Inference of reference conditions for nutrient concentrations of Chaohu Lake based on model extrapolation

• DOI: 10.1007/s11769-012-0571-8
• Publication Date: 2012-09-01T17:07:16Z
• Authors: Yuliang Zhou; Juliang Jin; Li Liu; Libing Zhang; Jun He; Zhesun Wang
• Keywords: 13. Climate action; 15. Life on land; 01 natural sciences; 6. Clean water; 0105 earth and related environmental sciences

In the mid-eastern China, there are few or no lakes which are in the absence of anthropogenic disturbances, or their sediments remain undisturbed. As a result, the reference lakes distribution and paleolimnological reconstruction approaches usually are inappropriate to estimate lake reference conditions for nutrients. This yields the necessity of using the extrapolation methods to estimate the lake reference conditions for nutrients within those regions. The lake reference conditions for nutrients could be inferred inversely from the law of mass conservation, current lake nutrient concentration, and the loadings from watershed. Considering the scarcity of hydrological and water quality data associated with lakes and watersheds in China, as well as the low requirement of the watershed nutrient loadings models for these data, the soil conservation service (SCS) distributed hydrological model and the universal soil loss equation (USLE) were applied. The SCS model simulates the runoff process of the watershed, thereby calculating dissolved nutrients annually. The USLE estimates the soil erosion and particulate nutrients annually in a watershed. Then, with the loadings from atmospheric deposition and point source, the previous annual average nutrient concentrations could be acquired given the current nutrient concentrations in a lake. Therefore, the nutrient reference conditions minimally impacted by human activities could be estimated. Based on the proposed model, the reference conditions for total nitrogen and total phosphorus of Chaohu Lake, Anhui Province, China are 0.031 mg/L and 0.640 mg/L, respectively. The proposed reference conditions estimation model is of clear physical concept, and less data required. Thus, the proposed approach can be used in other lakes with similar circumstances.