WaterWorld: A self-parameterising, physically based model for application in data-poor but problem-rich environments globally

Hydrology Research

Volumn 44, Issue 5, 2013, Pages 748-769

  Mulligan, Mark ^a  

^a KING'S COLLEGE LONDON   (United Kingdom)

Author keywords

Climate change; GIS; Hydrological model; Policy support; Remote sensing

Indexed keywords

ADAPTATION TO CLIMATE CHANGES; HETEROGENEOUS ENVIRONMENTS; HYDROLOGICAL MODELING; LAND-COVER CHANGE; PHYSICALLY BASED MODELING; POLICY SUPPORT; SPATIALLY EXPLICIT; VERY HIGH SPATIAL RESOLUTIONS;

CLIMATE CHANGE; GEOGRAPHIC INFORMATION SYSTEMS; HYDROLOGY; REMOTE SENSING;

WATER RESOURCES;

DATA SET; ENVIRONMENTAL POLICY; GIS; HYDROLOGICAL MODELING; LAND COVER; NUMERICAL MODEL; PARAMETERIZATION; REMOTE SENSING; SPATIAL RESOLUTION; TEMPORAL ANALYSIS; WATER BUDGET; WATER RESOURCE;

EID: 84890043577     PISSN: 00291277     EISSN: None     Source Type: Journal    
DOI: 10.2166/nh.2012.217     Document Type: Article

References (54)

1. Alemaw, B. F. & Chaoka, T. R. 2003 A continental scalewaterbalance model: a GIS-approach for Southern Africa. Physics and Chemistry of the Earth 28, 957-966.
2. Arazi, A., Sharon, D., Khain, A., Huss, A. & Mahrer, Y. 1996 The windfield and rainfall distribution induced within a small valley: field observations and 2-D numerical modelling. Boundary-Layer Meteorology 83, 349-374.
3. BADC 2004 Global Mean Sea-Level Pressure dataset. (Available online at http://badc.nerc.ac.uk/browse/badc/ukmo-gmslp, accessed May 2006).
4. Bastiaanssen, W. G. M. & Chandrapala, L. 2003 Water balance variability across Sri Lanka for assessing agricultural and environmental water use. Agricultural Water Management 58, 171-192.
5. Bruijnzeel, L. A., Mulligan, M. & Scatena, F. S. 2011 Hydrometeorology of tropical montane cloud forests: emerging patterns. Hydrological Processes 25, 465-498.
6. Buytaert, W., Celleri, R. & Timbe, L. 2009 Predicting climate change impacts on water resources in the tropical Andes: the effects of GCM uncertainty. Geophysical Research Letters 36, 1-11.
7. CIESIN, IFPRI, The World Bank & CIAT 2004 Center for International Earth Science Information Network (CIESIN), olumbia University, International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional de Agricultura Tropical (CIAT). Global Rural-Urban Mapping Project (GRUMP), Alpha Version: Urban Extents. Socioeconomic Data and Applications Center (SEDAC), Columbia University, Palisades, NY. (Available online at http://sedac.ciesin. columbia.edu/gpw/accessed July 2008).
8. Cereceda, P., Schemenauer, R. S. & Suit, M. 1992 Alternative water supply for Chilean Coastal Desert Villages. Water Resources Development 8, 53-59.
9. Chaponnière, A., Boulet, G, Chehbouni, A. & Aresmouk, M. 2008 Understanding hydrological processes with scarce data in a mountain environment. Hydrological Processes 22, 1908-1921.
10. Choi, W., Kim, S. J., Rasmussen, P. F. & Moor, A. R. 2009 Use of the North American Regional Reanalysis for Hydrological Modelling in Manitoba. Canadian Water Resources Journal 34, 17-36.
11. Collischonn, B., Collischonn, W. & Tucci, C. E. M. 2008 Daily hydrological modeling in the Amazon basin using TRMM rainfall estimates. Journal of Hydrology 360, 207-216.
12. Farr, T. G. & Kobrick, M. 2000 Shuttle Radar Topography Mission produces a wealth of data. Eos, Transactions of the American Geophysical Union 81, 583-585.
13. Gosling, S. N. & Arnell, N. W. 2010 Simulating current global river runoff with a global hydrological model: model revisions, validation, and sensitivity analysis. Hydrological Processes 25, 1129-1145.
14. GRDC 2012 Global Runoff Data Centre Station Catalogue. (Available online at http://www.bafg.de/cln-030/nn-294146/GRDC/EN/02-Services/01-RiverDischarge/ Catalogues/catalogues-node.html?-nnn=true, accessed 9 January 2012).
15. Hansen, M., DeFries, R, Townshend, J. R., Carroll, M., Dimiceli, C. & Sohlberg, R 2006 Vegetation Continuous Fields MOD44B, 2001 Percent Tree Cover, Collection 4. University of Maryland, College Park, Maryland. (Available online at http://www.glcf umd.edu/data/vcf/accessed December 2006).
16. Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G & Jarvis, A. 2005 Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25, 1965-1978.
17. IWMI 2011 International Water Management. In statute The Krishna Basin India. (Available online at http://www.iwmi. cgiar.org/Research-Impacts/ Benchmark-Basins/krishna.aspx accessed December 2011).
18. Jayakrishnan, R, Srinivasan, R., Santhi, C. & Arnold, J. G. 2005 Advances in the application of the SWAT model for water resources management. Hydrological Processes 19, 749-762.
19. Jarvis, A., Reuter, H. I., Nelson, A. & Guevara, E. 2008 Hole-filled SRTM for the Globe Version 4. (Available online http://srtm. csi.cgiar.org, accessed July 2006).
20. Lakshmi, V. 2004 The role of satellite remote sensing in the prediction of ungauged basins. Hydrological Processes 18, 1029-1034.
21. LandScan TM Global Population Database 2007 Oak Ridge National Laboratory, Oak Ridge, TN. (Available online at http://www.ornl.gov/landscan/, accessed August 2007).
22. Lehner, B., Verdin, K. & Jarvis, A. 2008 New global hydrography derived from spaceborne elevation data. Eos, Transactions of the AGU 89, 93-94.
23. Liebe, J. R, Van De Giesen, N., Andreini, M., Walter, M. T & Steenhuis, T. S. 2009 Determining watershed response in data poor environments with remotely sensed small reservoirs as runoff gauges. Water Resources Research 45, 1-12.
24. Mu, Q., Zhao, M. & Running, S. W. 2011 Improvements to a MODIS global terrestrial evapotranspiration algorithm. Remote Sensing of Environment 115, 1781-1800.
25. Mulligan, M. 1998 Modelling the geomorphological impact of climatic variability and extreme events in a semi-arid environment. Geomorphology 24, 59-89.
26. Mulligan, M. 2006a Global Gridded 1 km TRMM Rainfall Climatology and Derivatives. Version 1.0. (Available online at http://www.ambiotek.com/ 1kmrainfall).
27. Mulligan, M. 2006b 3 Hourly Near Global Point based Rainfall Time Series (1998-2007) Based on the TRMM 3B42 Product. Version 1.0. (Available online at http://www.ambiotek.com/trmmtimeseries).
28. Mulligan, M. 2006c MODIS MOD35 Pan-tropical Cloud Climatology. Version 1. (Available online at http://www.ambiotek.com/clouds).
29. Mulligan, M. 2011a SimTerra: A Consistent Global Gridded Database of Environmental Properties for Spatial Modelling [Mean Actual Evapotranspiration 2000-2010]. (Available online at http://www.policysupport.org/simterra).
30. Mulligan, M. 2011b SimTerra: A Consistent Global Gridded Database of Environmental Properties for Spatial Modelling [SRTM derived Drainage Direction]. (Available online at http://www.policysupport.org/simterra).
31. Mulligan, M. & Burke, S. M. 2005 FIESTA: Cloud water interception for the Enhancement of Streamflow in Tropical Areas. Report to UK DfID, 174 pp. (Available online at http://www.ambiotek.com/fiesta).
32. Mulligan, M., Rubiano, J., Hyman, G, White, D., Garcia, J., Saravia, M., Leon, J. G., Selvaraj, J. J., Gutierrez, T & Saenz-Cruz, L. 2010a The Andes 'basin': biophysical and developmental diversity in a climate of change. Water International 35, 472-492.
33. Mulligan, M., Rubiano, J. & Rincon-Romero, M. 2010b Hydrology and land cover change in tropical montane environments: the impact of pattern on process. In: Tropical Montane Cloud Forests: Science for Conservation and Management (L. A. Bruijnzeel, F. N. Scatena & L. S. Hamilton, eds). Cambridge University Press, Cambridge, pp. 516-525.
34. Mulligan, M., Saenz-Cruz, L., Van Soesbergen, A., Smith, V. T & Zurita, L. 2009 Global Dams Database and Geowiki. Version 1. (Available online at http://www.ambiotek.com/dams).
35. Mulligan, M., Saenz Cruz, L. L., Pena-Arancibia, J., Pandey, B., Mahé, G & Fisher, M. 2011c Water availability and use across the Challenge Program on Water and Food (CPWF) basins. Water International 36, 17-41.
36. Ndomba, P., Mtalo, F. & Killingtveit, A. 2008 SWAT model application in a data scarce tropical complex catchment in Tanzania. Physics and Chemistry of the Earth 33, 1-19.
37. New, M., Lister, D., Hulme, M. & Makin, I. 2003 A high-resolution data set of surface climate over global land areas. Climate Research 21, 1-25.
38. Oxley, T, Winder, N., McIntosh, B. S., Mulligan, M. & Engelen, G. 2004 Integrated catchment modelling & decision support tools: a mediterranean example. Environmental Modelling and Software 19, 999-1010.
39. Penman, H. L. 1948 Natural evaporation from open water, bare soil and grass. Proceedings of the Royal Society London A 194, 120-145.
40. Ramankutty, N., Evan, A. T, Monfreda, C. & Foley, J. A. 2008 Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000. Global Biogeochemical Cycles 22, 1-19.
41. Ramillien, G., Frappart, F., Cazenave, A. & Guentner, A. 2005 Change in land water storage from 2 years of GRACE satellite data. Earth and Planetary Science Letters 235, 283-301.
42. Ruel, J.-C, Mitchell, S. J. & Dornier, M. 2002 A GIS based approach to map wind exposure for Windthrow Hazard Rating. Northern Journal of Applied Forestry 19, 183-187.
43. Schuol, J. & Abbaspour, K. C. 2007 Using monthly weather statistics to generate daily data in a SWAT model application to West Africa. Ecological Modelling 201, 301-311.
44. Shrestha, R., Takara, K., Tachikawa, Y. & Jha, R. N. 2004 Water resources assessment in a poorly gauged mountainous catchment using a geographical information system and remote sensing. Hydrological Processes 18, 3061-3079.
45. Sivapalan, M. 2003 Prediction in ungauged basins: a grand challenge for theoretical hydrology. Hydrological Processes 17, 3163-3170.
46. Sperna Weiland, F. C, Van Beek, L. P. H., Kwadijk, J. C. J. & Bierkens, M. F. P. 2010 The ability of a GCM-forced hydrological model to reproduce global discharge variability. Hydrology and Earth System Sciences 14, 1595-1621.
47. Tarnavsky, E., Mulligan, M. & Husak, G. 2012 Spatial disaggregation and intensity correction of TRMM-based rainfall time series for hydrological applications in dryland catchments. Hydrological Sciences Journal 57, 248-264.
48. UNESCO-WWAP 2003 United Nations Educational Scientific and Cultural Organization World Water Assessment Programme Water for People-Water for Life. The United Nations World Water Development Report, Berghahn Books, Oxford.
49. Van Delden, H. P. & Engelen, G 2007 Integration of multi-scale dynamic spatial models of socio-economic and physical processes for river basin management. Environmental Modelling & Software 22, 223-238.
50. Van Delden, H., Ouessar, M., Sghaier, M., Ouled Belgacem, A., Mulligan, M., Luja, P., De Jonga, J., Fetoui, M. & Ben Zaied, M. 2008 User driven application and adaptation of an existing Policy Support System to a new region. iEMSs 2008. International Congress on Environmental Modelling and Software Integrating Sciences and Information Technology for Environmental Assessment and Decision Making, July 7-10, Barcelona, Catalonia, Spain.
51. Wagener, T 2004 Predictions in ungauged basins as a catalyst for multidisciplinary hydrology. Eos 85, 44.
52. Walter, M. T, Brooks, E. S., McCool, D. K., King, L. G, Molnau, M. & Boll, J. 2005 Process-based snowmelt modeling: does it require more input data than temperature-index modeling? Journal of Hydrology 300, 65-75.
53. Ward, E., Buytaert, W., Peaver, L. & Wheater, H. 2011 Evaluation of precipitation products over complex mountainous terrain: a water resources perspective. Advances in Water Resources 34, 1222-1231.
54. World Bank 2004 World Bank, World Development Indicators. The World Bank, Washington, DC.