Identifying Riparian Areas of Free Flowing Rivers for Legal Protection: Model Region Mongolia

Mongolia has globally significant biodiversity and pastoral traditions, and scarce water resources on which wildlife and people depend. Rapid growth of the mining sector is a threat to water resources and specifically river riparian zones. Mongolia has passed progressive laws for water and habitat c...

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Bibliographic Details
Main Authors: Purevdorj Surenkhorloo, Chimeddorj Buyanaa, Sanjmyatav Dolgorjav, Chimed-Ochir Bazarsad, Batjargal Zamba, Sainbuyan Bayarsaikhan, Michael Heiner
Format: Article
Language:English
Published: MDPI AG 2021-01-01
Series:Sustainability
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Online Access:https://www.mdpi.com/2071-1050/13/2/551
Description
Summary:Mongolia has globally significant biodiversity and pastoral traditions, and scarce water resources on which wildlife and people depend. Rapid growth of the mining sector is a threat to water resources and specifically river riparian zones. Mongolia has passed progressive laws for water and habitat conservation, including establishment of Integrated Water Resource Management (IWRM) and river basin governance organizations, and laws protecting the river riparian zone, but implementation is hindered by limited technical capacity and data-scarcity, specifically because consistent, accurate maps of the riparian zone did not exist. To address the gap, WWF-Mongolia and partners developed a national delineation of riparian areas based on a spatial model, then validated this with local River Basin Authorities and provincial governments to designate legal protection zones. As a result, 8.2 million hectares of water protection zones including riparian areas have been legally protected from mining and industrial development in the globally significant landscapes and riverscapes of the Amur, Yenisey, and Ob Rivers headwaters, the Altai Sayan ecoregion, and the Gobi-Steppe ecosystem. These findings demonstrate a pathway for implementing broad-scale, durable legal protection of riverine wetlands through a data-driven, participatory process.
ISSN:2071-1050