User menu

Validating a continental-scale groundwater diffuse pollution model using regional datasets

Bibliographic reference Ouedraogo, Issoufou ; Defourny, Pierre ; Vanclooster, Marnik. Validating a continental-scale groundwater diffuse pollution model using regional datasets. In: Environmental Science and Pollution Research, (2017)
Permanent URL
  1. Aljazzar, T. H., (2010). Adjustment of DRASTIC Vulnerability Index to Assess Groundwater Vulnerability for Nitrate Pollution Using the Advection-Diffusion Cell. Von der Fakultät für Georessourcen und Materialtechnik der Rheinisch-Westfälischen Technischen Hochschule Aachen Ph.D. thesis. 146pp.
  2. Ateawung, J. N. (2010). A GIS based water balance study of Africa. Master of physical land resources, Universiteit Gent Vrije Universiteit Brussel Belgium.55pp
  3. Barrio Irantzu, Arostegui Inmaculada, Quintana José M, Group IRYSS-COPD, Use of generalised additive models to categorise continuous variables in clinical prediction, 10.1186/1471-2288-13-83
  4. Bartram, J. and Ballance, R. [Eds] (1996). Water quality monitoring: a practical guide to the design and implementation of freshwater quality studies and monitoring programmes. Chapman and Hall, London. (Accessed online April 25th,2017).
  5. Bauder J. W., Sinclair K. N., Lund R. E., Physiographic and Land Use Characteristics Associated with Nitrate-Nitrogen in Montana Groundwater, 10.2134/jeq1993.00472425002200020004x
  6. Beven Keith J., Estimating transport parameters at the grid scale: on the value of a single measurement, 10.1016/0022-1694(93)90091-m
  7. Böhlke John-Karl, Groundwater recharge and agricultural contamination, 10.1007/s10040-001-0183-3
  8. Booker D.J., Snelder T.H., Comparing methods for estimating flow duration curves at ungauged sites, 10.1016/j.jhydrol.2012.02.031
  9. Boy-Roura, M. (2013). Nitrate groundwater pollution and aquifer vulnerability: the case of the Osana region. PhD thesis. Universitat de Girona. 143pp
  10. Boy-Roura Mercè, Nolan Bernard T., Menció Anna, Mas-Pla Josep, Regression model for aquifer vulnerability assessment of nitrate pollution in the Osona region (NE Spain), 10.1016/j.jhydrol.2013.09.048
  11. Breiman Leo, Statistical Modeling: The Two Cultures (with comments and a rejoinder by the author), 10.1214/ss/1009213726
  12. Breiman Leo, 10.1023/a:1010933404324
  13. Breiman L, Friedman JH, Olshen RA, Stone CJ (1984) Classification and regression trees. Wadsworth International Group, Belmont, California
  14. Chapman, D. (1996). Water quality assessments—a guide to use of biota, sediments, and water in environmental monitoring—second edition. 1996, 651 pages published on behalf of WHO by F & FN Spon. . (accessed online March18th 2017).
  15. Charrière Séverine, Aumond Claire, Managing the drinking water catchment areas: the French agricultural cooperatives feed back, 10.1007/s11356-016-6639-8
  16. Constant Thibaut, Charrière Séverine, Lioeddine Abdejalil, Emsellem Yves, Use of modeling to protect, plan, and manage water resources in catchment areas, 10.1007/s11356-015-5459-6
  17. Cutler D. Richard, Edwards Thomas C., Beard Karen H., Cutler Adele, Hess Kyle T., Gibson Jacob, Lawler Joshua J., RANDOM FORESTS FOR CLASSIFICATION IN ECOLOGY, 10.1890/07-0539.1
  18. Davies D B, Sylvester-Bradley R, The contribution of fertiliser nitrogen to leachable nitrogen in the UK: A review, 10.1002/jsfa.2740680402
  19. De’ath G (2002) Multivariate regression trees: a new technique for modeling species–environment relationships. Ecology 83(4):1105–1117. Stable URL
  20. De’ath G, Fabricius KE (2000) Classification and regression trees: a powerful yet simple technique for ecological data analysis. Ecology 81(11):3178–3192. [3178:CARTAP]2.0.CO;2
  21. Destouni Georgia, Stochastic modelling of solute flux in the unsaturated zone at the field scale, 10.1016/0022-1694(93)90088-q
  22. Díaz-Uriarte Ramón, Alvarez de Andrés Sara, 10.1186/1471-2105-7-3
  23. Donigan, A.S., Jr., and Rao, P.S.C. (1986). Examples models testing studies in vadose zone modelling of organic pollutants. Edited by S.C. Hem and S.LM Melancon, PP103–131, Lewis Publ., Chelsea, MI.
  24. Dupas Rémi, Curie Florence, Gascuel-Odoux Chantal, Moatar Florentina, Delmas Magalie, Parnaudeau Virginie, Durand Patrick, Assessing N emissions in surface water at the national level: Comparison of country-wide vs. regionalized models, 10.1016/j.scitotenv.2012.10.011
  25. El-Sadek, A. A. M. (2002). Engineering approach to water quantity and quality modelling at field and catchment scale. Ph.D. thesis. Katholieke Universiteit Leuven.251pp.
  26. Evans Jeffrey S., Murphy Melanie A., Holden Zachary A., Cushman Samuel A., Modeling Species Distribution and Change Using Random Forest, Predictive Species and Habitat Modeling in Landscape Ecology (2011) ISBN:9781441973894 p.139-159, 10.1007/978-1-4419-7390-0_8
  27. Fekete Alexander, Damm Marion, Birkmann Jörn, Scales as a challenge for vulnerability assessment, 10.1007/s11069-009-9445-5
  28. Foster S. S. D., The Ninth Ineson Lecture: Assessing and Controlling the Impacts of Agriculture on Groundwater--from Barley Barons to Beef Bans, 10.1144/qjegh.33.4.263
  29. Foster, S.; Garduño,H., Kemper, L., Tuinhof, A., Nanni, M., Dumars, C. (2003). Groundwater quality protection defining strategy and setting priorities. Briefing note 8.6pp. . Accessed online march 6th, 2017).
  30. Gemitzi A., Petalas C., Pisinaras V., Tsihrintzis V. A., Spatial prediction of nitrate pollution in groundwaters using neural networks and GIS: an application to South Rhodope aquifer (Thrace, Greece), 10.1002/hyp.7143
  31. Grömping Ulrike, Variable Importance Assessment in Regression: Linear Regression versus Random Forest, 10.1198/tast.2009.08199
  32. Gross, E. L. (2008). Ground water susceptibility to elevated nitrate concentrations in South Middleton Township, Cumberland County, Pennsylvania. Master of Science. Shippensburg University. 117pp. ; accessed online July 6th, 2015).
  33. Gubler S., Fiddes J., Keller M., Gruber S., Scale-dependent measurement and analysis of ground surface temperature variability in alpine terrain, 10.5194/tc-5-431-2011
  34. Gurdak Jason J., Qi Sharon L., Vulnerability of Recently Recharged Groundwater in Principle Aquifers of the United States To Nitrate Contamination, 10.1021/es300688b
  35. Gurdak Jason J., Geyer Gabriela E., Nanus Leora, Taniguchi Makoto, Corona Claudia R., Scale dependence of controls on groundwater vulnerability in the water–energy–food nexus, California Coastal Basin aquifer system, 10.1016/j.ejrh.2016.01.002
  36. Gurdak JJ (2014) Groundwater vulnerability handbook of engineering hydrology. CRC Press, Taylor & Francis Group 2014:33
  37. Haller, L., McCarthy, P., O'Brien, T., Riehle, J. and Stuhldreher, T. (2013). Nitrate pollution of groundwater. 2014: alpha water systems INC.
  38. Hamza Mounir, Larocque Denis, An empirical comparison of ensemble methods based on classification trees, 10.1080/00949650410001729472
  39. Hartmann Jens, Moosdorf Nils, The new global lithological map database GLiM: A representation of rock properties at the Earth surface : TECHNICAL BRIEF, 10.1029/2012gc004370
  40. Hastie T, Tibshirani R, Friedman J (2008) The elements of statistical learning, 2nd edn. Springer. isbn:0-387-95284-5
  41. Heidema A Geert, Boer Jolanda MA, Nagelkerke Nico, Mariman Edwin CM, van der A Daphne L, Feskens Edith JM, 10.1186/1471-2156-7-23
  42. Heuvelink Gerard B.M., Pebesma Edzer J., Spatial aggregation and soil process modelling, 10.1016/s0016-7061(98)00077-9
  43. Jones M. J., The weathered zone aquifers of the basement complex areas of Africa, 10.1144/gsl.qjeg.1985.018.01.06
  44. Jung Youn-Young, Koh Dong-Chan, Park Won-Bae, Ha Kyoochul, Evaluation of multiple regression models using spatial variables to predict nitrate concentrations in volcanic aquifers : Impact of Spatial Variables on Nitrate Contamination of Groundwater, 10.1002/hyp.10633
  45. Knudby Anders, Brenning Alexander, LeDrew Ellsworth, New approaches to modelling fish–habitat relationships, 10.1016/j.ecolmodel.2009.11.008
  46. Kulabako N.R., Nalubega M., Thunvik R., Study of the impact of land use and hydrogeological settings on the shallow groundwater quality in a peri-urban area of Kampala, Uganda, 10.1016/j.scitotenv.2007.03.035
  47. LAWLER JOSHUA J., WHITE DENIS, NEILSON RONALD P., BLAUSTEIN ANDREW R., Predicting climate-induced range shifts: model differences and model reliability, 10.1111/j.1365-2486.2006.01191.x
  48. Li X, Zhai T, Jiao Y, Wang G (2015) Using Bayesian hierarchical models and random forest algorithm for habitat use studies: a case of nest site selection of the crested ibis at regional scales. PeerJ PrePrints 3:e871v1.
  49. Liaw, A., Wiener, M., (2002). Classification and regression by random forest. Vol. 2/3, December 2002. (accessed online April, 16th 2017).
  50. MacDonald, A. (2010). Groundwater, health, and livelihoods in Africa. British Geological Survey © NERC 2010 Earthwise 26, 2pp. ORAL PRESENTATION. (Accessed online January 28th 2016).
  51. MacDonald A M, Bonsor H C, Dochartaigh B É Ó, Taylor R G, Quantitative maps of groundwater resources in Africa, 10.1088/1748-9326/7/2/024009
  52. MacDonald, A., M., R. Taylor, G., and H. Bonsor, C. (2013). (Eds.) Groundwater in Africa—is there sufficient water to support the intensification of agriculture from “Land Grabs”." Hand book of land and water grabs in Africa. pp 376–383
  53. MacDonald A, Davies J, Calow R (2008) African hydrogeology and rural water supply, Applied groundwater studies in Africa. IAH selected papers on hydrogeology, volume 13 (ed. by S. M. A. Adelana & a. M. MacDonald). CRC Press/Balkema, Leiden, The Netherlands
  54. MacDonald AM, Davies J (2000) A brief review of groundwater for rural water supply in sub-Saharan Africa, British Geological Survey, technical report WC/00/33. Overseas Geology Series, BGS, Nottingham, UK
  55. Margat, J. (2010). Ressources et utilisation des eaux souterraines en Afrique. Managing Shared Aquifer Resources in Africa, Third International Conférence Tripoli 25–27 may 2008. International Hydrological Programme, Division of Water Sciences, IHP-VII Series on groundwater No.1, UNESCO, pp 26–34
  56. Mfumu Kihumba Antoine, Ndembo Longo Jean, Vanclooster Marnik, Modelling nitrate pollution pressure using a multivariate statistical approach: the case of Kinshasa groundwater body, Democratic Republic of Congo, 10.1007/s10040-015-1337-z
  57. Mulla David J., Addiscott Thomas M., Validation approaches for field-, basin-, and regional-scale water quality models, Assessment of Non‐Point Source Pollution in the Vadose Zone (1999) ISBN:0875900917 p.63-78, 10.1029/gm108p0063
  58. National Research Council (NRC), (1993). Ground water vulnerability assessment: Predictive relative contamination potential under conditions of uncertainty. National Academy Press, Washington D.C., pp. 224. ISBN: 978–0–309-04799-9
  59. Nolan Bernard T., Hitt Kerie J., Vulnerability of Shallow Groundwater and Drinking-Water Wells to Nitrate in the United States, 10.1021/es060911u
  60. Nolan Bernard T., Gronberg JoAnn M., Faunt Claudia C., Eberts Sandra M., Belitz Ken, Modeling Nitrate at Domestic and Public-Supply Well Depths in the Central Valley, California, 10.1021/es405452q
  61. Oliveira Sandra, Oehler Friderike, San-Miguel-Ayanz Jesús, Camia Andrea, Pereira José M.C., Modeling spatial patterns of fire occurrence in Mediterranean Europe using Multiple Regression and Random Forest, 10.1016/j.foreco.2012.03.003
  62. Ouedraogo I, Vanclooster M (2016a) A meta-analysis and statistical modelling of nitrates in groundwater at the African scale. Hydrology and Earth System Sciences, Vol 20, no6 20(6):2353–2381.
  63. Ouedraogo I, Vanclooster M (2016b) Shallow groundwater poses pollution problem for Africa. In: SciDev.Net, p 4.
  64. Ouedraogo, I., Defourny, P., and Vanclooster, M.(2016a). Modeling groundwater nitrate concentrations at the African scale using random forest regression techniques. Accepted April 24th to review in the special issue on groundwater in sub-Saharan Africa for Hydrogeological Journal (HJ) (in progress, book expected in December 2017).
  65. Ouedraogo Issoufou, Defourny Pierre, Vanclooster Marnik, Mapping the groundwater vulnerability for pollution at the pan African scale, 10.1016/j.scitotenv.2015.11.135
  66. Pearson S (2015) Identifying groundwater vulnerability from nitrate contamination: comparison of the DRASTIC model and environment Canterbury’s method. Lincoln University, Degree of Master of Applied Science (Environmental Management), 58 pp
  67. Postnote (2011). Water Adaptation in Africa. Number 373 April 2011. (Accessed online January 26th, 2016)
  68. Prasad Anantha M., Iverson Louis R., Liaw Andy, Newer Classification and Regression Tree Techniques: Bagging and Random Forests for Ecological Prediction, 10.1007/s10021-005-0054-1
  69. Puckett Larry J., Tesoriero Anthony J., Dubrovsky Neil M., Nitrogen Contamination of Surficial Aquifers—A Growing Legacy†, 10.1021/es1038358
  70. Applied Regression Analysis, ISBN:0387984542, 10.1007/b98890
  71. Refsgaard J.C., Thorsen M., Jensen J.B., Kleeschulte S., Hansen S., Large scale modelling of groundwater contamination from nitrate leaching, 10.1016/s0022-1694(99)00081-5
  72. Refsgaard, J.C., and Butts, M.B. (1999). Determination of grid scale parameters in catchment modelling by upscaling local scale parameters. Proceeding of the Int. workshop on modelling transport process in soils. EurAEng’s IG on soil and water, Leuven, Belgium, 24-26 Nov., 650-665
  73. Rodriguez-Galiano Victor, Mendes Maria Paula, Garcia-Soldado Maria Jose, Chica-Olmo Mario, Ribeiro Luis, Predictive modeling of groundwater nitrate pollution using Random Forest and multisource variables related to intrinsic and specific vulnerability: A case study in an agricultural setting (Southern Spain), 10.1016/j.scitotenv.2014.01.001
  74. Royal Society of Chemistry (RSC) (2010) Africa’s water quality. Last accessed August 2016
  75. Schwarz Gregory E., Alexander Richard B., Smith Richard A., Preston Stephen D., The Regionalization of National-Scale SPARROW Models for Stream Nutrients1 : The Regionalization of National-Scale SPARROW Models for Stream Nutrients, 10.1111/j.1752-1688.2011.00581.x
  76. Shamsudduha M, Taylor RG, Chandler RE (2015) A generalized regression model of arsenic variations in the shallow groundwater of Bangladesh. Water Resour Res 51(1):685–703.
  77. Sharaky, A. M. (2016). Geology and water resources in Africa. Institute of African Research and Studies. The university of Cairo. . 40pp (accessed online 19th August 2016)
  78. Spalding R. F., Exner M. E., Occurrence of Nitrate in Groundwater—A Review, 10.2134/jeq1993.00472425002200030002x
  79. Strebel, O., Duynisveld, W. H. M., and Böttcher, J. (1989). Nitrate pollution of groundwater in Western Europe, Agric. Ecosyst. Environ. 26, 189–214. (89)90013-3
  80. Strobl Carolin, Boulesteix Anne-Laure, Zeileis Achim, Hothorn Torsten, 10.1186/1471-2105-8-25
  81. UNEP (United Nations Environment Programme). (2010). Africa Water Atlas. Nairobi, UNEP, Division of Early Warning and Assessment (DEWA). africaWater/book.php.
  82. UNEP/DEWA, (2014). Sanitation and Groundwater Protection –a UNEP Perspective UNEP/DEWA, . 18pp (Accessed online August 14th 2014).
  83. Wakida Fernando T., Lerner David N., Non-agricultural sources of groundwater nitrate: a review and case study, 10.1016/j.watres.2004.07.026
  84. Ward Mary H., deKok Theo M., Levallois Patrick, Brender Jean, Gulis Gabriel, Nolan Bernard T., VanDerslice James, Workgroup Report: Drinking-Water Nitrate and Health—Recent Findings and Research Needs, 10.1289/ehp.8043
  85. Wheeler David C., Nolan Bernard T., Flory Abigail R., DellaValle Curt T., Ward Mary H., Modeling groundwater nitrate concentrations in private wells in Iowa, 10.1016/j.scitotenv.2015.07.080
  86. WHO (1992). GEMS/WATER Operational Guide. Third edition. World Health Organization, Geneva. 121pp. . (Accessed online March 18th 2017)
  87. Groundwater Pollution in Africa, ISBN:9780415411677, 10.1201/9780203963548
  88. Yee Thomas W., Mitchell Neil D., Generalized additive models in plant ecology, 10.2307/3236170
  89. Zhao Changsen, Liu Changming, Xia Jun, Zhang Yongyong, Yu Qiang, Eamus Derek, Recognition of key regions for restoration of phytoplankton communities in the Huai River basin, China, 10.1016/j.jhydrol.2011.12.016