Kleeschulte S, Svendsen H
(1999) Uncertainty in simulated nitrate leaching due to uncertainty in input data. A case study. Soil Use and Management 15, 167–175.
Hewitt, AE (1998). ‘New Zealand soil classification’. Landcare Research Science Series No. 1. 2nd edn . (Manaaki Whenua Press: Lincoln, New Zealand)
Hole, FD ,
and
Campbell, JB (1985).
Karageorgis D
(1980) Soil variability and related crop productivity within a sample area of the Templeton soil mapping unit. MAgric. thesis, University of Canterbury, Christchurch, New Zealand.
Kear BS, Gibbs HS, Miller RB
(1967) Soils of the downs and plains of Canterbury and North Otago, New Zealand. New Zealand Soil Bureau Bulletin 14, DSIR, Wellington.
Knisel WG
(1993) GLEAMS: Groundwater Loading Effects Of Agricultural Management Systems, version 2.10. University of Georgia, Coastal Plain Experimental Station, Biological and Agricultural Engineering Department Publication No. 5.
Lee R,
Bailey JM,
Northey RD,
Barker PR, Gibson EJ
(1974) Variation in some chemical and physical properties of three related soil types: Dannevirke silt loam, Kiwitea silt loam, and Marton silt loam. New Zealand Journal of Agricultural Research 18, 29–36.
Leonard RA,
Knisel WG, Still DA
(1987) GLEAMS: Groundwater loading effects of agricultural management systems. Transactions of the American Society of Agricultural Engineers 30, 1403–1418.
Lilburne LR, Webb TH
(2002) Effect of soil variability, within and between soil taxonomic units, on simulated nitrate leaching under arable farming, New Zealand. Australian Journal of Soil Research 40, 1187–1199.
| Crossref | GoogleScholarGoogle Scholar |
Lilburne LR,
Webb TH, Francis GS
(2003) Relative effect of climate, soil, and management on risk of nitrate leaching under wheat production in Canterbury, New Zealand. Australian Journal of Soil Research 41, 699–709.
| Crossref | GoogleScholarGoogle Scholar |
Nofziger DL, Chen J-S, Hornsby AG
(1996) Uncertainty in pesticide leaching risk due to soil variability. ‘Data reliability and risk assessment in soil interpretations’. Soil Science Society of America Special Publication 47. pp. 99–129., (Soil Science Society of America: Madison, WI)
Petach MC,
Wagenet RJ, DeGloria SD
(1991) Regional water flow and pesticide leaching using simulations with spatially distributed data. Geoderma 48, 245–269.
| Crossref | GoogleScholarGoogle Scholar |
Rogowski AS
(2000) Incorporating soil variability into a spatially distributed model of percolate accounting. ‘Quantifying spatial uncertainty in natural resources: theory and applications for GIS and remote sensing’. (Eds HT Mowrer, R Congalton)
pp. 183–202. (Ann Arbor Press: Chelsea, MI)
Rogowski AS, Wolf JK
(1994) Incorporating variability into soil map unit delineations. Soil Science Society of America Journal 58, 163–174.
Shirmohammadi A, Knisel WG
(1989) Irrigated agriculture and water quality in the South. Journal of Irrigation and Drainage Engineering 115, 823–838.
Soil Survey Staff (1998).
Soutter M, Musy A
(1998) Coupling 1D Monte Carlo simulations and geostatistics to assess groundwater vulnerability to pesticide contamination on a regional scale. Journal of Contaminant Hydrology 32, 25–39.
| Crossref | GoogleScholarGoogle Scholar |
SYSTAT (1996).
Taylor NH, Pohlen IJ
(1970)
Wagenet RJ, Hutson JL
(1996) Scale-dependency of solute transport modeling/GIS applications. Journal of Environmental Quality 25, 499–510.
Webb TH,
Claydon JJ, Harris SR
(2000) Quantifying variability of soil physical properties within map units to address modern land-use issues on the Canterbury Plains, New Zealand. Australian Journal of Soil Research 38, 1115–1129.
| Crossref | GoogleScholarGoogle Scholar |
Webb TH, Lilburne LR
(1999) Use of the LEACHM model and the DRASTIC index to map relative risk of groundwater contamination by pesticide leaching. Journal of Hydrology NZ 38, 271–288.
Webb TH,
Lilburne LR, Francis GS
(2001) Validation of the GLEAMS simulation model for estimating net nitrogen mineralisation and nitrate leaching under cropping in Canterbury. Australian Journal of Soil Research 39, 1015–1025.
| Crossref | GoogleScholarGoogle Scholar |
Workman SR, Ward AD, Knisel WG
(1992) Assessing the leaching potential of herbicides at the Ohio MESA. ‘Irrigation and Drainage session at Water Forum′92’. (Ed. T Engman)
pp. 413–418. (American Society of Civil Engineers: Baltimore, MD)
Wu QJ,
Ward AD, Workman SR
(1996) Using GIS in simulation of nitrate leaching from heterogeneous unsaturated soils. Journal of Environmental Quality 25, 526–534.
