Suspended solids uncertainty

Typical quantitative results of water quality uncertainty studies: Suspended solids.

This table originated from McMillan et al. (2012) but is now open to the community to add to and use as a resource.

PDF = probability density function; RMSE = root mean square error; WY = water year

Uncertainty Type	Estimation Method	Magnitude	Location	Reference
Instantaneous concentration	Relative difference between auto & manual dublicates	Auto sample within 10 % of manual sample	Devon, UK	Walling & Teed (1971)
8-year load; effect of estimation method	Bias relative to reference load from daily data (1974/75-1981/82); 12 methods tested; 6 sampling frequencies simulated via sub-sampling	-22 to 10 %	Euphrates (444000 km2) at Haditha, Iraq. Ave. annual precipitation <100 mm (South) – 800 mm (north), ave. annual discharge 776 m3 s-1, ave. annual sediment load 1.4 107 t.	Al-Ansari et al. (1988); values calculated from original absolute values
8-year load; effect of sampling frequency		-4 to 6 %
Instantaneous concentration; effect of cross-section sampling method	Average coefficient of variation with respect to depth- & width-integrated reference concentration	25 %	Various in USA	Horowitz et al. (1990); values calculated from original table
Instantaneous concentration; horizontal cross-section variation	Average coefficient of variation with respect to 5-point average	26 %
Instantaneous concentration; sampler effect	Difference between two samplers (EPIC – USGS)	36 % initially, then -1 to -15 %	Humber catchment, UK	Evans et al. (1997); values gleaned from original graph
Concentration exceedance frequency; effect of distribution assumption given censored data	Absolute difference between lognormal & normal models	0-3%, increasing with censoring	Little Cataraqui Creek (45 km2), Kingston Township, Ontario, Canada. Half urban, half forested, flat, ave. annual precipitation 900 mm (~22% snow).	van Buren et al. (1997)
Load; effect of distribution assumption given censored data	Relative difference between lognormal & normal models, relative to lognormal model	25-37 % (calculated from original table)
Instantaneous load; horizontal & vertical cross-section variation	Error of point turbidity measurement compared to width- & depth- integrated sample	-2.18 to -14.3 %	Humber catchment, UK, 8 sites (484.3-8231 km2). Wide range of geology, climate, soils and land cover, ave. annual precipitation 600 (east) – 1600 (Pennine Hills) mm.	Wass & Leeks (1999); values from original table
5-year load; effect of rating curve choice and sampling frequency	Bias relative to reference load from daily data (1979-1983); 4 rating curves tested; 4 sampling frequencies simulated via sub-sampling	-56 to 10 %	Rhine catchment above Rees, Germany (165000 km2), 5 locations. Temperate climate, 600 (lower Rhine) – 2500 (Alpes) mm precipitation, ave. annual discharge 2300 m3 s-1, ave. annual sediment load 3.14 106 t.	Asselman (2000)
Annual & 5-year load; effect of rating curve choice and sampling frequency	Bias relative to reference load from daily data; 4 rating curves tested; 12 subsets of data used to construct rating curves; various sampling frequencies simulated via sub-sampling	WY 1996-2000: -7 to 6 % at 50 d down to -3 % at 1 d; WY 1989 (low flow year): -10 to 3 % at 30 d down to -6 % at 1 d; WY 1995 (median flow year): -11 to 7 % at 30 d down to -1 % at 1 d; WY1982 (high flow year): -11 to 8 % at 30 d down to 3 % at 1 d	Mississippi at Thebes, Illinois, USA (1847188 km2), 01/10/1980-30/09/2000	Horowitz (2003); values gleaned from original graphs
		WY 1989-1993: -7 to 13 % at 50 d down to 2 % at 1 d; WY 1976 (low flow year): -11 to 10 % at 50 d down to 0 % at 1 d; WY 1980 (median flow year): -15 to 5 % at 30 d down to -3 % at 1 d; WY1987 (high flow year): -15 to 10 % at 30 d down to -5 % at 1 d	Rhine at Maxau, Germany (50200 km2), 31/10/1973-30/10/1993
Annual load; effect of temporal sampling method	Relative error with respect to reference method (composite sampling)	-9.1 to 2.7 %	USDA-ARS Grassland Soil & Water Research Laboratory (4.6-125.1 ha), Texas, USA. Vertisol soil, 2-4 % slope, mixed land cover.	Harmel & King (2005)
Storm load; effect of minimum flow threshold for sampling	Professional judgement based on Harmel et al. (2002)	±1-81 %		Harmel et al. (2006)
Storm load; uncertainty due to manual sampling		±15-50 % & more		Quoted in Harmel et al. (2006): Slade (2004)
Storm load; uncertainty due to automatic sampling (intake)		14-33 %		Quoted in Harmel et al. (2006): Martin et al. (1992)
Storm load; uncertainty due to automatic sampling (timing)		-65 to 51 %		Quoted in Harmel et al. (2006)
Storm load; analytical uncertainty	95 % confidence interval	-9.8 to 5.1 % (sandy); -5.3 to 4.4 % (fine)		Quoted in Harmel et al. (2006): Gordon et al. (2000)
Annual load; effect of sampling frequency	Bias relative to reference load from daily data (1961-1988); 28 sampling frequencies (2-30 d) simulated via sub-sampling (50 repeats, multiple years)	±30 % at 30 d (central 80 % from repeats & multiple years); decreasing with increasing sampling frequency	Mississippi at St Louis, Missouri, USA (251121 km2). Ave. annual discharge 20.1 l s-1 km-2, ave. annual sediment load 447 t yr-1 km-2.	Moatar et al. (2006); values gleaned from original graph; results from 35 more stations in USA and EU reported as well
Instantaneous concentration	Coefficient of variation between dublicates	33 % (at 15 mg l-1); 10 % (at 242 mg l-1); 0.76 % (at 1707 mg l-1)		Rode & Suhr (2007)
Analytical errors	PDF, coefficient of variation	Lognormal, 13 %		Quoted in Rode & Suhr (2007)
Storm load; effect of estimation method	Bias relative to reference load from 1-6 h data (2 events in Sep 1994 & Nov 1999); 6 estimation methods tested; continuous thinning of data down to 1 sample per event	-52 to 19 %	Vène catchment, France (67 km2). Karst geology overlain by clay, mixed fruit/vegetables and urban land cover.	Salles et al. (2008); values gleaned from original graphs
Storm load; effect of sampling frequency		-25 to 30 % at 1 sample per event; decreasing exponentially with increasing sampling frequency
Instantaneous concentration	Absolute difference between auto & manual dublicates	0-100 mg l-1; decreasing with flow	Rowden Experimental Research Platform (1 ha fields), Devon, UK. Dystric Gleysol soil, 7-9 % slope, grassland, ave. annual precipitation 1055 mm, 250 x 37 cm weir box.	Krueger et al. (2009)
Storm concentrations & load	Total probable error (median in parentheses) based on RMSE propagation method	12-26(18) % (concentrations); 15-35(20) % (load)	Various in USA (2.2-5506 ha)	Harmel et al. (2009) based on Harmel et al. (2006)
Concentration exceedance frequency	Uncertainty range based on bootstrapping low resolution data	Approx.10 %	Den Brook catchment (48 ha), Devon, UK. Dystric Gleysol soil, intensive grazing, ave. annual precipitation 1050 mm, flashy response, underdrained.	Bilotta et al. (2010); values gleaned from original graph
Flow-weighted mean concentration (hourly)	Trapezoidal fuzzy number based on analysis of bulk uncertainty as function of number of sub-samples for three timesteps	±10 % core (5-6 samples per hour); ±50 % support (1 sample per hour)		Krueger et al. (2012)

References

Al-Ansari, N.A., Asaad, N.M., Walling, D.E., Hussan, S.A., 1988. The suspended sediment discharge of the River Euphrates at Haditha, Iraq: An assessment of the potential for establishing sediment rating curves. Geografiska Annaler, Series A, Physical Geography, 70(3): 203-213.

Asselman, N. E. M., 2000. Fitting and interpretation of sediment rating curves. Journal of Hydrology, 234(3-4): 228-248.

Bilotta, G.S., Krueger, T., Brazier, R.E., Butler, P., Freer, J., Hawkins, J.M.B., Haygarth, P.M., Macleod, C.J.A., Quinton, J.N., 2010. Assessing catchment-scale erosion and yields of suspended solids from improved temperate grassland. Journal of Environmental Monitoring, 12(3): 731-739.

Evans, J.G., Wass, P.D., Hodgson, P., 1997. Integrated continuous water quality monitoring for the LOIS river programme. Science of the Total Environment, 194: 111-118.

Gordon, J. D., Newland, C.A., Gagliardi, S.T., 2000. Laboratory performance in the sediment laboratory quality-assurance project, 1996-98. USGS Water Resources Investigations Report 99-4184. Washington, D.C.: USGS.

Harmel, R.D., Cooper, R.J., Slade, R.M., Haney, R.L., Arnold, J.G., 2006. Cumulative uncertainty in measured streamflow and water quality data for small watersheds. Transactions of the ASABE, 49(3): 689-701.

Harmel, R.D., King, K.W., 2005. Uncertainty in measured sediment and nutrient flux in runoff from small agricultural watersheds. Transactions of the ASAE, 48(5): 1713-1721.

Harmel, R.D., Smith, D.R., King, K.W., Slade, R.M., 2009. Estimating storm discharge and water quality data uncertainty: A software tool for monitoring and modeling applications. Environmental Modelling & Software, 24(7): 832-842.

Horowitz, A.J., 2003. An evaluation of sediment rating curves for estimating suspended sediment concentrations for subsequent flux calculations. Hydrological Processes, 17(17): 3387-3409.

Horowitz, A.J., Rinella, F.A., Lamothe, P., Miller, T.L., Edwards, T.K., Roche, R.L., Rickert, D.A., 1990. Variations in suspended sediment and associated trace-element concentrations in selected riverine cross-sections. Environmental Science & Technology, 24(9): 1313-1320.

Krueger, T., Quinton, J.N., Freer, J., Macleod, C.J.A., Bilotta, G.S., Brazier, R.E., Butler, P., Haygarth, P.M., 2009. Uncertainties in data and models to describe event dynamics of agricultural sediment and phosphorus transfer. Journal of Environmental Quality, 38(3): 1137-1148.

Krueger, T., Quinton, J.N., Freer, J., Macleod, C.J.A., Bilotta, G.S., Brazier, R.E., Hawkins, J.M.B., Haygarth, P.M., 2012. Comparing empirical models for sediment and phosphorus transfer from soils to water at field and catchment scale under data uncertainty. European Journal of Soil Science. doi:10.1111/j.1365-2389.2011.01419.x

Martin, G. R., Smoot, J. L., White, K. D., 1992. A comparison of surface-grab and cross-sectionally integrated stream-water-quality sampling methods. Water Environ. Res. 64(7): 866-876.

McMillan, H., Krueger, T., Freer, J., 2012. Benchmarking observational uncertainties for hydrology: Rainfall, river discharge and water quality. Hydrological Processes.

Moatar, F., Person, G., Meybeck, M., Coynel, A., Etcheber, H., Crouzet, P., 2006. The influence of contrasting suspended particulate matter transport regimes on the bias and precision of flux estimates. Science of the Total Environment, 370(2-3): 515-531.

Rode, M., Suhr, U., 2007. Uncertainties in selected river water quality data. Hydrology and Earth System Sciences, 11(2): 863-874.

Salles, C., Tournoud, M.G., Chu, Y., 2008. Estimating nutrient and sediment flood loads in a small Mediterranean river. Hydrological Processes, 22(2): 242-253.

Slade, R. M., 2004. General Methods, Information, and Sources for Collecting and Analyzing Water-Resources Data. CD-ROM. Copyright 2004 Raymond M. Slade, Jr.

van Buren, M.A., Watt, W.E., Marsalek, J., 1997. Application of the log-normal and normal distributions to stormwater quality parameters. Water Research, 31(1): 95-104.

Walling, D.E., Teed, A., 1971. A simple pumping sampler for research into suspended sediment transport in small catchments. Journal of Hydrology, 13: 325-337.

Wass, P.D., Leeks, G.J.L., 1999. Suspended sediment fluxes in the Humber catchment, UK. Hydrological Processes, 13(7): 935-953.