a b s t r a c t
Excessive pollutant discharge from multi-pollution resources can lead to a rise in downriver contaminant
concentration in river segments. A multi-pollution source water quality model (MPSWQM) was integrated
with Bayesian statistics to develop a robust method for supporting load (I) reduction and effective
water quality management in the Harbin City Reach of the Songhua River system in northeastern China.
The monthly water quality data observed during the period 2005e2010 was analyzed and compared,
using ammonia as the study variable. The decay rate (k) was considered a key factor in the MPSWQM,
and the distribution curve of k was estimated for the whole year. The distribution curves indicated small
differences between the marginal distribution of k of each period and that water quality management
strategies can be designed seasonally. From the curves, decision makers could pick up key posterior
values of k in each month to attain the water quality goal at any specified time. Such flexibility is an
effective way to improve the robustness of water quality management. For understanding the potential
collinearity of k and I, a sensitivity test of k for I2i (loadings in segment 2 of the study river) was done
under certain water quality goals. It indicated that the posterior distributions of I2i show seasonal variation
and are sensitive to the marginal posteriors of k. Thus, the seasonal posteriors of k were selected
according to the marginal distributions and used to estimate I2i in next water quality management. All
kinds of pollutant sources, including polluted branches, point and non-point source, can be identified for
multiple scenarios. The analysis enables decision makers to assess the influence of each loading and how
best to manage water quality targets in each period. Decision makers can also visualize potential load
reductions under different water quality goals. The results show that the proposed method is robust for
management of multi-pollutant loadings under different water quality goals to help ensure that the
water quality of river segments meets targeted goals.
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