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T. R. Marthews; S. J. Dadson; B. Lehner; S. Abele; N. Gedney (2015)
Publisher: Copernicus Publications
Journal: Hydrology and Earth System Sciences
Languages: English
Types: Article
Subjects: T, G, GE1-350, Geography. Anthropology. Recreation, Environmental technology. Sanitary engineering, Environmental sciences, Technology, TD1-1066
Modelling land surface water flow is of critical importance for simulating land surface fluxes, predicting runoff and water table dynamics and for many other applications of Land Surface Models. Many approaches are based on the popular hydrology model TOPMODEL (TOPography-based hydrological MODEL), and the most important parameter of this model is the well-known topographic index. Here we present new, high-resolution parameter maps of the topographic index for all ice-free land pixels calculated from hydrologically conditioned HydroSHEDS (Hydrological data and maps based on SHuttle Elevation Derivatives at multiple Scales) data using the GA2 algorithm (GRIDATB 2). At 15 arcsec resolution, these layers are 4 times finer than the resolution of the previously best-available topographic index layers, the compound topographic index of HYDRO1k (CTI). For the largest river catchments occurring on each continent we found that, in comparison with CTI our revised values were up to 20% lower in, e.g. the Amazon. We found the highest catchment means were for the Murray–Darling and Nelson–Saskatchewan rather than for the Amazon and St. Lawrence as found from the CTI. For the majority of large catchments, however, the spread of our new GA2 index values is very similar to those of CTI, yet with more spatial variability apparent at fine scale. We believe these new index layers represent greatly improved global-scale topographic index values and hope that they will be widely used in land surface modelling applications in the future.
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    • Baker, C., Thompson, J. R., and Simpson, M.: Hydrological Dynamics I: Surface Waters, Flood and Sediment Dynamics, in: The Wetlands Handbook, edited by: Maltby, E. and Barker, T., WileyBlackwell, Chichester, UK, 120-168, 2009.
    • Beven, K. J.: TOPMODEL: a critique, Hydrol. Process., 11, 1069- 1085, 1997.
    • Beven, K. J.: Rainfall-Runoff Modelling The Primer, 2nd Edn., Wiley-Blackwell, Chichester, UK, 2012.
    • Beven, K. J. and Cloke, H. L.: Comment on “Hyperresolution global land surface modeling: Meeting a grand challenge for monitoring Earth's terrestrial water” by Eric F. Wood et al., Water Resour. Res., 48, W01801, doi:10.1029/2011WR010982, 2012.
    • Beven, K. J. and Kirkby, M. J.: A physically based, variable contributing area model of basin hydrology, Hydrological Sciences - Bulletin des Sciences Hydrologiques, 24, 43-69, 1979.
    • Buytaert, W.: topmodel: Implementation of the hydrological model TOPMODEL in R, version 0.7.2-2, R Package, available at: http: //cran.r-project.org/web/packages/topmodel/index.html (last access: 6 June 2014), 2011.
    • Castanho, A. D. A., Coe, M. T., Costa, M. H., Malhi, Y., Galbraith, D., and Quesada, C. A.: Improving simulated Amazon forest biomass and productivity by including spatial variation in biophysical parameters, Biogeosciences, 10, 2255-2272, doi:10.5194/bg-10-2255-2013, 2013.
    • Chappell, N. A., Vongtanaboon, S., Jiang, Y., and Tangtham, N.: Return-flow prediction and buffer designation in two rainforest headwaters, Forest Ecol. Manage., 224, 131-146, 2006.
    • Choi, H. I.: Application of a Land Surface Model Using Remote Sensing Data for High Resolution Simulations of Terrestrial Processes, Remote Sensing, 5, 6838-6856, 2013.
    • Clark, D. B. and Gedney, N.: Representing the effects of subgrid variability of soil moisture on runoff generation in a land surface model, J Geophys. Res. D, 113, D10111, doi:10.1029/2007JD008940, 2008.
    • Coe, M. T.: A linked global model of terrestrial hydrologic processes: Simulation of modern rivers, lakes, and wetlands, J Geophys. Res.-Atmos., 103, 8885-8899, 1998.
    • Coe, M. T., Costa, M. H., and Soares-Filho, B. S.: The influence of historical and potential future deforestation on the stream flow of the Amazon River - Land surface processes and atmospheric feedbacks, J. Hydrol., 369, 165-174, 2009.
    • Collins, W. J., Bellouin, N., Doutriaux-Boucher, M., Gedney, N., Halloran, P., Hinton, T., Hughes, J., Jones, C. D., Joshi, M., Liddicoat, S., Martin, G., O'Connor, F., Rae, J., Senior, C., Sitch, S., Totterdell, I., Wiltshire, A., and Woodward, S.: Development and evaluation of an Earth-System model - HadGEM2, Geosci. Model Dev., 4, 1051-1075, doi:10.5194/gmd-4-1051- 2011, 2011.
    • Dadson, S. J. and Bell, V. A.: Comparison of Grid-2-Grid and TRIP runoff routing schemes, Report, Centre for Ecology & Hydrology, Wallingford, UK, 2010.
    • Dadson, S. J., Ashpole, I., Harris, P., Davies, H. N., Clark, D. B., Blyth, E., and Taylor, C. M.: Wetland inundation dynamics in a model of land surface climate: Evaluation in the Niger inland delta region, J. Geophys. Res.-Atmos., 115, D23114, doi:10.1029/2010JD014474, 2010.
    • Dadson, S. J., Bell, V. A., and Jones, R. G.: Evaluation of a gridbased river flow model configured for use in a regional climate model, J. Hydrol., 411, 238-250, 2011.
    • Dharssi, I., Vidale, P. L., Verhoef, A., Macpherson, B., Jones, C., and Best, M.: New soil physical properties implemented in the Unified Model at PS18, Met Office Technical Report 528, The Met Office, Exeter, UK, 2009.
    • Ducharne, A.: Reducing scale dependence in TOPMODEL using a dimensionless topographic index, Hydrol. Earth Syst. Sci., 13, 2399-2412, doi:10.5194/hess-13-2399-2009, 2009.
    • Evans, J.: CTI.aml Compound Topographic Index AML script, available at: http://arcscripts.esri.com/details.asp?dbid=11863 (last access: 6 June 2014), 2003.
    • Falloon, P. and Betts, R.: Climate impacts on European agriculture and water management in the context of adaptation and mitigation - The importance of an integrated approach, Sci. Total Environ., 408, 5667-5687, 2010.
    • Gedney, N. and Cox, P. M.: The Sensitivity of Global Climate Model Simulations to the Representation of Soil Moisture Heterogeneity, J. Hydrometeorol., 4, 1265-1275, 2003.
    • Gedney, N., Cox, P. M., and Huntingford, C.: Climate feedback from wetland methane emissions, Geophys. Res. Lett., 31, L20503, doi:10.1029/2004GL020919, 2004.
    • Gedney, N., Cox, P. M., Betts, R. A., Boucher, O., Huntingford, C., and Stott, P. A.: Detection of a direct carbon dioxide effect in continental river runoff records, Nature, 439, 835-838, 2006.
    • Gerten, D., Schaphoff, S., Haberlandt, U., Lucht, W., and Sitch, S.: Terrestrial vegetation and water balance - hydrological evaluation of a dynamic global vegetation model, J. Hydrol., 286, 249- 270, 2004.
    • Harding, R. J. and Warnaars, T. A.: Water and global change: The WATCH Project Outreach Report, Centre for Ecology and Hydrology, Wallingford, UK, 2011.
    • Harding, R. J., Blyth, E. M., Tuinenburg, O. A., and Wiltshire, A.: Land atmosphere feedbacks and their role in the water resources of the Ganges basin, Sci. Total Environ., 468, S85-S92, 2013.
    • Hjerdt, K. N., McDonnell, J. J., Seibert, J., and Rodhe, A.: A new topographic index to quantify downslope controls on local drainage, Water Resour. Res., 40, W05602, doi:10.1029/2004WR003130, 2004.
    • IPCC - Intergovernmental Panel on Climate Change: Climate Change 2013: The Physical Science Basis, CUP, Cambridge, UK, 2013.
    • Junk, W. J., Piedade, M. T. F., Schöngart, J., Cohn-Haft, M., Adeney, J. M., and Wittmann, F.: A Classification of Major Naturally-Occurring Amazonian Lowland Wetlands, Wetlands, 31, 623-640, 2011.
    • Ke, Y., Leung, L. R., Huang, M., Coleman, A. M., Li, H., and Wigmosta, M. S.: Development of high resolution land surface parameters for the Community Land Model, Geosci. Model Dev., 5, 1341-1362, doi:10.5194/gmd-5-1341-2012, 2012.
    • Kirkby, M.: Hydrograph Modelling Strategies., in: Processes in Physical and Human Geography, edited by: Peel, R., Chisholm, M., and Haggett, P., Heinemann, London, UK, 69-90, 1975.
    • Lang, M., McCarty, G., Oesterling, R., and Yeo, I.-Y.: Topographic Metrics for Improved Mapping of Forested Wetlands, Wetlands, 33, 141-155, 2013.
    • Lehner, B.: HydroSHEDS Technical Documentation (Version 1.2), World Wildlife Fund, Washington, D.C., available at: http:// hydrosheds.org/page/development (last access: 6 June 2014), 2013.
    • Lehner, B. and Döll, P.: Development and validation of a global database of lakes, reservoirs and wetlands, J. Hydrol., 296, 1-22, 2004.
    • Lehner, B. and Grill, G.: Global river hydrography and network routing: baseline data and new approaches to study the world's large river systems, Hydrol. Process., 27, 2171-2186, 2013.
    • Lehner, B., Verdin, K., and Jarvis, A.: New Global Hydrography Derived From Spaceborne Elevation Data, Eos, 89, 93-94, 2008.
    • Lewis, S.: Hydrologic Sub-basins of Greenland. Dataset, National Snow and Ice Data Center (NSIDC), Boulder, Colorado, available at: http://nsidc.org/data/nsidc-0371.html (last access: 6 June 2014), 2009.
    • MacKellar, N. C., Dadson, S. J., New, M., and Wolski, P.: Evaluation of the JULES land surface model in simulating catchment hydrology in Southern Africa, Hydrol. Earth Syst. Sci. Discuss., 10, 11093-11128, doi:10.5194/hessd-10-11093-2013, 2013.
    • Marthews, T. R., Malhi, Y., Girardin, C. A. J., Silva-Espejo, J. E., Aragão, L. E. O. C., Metcalfe, D. B., Rapp, J. M., Mercado, L. M., Fisher, R. A., Galbraith, D. R., Fisher, J. B., Salinas-Revilla, N., Friend, A. D., and Restrepo-Coupe, N.: Simulating forest productivity along a neotropical elevational transect: temperature variation and carbon use efficiency, Global Change Biol., 18, 2882-2898, 2012.
    • Marthews, T. R., Quesada, C. A., Galbraith, D. R., Malhi, Y., Mullins, C. E., Hodnett, M. G., and Dharssi, I.: High-resolution hydraulic parameter maps for surface soils in tropical South America, Geosci. Model Dev., 7, 711-723, doi:10.5194/gmd-7- 711-2014, 2014.
    • Milly, P. C. D., Betancourt, J., Falkenmark, M., Hirsch, R. M., Kundzewicz, Z. W., Lettenmaier, D. P., and Stouffer, R. J.: Stationarity Is Dead: Whither Water Management?, Science, 319, 573-574, 2008.
    • Moore, I. D., Lewis, A., and Gallant, J. C.: Terrain Attributes: Estimation Methods and Scale Effects, in: Modelling Change in Environmental Systems, edited by: Jakeman, A. J., Beck, M. B., and McAleer, M. J., John Wiley & Sons Ltd., Chichester, UK, 189-214, 1993.
    • O'Connor, F. M., Boucher, O., Gedney, N., Jones, C. D., Folberth, G. A., Coppell, R., Friedlingstein, P., Collins, W. J., Chappellaz, J., Ridley, J., and Johnson, C. E.: Possible role of wetlands, permafrost, and methane hydrates in the methane cycle under future climate change: A review, Rev. Geophys., 48, RG4005, doi:10.1029/2010RG000326, 2010.
    • Orlandini, S., Moretti, G., and Gavioli, A.: Analytical basis for determining slope lines in grid digital elevation models, Water Resour. Res., 50, 529-539, doi:10.1002/2013WR014606, 2014.
    • OSGF - Open Source Geospatial Foundation: Geospatial Data Abstraction Library (version 1.9.0), Translator library, available at: http://www.gdal.org/ (last access: 6 June 2014), 2011.
    • Pangala, S. R., Moore, S., Hornibrook, E. R. C., and Gauci, V.: Trees are major conduits for methane egress from tropical forested wetlands, New Phytol., 197, 524-531, 2013.
    • Pfeffer, W. T., Arendt, A. A., Bliss, A., Bolch, T., Cogley, J. G., Gardner, A. S., Hagen, J.-O., Hock, R., Kaser, G., Kienholz, C., Miles, E. S., Moholdt, G., Mölg, N., Paul, F., Radic´, V., Rastner, P., Raup, B. H., Rich, J., Sharp, M. J., and The Randolph Consortium: The Randolph Glacier Inventory: a globally complete inventory of glaciers, J. Glaciol., 60, 537-552, 2014.
    • Prentice, I. C., Bondeau, A., Cramer, W., Harrison, S. P., Hickler, T., Lucht, W., Sitch, S., Smith, B., and Sykes, M. T.: Dynamic Global Vegetation Modeling: Quantifying Terrestrial Ecosystem Responses to Large-Scale Environmental Change, in: Terrestrial Ecosystems in a Changing World, edited by: Canadell, J. G., Pataki, D. E., and Pitelka, L. F., Springer, Berlin, Germany, 175- 192, 2007.
    • Prigent, C., Papa, F., Aires, F., Rossow, W. B., and Matthews, E.: Global inundation dynamics inferred from multiple satellite observations, 1993-2000, J Geophys. Res., 112, D12107, doi:10.1029/2006JD007847, 2007.
    • Quinn, P., Beven, K., Chevallier, P., and Planchon, O.: The prediction of hillslope flow paths for distributed hydrological modelling using digital terrain models, Hydrol. Process., 5, 59-79, 1991.
    • Quinn, P. F., Beven, K. J., and Lamb, R.: The ln.a= tan / index: how to calculate it and how to use it within the TOPMODEL framework, Hydrol. Process., 9, 161-182, 1995.
    • R Development Core Team: R: A language and environment for statistical computing, version 3.0.2, R Foundation for Statistical Computing, Vienna, available at: http://www.R-project.org (last access: 6 June 2014), 2013.
    • Rice, S., Roy, A., and Rhoads, B.: River Confluences, Tributaries and the Fluvial Network. John Wiley & Sons, Chichester, UK, 2008.
    • Sanderson, M. G., Wiltshire, A. J., and Betts, R. A.: Projected changes in water availability in the United Kingdom, Water Resour. Res., 48, W08512, doi:10.1029/2012WR011881, 2012.
    • Seneviratne, S. I., Lüthi, D., Litschi, M., and Schär, C.: Landatmosphere coupling and climate change in Europe, Nature, 443, 205-209, 2006.
    • Seneviratne, S. I., Corti, T., Davin, E. L., Hirschi, M., Jaeger, E. B., Lehner, I., Orlowsky, B., and Teuling, A.J.: Investigating soil moisture-climate interactions in a changing climate: A review, Earth-Sci. Rev., 99, 125-161, 2010.
    • USGS - US Geological Survey: HYDRO1k Elevation derivative database, US Geological Survey Earth Resources Observation and Science (EROS) Center, Sioux Falls, South Dakota, available at: https://lta.cr.usgs.gov/HYDRO1K (last access: 6 June 2014), 2000.
    • Wainwright, J. and Mulligan, M.: Environmental Modelling Finding Simplicity in Complexity, 2nd Edn., Wiley-Blackwell, Chichester, UK, 2013.
    • Ward, R. C. and Robinson, M.: Principles of Hydrology, 4th Edn., McGraw-Hill, Maidenhead, UK, 2000.
    • Wilson, J. P. and Gallant, J. C.: Terrain analysis Principles and Applications, John Wiley & Sons, New York, 2000.
    • Wolock, D. M.: Simulating the variable-source-area concept of streamflow generation with the watershed model TOPMODEL, United States Geological Survey Water-Resources Investigations Report 93-4124, US Geological Survey, Lawrence, Kansas, USA, 1993.
    • Wolock, D. M. and McCabe, G. J.: Comparison of single and multiple flow direction algorithms for computing topographic parameters in TOPMODEL, Water Resour. Res., 31, 1315-1324, 1995.
    • Wood, E. F., Roundy, J. K., Troy, T. J., van Beek, L. P. H., Bierkens, M. F. P., Blyth, E., de Roo, A., Döll, P., Ek, M., Famiglietti, J., Gochis, D., van de Giesen, N., Houser, P., Jaffé, P. R., Kollet, S., Lehner, B., Lettenmaier, D. P., Peters-Lidard, C., Sivapalan, M., Sheffield, J., Wade, A., and Whitehead, P.: Hyperresolution global land surface modeling: Meeting a grand challenge for monitoring Earth's terrestrial water, Water Resour. Res., 47, W05301, doi:10.1029/2010WR010090, 2011.
    • Wood, E. F., Roundy, J. K., Troy, T. J., van Beek, R., Bierkens, M., Blyth, E., de Roo, A., Döll, P., Ek, M., Famiglietti, J., Gochis, D., van de Giesen, N., Houser, P., Jaffe, P., Kollet, S., Lehner, B., Lettenmaier, D. P., Peters-Lidard, C. D., Sivapalan, M., Sheffield, J., Wade, A. J., and Whitehead, P.: Reply to comment by Keith J. Beven and Hannah L. Cloke on “Hyperresolution global land surface modeling: Meeting a grand challenge for monitoring Earth's terrestrial water”, Water Resour. Res., 48, W01802, doi:10.1029/2011WR011202, 2012.
    • Yang, X., Chapman, G. A., Gray, J. M., and Young, M. A.: Delineating soil landscape facets from digital elevation models using compound topographic index in a geographic information system, Aust. J. Soil Res., 45, 569-576, 2007.
    • Zhao, G., Gao, J., Tian, P., and Tian, K.: Comparison of two different methods for determining flow direction in catchment hydrological modeling, Water Sci. Eng., 2, 1-15, doi:10.1029/2011WR011202, 2009.
    • Zulkafli, Z., Buytaert, W., Onof, C., Lavado, W., and Guyot, J. L.: A critical assessment of the JULES land surface model hydrology for humid tropical environments, Hydrol. Earth Syst. Sci., 17, 1113-1132, doi:10.5194/hess-17-1113-2013, 2013.
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