Jing Yao

TL;DR: In this paper, a physically-based hydrodynamic model was employed to explore catchment and Yangtze River controls on the Poyang Lake's hydrology, and it was shown that changes in lake hydrological regimes and the associated impacts on water supplies and ecosystems are internationally recognized issues.

TL;DR: In this paper, a distributed catchment-hydrology model and a physically based lake hydrodynamic model were used to simulate the large-scale and highly dynamic lake catchment system of Poyang Lake, in the middle reach of the Yangtze River basin, China.

TL;DR: The findings of this study support the management of both Poyang Lake and the floodplain wetlands by providing important information on both water resource and water quality, and proposals to better manage the impacts of intensive human activities.

TL;DR: In this article, a back-propagation neural network (BPNN) is applied as a first attempt to simulate the water-level variations of a large lake, exemplified by the Poyang Lake (China) case study.

TL;DR: In this paper, the effects of backflow on the lake hydrology were explored using a physically-based hydrodynamic model and a particle-tracking model, and it was shown that backflow disturbs the normal northward water flow direction in Poyang Lake and transports mass ~20 km southward into the lake.