Hyperresolution information and hyperresolution ignorance in modelling the hydrology of the land surface

详细信息    查看全文

• 作者：Keith Beven (1) (8)
  Hannah Cloke (2)
  Florian Pappenberger (3) (4) (5)
  Rob Lamb (6)
  Neil Hunter (7)
  
  1. Lancaster Environment Centre ; Lancaster University ; Lancaster ; LA1 4YQ ; UK
  8. Department of Earth Sciences ; Uppsala University ; Uppsala ; Sweden
  2. Department of Geography and Environmental Science ; Department of Meteorology ; University of Reading ; Reading ; UK
  3. European Centre for Medium-range Weather Forecasts ; Reading ; UK
  4. School of Geographical Sciences ; University of Bristol ; Bristol ; UK
  5. College of Hydrology and Water Resources ; Hehai University ; Nanjing ; 210098 ; China
  6. JBA Trust ; South Barn ; Broughton Hall ; Skipton ; BD23 3AE ; UK
  7. JBA Consulting ; South Barn ; Broughton Hall ; Skipton ; BD23 3AE ; UK
  
• 关键词：hyperresolution models ; epistemic uncertainties ; models of everywhere ; communicating uncertainty ; flood risk
• 刊名：Science China Earth Sciences
• 出版年：2015
• 出版时间：January 2015
• 年：2015
• 卷：58
• 期：1
• 页码：25-35
• 全文大小：1,540 KB
• 参考文献：1. Albergel C, Calvet J C, Gibelin A L, et al. 2010. Observed and modelled ecosystem respiration and gross primary production of a grassland in southwestern France. Biogeosciences, 7: 1657鈥?668 CrossRef
  2. Alfieri L, Salamon P, Bianchi A, et al. 2013a. Advances in pan-European flood hazard mapping. Hydrol Process, doi: 10.1002/hyp.9947
  3. Alfieri L, Burek P, Dutra E, et al. 2013b. GloFAS-Global ensemble stream-flow forecasting and flood early warning. Hydrol Earth Syst Sci, 17: 1161鈥?175 CrossRef
  4. Antonarakis A S, Richards K S, Brasington J. 2008. Object-based land cover classification using airborne LiDAR. Rem Sens Environ, 112: 2988鈥?998 CrossRef
  5. Baldauf M, Seifert A, F枚rstner J, et al. 2011. Operational convective-scale numerical weather prediction with the COSMO Model: Description and sensitivities. Mon Weather Rev, 139: 3887鈥?905 CrossRef
  6. Balsamo G, Viterbo P, Beljaars A, et al. 2009. A revised hydrology for the ECMWF Model: Verification from field site to terrestrial water storage and impact in the integrated forecast system. J Hydrometeor, 10: 623鈥?43 CrossRef
  7. Barling R D, Moore I D, Grayson R B. 1994. A quasi-dynamic wetness index for characterising the spatial distribution of zones of surface saturation and soil water content. Wat Resour Res, 30: 1029鈥?044 CrossRef
  8. Bashford K E, Beven K J, Young P C. 2002. Observational data and scale dependent parameterisations: explorations using a virtual hydrological reality. Hydrol Process, 16: 293鈥?12 CrossRef
  9. Beven K J. 1981. Comments on鈥?A stochastic-conceptual analysis of rainfall-runoff processes on a hillslope鈥?by R. Allan Freeze. Wat Resour Res, 17: 431鈥?32 CrossRef
  10. Beven K J. 1989. Changing ideas in hydrology: The case of physically based models. J Hydrol, 105: 157鈥?72 CrossRef
  11. Beven K J. 2006. The Holy Grail of scientific hydrology: \(Q_t = H(\underset{\raise0.3em\hbox{\)\smash{\scriptscriptstyle\leftarrow}\(}}{S} \underset{\raise0.3em\hbox{\)\smash{\scriptscriptstyle\leftarrow}\(}}{R} )\) / Aas closure. Hydrol Earth Syst Sci, 10: 609鈥?18 CrossRef
  12. Beven K J. 2010. Preferential flows and travel time distributions: Defining adequate hypothesis tests for hydrological process models. Hydrol Process 24: 1537鈥?547 CrossRef
  13. Beven K J. 2012. Causal models as multiple working hypotheses about environmental processes. CRAS Geosci 344: 77鈥?8 CrossRef
  14. Beven K J, Alcock R. 2012. Modelling everything everywhere: A new approach to decision making for water management under uncertainty. Freshw Biol, 56, doi: 10.1111/j.1365-2427.2011.02592.x
  15. Beven K J, Buytaert W, Smith, L A. 2012a. On virtual observatories and modeled realities (or why discharge must be treated as a virtual variable). Hydrol Process, 26, doi: 10.1002/hyp.9261
  16. Beven K J, Cloke H L. 2012. Comment on 鈥淗yperresolution global land surface modeling: Meeting a grand challenge for monitoring Earth鈥檚 terrestrial water鈥?by Wood et al (2011). Wat Resour Res, 48: W01801, doi: 10.1029/2011WR010982 CrossRef
  17. Beven K J, Germann P F. 1982. Macropores and water flow in soils. Wat Resour Res, 18: 1311鈥?325 CrossRef
  18. Beven K J, Germann P F. 2013. Macropores and water flow in soils revisited. Water Resour Res, 49: 3071鈥?092 CrossRef
  19. Beven K J, Lamb R, Leedal D T, et al. 2014a. Communicating uncertainty in flood risk mapping: A case study. Int J Riv Basin Manag, doi: 10.1080/15715124.2014.917318
  20. Beven K J, Leedal D T, McCarthy S. 2014b. Framework for assessing uncertainty in fluvial flood risk mapping. CIRIA Report C721: 2014, CIRIA: London at http://www.ciria.org/Resources/Free_publications/fluvial_flood_risk_mapping.aspx
  21. Beven K J, Smith P J, Wood A. 2011. On the colour and spin of epistemic error (and what we might do about it). Hydrol Earth Syst Sci, 15: 3123鈥?133 CrossRef
  22. Beven K J, Smith P, Westerberg I, et al. 2012b. Comment on 鈥淧ursuing the method of multiple working hypotheses for hydrological modeling鈥?by P. Clark et al.. Wat Resour Res, 48: W11801, doi: 10.1029/2012WR 012282 CrossRef
  23. Beven K J, Smith P J. 2014. Concepts of information content and likelihood in parameter calibration for hydrological simulation models. ASCE J Hydrol Eng, doi: 10.1061/(ASCE)HE.1943-5584.0000991
  24. Beven K J, Westerberg I. 2011. On red herrings and real herrings: Disinformation and information in hydrological inference. Hydrol Process, 25: 1676鈥?680 CrossRef
  25. Binley A M, Elgy J, Beven K J. 1989a. A physically-based model of heterogeneous hillslopes. I. Runoff production. Wat Resour Res, 25: 1219鈥?226 CrossRef
  26. Binley A M, Beven K J, Elgy J. 1989b. A physically-based model of heterogeneous hill-slopes. II. Effective hydraulic conductivities. Wat Resour Res, 25: 1227鈥?233 CrossRef
  27. Binley A, Beven K J. 2003. Vadose zone model uncertainty as conditioned on geophysical data. Ground Water, 41: 119鈥?27 CrossRef
  28. Blyth E, Gash J, Lloyd A, et al. 2010. Evaluating the JULES land surface model energy fluxes using FLUXNET data. J Hydrometeor, 11: 509鈥?19 CrossRef
  29. Boussetta S, Balsamo G, Beljaars A, et al. 2013. Natural land carbon dioxide exchanges in the ECMWF Integrated Forecasting System: Implementation and offline validation. J Geophys Res, 118: 5923鈥?946
  30. Casas A, Lane S N, Yu D, et al. 2010. A method for parameterising roughness and topographic sub-grid scale effects in hydraulic modelling from LiDAR data. Hydrol Earth Syst Sci, 14: 1567鈥?579 CrossRef
  31. Chrisman B, Zreda M. 2013. Quantifying mesoscale soil moisture with the cosmic-ray rover. Hydrol Earth Syst Sci, 17: 5097鈥?108 CrossRef
  32. Cloke H L, Pappenberger F. 2009. Ensemble flood forecasting: A review. J Hydrol, 375: 613鈥?26 CrossRef
  33. Cloke H L, Jeffers C, Wetterhall F, et al. 2010. Climate impacts on river flow: Projections for the Medway catchment, UK, with UKCP09 and CATCHMOD. Hydrol Process, 24: 3476鈥?489 CrossRef
  34. Cloke H L, Wetterhall F, He Y, et al. 2012. Modelling climate impact on floods with ensemble climate projections. Quart J Roy Meteor Soc, 139: 282鈥?97 CrossRef
  35. Crossley A, Lamb R, Waller S, et al. 2010a. Fast 2D Flood Modelling using GPU Technology. European Geosciences Union, General Assembly, Vienna, Austria, May 2010
  36. Crossley A, Lamb R, Waller S. 2010b. Fast solution of the Shallow Water Equations using GPU technology. Proceedings of the BHS Third International Conference. London: British Hydrological Society
  37. Dee D P, Uppala S M, Simmons A J, et al. 2011. The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Quart J Roy Meteor Soc, 137: 553鈥?97 CrossRef
  38. Dorigo W A, Wagner W, Hohensinn R, et al. 2011. The International Soil Moisture Network: A data hosting facility for global / in situ soil moisture measurements. Hydrol Earth Syst Sci, 15: 1675鈥?698 CrossRef
  39. Drusch M, Viterbo P. 2007. Assimilation of screen-level variables in ECMWF鈥檚 Integrated Forecast System: A study on the impact on the forecast quality and analyzed soil moisture. Mon Weather Rev, 135: 300鈥?14 CrossRef
  40. Ebel B A, Loague K, Montgomery D R, et al. 2008. Physics-based continuous simulation of long-term near-surface hydrologic response for the Coos Bay experimental catchment. Wat Resour Res, 44: W07417, doi: 10.1029/2007WR006442 CrossRef
  41. Emanuel R E, Hazen A G, McGlynn B L, et al. 2013. Vegetation and topographic influences on the connectivity of shallow groundwater between hillslopes and streams. Ecohydrology, 7: 887鈥?95 CrossRef
  42. Entekhabi D, Njoku E G, O鈥橬eill P E, et al. 2010. The soil moisture active passive (SMAP) mission. Proc IEEE, 98: 704鈥?16 CrossRef
  43. Environment A. 2013. Updated Flood Map for Surface Water-National Scale Surface Water Flood Mapping Methodology. Bristol: Environment Agency Horizon House. 54
  44. Faulkner D S. 1999. Flood Estimation Handbook. Volume 2: Rainfall Frequency Estimation. Wallingfor: Institute of Hydrology. 110
  45. Faulkner H, Parker D, Green C, et al. 2007. Developing a translational discourse to communicate uncertainty in flood risk between science and the practitioner. Ambio, 16: 692鈥?03 CrossRef
  46. Feyen L, Caers J. 2006. Quantifying geological uncertainty for flow and transport modeling in multi-modal heterogeneous formations. Adv Wat Resour, 29: 912鈥?29 CrossRef
  47. Franks S, Beven K J. 1997. Estimation of evapotranspiration at the landscape scale: A fuzzy disaggregation approach. Wat Resour Res, 33: 2929鈥?938 CrossRef
  48. Freer J, McDonnell J, Beven K J, et al. 2002. The role of bedrock topography on subsurface stormflow. Wat Resour Res, 38: W01269, doi: 10.1029/2001WR000872 CrossRef
  49. Freeze R A. 1975. A stochastic-conceptual analysis of one-dimensional groundwater flow in nonuniform homogeneous media. Wat Resour Res, 11: 725鈥?41 CrossRef
  50. Freeze R A. 1980. A stochastic-conceptual analysis of rainfall-runoff processes on a hillslope. Wat Resour Res, 16: 391鈥?08 CrossRef
  51. Golding B W. 2009. Long lead time flood warnings: reality or fantasy? Meteor Apps, 16: 3鈥?2 CrossRef
  52. Gudmundsson L, Tallaksen L M, Stahl K, et al. 2012. Comparing large-scale hydrological model simulations to observed runoff percentiles in Europe. J Hydrometeor, 13: 604鈥?20 CrossRef
  53. Guilleminot J, Soize C, Ghanem R G. 2012. Stochastic representation for anisotropic permeability tensor random fields. Int J Numer Analyt Methods Geomech, 36: 1592鈥?608 CrossRef
  54. Haddeland I, Clark D B, Franssen W, et al. 2011. Multimodel estimate of the global terrestrial water balance: Setup and first results. J Hydrometeor, 12: 869鈥?84 CrossRef
  55. Hannah D M, Demuth S, van Lanen H A J, et al. 2011. Large-scale river flow archives: Importance, current status and future needs. Hydrol Process, 25: 1191鈥?200 CrossRef
  56. Henriksen H J, Troldborg L, Hojberg A L, et al. 2008. Assessment of exploitable groundwater resources of Denmark by use of ensemble resource indicators and a numerical groundwater-surface water model. J Hydrol, 348: 224鈥?40 CrossRef
  57. Heppner C S, Loague K, VanderKwaak J E. 2007. Long-term InHM simulations of hydrologic response and sediment transport for the R-5 catchment. Earth Surf Process Landf, 32: 1273鈥?292 CrossRef
  58. Hunter N, Waller S, Balmbra V, et al. 2010. Broad Scale Mapping of Surface Water Flooding鈥擯resent Status and Future Improvements. Proc Environment Agency FCRM10 Conference, 29 June鈥? July 2010. Paper O80
  59. Ines A V, Hansen J W. 2006. Bias correction of daily GCM rainfall for crop simulation studies. Agric Forest Meteor, 138: 44鈥?3 CrossRef
  60. Kauffeldt A, Halldin S, Rodhe A, et al. 2013. Disinformative data in large-scale hydrological modelling. Hydrol Earth Syst Sci, 17: 2845鈥?857 CrossRef
  61. Kollet S J, Maxwell R M, Woodward C S, et al. 2010. Proof of concept of regional scale hydrologic simulations at hydrologic resolution utilizing massively parallel computer resources. Wat Resour Res, 46: W04201, doi: 10.1029/2009WR008730 CrossRef
  62. Lamb R, Crossley A, Waller S. 2009. A fast two-dimensional floodplain inundation model. Proc ICE Water Manag, 162: 363鈥?70 CrossRef
  63. Lane S J. 1998. Hydraulic modelling in hydrology and geomorphology: A review of high resolution approaches. Hydrol Process, 12: 1131鈥?150 CrossRef
  64. Lane S J, Odoni N, Landstr枚m C, et al. 2011. Doing flood risk science differently: An experiment in radical scientific method. Trans Inst Brit Geogr, 36: 15鈥?6 CrossRef
  65. Lawrence D M, Oleson K W, Flanner M G, et al. 2011. Parameterization improvements and functional and structural advances in version 4 of the Community Land Model. J Adv Model Earth Syst, 3, doi: 10.1029/2011MS000045
  66. Leedal D T, Neal J, Beven, K J, et al. 2010. Visualization approaches for communicating real-time flood forecasting level and inundation information. J Flood Risk Manag, 3: 140鈥?50 CrossRef
  67. Leli猫vre P G, Farquharson C G. 2013. Gradient and smoothness regularization operators for geophysical inversion on unstructured meshes. Geophys J Int, 195: 330鈥?41 CrossRef
  68. Loague K. 1990. R-5 revisited: 2. Reevaluation of a quasi-physically based rainfall-runoff model with supplemental information. Wat Resour Res, 26: 973鈥?87 CrossRef
  69. Loague K, Gander G E, VanderKwaak J E, et al. 2000. Simulating hydrologic response for the R-5 catchment: A never ending story. J Floodpl Manag, 1: 57鈥?3
  70. McDonnell J J, Beven, K J. 2014. Debates鈥擳he future of hydrological sciences: A (common) path forward? A call to action aimed at understanding velocities, celerities, and residence time distributions of the headwater hydrograph. Wat Resour Res, 50, doi: 10.1002/2013WR015141.
  71. McMillan H, Freer J, Pappenberger F, et al. 2010. Impacts of uncertain river flow data on rainfall-runoff model calibration and discharge predictions. Hydrol Process, 24: 1270鈥?284
  72. McMillan H, Krueger T, Freer J. 2012. Benchmarking observational uncertainties for hydrology: Rainfall, river discharge and water quality. Hydrol Process, 26: 4078鈥?111 CrossRef
  73. Meerschaert M M, Dogan M, Dam R L, et al. 2013. Hydraulic conductivity fields: Gaussian or not? Wat Resour Res, 49: 4730鈥?737 CrossRef
  74. Michael H A, Li H, Boucher A, et al. 2010. Combining geologic-process models and geostatistics for conditional simulation of 3-D subsurface heterogeneity. Wat Resour Res, 46: W05527 CrossRef
  75. Mitchell S, Freer J, Beven K J. 2009. Multiple sources of predictive uncertainty in modeled estimates of net ecosystem CO₂ exchange. Ecol Model, 220: 3259鈥?270 CrossRef
  76. Mitchell S, Beven K J, Freer J, et al. 2011. Processes influencing model-data mismatch in drought-stressed, fire-disturbed, eddy flux sites. JGR-Biosci, 116, doi: 10.1029/2009JG001146
  77. Mohanty B P. 2013. Soil hydraulic property estimation using remote sensing: A review. Vadose Zone J, 12, doi: 10.2136/vzj2013.06.0100
  78. Musgrave H, Binley A. 2011. Revealing the temporal dynamics of subsurface temperature in a wetland using time-lapse geophysics. J Hydrol, 396: 258鈥?66 CrossRef
  79. Neal J, Keef C, Bates P, et al. 2013. Probabilistic flood risk mapping including spatial dependence. Hydrol Process, 27: 1349鈥?363 CrossRef
  80. Odoni N A, Lane S N. 2010. Knowledge-theoretic models in hydrology. Prog Phys Geog, 34: 151鈥?71 CrossRef
  81. Pacific V J, McGlynn B L, Riveros-Iregui D A, et al. 2011. Landscape structure, groundwater dynamics, and soil water content influence soil respiration across riparian-hillslope transitions in the Tenderfoot Creek Experimental Forest, Montana. Hydrol Process, 25: 811鈥?27 CrossRef
  82. Pappenberger F, Beven K J, Frodsham K, et al. 2007. Grasping the unavoidable subjectivity in calibration of flood inundation models: A vulnerability weighted approach. J Hydrol, 333: 275鈥?87 CrossRef
  83. Pappenberger F, Dutra E, Wetterhall F, et al. 2012. Deriving global flood hazard maps of fluvial floods through a physical model cascade. Hydrol Earth Syst Sci, 16: 4143鈥?156 CrossRef
  84. Pappenberger F, Thielen J, del Medico M. 2010. The impact of weather forecast improvements on large scale hydrology: Analysing a decade of forecasts of the European Flood Alert System. Hydrol Process, 25: 1091鈥?113 CrossRef
  85. Pappenberger F, Stephens E, Thielen J, et al. 2013. Visualizing probabilistic flood forecast information: Expert preferences and perceptions of best practice in uncertainty communication. Hydrol Process, 27: 132鈥?46 CrossRef
  86. Perri M T, Cassiani G, Gervasio I, et al. 2012. A saline tracer test monitored via both surface and cross-borehole electrical resistivity tomography: Comparison of time-lapse results. J Appl Geophys, 79: 6鈥?6 CrossRef
  87. Piani C, Weedon G P, Best M, et al. 2010. Statistical bias correction of global simulated daily precipitation and temperature for the application of hydrological models. J Hydrol, 395: 199鈥?15 CrossRef
  88. Richardson D S, Bidlot J, Ferranti L, et al. 2013. Evaluation of ECMWF forecasts, including 2012鈥?013 upgrades. ECMWF Technical Memorandum 710 November 2013. ECMWF. 55. doi: http://dx.doi.org/10.1175/MWR3309.1
  89. Smith L, Schwartz F W. 1980. Mass transport: 1. A stochastic analysis of macroscopic dispersion. Wat Resour Res, 16: 303鈥?13 CrossRef
  90. Smith P J, Beven K J, Leedal D T, et al. 2014. Testing probabilistic adaptive real-time flood forecasting models. J Flood Risk Manag, 7: 265鈥?79
  91. Smith R E, Hebbert R H B. 1979. A Monte Carlo analysis of the hydrologic effects of spatial variability of infiltration. Wat Resour Res, 15: 419鈥?29 CrossRef
  92. Smith T, Marshall L, McGlynn B, et al. 2013. Using field data to inform and evaluate a new model of catchment hydrologic connectivity. Wat Resour Res, 49: 6834鈥?846 CrossRef
  93. Tian X, Xie Z, Dai A, et al. 2009. A dual-pass variational data assimilation framework for estimating soil moisture profiles from AMSR-E microwave brightness temperature. J Geophys Res, 114: D16102, doi: 10.1029/2008jd011600 CrossRef
  94. Wang H, Jia L, Steffen H, et al. 2013. Increased water storage in North America and Scandinavia from GRACE gravity data. Nature Geosci, 6: 38鈥?2
  95. Weusthoff T, Ament F, Arpagaus M, et al. 2010. Assessing the benefits of convection-permitting models by neighborhood verification: Examples from MAP D-PHASE. Mon Weather Rev, 138: 3418鈥?433 CrossRef
  96. Wetterhall F, Pappenberger F, Alfieri L, et al. 2013. HESS Opinions: Forecaster priorities for improving probabilistic flood forecasts. Hydrol Earth Syst Sci, 17: 4389鈥?399 CrossRef
  97. Whatmore S J, Lane S N, Odoni N A, et al. 2011. Coproducing flood risk knowledge: Redistributing expertise in critical participatory modelling. Environ Plann A, 43: 1617鈥?633 CrossRef
  98. Wilby R L. 2010. Evaluating climate model outputs for hydrological applications. Hydrol Sci J, 55: 1090鈥?093 CrossRef
  99. Wilson K, Goldstein A, Falge E, et al. 2002. Energy balance closure at FLUXNET sites. Agric Forest Meteor, 113: 223鈥?43 CrossRef
  100. Winsemius H C, Van Beek L P H, Jongman B, et al. 2013. A framework for global river flood risk assessments. Hydrol Earth Syst Sci, 17: 1871鈥?892 CrossRef
  101. Wood E F, Roundy J K, Troy T J, et al. 2011. Hyperresolution global land surface modeling: Meeting a grand challenge for monitoring Earth鈥檚 terrestrial water. Wat Resour Res, 47: W05301, doi: 10.1029/2010-WR010090 CrossRef
  102. Zinn B, Harvey C F. 2003. When good statistical models of aquifer heterogeneity go bad: A comparison of flow, dispersion, and mass transfer in connected and multivariate Gaussian hydraulic conductivity fields. Wat Resour Res, 42: 1051, doi: 10.1029/2001WR001146.
  103. Zreda M, Shuttleworth W J, Zeng X, et al. 2012. COSMOS: The COsmic-ray Soil Moisture Observing System. Hydrol Earth Syst Sci, 16: 4079鈥?099 CrossRef
  
• 刊物主题：Earth Sciences, general;
• 出版者：Springer Berlin Heidelberg
• ISSN：1869-1897

文摘

There is a strong drive towards hyperresolution earth system models in order to resolve finer scales of motion in the atmosphere. The problem of obtaining more realistic representation of terrestrial fluxes of heat and water, however, is not just a problem of moving to hyperresolution grid scales. It is much more a question of a lack of knowledge about the parameterisation of processes at whatever grid scale is being used for a wider modelling problem. Hyperresolution grid scales cannot alone solve the problem of this hyperresolution ignorance. This paper discusses these issues in more detail with specific reference to land surface parameterisations and flood inundation models. The importance of making local hyperresolution model predictions available for evaluation by local stakeholders is stressed. It is expected that this will be a major driving force for improving model performance in the future.