Your search found 5 records
1 Alcamo, J.; Doll, P.; Henrichs, T.; Kaspar, F.; Lehner, B.; Rosch, T.; Siebert, S. 2003. Development and testing of the WaterGAP 2 global model of water use and availability. Hydrological Sciences Journal, 48(3):317- 337.
Water availability ; Assessment ; River basins ; Hydrology ; Models ; Calibration ; Runoff ; Water balance ; Water scarcity ; Water stress ; Water use ; Domestic water ; Industrialization ; Irrigation water
(Location: IWMI HQ Call no: e-copy only Record No: H041280)
http://www.informaworld.com/smpp/ftinterface~content=a918693024~fulltext=713240930~frm=content
https://vlibrary.iwmi.org/pdf/H041280.pdf
https://vlibrary.iwmi.org/pdf/H041280.pdf
2 Wood, E. F.; Roundy, J. K.; Troy, T. J.; van Beek, L. P. H.; Bierkens, M. F. P.; Blyth, E.; de Roo, A.; Doll, P.; Ek, M.; Famiglietti, J.; Gochis, D.; van de Giesen, N.; Houser, P.; Jaffe, P. R.; Kollet, S.; Lehner, B.; Lettenmaier, D. P.; Peters-Lidard, C.; Sivapalan, M.; Sheffield, J.; Wade, A.; Whitehead, P. 2011. Hyperresolution global land surface modeling: meeting a grand challenge for monitoring earth’s terrestrial water. Water Resources Research, 47:10.
Land cover ; Surface water ; Hydrology ; Social aspects ; Water quality ; Soil moisture ; Weather ; Climate
(Location: IWMI HQ Call no: e-copy only Record No: H045083)
(1.23 MB)
3 Fluet-Chouinard, E.; Lehner, B.; Rebelo, Lisa-Maria; Papa, F.; Hamilton, S. K. 2015. Development of a global inundation map at high spatial resolution from topographic downscaling of coarse-scale remote sensing data. Remote Sensing of Environment, 158:348-361. [doi: https://doi.org/10.1016/j.rse.2014.10.015]
Flooding ; Floodplains ; Mapping ; Land cover ; Satellite imagery ; Remote sensing ; Surface water ; Topography ; Decision support systems ; Databases ; Hydrology ; Models ; Wetlands ; Ecosystems
(Location: IWMI HQ Call no: e-copy only Record No: H047384)
(3.18 MB)
Large-scale estimates of the area of terrestrial surface waters have greatly improved over time, in particular through the development of multi-satellite methodologies, but the generally coarse spatial resolution (tens of kms) of global observations is still inadequate for many ecological applications. The goal of this study is to introduce a new, globally applicable downscaling method and to demonstrate its applicability to derive fine resolution results from coarse global inundation estimates. The downscaling procedure predicts the location of surface water cover with an inundation probability map that was generated by bagged decision trees using globally available topographic and hydrographic information from the SRTM-derived HydroSHEDS database and trained on the wetland extent of the GLC2000 global land cover map. We applied the downscaling technique to the Global Inundation Extent from Multi-Satellites (GIEMS) dataset to produce a new high-resolution inundation map at a pixel size of 15 arc-seconds, termed GIEMS-D15. GIEMS-D15 represents three states of land surface inundation extents: mean annual minimum (total area, 6.5 × 106 km2 ), mean annual maximum (12.1 × 106 km2 ), and long-term maximum ( 17.3 × 106 km2 ); the latter depicts the largest surface water area of any global map to date. While the accuracy of GIEMS-D15 reflects distribution errors introduced by the downscaling process as well as errors from the original satellite estimates, overall accuracy is good yet spatially variable. A comparison against regional wetland cover maps generated by independent observations shows that the results adequately represent large floodplains and wetlands. GIEMS-D15 offers a higher resolution delineation of inundated areas than previously available for the assessment of global freshwater resources and the study of large floodplain and wetland ecosystems. The technique of applying inundation probabilities also allows for coupling with coarse-scale hydro-climatological model simulations.
4 Linke, S.; Lehner, B.; Dallaire, C. O.; Ariwi, J.; Grill, G.; Anand, M.; Beames, P.; Burchard-Levine, V.; Maxwell, S.; Moidu, H.; Tan, F.; Thieme, M. 2019. Global hydro-environmental sub-basin and river reach characteristics at high spatial resolution. Scientific Data, 6:1-15. [doi: https://doi.org/10.1038/s41597-019-0300-6]
River basins ; Databases ; Hydrology ; Environmental effects ; Freshwater ; Watersheds ; Land cover ; Land use ; Anthropogenic factors ; Geometry ; Runoff ; Discharges
(Location: IWMI HQ Call no: e-copy only Record No: H049392)
(3.29 MB) (3.29 MB)
The HydroATLAS database provides a standardized compendium of descriptive hydro-environmental information for all watersheds and rivers of the world at high spatial resolution. Version 1.0 of HydroATLAS offers data for 56 variables, partitioned into 281 individual attributes and organized in six categories: hydrology; physiography; climate; land cover & use; soils & geology; and anthropogenic influences. HydroATLAS derives the hydro-environmental characteristics by aggregating and reformatting original data from well-established global digital maps, and by accumulating them along the drainage network from headwaters to ocean outlets. The attributes are linked to hierarchically nested sub-basins at multiple scales, as well as to individual river reaches, both extracted from the global HydroSHEDS database at 15 arc-second (~500 m) resolution. The sub-basin and river reach information is offered in two companion datasets: BasinATLAS and RiverATLAS. The standardized format of HydroATLAS ensures easy applicability while the inherent topological information supports basic network functionality such as identifying up- and downstream connections. HydroATLAS is fully compatible with other products of the overarching HydroSHEDS project enabling versatile hydro-ecological assessments for a broad user community.
5 Kuehne, L. M.; Dickens, Chris; Tickner, D.; Messager, M. L.; Olden, J. D.; O’Brien, G.; Lehner, B.; Eriyagama, Nishadi. 2023. The future of global river health monitoring. PLOS Water, 2(9):e0000101. [doi: https://doi.org/10.1371/journal.pwat.0000101]
Rivers ; Environmental health ; Monitoring ; Frameworks ; Freshwater ecosystems ; Biodiversity ; Indicators ; Water quality ; Habitats ; Biology ; Hydrology ; Surface water ; Environmental restoration ; Agreements ; Policies ; Sustainable Development Goals
(Location: IWMI HQ Call no: e-copy only Record No: H052227)
https://journals.plos.org/water/article/file?id=10.1371/journal.pwat.0000101&type=printable
https://vlibrary.iwmi.org/pdf/H052227.pdf
https://vlibrary.iwmi.org/pdf/H052227.pdf
(1.33 MB) (1.33 MB)
Rivers are the arteries of human civilisation and culture, providing essential goods and services that underpin water and food security, socio-economic development and climate resilience. They also support an extraordinary diversity of biological life. Human appropriation of land and water together with changes in climate have jointly driven rapid declines in river health and biodiversity worldwide, stimulating calls for an Emergency Recovery Plan for freshwater ecosystems. Yet freshwater ecosystems like rivers have been consistently under-represented within global agreements such as the UN Sustainable Development Goals and the UN Convention on Biological Diversity. Even where such agreements acknowledge that river health is important, implementation is hampered by inadequate global-scale indicators and a lack of coherent monitoring efforts. Consequently, there is no reliable basis for tracking global trends in river health, assessing the impacts of international agreements on river ecosystems and guiding global investments in river management to priority issues or regions. We reviewed national and regional approaches for river health monitoring to develop a comprehensive set of scalable indicators that can support “top-down” global surveillance while also facilitating standardised “bottom-up” local monitoring efforts. We evaluate readiness of these indicators for implementation at a global scale, based on their current status and emerging improvements in underlying data sources and methodologies. We chart a road map that identifies data and technical priorities and opportunities to advance global river health monitoring such that an adequate monitoring framework could be in place and implemented by 2030, with the potential for substantial enhancement by 2050. Lastly, we present recommendations for coordinated action and investment by policy makers, research funders and scientists to develop and implement the framework to support conservation and restoration of river health globally.
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