Temporal and Spatial Pattern Evolution Model of Constructed Wetland Based on GIS

Shenmin Wang, Yue Han, Qifang Ma, Hanwei Liang

Ekoloji, 2019, Issue 108, Pages: 1259-1264


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Temporal and spatial pattern evolution model of constructed wetland is a kind of based on ecological processes, can fully display the wetland ecological pattern of time and space dynamic evolution mechanism of spatial display model. Because the model involves a series of ecological processes and can reveal the change process of wetland system structure and function, it has become an important means of wetland planning, evaluation and management. The temporal and spatial pattern evolution model of wetland is one of the hot research areas in recent years. Constructed wetlands are characterized by high complexity and dynamic changes. This paper studies them from the aspects of theoretical basis, key issues of model construction and basic processes. The main contents are as follows: 1. To understand the ecological elements of wetland ecosystem and their interactions. The ecological factors driving the evolution of wetland ecosystem include hydrology, soil, plant community types, climate, landform and other natural geographical factors. It is the key to reveal the spatial heterogeneity of these factors and its influence on the evolution of wetland system. 2. Key problems to be solved in model construction include model structure, appropriate spatial scale and model construction method; 3. The key technology of model construction is the integration of ecosystem model and GIS technology. The research in this paper is mainly aimed at the characteristics of the evolution of the spatio-temporal pattern of wetlands, and is of great significance for wetland planning, protection and management.


GIS, constructed wetlands, spatial and temporal pattern, evolution, model design


  • Lu XN, Huang Y, Hong J, et al (2018) Spatial and temporal variations in wetland landscape patterns in the Yellow River Delta based on Landsat images. China Environmental Science 38(11):4314-4324.
  • Ozengin N, Elmaci A, Yonar T (2016) Application of artificial neural network in horizontal subsurface flow constructed wetland for nutrient removal prediction. Applied Ecology and Environmental Research 14(4):305-324.
  • Ren SX, Xie ZX, Li Y, et al (2017) Study on spatiotemporal pattern evolution of urban efficiency in Central Plains Economic Region. Journal of Henan University (Natural Science) 47(2):147-154.
  • Riggio VA, Ruffino B, Campo G, et al (2018) Constructed wetlands for the reuse of industrial wastewater: a case-study. Journal of Cleaner Production 171:723-732.
  • Shen Y, Zhao N, Xia M, et al (2017) A deep q-learning network for ship stowage planning problem. Polish Maritime Research 24(SI):102-109.
  • Wu JJ, Li YZ. Yu LJ, et al (2018) Dynamic changes and driving factors of landscape connectivity for natural wetland in Yellow River Delta. Ecology and Environment Sciences 27(1):71-78.
  • Zhang M, Zeng YN (2018) Temporal and spatial dynamic changes and driving forces analysis of wetland landscape of Chang-Zhu-Tan urban agglomeration. Transactions of the Chinese Society of Agricultural Engineering 34(1):241-249.