From global to local: Testing the potential of cross-scaling in global data sets |
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| Authors: | Nidhi Nagabhatla R Wickramasuriya S N Prasad |
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| Institution: | (1) Said Business School, University of Oxford, Oxford, UK;(2) International Water Management Institute (IWMI) Southeast Asia Regional Office, Vientiane, Lao PDR;(3) Environment Canada, National Water Research Institute, Canada Centre for Inland Waters, 867 Lakeshore Rd., PO Box 5050, Burlington, ON,, L7R 4A6, Canada;(4) ILWS, Charles Sturt University, Albury, NSW, Australia;(5) School of Earth and Environmental Sciences, University of Wollongong, Wollongong, 2522, NSW, Australia;(6) Challenge Program on Water and Food (CPWF), Colombo, Sri Lanka;(7) Salim Ali Centre for Ornithology and Natural History (SACON), Hyderabad, India |
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| Abstract: | The present study investigates the potential of readily available and easily accessible global data sets to understand regional/local
level interactions in wetland systems. The biogeographical zones of India were used a base-frame to select three sites. The
study well fits the interests of National Wetland Committee of India to investigate and document fundamental information on
wetland extent/distribution. The national partnership with SACON represents this interest. SACON commenced the inland wetland
inventory module at national scale using geospatial data, although the provincial scale analysis is underway. In addition,
the global irrigated area mapping (GIAM-IWMI) project generated multi-scalar spatial outputs for irrigated/rain-fed areas.
With the existing information base, a multi-level geospatial analysis using Arc GIS algorithmic modelling was used to derive
comprehensive appraisal of wetland systems complementing the data from GIAM and SACON. It was observed that the overlap between
the two layers was 58 percent for Gujarat and 10 percent in Tamil Nadu. In Krishna basin the wetland’s cover 1.04 million
hectare excluding the rice agro-ecosystem. The difference in the biogeography of the case sites governs the gradient of information
derived from both data layers. Additionally, the global lakes and wetlands database (GLWD) database added thematic information
on coastal wetlands. In summary we describe the cross-scaling the global data layers to compliment the regional/national level
monitoring assignments. |
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