TY - JOUR
T1 - How uncertain is model-based prediction of copper loads in stormwater runoff?
AU - Lindblom, Erik Ulfson
AU - Ahlman, S.
AU - Mikkelsen, Peter Steen
PY - 2007
Y1 - 2007
N2 - In this paper, we conduct a systematic analysis of the uncertainty related with estimating the total load of pollution (copper) from a separate stormwater drainage system, conditioned on a specific combination of input data, a dynamic conceptual pollutant accumulation-washout model and measurements (runoff volumes and pollutant masses). We use the generalized likelihood uncertainty estimation (GLUE) methodology and generate posterior parameter distributions that result in model outputs encompassing a significant number of the highly variable measurements. Given the applied pollution accumulation-washout model and a total of 57 measurements during one month, the total predicted copper masses can be predicted within a range of +/-50% of the median value. The message is that this relatively large uncertainty should be acknowledged in connection with posting statements about micropollutant loads as estimated from dynamic models, even when calibrated with on-site concentration data.
AB - In this paper, we conduct a systematic analysis of the uncertainty related with estimating the total load of pollution (copper) from a separate stormwater drainage system, conditioned on a specific combination of input data, a dynamic conceptual pollutant accumulation-washout model and measurements (runoff volumes and pollutant masses). We use the generalized likelihood uncertainty estimation (GLUE) methodology and generate posterior parameter distributions that result in model outputs encompassing a significant number of the highly variable measurements. Given the applied pollution accumulation-washout model and a total of 57 measurements during one month, the total predicted copper masses can be predicted within a range of +/-50% of the median value. The message is that this relatively large uncertainty should be acknowledged in connection with posting statements about micropollutant loads as estimated from dynamic models, even when calibrated with on-site concentration data.
U2 - 10.2166/wst.2007.748
DO - 10.2166/wst.2007.748
M3 - Journal article
SN - 0273-1223
VL - 56
SP - 65
EP - 72
JO - Water Science and Technology
JF - Water Science and Technology
IS - 11
ER -