Model Library

Capabilities

• PCLake can simulate water quality based on ecological interactions in shallow, non-stratifying lakes in the temperate climate zone (Janssen et al., 2019);
• PCLake is a comprehensive model for complex aquatic ecosystems (Shi et al., 2023);
• PCLake includes key lake food web components (Janssen et al., 2019);
• The power of PCLake lies in the coherence of the ecological process formulations, minimal overhead and run time and limited input requirements (Janssen et al., 2019).

Limitations

• Applicability of PCLake in subtropical regions remains to be explored (Shi et al., 2023);
• PCLake computes a zero-dimensional system with homogeneous concentrations vertically and horizontally and can thus not account for possible near-surface accumulations (Nielsen et al., 2014);
• PCLake produces an all-or-nothing response in water quality variables (Mooij et al., 2010; Nielsen et al., 2014);
• Ice-cover formation is not included in PCLake (Nielsen et al., 2014);
• Given the complex nature of PCLake, the model is characterized strongly by the non-uniqueness (equifinality) issue (Nielsen et al., 2014);
• The phenology of macrophytes in PCLake is too rigid for global applications, and the light module does not account for latitudinal differences in light intensity (Janssen et al., 2019);
• PCLake is no longer updated.

Inputs

Meteorological data, Water environmental and ecological indicators

Outputs

The outputs of the PCLake model include nutrient concentrations, phytoplankton, zooplankton, macrophyte, fish biomass, water clarity, oxygen levels, and sediment nutrient concentrations in shallow lakes and ponds.

Reference

Shi, T., Chen, Y., Zhang, H., Wang, H., & Liu, Z. (2023). Numerical study on regime shifts in an urban subtropical shallow lake: Xinglong Lake, China. Ecological Indicators, 154, 110600. https://doi.org/10.1016/j.ecolind.2023.110600

Objective

This study aimed to: 1) Construct an aquatic ecological model based on PCLake to simulate and predict the aquatic ecological changes in Xinglong Lake, a subtropical artificial shallow lake in China, before and after restoration efforts. 2) Use the model to predict future levels of key water quality parameters (TN, TP, Chl-a) and aquatic vegetation biomass, as well as identify the thresholds for regime shifts in the lake's ecosystem. 3) Quantify the impact of common management measures, such as pollution control and water level regulation, on the stability of the lake's aquatic ecosystem.