On digital soil assessment with models and the Pedometrics agenda

Geoderma

Volumn 171-172, Issue , 2012, Pages 3-15

  Finke, Peter A ^a  

^a GHENT UNIVERSITY   (Belgium)

Author keywords

Calibration; Digital soil assessment; Digital soil mapping; Ensemble modelling; Pedometrics; Process modelling

Indexed keywords

DIGITAL SOIL ASSESSMENT; DIGITAL SOIL MAPPING; ENSEMBLE MODELLING; PEDOMETRICS; PROCESS MODELLING;

AGRICULTURE; ARTIFICIAL INTELLIGENCE; CALIBRATION; DECISION SUPPORT SYSTEMS; MAPPING; PROFITABILITY; RATING; SOILS;

GEOLOGIC MODELS;

ASSESSMENT METHOD; CALIBRATION; DECISION SUPPORT SYSTEM; IDENTIFICATION METHOD; MAPPING METHOD; NUMERICAL MODEL; PEDOGENESIS; SOIL SCIENCE; SOIL TYPE; STAKEHOLDER; UNCERTAINTY ANALYSIS;

EID: 84857086642     PISSN: 00167061     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.geoderma.2011.01.001     Document Type: Article

References (124)

1. Ajami N.K., Gu C.H. Complexity in microbial metabolic processes in soil nitrogen modeling: a case for model averaging. Stochastic Environmental Research and Risk Assessment 2010, 24(6):831-844.
2. Alcamo J., van Vuuren D., Cramer W. Chapter 9: Changes in Ecosystem Services and Their Drivers Across the Scenarios. Millennium Ecosystem Assessment Series 2005, vol. 2. 596pp.
3. Babak O., Deutsch C.V. Uncertainty as the overlap of alternate conditional distributions. Computational Geosciences 2008, 12:503-512.
4. Batjes N.H. Documentation to ISRIC-WISE global data set of derived soil properties on a 0.5 by 0.5° grid. Report 96/05 1996, International Soil Reference and Information Centre, Wageningen.
5. Bertino L., Eversen G., Wackernagel H. Sequential data assimilation techniques in oceanography. International Statistical review 2003, 71(2):223-241.
6. Bierkens M.F.P., Finke P.A., de Willigen P. Upscaling and Downscaling Methods for Environmental Research 2000, Kluwer Academic Publishers, Dordrecht, ISBN 0-7923-6399-6.
7. Bishop T.F.A., McBratney A.B., Laslett G.M. Modelling soil attribute depth functions with equal-area quadratic smoothing splines. Geoderma 1999, 91(1-2):27.
8. Bormann H. Evaluation of hydrological models for scenario analyses: signal-to-noise-ratio between scenario effects and model uncertainty. Advances in Geosciences 2005, 5:43-48.
9. Bouma J. Soils are back on the global agenda: now what?. Geoderma 2009, 150:224-225.
10. Cain J. Planning improvements in natural resources management: guidelines for using Bayesian networks to support the planning and management of development programmes in the water sector and beyond. Centre for Ecology and Hydrology, Crowmarsh Gifford, Wallingford, Oxon: UK 2001.
11. Carré F., McBratney A.B., Minasny B. Estimation and potential improvement of the quality of legacy soil samples for digital soil mapping. Geoderma 2007, 141:1-14.
12. Carré F., McBratney A.B., Mayr T., Montanarella L. Digital soil assessments: beyond DSM. Geoderma 2007, 142:69-79.
13. Dann R.L., Close M.E., Lee R., Pang L. Impact of data quality and model complexity on prediction of pesticide leaching. J Environ Qual 2006, 35:628-640.
14. De Gruijter J.J., Brus D.J., Bierkens M.F.P., Knotters M. Sampling for Natural Resource Monitoring 2006, Springer-Verlag, Berlin, Heidelberg.
15. De Lannoy G.J.M., Houser P.R., Pauwels V.R.N., Verhoest N.E.C. Assessment of model uncertainty for soil moisture through ensemble verification. Journal of Geophysical Research-Atmospheres 2006, 111.
16. De Vries W., Kros J., Van der Salm C., Groenenberg J.E., Reinds G.J. The use of upscaling procedures in the application of soil acidification models at different spatial scales. Nutrient Cycling in Agroecosystems 1998, 50:223-236.
17. Dobos E., Carré F., Hengl T., Reuter H.I., Tóth G. Digital Soil Mapping as a Support to Production of Functional Maps. EUR 22123 EN 2006, Office for Official Publications of the European Communities, Luxemburg, 68pp.
18. Doherty J. PEST: Model Independent Parameter Estimation. Fifth edition of user manual, Watermark Numerical Computing, Brisbane, Australia 2004.
19. Eckelmann W., Baritz R., Bialousz S., Bielek P., Carre F., Houšková B., Jones R.J.A., Kibblewhite M.G., Kozak J., Le Bas C., Tóth G., Tóth T., Várallyay G., Yli Halla M., Zupan M. Common Criteria for Risk Area Identification according to Soil Threats. European Soil Bureau Research Report No.20, EUR 22185 EN 2006, Office for Official Publications of the European Communities, Luxembourg, 94pp.
20. Ehlschlaeger C.R., Shortridge A.M., Goodchild M.F. Visualizing spatial data uncertainty using animation. Computers and Geosciences 1997, 23(4):387-395.
21. EU, 2006a. Thematic Strategy for Soil Protection. COM (2006) 231 final.
22. EU, 2006b. Proposal for a Directive of the European parliament and of the council establishing a framework for the protection of soil and amending Directive 2004/35/EC. COM (2006) 232 final.
23. EU, 2006c. Impact assessment of the thematic strategy on soil protection. COM(2006) 231 final/SEC(2006) 1165.
24. Evensen G. Sequential data assimilation with a non-linear quasi-geostrophic model using Monte-Carlo methods to forecast error statistics. Journal of Geophysical Research-Oceans 1994, 99(C5):17905-17924.
25. Finke P.A. Quality Assessment of Digital Soil Maps: Producers and Users Perspectives. Developments in Soil Science 31 2007, 523-541. Elsevier, Amsterdam. P. Lagacherie, A. McBratney, M. Voltz (Eds.).
26. Finke P.A. Modelling soil formation along a loess toposequence. World Congress Soil Science Proceedings 2010, Brisbane 2010.
27. Finke P.A., Bosma W.J.P. Obtaining basic simulation data for a heterogeneous field with stratified marine soils. Hydrological Processes 1993, 7:63-75.
28. Finke P.A., Hutson J.L. Modelling soil genesis in calcareous löss. Geoderma 2008, 145:462-479.
29. Finke P.A., Wösten J.H.M., Jansen M.J.W. Effects of uncertainty in major input variables on simulated functional soil behaviour. Hydrological Processes 1996, 10:661-669.
30. Finke P.A., Meylemans E., Van de Wauw J. Mapping the possible occurrence of archaeological sites by Bayesian inference. Journal of Archaeological Science 2008, 35:2786-2796.
31. Fujino J. Development of AIM-Trend Model as a Communication Tool to Enhance Discussions about Prospect of Energy and Environment in each Asia-Pacific Country. Yokohama: IFAC Workshop on Modelling and Control in Environmental Issues, 2001 2001, 109-114.
32. Goovaerts P. Geostatistics for Natural Resources Evaluation 1997, Oxford University Press, Oxford, 483pp.
33. Grimm R., Behrens T. Uncertainty analysis of sample locations within digital soil mapping approaches. Geoderma 2010, 155(3-4):154-163.
34. Grunwald S. Multi-criteria characterization of recent digital soil mapping and modeling approaches. Geoderma 2009, 152:195-207.
35. Guber A.K., Pachepsky Y.A., van Genuchten M.Th., Simunek J., Jacques D., Nemes A., Nicholson T.J., Cady R.E. Multimodel Simulation of Water Flow in a Field Soil Using Pedotransfer Functions. Vadose Zone Journal 2009, 8:1-10.
36. Hack-ten Broeke M.J.D., Hegmans J.H.B.M. Use of soil physical characteristics from laboratory measurements or standard series for modelling unsaturated water flow. Agricultural Water Management 1996, 29(2):201-213.
37. Hartemink A.E., McBratney A.B. A soil science renaissance. Geoderma 2008, 148:123-129.
38. Hartemink A.E., McBratney A.B., de Lourdes Mendonça Santos M. Digital Soil Mapping with Limited Data 2008, Springer, Netherlands.
39. Hassan R., Scholes R., Ash N. Ecosystems and Human Well-Being: Current State and Trends Findings of the Condition and Trends Working Group 2005, Island Press, 948pp.
40. Hegerl G.C., Zwiers F.W., Braconnot P., Gillett N.P., Luo Y., Marengo Orsini J.A., Nicholls N., Penner J.E., Stott P.A. Understanding and Attributing Climate Change. Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change 2007, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. S. Solomon, D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor, H.L. Miller (Eds.).
41. Hengl T. A Practical Guide to Geostatistical Mapping of Environmental Variables. EUR 22904 EN Scientific and Technical Research series 2007, Office for Official Publications of the European Communities, Luxemburg, 143pp.
42. Hengl T., Heuvelink G.M.B., Stein A. A generic framework for spatial prediction of soil variables based on regression-kriging. Geoderma 2004, 122(1-2):75-93.
43. Hengl T., Walvoort D.J.J., Brown A., Rossiter D.G. A double continuous approach to visualization and analysis of categorical maps. International Journal of Geographical Information Science 2004, 18(2):183-202.
44. Heuvelink G.B.M. Error Propagation in Environmental Modelling with GIS 1998, Taylor & Francis, London.
45. Heuvelink G.B.M. Accuracy Assessment. EUR 22123 EN 2007, Office for Official Publications of the European Communities, Luxemburg, 68pp. E. Dobos, F. Carré, T. Hengl, H.I. Reuter, G. Tóth (Eds.).
46. Heuvelink G.B.M., Brown J.D. Towards a Soil Information System for Uncertain Soil Data. Developments in Soil Science 31 2007, 97106. Elsevier, Amsterdam. P. Lagacherie, A. McBratney, M. Voltz (Eds.).
47. Heuvelink G.B.M., Webster R. Modelling soil variation: past, present, and future. Geoderma 2001, 100(3-4):269-301.
48. Heuvelink G.B.M., Brown J.D., van Loon E.E. A probabilistic framework for representing and simulating uncertain environmental variables. International Journal of Geographical Information Science 2007, 21(5):497-513.
49. Hoosbeek M.R., Bryant R. Towards the modelling of pedogenesis - a review. Geoderma 1992, 55:183-210.
50. Hopkins J.C., Leipold R.J. On the dangers of adjusting the parameter valuies of mechanism-based mathematical models. Journal of Theoretical Biology 1996, 183:417-427.
51. IMAGE team The IMAGE2.2 Implementation of the SRES Scenarios. RIVM CD-ROM publication 481508018 2001, National Institute for Public Health and the Environment, Bilthoven.
52. IMAGE team The IMAGE2.2 Implementation of the SRES Scenarios: Climate Change Scenarios Resulting from Runs with Several GCMs. RIVM CD-ROM Publication 481508019 2001, National Institute for Public Health and the Environment, Bilthoven.
53. IPCC Climate Change 2001: The Scientific Basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change 2001, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 881pp. J.T. Houghton, Y. Ding, D.J. Griggs, M. Noguer, P.J. van der Linden, X. Dai, K. Maskell, C.A. Johnson (Eds.).
54. Irvine K., Mills P., Bruen M., Walley W., Hartnett M., Black A., Tynan S., Duck R., Bragg O., Rowen J., Wilson J., Johnston P., O'Toole C. Water Framework Directive. Environmental Protection Agency 2005, Johnstown Castle, Co., Wexford, Ireland.
55. Jansen M.W.J. Prediction error through modelling concepts and uncertainty from basic data. Nutrient Cycling in Agroecosystems 1998, 50:247-253.
56. Jones J.W., Koo J., Naab J.B., Bostick W.M., Traore S., Graham W.D. Integrating stochastic models and in situ sampling for monitoring soil carbon sequestration. Agricultural systems 2007, 94:52-62.
57. Kempen B., Brus D.J., Heuvelink G.B.M., Stoorvogel J.J. Updating the 1:50, 000 Dutch soil map using legacy soil data: a multinominal logiostic regression approach. Geoderma 2009, 151:311-326.
58. Molecular Modelling in Heavy Hydrocarbon Conversions 2006, CRC/Taylor & Francis, 237pp. M.T. Klein, G. Hou, R.J. Bertolacini, L.J. Broadbelt, A. Kumar (Eds.).
59. Kros J., Pebesma E.J., Reinds G.J., Finke P.A. Uncertainty in modelling soil acidification at the European scale, a case study. Journal of Environmental Quality 1999, 28:366-377.
60. Kros J., Mol-Dijkstra J.P., Pebesma E.J. Assessment of the prediction error in a large-scale application of a dynamic soil acidification model. Stoch. Env. Res Risk Assessm 2002, 16:279-306.
61. Lagacherie P., McBratney A.B. Spatial Information Systems and Spatial Soil Inference Systems: Perspectives for Digital Soil Mapping. 2006 Digital Soil Mapping: An Introductory Perspective. Developments in Soil Science 31 2007, 523-541. Elsevier, Amsterdam. P. Lagacherie, A. McBratney, M. Voltz (Eds.).
62. Leon A., Gonzalez R.L. Predicting soil organic carbon percentage from loss-on-ignition using Bayesian Model Averaging. Australian Journal of Soil Research 2009, 47(8):763-769.
63. Léon-Rojas J.-M., Masero V., Morales M. On the Fuzzy Bayesian Inference of Population Annoyance Level Caused by Noise Exposure. Proceedings of the 2003 ACM symposium on Applied Computing 2003, 227-234. G.B. Lamont, H. Haddad, G.A. Papadopoulos, B. Panda (Eds.).
64. Leopold U., Heuvelink G.B.M., Tiktak A., Finke P.A., Schoumans O. Accounting for Change of Support in Spatial Accuracy Assessment of Modelled Soil Mineral Phosphorous Concentration. Geoderma 2006, 130:368-386.
65. Leroy S.S. Detecting climate signals: some Bayesian aspects. Jornal of Climate 1997, 11:640-641.
66. Loague K.M., Green R.E. Statistical and graphical methods for evaluating solute transport models. Journal of Contaminant Hydrology 1991, 7:51-73.
67. Marker, M., Florke, M., Vassolo, S. and Alcamo, J.G.P., 2003. Preliminary assessment of IPCC-SRES scenarios on future water resources using the WaterGAP 2 model. MODSIM 2003: international congress on modelling and simulation, vols 1-4 - vol 1: natural systems, pt 1; vol 2: natural systems, pt 2; vol 3: socio-economic systems; vol 4: general systems. P.440-445.
68. Matthews E., Payne R., Rohweder M., Murray S. Pilot analysis of global ecosystems. Forest Ecosystems 2000, World Resources Insititute, ISBN: 1-56793-459-3.
69. Mayr T.R., Palmer R.C., Cooke H.J. Digital Soil Mapping Using Legacy Data in the Eden Valley, UK. Digital Soil Mapping With Limited Data 2008, Springer, Netherlands. A.E. Hartemink, A.B. McBratney, M. de Lourdes Mendonça Santos (Eds.).
70. McBratney, A.B., 1986. Introduction to pedometrics: a course of lectures. CSIRO Australia, Division of Soils Technical Memorandum 53/1986, Private Bag 2, Glen Osmond, S.A. 5064.
71. McBratney A.B., Minasny B., Cattle S.R., Vervoort R.W. From pedotransfer functions to soil inference systems. Geoderma 2002, 109:41-73.
72. McBratney A.B., Mendonça Santos M.L., Minasny B. On digital soil mapping. Geoderma 2003, 117:3-52.
73. McKenzie N.J., Gallant J.C. Digital Soil Mapping with Improved Environmental Predictors and Models of Pedogenesis. Developments in Soil Science 31 2007, 327-349. Elsevier, Amsterdam. P. Lagacherie, A. McBratney, M. Voltz (Eds.).
74. McNeill J.M., MacEwan R.J., Crawford D. Using GIS and a land use impact model to assess risk of soil erosion in West Gippsland. Applied GIS 2006, 2(3). 10.2104/ag060019.
75. Meehl G.A., Stocker T.F., Collins W.D., Friedlingstein P., Gaye A.T., Gregory J.M., Kitoh A., Knutti R., Murphy J.M., Noda A., Raper S.C.B., Watterson I.G., Weaver A.J., Zhao Z.-C. Global Climate Projections. In: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change 2007, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. S. Solomon, D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor, H.L. Miller (Eds.).
76. Min S.-K., Hense A. A Bayesian assessment of climate change using multimodel ensembles. Part II: regional and seasonal mean surface temperatures. Journal of Climate 2007, 20:2769-2790.
77. Minasny B., McBratney A.B. A rudimentary mechanistic model for soil production and landscape development. Geoderma 1999, 90:3-21.
78. Minasny B., McBratney A.B. A rudimentary mechanistic model for soil production and landscape development II. A two-dimensional model incorporating chemical weathering. Geoderma 2001, 103:161-179.
79. Minasny B., McBratney A.B. Mechanistic soil-landscape modelling as an approach to developing pedogenetic classifications. Geoderma 2006, 133:138-149.
80. Moradkhani H., Sooroshian S., Gupta H.V., Houser P.R. Dual-state parameter estimation of hydrological models using ensemble Kalman filter. Advances in Water Research 2005, 28:135-147.
81. Mora-Vallejo A., Claessens L., Stoorvogel J.J., Heuvelink G.B.M. Small scale digital soil mapping in Southeastern Kenya. Catena 2008, 76:44-53.
82. Moyeed R.A., Papritz A. An empirical comparison of kriging methods for nonlinear spatial point prediction. Mathematical Geology 2002, 34:365-386.
83. Murphy J.M., Sexton D.M.H., Barnett D.N., Jones G.S., Webb M.J., Collins M., Stainforth D.A. Quantification of modelling uncertainties in a large ensemble of climate change simulations. Nature 2004, 430:768-772.
84. Myers, D.B., 2008. Methods for high-resolution soil-landscape modelling in midwest upland landscapes. PhD-thesis, University of Missouri, U.S.A.
85. Oldeman L.R., Hakkeling R.T.A., Sombroek W.G. World Map of the Status of Human Induced Soil Degradation - An Explanatory Note (GLASOD) 1991, ISRIC/UNEP, Wageningen/Nairobi. 2nd revised ed.
86. Pachepsky Y., Guber A., Jacques D., Simunek J., Van Genuchten M.T., Nicholson T., Cady R. Information content and complexity of simulated soil water fluxes. Geoderma 2006, 134:253-266.
87. Parton W.J., Schimel D.S., Cole C.V., Ojima D.S. Analysis of factors controlling soil organic matter levels in Great Plains grasslands. Soil Science Society of America Journal 1987, 51:1173-1179.
88. Pearson K. Contributions to the mathematical theory of evolution. II. Skew variation in homogeneous material. Philosophical Transactions of the Royal Society of London. A 1895, 186:186-343.
89. Randall D.A., Wood R.A., Bony S., Colman R., Fichefet T., Fyfe J., Kattsov V., Pitman A., Shukla J., Srinivasan J., Stouffer R.J., Sumi A., Taylor K.E. Climate Models and Their Evaluation. Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change 2007, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. S. Solomon, D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor, H.L. Miller (Eds.).
90. Reible D., Mohanty S. A levy flight-random walk model for bioturbation. Environmental Toxicology and Chemistry 2002, 21(4):875-881.
91. Reinds G.J., Van Oijen M., Heuvelink G.B.M., Kros J. Bayesian calibration of the VSD soil acidification model using European forest monitoring data. Geoderma 2008, 146:475-488.
92. RIVM A General Strategy for Integrated Environmental Assessment at the European Environment Agency 1995, RIVM, Bilthoven.
93. Robertson A. Experimental design in the evaluation of genetic parameters. Biometrics 1959, 219-226.
94. Samouëlian A., Cornu S. Modelling the formation and evolution of soils, towards an initial synthesis. Geoderma 2008, 145(3-4):401-409.
95. Sanchez P.A., Ahamed S., Carré F., Hartemink A.E., Hempel J., Huising J., Lagacherie P., McBratney A.B., McKenzie N.J., de Lourdes Mendonça-Santos M., Minasny B., Montanarella L., Okoth P., Palm C.A., Sachs J.D., Shepherd K.D., Vågen T.G., Vanlauwe B., Walsh M.G., Winowiecki L.A., Zhang G.L. Digital soil map of the world. Science 2009, 325(5941):680-681.
96. Sauer D., Schulli-Maurer I., Sperstad R., Sorensen R., Stahr K. Podzol development with time in sandy beach deposits in southern Norway. Journal of Plant Nutrition and Soil Science - Zeitschrift fur Pflanzenernahrung und Bodenkunde 2008, 171(4):483-497.
97. Schaetzl R.J., Schwenner C. An application of the Runge "Energy Model" of soil development in Michigan's upper peninsula. Soil Science 2006, 171(2):152-166.
98. Schils R., Kuikman P., Liski J., van Oijen M., Smith P., Webb J., Alm J., Somogyi Z., van den Akker J., Billett M., Emmett B., Evans C., Lindner M., Palosuo T., Bellamy P., Alm J., Jandl R., Hiederer R. Review of Existing Information on the Interrelations between Soil and Climate Change (CLIMSOIL) 2008, 208pp.
99. Schimmack W., Feria Marquez F. Migration of fallout radiocaesium in a grassland soil from 1986 to 2001: Part II: evaluation of the activity-depth profiles by transport models. Science of the Total Environment 2006, 368(2-3):863-874.
100. Schulp C.J.E., Nabuurs G., Verburg P. Future carbon sequestration in Europe - effects of land use changes. Agriculture, ecosystems and environment 2008, 127:251-264.
101. Selle B., Lischeld G., Huwe B. Effective modelling of percolation at the landscape scale using data-based approaches. Computers & Geosciences 2008, 34(6):699-713.
102. Shibab K. Modelling groundwater quality with Bayesian techniques. Proceedings of trhe 2005 5th Int. Conf. on Intelligent Systems Design and Applications (ISDA'05) 2005.
103. Smith L.A. What might we learn from climate forecasts?. Proc. Natl. Acad. Sci. U.S.A. 2002, 99:2487-2492.
104. Smith C.S., Howes A.L., Price B., McAlpine C.A. Using a Bayesian belief network to predict suitable habitat of an endangered mammal - the Julia Creek dunnart (Sminthopsis douglasi). Biological Conservation 2007, 139(3-4):333-347.
105. Solomon S., Qin D., Manning M., Alley R.B., Berntsen T., Bindoff N.L., Chen Z., Chidthaisong A., Gregory J.M., Hegerl G.C., Heimann M., Hewitson B., Hoskins B.J., Joos F., Jouzel J., Kattsov V., Lohmann U., Matsuno T., Molina M., Nicholls N., Overpeck J., Raga G., Ramaswamy V., Ren J., Rusticucci M., Somerville R., Stocker T.F., Whetton P., Wood R.A., Wratt D. Technical Summary. Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change 2007, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. S. Solomon, D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor, H.L. Miller (Eds.).
106. Stoorvogel J.J., Kempen B., Heuvelink G.B.M., De Bruin S. Implementation and evaluation of existing knowledge for digital soil mapping in Senegal. Geoderma 2009, 149:161-170.
107. Takeshi S., Kazuo I., Hideaki H., Ikutaro K., Masayoshi W., Yoshio H. Weathering estimate of decomposed granite by particle distribution analysis (in Japanese). Proceedings of JSCE (Japan Society of Civil Engineers) 1999, 631:97-108. ISSN:0289-7806.
108. UN Millennium Project Halving hunger: it can be done. Task Force on Hunger 2005.
109. UNDP Human Development Report 2007/2008 2007, Palgrave Macmillan Hampshire/New York.
110. UNEP GEO-3. Past, Present and Future Perspectives 2002.
111. UNEP The GEO-3 Scenarios 2002-2032: Quantification and Analysis of Environmental Impacts. UNEP/DEWA/RS.03-4 and RIVM 402001022 2004, J. Potting, J. Bakkes (Eds.).
112. UNEP GEO-4. Environment for Development 2007.
113. Van Engelen V., Verdoodt A., Dijkshoorn K., Van Ranst E. Soil and Terrain Database of Central Africa - DR of Congo, Burundi and Rwanda (SOTERCAF, version 1.0) 2006, ISRIC, Wageningen.
114. Van Grinsven H.J.M., Driscoll C.T., Tiktak A. Preface on workshop on comparison of forest-soil-atmosphere models. Ecological Modelling 1995, 83:1-6.
115. Van Oijen M., Rougier J., Smith R. Bayesian calibration of process-based forest models: bridging the gap between models and data. Tree Physiology 2005, 25:915-927.
116. Vereecken H., Jansen E.J., Hack-ten Broeke M.J.D., Swerts M., Engelke R., Fabrewitz S., Hansen S. Comparison of Simulation Results of Five Nitrogen Models using Different Data Sets. Nitrate in soils 1991, 321-338. Commission of the European Communities. A.J. Thomasson, J. Bouma, H. Lieth (Eds.).
117. Vereecken H., Diels J., Van Orshoven J., Feyen J., Bouma J. Functional evaluation of pedotransfer functions for the estimation of soil hydraulic properties. Soil Science Society of America Journal 1992, 56:1371-1378.
118. Viertl R. Is it necessary to develop a Fuzzy Bayesian Inference?. Probability and Bayesian Statistics 1987, 471-475. Plenum Publishing Company, New York. R. Viertl (Ed.).
119. Vrugt J.A., ter Braak C.J.F., Clark M.P., Hyman J.M., Robinson B.A. Treatment of input uncertainty in hydrologic modeling: doing hydrology backward with Markov chain Monte Carlo simulation. Water Resources Research 2008, 44. 10.1029/2007WR006720.
120. Vrugt J.A., ter Braak C.J.F., Diks C.G.H., Robinson B.A., Hyman J.M., Higdon D. Accelerating Markov Chain Monte Carlo simulation by differential evolution with self-adaptive randomized subspace sampling. International Journal of Nonlinear Sciences & Numerical simulation 2009, 10(3):273-290.
121. Walley W.J., O'Connor M.A., Trigg D.J., Martin R.W. Diagnosing and predicting river health from biological survey data using pattern recognition and plausible reasoning. R&D Technical Report E1-056/TR2 2002, Environment Agency, Bristol.
122. Williams M., Schwartz P.A., Law B.E., Irvine J., Kurpius M.R. An improved analysis of forest carbon dynamics using data assimilation. Global Change Biology 2005, 11:89-105.
123. Wohling T., Vrugt J.A. Combining multiobjective optimization and Bayesian model averaging to calibrate forecast ensembles of soil hydraulic models. Water Resources Research 2008, 44(12):W12432.
124. Wood S., Sebastian K., Scherr S.J. Pilot analysis of global ecosystems. Agroecosystems 2000, World Resources Insititute.