The objective of this work was to examine whether the standard particulate backscattering IOP (Inherent Optical Properties) measurement method could be simplified. IOP measurements are essential for parameterising several forms of algorithms used to estimate water quality parameters from airborne and satellite images. Field measurements of the backscattering IOPs are more difficult to make than absorption measurements as correction of the raw <i>Hydroscat-6</i> backscattering sensor observations is required to allow for the systematic errors associated with the water and water quality parameter absorption. The standard approach involves making simultaneous measurement of the absorption and attenuation of the water with an absorption and attenuation meter (<i>ac-9</i>) or making assumptions about the particulate backscattering probability. Recently, a number of papers have been published that use an alternative method to retrieve the particulate backscattering spectrum by using laboratory measured absorption values and <i>in situ</i> spectroradiometric observations. The alternative method inverts a model of reflectance iteratively using non-linear least squares fitting to solve for the particulate backscattering at 532 nm (b_bp0(532)) and the particulate backscattering spectral slope (<i>&gamma;</i>). In this paper, eleven observations made at Burdekin Falls Dam, Australia are used to compare the alternative reflectance method to the conventional corrected <i>Hydroscat-6</i> observations. Assessment of the alternative reflectance method showed that the result of the inversions were highly dependent on the starting conditions. To overcome this limitation, Particle Swarm Optimisation, a stochastic search technique which includes a random element in the search approach, was used. It was found that when compared to the conventionally corrected <i>Hydroscat-6</i> observations, the alternative reflectance method underestimated b_bp0(532) by approximately 50% and overestimated <i>&gamma;</i> by approximately 40%. Differences of this scale in specific backscattering spectra will have a pronounced effect on the parameterisation and subsequent performance of semi-analytical water quality parameter retrieval algorithms. This has implications for any water quality monitoring regimes that rely on semi-analytical algorithms.