River water chemistry offers information on watershed weathering and responds to the global carbon cycle. Watershed weathering processes and water chemistry in stratified water are still unclear in Xiaojiang River, as a major tributary of the Three Gorges Reservoir (TGR) which is the largest reservoir in the world. Major ions of river water at different depths were measured to reveal the ionic composition and chemical weathering properties by principal component analysis and stoichiometry in Xiaojiang River. Ca2+−HCO3− dominated the hydrochemical facies of river. Surface river water had the lowest total dissolved solid (146 mg/L) compared to other layers of water. According to principal component analysis, the major ions were divided into two principal components. PC1 was the weathering end-member of rocks, including the main ions except K+ and NO3–N, and PC2 may be the mixed end-member of atmospheric input and anthropogenic input. From stoichiometry, carbonate weathering dominated the cationic composition, with a contribution ratio of 56.7%, whereas atmospheric input (15.2%) and silicates weathering (13.9%) had similar extent of contribution. Compared with other major tributaries of TGR, Xiaojiang had more intense chemical weathering processes. The weathering rates of carbonates and silicates were 19.33 ± 0.68 ton/km2/year and 3.56 ± 0.58 ton/km2/year, respectively. Sulfuric acid as a proton may have participated less in the weathering processes of Xiaojiang River. The CO2 consumption budgets for silicates and carbonates weathering were 0.8 ± 0.2 × 109 mol/year and 2.8 ± 0.2 × 109 mol/year, respectively. These results enrich the watershed weathering information of TGR tributaries and provide data support for understanding the global carbon cycle.

The prevention and control of non-point source pollution is an important link in managing basin water quality and is an important factor governing the environmental protection of watershed water in China over the next few decades. The control of non-point source pollution relies on the recognition of the amount, location, and influencing factors. The watershed nonpoint source pollution mechanism model is an effective method to address the issue. However, due to the complexity and randomness of non-point source pollution, both the development and application of the watershed water environment model have always focused on the accuracy and rationality of model parameters. In this pursuit, the present study envisaged the temporal and spatial heterogeneity of non-point source pollution caused by the complex underlying surface conditions of the watershed, and the insufficient coverage of hydrological and water quality monitoring stations. A refined watershed non-point source pollution simulation method, combining the Monte Carlo analytic hierarchy process (MCAHP) and the sub-watershed parameter transplantation method (SWPT), was established on the basis of the migration and transformation theory of the non-point source pollution, considering the index selection, watershed division, sub-watershed simulation, and parameter migration. Taking the Erhai Lake, a typical plateau lake in China, as the representative research object, the MCAHP method effectively reduced the uncertainty of the weights of the watershed division indexes compared to the traditional AHP method. Furthermore, compared to the traditional all watershed parameter simulation (AWPS) approach, the simulation accuracy was improved by 40% using the SWPT method, which is important for the prevention and control of non-point source pollution in large-scale watersheds with significant differences in climatic and topographic conditions. Based on the simulation results, the key factors affecting the load of the non-point source pollution in the Erhai watershed were identified. The results showed that the agricultural land in Erhai Lake contributed a majority of the load for several reasons, including the application of nitro phosphor complex fertilizer. Among the different soil types, paddy soil was responsible for the largest pollution load of total nitrogen and total phosphorus discharge into the lake. The zones with slopes of 0°‒18° were found to be the appropriate area for farming. Our study presents technical methods for the assessment, prevention, and control of non-point source pollution load in complex watersheds.

For the implementation of lake ecological protection, understanding the water pollution status and spatio–temporal variation of water quality has become the most important thing for water safety in the basin. To analyze the water quality in recent years, water quality data in Erhai lake from 2013 to 2017 were first collected from typical nine monitoring stations. Based on the comprehensive water quality index (WQI) method, the temporal and spatial variation characteristics of water quality in Erhai lake were analyzed, and the main factors affecting water quality in Erhai lake were explored. The results indicated that the water quality of Erhai lake was worse than its target water quality, and total nitrogen (TN) and total phosphorus (TP) exceeded the Class Ⅱ standards (TN: 0.5 mg L−1, TP: 0.025 mg L−1) of China’s Environmental Quality Standard for Surface Water (GB3838-2002). In terms of changes across seasons, the overall lake water quality in the dry season was better than that in the wet season, and TN and TP reached the peak value in September. In terms of spatial distribution, water quality of the northern area was better than that of the southern area in the dry season, whereas water quality of the southern area was better than that of the northern area in the wet season. At present, Erhai lake is at a critical turning point of water eutrophication, and its nutrition status is mainly affected by both nitrogen and phosphorus. The pollution load from the land area is the main factor affecting the deterioration of Erhai lake. Our results can provide a scientific basis for the treatment of the water environment of Erhai lake.