INTEGRATING MULTI-SCALE DATA FOR THE ASSESSMENT OF WATER AVAILABILITY AND QUALITY IN THE KHARAA - ORKHON - SELENGA RIVER SYSTEM

Geography, Environment, Sustainability

Marcus Malsy¹  Melanie Hartwig²  Daniel Karthe²  Philipp Theuring²  Christian Schweitzer³  Jörg Priess³  Lucas Menzel⁴  Nikolay S. Kasimov⁵  Mikhail Lychagin⁵  Galina L. Shinkareva⁵  Sergey R. Chalov⁵  Jürgen Hofmann⁶ 

[1] Center for Environmental Systems Research, Kassel University, Kassel, Germany;Department of Aquatic Ecosystem Analysis and Management, Helmholtz Centre for Environmental Research, Magdeburg, Germany;Department of Computational Landscape Ecology, Helmholtz Centre for Environmental Research;Department of Hydrogeography and Climatology, Heidelberg University, Heidelberg, Germany;Faculty of Geography, Lomonosov Moscow State University, Moscow, Russia;Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB), Department Ecohydrology;

关键词: hydrology;    water availability;    water quality;    central asia;    mongolia;    russia;   

DOI  :  10.24057/2071-9388-2014-7-3-40-49

来源: DOAJ

【 摘 要 】

The environmental and socio-enonomic impacts of water pollution are particularly severe in regions with relatively limited water resources [WWAP, 2012]. Water quantity and quality are closely interlinked aspects which are relevant for surface water ecology, water use, and integrated management approaches. However, an intensive monitoring of both is usually prohibitive for very large areas, particularly if it includes the investigation of underlying processes and causes. For the Kharaa - Orkhon - Selenga River system, this paper combines results from the micro (experimental plots, individual point data), meso (Kharaa River Basin) and macro (Selenge River Basin) scales. On the one hand, this integration allows an interpretation of existing data on surface water quantity and quality in a wider context. On the other hand, it empirically underpins the complimentary character of intensive monitoring in selected model regions with more extensive monitoring in larger areas.

【 授权许可】

Unknown