Publications by authors named "Yinzhu Liu"

Although the effects of human-enhanced atmospheric nitrogen (N) deposition are well documented, the response of dryland soils to N deposition remains unclear owing to the divergence in hydrological outputs and soil heterogeneity. We selected a typical desert steppe in western China to simulate the effects of long-term N deposition by applying 0 (CK), 3.5, 7, and 14 g N m yr for 12 consecutive years.

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Good water quality is critical to public health and aquatic ecological security of global reservoirs. In stratified reservoirs, increasing near-term management demands foster extremely high monitoring and forecasting needs. In this study, a management assistant for stratified reservoirs (MASR) was developed, including a wave-driven monitoring platform and interpretation platform for multiple reservoir water quality variables.

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Shallow lakes are greatly influenced by submerged aquatic vegetation (SAV), which affects hydraulic and water quality during their entire life cycle. An integrated model was developed based on the Environmental Fluid Dynamics Code (EFDC), which considers the dynamic bottom roughness and sediment release flux related to SAV growth and decomposition. Model results of hydrodynamics, water quality, and sediment-P release in Baiyangdian Lake (BL) were analyzed with and without the SAV module.

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Understanding dynamic future changes in precipitation can provide prior information for nonpoint source pollution simulations under global warming. However, the evolution of the dependence structure and the unevenness characteristics of precipitation are rarely considered. This study applied a two-stage bias correction to daily precipitation and max/min temperature data in the Daqing River Basin (DQRB) with the HadGEM3-RA climate model.

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A temperature control curtain can effectively mitigate the negative effect of outflow temperature on the river eco-environment downstream. To investigate the response of outflow temperature to influence factors (i.e.

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The risk of water shortage caused by uncertainties, such as frequent drought, varied precipitation, multiple water resources, and different water demands, brings new challenges to the water transfer projects. Uncertainties exist for transferring water and local surface water; therefore, the relationship between them should be thoroughly studied to prevent water shortage. For more effective water management, an uncertainty-based water shortage risk assessment model (UWSRAM) is developed to study the combined effect of multiple water resources and analyze the shortage degree under uncertainty.

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