Parameter uncertainty analysis of the non-point source pollution in the Daning River watershed of the Three Gorges Reservoir Region, China.
The generation and formation of non-point source pollution involves great uncertainty, and this uncertainty makes monitoring and controlling pollution very difficult. Understanding the main parameters that affect non-point source pollution uncertainty is necessary to provide the basis for the planning and design of control measures. In this study, three methods were adopted to do the parameter uncertainty analysis with the Soil and Water Assessment Tool (SWAT). Based on the results of parameter sensitivity analysis by the Morris screening method, the ten parameters that most affect runoff, sediment, organic N, nitrate, and total phosphorous (TP) were chosen for further uncertainty analysis. First-order error analysis (FOEA) and the Monte Carlo method (MC) were used to analyze the effect of parameter uncertainty on model outputs. FOEA results showed that only a few parameters had significantly affected the uncertainty of the final simulation results, and many parameters had little or no effect. The SCS curve number was the parameter with significant uncertainty impact on runoff, sediment, organic N, nitrate and TP, and it showed that the runoff process was mainly responsible for the uncertainty of non-point source pollution load. The uncertainty of sediment was the biggest among the five model output results described above. MC results indicated that neglecting the parameter uncertainty of the model would underestimate the non-point source pollution load, and that the relationship between model input and output was non-linear. The uncertainty of non-point source pollution exhibited a temporal pattern: It was greater in summer than in winter. The uncertainty of runoff was smaller compared to that of sediment, organic N, nitrate, and TP, and the source of uncertainty was mainly affected by parameters associated with runoff.
Shen
Zhenyao
Z
State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, PR China. z.y.shen@163.com
Hong
Qian
Q
Yu
Hong
H
Liu
Ruimin
R
D002681:China; D004784:Environmental Monitoring; D019015:Geologic Sediments / Q000737:chemistry; D008962:Models, Theoretical; D009010:Monte Carlo Method; D009566:Nitrates / Q000032:analysis; D009584:Nitrogen / Q000032:analysis; D010758:Phosphorus / Q000032:analysis; D045483:Rivers / Q000737:chemistry*; D035501:Uncertainty; D014876:Water Pollution / Q000032:analysis*; D014881:Water Supply
D009566:Nitrates; D010758:Phosphorus; D009584:Nitrogen