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@article{207557,
        author = {Dr Ravindra Pratap Singh},
        title = {Economic Valuation of Wetland Ecosystem Services: A Case Study of Sarsai Nawar Jheel},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {3},
        pages = {2486-2491},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=207557},
        abstract = {Wetlands deliver a complex suite of provisioning, regulating, supporting, and cultural services that underpin both ecological health and human prosperity. Nevertheless, these ecosystems—particularly within India's Gangetic floodplain—are routinely undervalued in regional planning and policy frameworks. This study provides a detailed economic valuation of the ecosystem services generated by Sarsai Nawar Jheel, a 161-hectare freshwater marsh in Uttar Pradesh recognized as a Ramsar site in 2019. Using data from the Ministry of Environment, Forest and Climate Change, the Uttar Pradesh State Wetland Authority, and peer-reviewed literature, the research quantifies the economic contributions of three primary ecosystem services: biodiversity conservation, groundwater recharge, and local livelihood support. By applying the Total Economic Value (TEV) framework alongside a benefit transfer methodology adjusted for local biophysical conditions, the study estimates the wetland’s aggregate annual economic value to be between INR 4.23 crore and INR 7.90 crore (roughly USD 0.51 million to USD 0.95 million). Biodiversity conservation emerges as the most economically significant service. These findings provide a strong economic justification for increasing conservation investments and highlight the critical need to integrate ecosystem service valuation into formal wetland governance and policy structures.},
        keywords = {Ramsar Convention, ecosystem services, economic valuation, benefit transfer, Sarus crane, groundwater recharge, Indo-Gangetic floodplain, Uttar Pradesh.},
        month = {August},
        }