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Development of a Novel Fuzzy Logic-Based Wetland Health Assessment Approach for the Management of Freshwater Wetland Ecosystems

  • Applied Wetland Science
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Abstract

In the present study, a new wetland health assessment approach based on the fuzzy inference system (FIS) was developed and proposed for the first time to improve a traditional wetland classification and assessment index. One primary purpose of the study is to modify the indicators of the traditional assessment approach to suit the regional environmental conditions of the selected areas. As two of the twenty-five Iranian wetlands with international importance, Kanibarazan and Choghakhor wetlands were selected as the study areas due to their significant roles in protecting the biodiversity of their regions. The wetlands are supported by the international Ramsar Convention on Wetlands to mandate and encourage the local authorities towards their conservation and sustainable exploitation. In this regard, the Iranian Department of Environment, in cooperation with the Global Environment Facility (GEF) and the United Nations Development Programme (UNDP), selected these wetlands to demonstrate new approaches of managing the wetland areas protected by the Conservation of Iranian Wetlands Project (CIWP). A real-time wetland monitoring station with hydrological instruments, including water level, air temperature, air humidity, and water quality multi-parameter sensors recording water temperature, pH, electrical conductivity, and dissolved oxygen (DO), was implanted at the deepest part of both wetlands. The manual sampling of water quality parameters was also carried out periodically during specific intervals. The relative importance of the wetland health indicators involved in the FIS was determined via the analytic hierarchy process (AHP), utilizing the knowledge of local experts, including academic staff, environmental specialists, and natives, to localize the traditional assessment approach. In turn, the health level categories of both wetlands were assessed using the traditional and proposed wetland health assessment approaches. The efficiency of the proposed method was evaluated with the selected case studies, and it proved to be a more flexible and appropriate approach for wetland health assessment. Furthermore, the observed differences between the health level of the first case study pointed to the efficiency of the AHP-FIS method in improving the traditional index. Besides, feedforward neural network (FFNN) and support vector regression (SVR) artificial intelligence (AI) methods were used to model DO as one of the most critical water quality parameters in maintaining the biological integrity of wetland ecosystems. The obtained results indicated that FFNN performed slightly better than SVR in predicting DO of both wetlands. Consequently, the results of DO modeling were used to investigate the possibility of employing AI models in wetland health assessment in case of unavailability or failures of DO sensors, which was considered practical considering the suitable performance of AI models and the obtained wetland health level results based on the predicted DO.

Highlights

1. A wetland health assessment approach based on fuzzy logic was developed.

2. Two freshwater wetlands were selected as real case study areas.

3. The fuzzy inference system and analytic hierarchy process were used to improve the process.

4. The proposed approach showed more flexibility and efficiency.

5. Two AI methods were used to model DO and investigate their applicability in health assessment.

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Acknowledgments

The authors graciously acknowledge the “Conservation of Iranian Wetlands Project” office for assistance in data acquisition and partially supported by the Iranian Department of Environment under the project No. t/9863.

Data Availability

Data cannot be made publicly available; readers should contact the corresponding author for details.

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The code will be available upon request.

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Not applicable. This study was not funded by any company or other references.

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Authors and Affiliations

  1. Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran

    Sajad Soleymani Hasani & Alireza Mojtahedi

  2. Faculty of Civil Engineering, K. N. Toosi University of Technology, Tehran, Iran

    Mir Amir Mohammad Reshadi

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  1. Sajad Soleymani Hasani
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  2. Alireza Mojtahedi
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Contributions

SSH contributed to developing the overall methodology, goals of the study, performed the software-based parts and wrote the original draft. AM supervised and administrated the project and designed the overall scheme of the research, conceptualization, and final editing. AMR took his part in conceptualization and writing the original draft.

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Correspondence to Alireza Mojtahedi.

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This article does not violate rights of any kind, as it does not contain any studies with human participants performed by any of the authors. This article does not contain any studies with animals performed by any of the authors. Informed consent was obtained from all individual participants included in the study.

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The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Hasani, S.S., Mojtahedi, A. & Reshadi, M.A.M. Development of a Novel Fuzzy Logic-Based Wetland Health Assessment Approach for the Management of Freshwater Wetland Ecosystems. Wetlands 41, 100 (2021). https://doi.org/10.1007/s13157-021-01499-2

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