Uncertainties hamper the implementation of strategic environmental assessment (SEA). In order to quantitatively characterize the uncertainties of environmental impacts, this paper develops an integrated methodology through uncertainty analysis on land use change, which combines the scenario analysis approach, stochastic simulation technique, and statistics. Dalian city in China was taken as a case study in the present work. The results predict that the Fuzhou River poses the highest environmental pollution risk with a probability of 89.63% for COD in 2020. Furthermore, the Biliu River, Fuzhou River, Zhuang River, and Dasha River have 100% probabilities for NH3-N. NH3-N is a more critical pollutant than COD for all rivers. For COD, industry is the critical pollution source for all rivers except the Zhuang River. For NH3-N, agriculture is the critical pollution source for the Biliu River, Yingna River, and Dasha River, sewage for the Fuzhou River and Zhuang River, and industry for the Dengsha River. This methodology can provide useful information, such as environmental risk, environmental pressure, and extremely environmental impact, especially under considerations of uncertainties. It can also help to ascertain the significance of each pollution source and its priority for control in urban planning.