Department of Civil Engineering, Birla Institute of Technology and Science, Pilani, Rajasthan, 333031, India.
Computer Science and Engineering, Indraprastha Institute of Information Technology, New Delhi, India.
Environ Sci Pollut Res Int. 2023 Jun;30(28):72900-72915. doi: 10.1007/s11356-023-27556-3. Epub 2023 May 15.
Wetlands are significant ecosystems which perform several functions such as ground water recharge, flood control, carbon sequestration, and pollution reduction. Accurate evaluation of wetland functions is challenging, due to uncertainty associated with variables such as vegetation, soil, hydrology, land use, and landscape. Uncertainty is due to the factors such as the cost of evaluating quality parameters, measurement, and human errors. This study proposes an innovative framework based on modified hydrogeomorphic approach (HGMA) using fuzzy α-cut technique. HGMA has been used for wetland functional assessment and α-cut technique is used to characterize uncertainty corresponding to the input variables and wetland functions. The most uncertain variables were found to be the density of wetlands and basin count in the landscape assessment area with the scores of 4.38% and 3.614% respectively. Among the functions, the highest uncertainty is found in functional capacity index (FCI) corresponding to water storage (1.697%) and retain particulate (1.577%). The quantified uncertainty can help the practitioners to make informed decisions regarding planning best management practices for preserving and restoring the wetland functionality.
湿地是具有多种功能的重要生态系统,如地下水补给、洪水控制、碳封存和减少污染。由于与植被、土壤、水文学、土地利用和景观等变量相关的不确定性,准确评估湿地功能具有挑战性。不确定性是由于评估质量参数、测量和人为错误的成本等因素造成的。本研究提出了一种基于改进的水文地貌方法(HGMA)和模糊α-切割技术的创新框架。HGMA 已用于湿地功能评估,α-切割技术用于描述与输入变量和湿地功能相关的不确定性。在景观评估区域中,最不确定的变量是湿地密度和流域计数,分别为 4.38%和 3.614%。在功能方面,发现与储水(1.697%)和保留颗粒物(1.577%)相对应的功能能力指数(FCI)的不确定性最高。量化的不确定性可以帮助从业者在规划最佳管理实践以保护和恢复湿地功能方面做出明智的决策。