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Influenced by the water design principle of Chinese classical garden, the design of urban waterbodies (lakes, ponds and wetlands) in China typically exhibits natural-like morphological characteristics, but what similarities and differences among these characteristics remain unclear. Also, the morphology of urban waterbodies is mostly designed with beauty and lacks quantitative research and methodological support, which is not favourable to the exploration of the correlation between waterbody morphology and ecology. In this study, 11 quantifiable morphological indicators are selected from water surface, shoreline complexity and water-land spatial morphology. A Grasshopper-based model for waterbody morphology quantification and analysis was constructed and applied to 42 cases in China. Combined with frequency, correlation and PCA analysis, the cases and indicators with higher composite scores generally showed more natural water surface morphology, island distribution, and diversified land and water spaces. The thresholds for the more representative indicators are 0.10–0.60 for the circularity ratio (C), 1.01–1.15 for the shoreline fractal dimension (D0), 1.58–29.42 for the island nearest-neighbour index (NN), 1.20–2.50 for the shoreline development index (SDI), 0.20–0.55 for the compactness ratio (Rc) and 0.30–0.85 for the unit water surface morphological difference ratio (ΔB). Focusing on these indicators, along with ΔB and I which describe spatial inclusiveness and island distribution, their regression equations and threshold ranges provide a primary basis for developing waterbody morphology designs and generative algorithms. This methodology has been experimentally applied in the design of a case waterbody in Suqian City Park. Overall, this study constructs and validates the feasibility of a Grasshopper-based algorithm for the quantitative analysis and morphogenetic design of waterbody morphology. It demonstrates the potential of this method for understanding complex waterbody morphology and water-land spaces, and supports a new digital methodology for the optimisation of waterscape design. |
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