Integrated model projections of climate change impacts on water-level dynamics in the large Poyang Lake (China)

Abstract

Abstract This study outlines a framework for examining potential impacts of future climate change in Poyang Lake water levels using linked models. The catchment hydrological model (WATLAC) was used to simulate river runoffs from a baseline period (1986–2005) and near-future (2020–2035) climate scenarios based on eight global climate models (GCMs). Outputs from the hydrological model combined with the Yangtze River's effects were fed into a lake water-level model, developing in the back-propagation neural network. Model projections indicate that spring–summer water levels of Poyang Lake are expected to increase by 5–25%, and autumn–winter water levels are likely to be lower and decrease by 5–30%, relative to the baseline period. This amounts to higher lake water levels by as much as 2 m in flood seasons and lower water levels in dry seasons in the range of 0.1–1.3 m, indicating that the lake may be wet-get-wetter and dry-get-drier. The probability of occurrence for both the extreme high and low water levels may exhibit obviously increasing trends by up to 5% more than at present, indicating an increased risk in the severity of lake floods and droughts. Projected changes also include possible shifts in the timing and magnitude of the lake water levels.