Hydrogeology Journal

, Volume 18, Issue 3, pp 625–649 | Cite as

Development of a three-dimensional model of sedimentary texture in valley-fill deposits of Central Valley, California, USA

  • Claudia C. Faunt
  • Kenneth Belitz
  • Randall T. Hanson
Paper

Abstract

A three-dimensional (3D) texture model was developed to help characterize the aquifer system of Central Valley, California (USA), for a groundwater flow model. The 52,000-km2 Central Valley aquifer system consists of heterogeneous valley-fill deposits. The texture model was developed by compiling and analyzing approximately 8,500 drillers’ logs, describing lithologies up to 950 m below land surface. The lithologic descriptions on the logs were simplified into a binary classification of coarse- and fine-grained. The percentage of coarse-grained sediment, or texture, was then computed for each 15-m depth interval. The model was developed by 3D kriging of the percentage of coarse-grained deposits onto a 1.6-km spatial grid at 15-m depth intervals from land surface down to 700 m below land surface. The texture model reflects the known regional, spatial, and vertical heterogeneity in the aquifer system. The texture model correlates to sediment source areas, independently mapped geomorphic provinces, and factors affecting the development of alluvial fans, thus demonstrating the utility of using tcdrillers’ logs as a source of lithologic information. The texture model is upscaled to a layered groundwater flow model for use in defining the hydraulic properties of the aquifer system.

Keywords

USA General hydrogeology Geostatistics Unconsolidated sediments 

Développement d’un modèle tridimensionnel de la texture sédimentaire des dépôts de remplissage de la Vallée Centrale, Californie, Etats-Unis

Résumé

Un modèle tridimensionnel (3D) dit « de texture » a été développé pour aider à la caractérisation de l’aquifère de la Vallée Centrale en Californie (Etats-Unis) par un modèle hydrodynamique. Les 52,000 km2 de l’aquifère de la Vallée Centrale sont constitués de dépôts hétérogènes de remblayage de vallées. Le modèle de texture a été développé en combinant et analysant environ 8500 logs de sondage et en décrivant les lithologies jusqu’à plus de 950 m sous la surface du sol. Les descriptions lithologiques des logs ont été simplifiées en une classification binaire grains grossiers et grains fins. Le pourcentage de sédiment grossier, ou texture, a ensuite été calculé pour chaque intervalle de profondeur de 15 m. Le modèle a été développé avec un kriging 3D du pourcentage de grain grossier dans les dépôts dans une grille de 1.6 km de côté pour des intervalles de profondeur de 15 m et jusqu’à 700 m sous la surface du sol. Le modèle de texture reflète l’hétérogénéité régionale, spatiale et verticale connue du système aquifère. Le modèle de texture se corrèle avec la localisation des sources de sédiments, les provinces géomorphologiques indépendamment cartographiées et les facteurs influençant le développement des cônes alluviaux, montrant ainsi l’utilité d’utiliser les logs de sondage comme source d’information lithologique. Le modèle de texture est ensuite utilisé dans un modèle d’écoulement de l’eau souterraine à couches afin de permettre la détermination des propriétés hydrauliques de l’aquifère.

Desarrollo de un modelo tridimensional de la textura sedimentaria en depósitos de relleno de valle del Central Valley, California, EEUU

Resumen

Se desarrolló un modelo tridimensional (3D) de textura para ayudar a caracterizar el sistema acuífero del Central Valley, California (EEUU), para un modelo de flujo de aguas subterráneas. Los 52,000 km2 del sistema de acuíferos del Central Valley consisten de depósitos heterogéneos de relleno de valle. El modelo de textura fue desarrollado compilando y analizando aproximadamente 8,500 perfiles de perforaciones, que describen las litologías hasta 950 m por debajo de la superficie del terreno. Las descripciones litológicas de los perfiles fueron simplificadas en una clasificación binaria de granos finos y gruesos. El porcentaje de sedimentos de grano grueso, o textura fue luego calculada para cada intervalo de 15 m de profundidad. El modelo fue desarrollado por un kriging 3 D de los porcentajes de depósitos de granos gruesos en una grilla espacial de 1.6 km en intervalos de 15-m de profundidad a partir de la superficie del terreno a 700 m debajo de la superficie. El modelo textural refleja la conocida heterogeneidad regional, espacial y vertical en el sistema acuífero. El modelo de textura correlaciona con las áreas de fuentes de sedimentos, de las regiones geomorfológicas independientemente mapeadas, y los factores que afectan el desarrollo de los abanicos aluviales, demostrando así la utilidad de los perfiles de perforaciones como una fuente de información litológica. El modelo de textura está reescalado a un modelo de flujo en capas para usarlo en la definición de las propiedades hidráulica del acuífero.

美国加州中央谷地区的河谷堆积物沉积结构三维模型的建立

摘要

为建立加州中央谷地区地下水流模型, 特建立一个刻画其含水层系统特征的三维 (3D) 结构模型。52,000 km2的中央谷含水层系统由非均质河谷堆积物沉积形成。汇编分析约8500个钻孔的录井资料后建成该结构模型, 描述了深度达地面以下950米的岩性情况。录井资料中岩性简化至粗颗粒和细颗粒的二元划分。以15m为间隔计算粗颗粒沉积物或结构的百分比。该模型基于3D克里格在水平1.6 km、垂向15m间距直至地下700m深度建立沉积物的空间网格。该结构模型反应了对该含水层系统在区域、空间和垂向上的非均质性的现有认识。结构模型与沉积物源区、独立绘制的地貌省和影响冲积扇形成的因子相关, 因此, 说明了将钻孔记录作为岩性信息来源的效用。当定义含水层系统的水力特征时, 结构模型可扩展为层状地下水流模型。

Desenvolvimento de um modelo tridimensional da textura sedimentar dos depósitos de enchimento de vale do Central Valley, Califórnia, EUA

Resumo

Foi desenvolvido um modelo tridimensional (3D) da textura para ajudar a caracterizar o sistema aquífero de Central Valley, Califórnia (EUA), num modelo de fluxo de água subterrânea. Com 52,000 km2, o sistema aquífero de Central Valley é formado por depósitos heterogéneos de enchimento de vale. O modelo de textura foi desenvolvido através da compilação e análise de aproximadamente 8,500 registos de sondagem (log's), que descrevem as litologias até 950 m abaixo da superfície do terreno. As descrições litológicas dos registos foram simplificadas numa classificação binária de granulometria grosseira e fina. A percentagem de sedimentos de granulometria grosseira, ou textura grosseira, foi posteriormente calculada para cada intervalo de profundidade de 15 metros. O modelo foi desenvolvido por kriging 3D da percentagem de depósitos sedimentares grosseiros numa malha espacial de 1.6 km com intervalos de profundidade de 15 metros, desde a superfície do terreno até 700 m abaixo. O modelo de textura reflecte a conhecida heterogeneidade regional, espacial e vertical do sistema aquífero. O modelo de textura correlaciona-se com áreas de proveniência dos sedimentos, com províncias geomorfológicas cartografadas independentemente e com factores que afectam o desenvolvimento de leques aluviais, demonstrando dessa forma a utilidade dos registos de sondagem como fonte de informação litológica. O modelo de textura foi transformado num modelo de fluxo de água subterrânea multicamada e usado na definição das propriedades hidráulicas do sistema aquífero.

Supplementary material

10040_2009_539_MOESM1_ESM.xls (14.5 mb)
ESM 1(XLS 14.5 mb)

References

  1. Bartow JA (1991) The Cenozoic evolution of the San Joaquin Valley, California. US Geol Surv Prof Pap 1501, 40 ppGoogle Scholar
  2. Belitz K, Heimes FJ (1990) Character and evolution of the ground-water flow system in the central part of the western San Joaquin Valley, California. US Geol Surv Water Suppl Pap 2348, 28 ppGoogle Scholar
  3. Belitz K, Phillips SP (1995) Alternative to agricultural drains in California’s San Joaquin Valley: results of a regional-scale hydrogeologic approach. Water Resour Res 31(8):1845–1862CrossRefGoogle Scholar
  4. Belitz K, Phillips SP, Gronberg JM (1993) Numerical simulation of ground-water flow in the central part of the Western San Joaquin Valley, California. US Geol Surv Water Suppl Pap 2396, 69 ppGoogle Scholar
  5. Bryan K (1923) Geology and ground-water resources of Sacramento Valley, California. US Geol Surv Water Suppl Pap 495, 285 ppGoogle Scholar
  6. Bureau of Reclamation (1994) The Central Valley Project overview: Bureau of Reclamation History Program research on historic reclamation projects. http://www.usbr.gov/dataweb/html/cvpintro.html. Cited 15 April 2009
  7. Burow KR, Shelton JL, Hevesi JA, Weissmann GS (2004) Hydrogeologic characterization of the Modesto area, San Joaquin Valley, California. US Geol Surv Sci Invest Rep 2004-5232, 54 ppGoogle Scholar
  8. California Department of Water Resources (2003) California’s groundwater, Bulletin 118, update 2003. California Department of Water Resources, Sacramento, CA, 246 ppGoogle Scholar
  9. Carle SF, Fogg GE (1996) Transition probability: based indicator geostatistics. Math Geol 28:453–476CrossRefGoogle Scholar
  10. Carle SF, Labolle EM, Weissmann GS, Vanbrocklin D, Fogg GE (1998) Conditional simulation of hydrofacies architecture: a transition probability/Markov approach. In: Fraser GS, and Davis JM (eds) Hydrogeologic models of sedimentary aquifers. Concepts in Hydrogeology and Environmental Geology no. 1, SEPM, Tulsa, OK, pp 147–170Google Scholar
  11. Davis GH, Green JH, Olmsted FH, Brown DW (1959) Groundwater conditions and storage capacity in the San Joaquin Valley, California. US Geol Surv Water Suppl Pap 1469, 287 ppGoogle Scholar
  12. Davis GH, Lofgren BE, Mack S (1964) Use of ground-water reservoirs for storage of surface water in the San Joaquin Valley, California. US Geol Surv Water Suppl Pap 1618, 125 ppGoogle Scholar
  13. Desbarats AJ (1991) Spatial averaging of hydraulic conductivity in three-dimensional heterogeneous porous media. Math Geol 24(3):249–267CrossRefGoogle Scholar
  14. Dimitrakopoulos R, Desbarats AJ (1993) Geostatistical modeling of grid block permeabilities for 3D reservoir simulators. Reservoir Eng 8:13–18Google Scholar
  15. Farrar CD, Bertoldi GL (1988) Region 4, Central Valley and Pacific Coast Ranges. In: Back W, Rosenshein JS, Seaber PR (eds) Hydrogeology: geology of North America, vols O-2. Geological Society of America, Boulder, Colorado, pp 59–67Google Scholar
  16. Faunt, CC, Hanson, RT, Belitz, K, Schimid, W, Predmore, SP, Rewis, DL, McPherson KR (2009) Numerical model of the hydrologic landscape and groundwater flow in California’s Central Valley, chap. C. In: Faunt CC (ed) Groundwater availability of the Central Valley Aquifer, California. US Geol Surv Prof Pap 1776, pp 121–212. http://pubs.usgs.gov/pp/1766/PP_1766.pdf. Cited 1 August 2009
  17. Fogg GE, Carle S, Green CT (2001) A connected network paradigm for the alluvial aquifer system. In: Dongxiao Z, Winter CL (eds) Theory, modeling and field investigation in hydrogeology. GSA Special Publication, A special volume in honor of Shlomo P. Neuman’s 60th birthday, GSA, Boulder, CO, 252 ppGoogle Scholar
  18. Great Valley Center (2005) State of the Great Central Valley: assessing the region via indicators: the economy (2005): State of the Great Central Valley Indicators Series, Great Valley Center, Modesto, CA, 49 pp. http://www.greatvalley.org/pub_documents/2005_1_18_13_59_43_indicator_econ05_report.pdf. Cited 15 April 2009
  19. Hanson RT (1988) Aquifer-system compaction, Tucson Basin and Avra Valley, Arizona. US Geol Surv Water Resour Invest Rep 88–4172, 69 ppGoogle Scholar
  20. Isaaks EH, Srivastava RM (1989) An introduction to applied geostatistics. Oxford University Press, New YorkGoogle Scholar
  21. Jennings CW (1977) Geologic map of California, 1:750, 000. California Division of Mines and Geology, Sacramento, CAGoogle Scholar
  22. Journel AG, Huijbregts CJ (1978) Mining geostatistics. Academic Press, New York, 600 ppGoogle Scholar
  23. Koltermann CE, Gorelick SM (1992) Paleoclimatic signature in terrestrial flood deposits. Science 256(5065):1775–1782. doi:10.1126/science.256.5065.1775 CrossRefGoogle Scholar
  24. Laudon J, Belitz K (1991) Texture and depositional history of Late Pleistocene-Holocene alluvium in the central part of the western San Joaquin Valley, California. Bull Assoc Eng Geol 28(1):73–88Google Scholar
  25. Matthes FE (1960) Reconnaissance of the geomorphology and glacial geology of the San Joaquin Basin, Sierra Nevada, California. US Geol Surv Prof Pap 329, 62 ppGoogle Scholar
  26. Mendenhall WC, Dole RB, Stabler H (1916) Ground water in San Joaquin Valley, California. US Geol Surv Water Suppl Pap 398, 310 ppGoogle Scholar
  27. Miller RE, Green JH, Davis GH (1971) Geology of the compacting deposits in the Los Banos-Kettleman City subsidence area, California. US Geol Surv Prof Pap 497-E, 45 ppGoogle Scholar
  28. Olmsted FH, Davis GH (1961) Geologic features and ground-water storage capacity of the Sacramento Valley, California. US Geol Surv Water Suppl Pap 1497, 287 ppGoogle Scholar
  29. Page RW (1983) Geology of the Tulare formation and other continental deposits, Kettleman City area, San Joaquin Valley, California, with a section on ground-water management considerations and use of texture maps. US Geol Surv Water Resour Invest Rep 83–4000, 24 ppGoogle Scholar
  30. Page RW (1986) Geology of the fresh ground-water basin of the Central Valley, California, with texture maps and sections. US Geol Surv Prof Pap 1401-C, 54 ppGoogle Scholar
  31. Phillips SP, Belitz K (1991) Calibration of a textured-based model of a ground-water flow system, western San Joaquin Valley, California. Ground Water 29(5):702–715CrossRefGoogle Scholar
  32. Phillips SP, Green CT, Burow KR, Shelton JL, Rewis DL (2007) Simulation of multiscale ground-water flow in part of the northeastern San Joaquin Valley, California. US Geol Surv Sci Invest Rep 2007–5009, 43 ppGoogle Scholar
  33. Planert M, Williams JS (1995) Groundwater atlas of the United States: segment 1, California, Nevada. US Geological Survey Hydrologic Atlas 730-B, 1 atlas, US Geological Survey, Reston, VA, 28 ppGoogle Scholar
  34. Prokopovich NP (1987) Textural composition of near-surface alluvium in west-central San Joaquin CA. Bull Assoc Eng Geol 24(1):59–81Google Scholar
  35. Repenning CA (1960) Geologic summary of the Central Valley of California with reference to disposal of liquid radioactive waste. US Geol Surv Open-File Rep 61-127, 69 ppGoogle Scholar
  36. Ritzi RW Jr (2000) Behavior of indicator variograms and transition probabilities in relation to the variance in lengths of hydrofacies. Water Resour Res 36:3375–3381CrossRefGoogle Scholar
  37. Russo D, Bouton M (1992) Statistical analysis of spatial variability in unsaturated flow parameters. Water Resour Res 28(7):1911–1925CrossRefGoogle Scholar
  38. Sumners WK, Weber (1984) The relationship of grain-size distribution and hydraulic conductivity: an alternate approach. Ground Water 22(4):474–475CrossRefGoogle Scholar
  39. Webb EK (1994) Simulating the three-dimensional distribution of sediment units in braided-stream deposits. J Sediment Res 64b(2):219–231. doi:10.1306/D4267F96-2B26-11D7-8648000102C1865D Google Scholar
  40. Weissmann GS, Fogg GE (1999) Multi-scale alluvial fan heterogeneity modeled with transition probability geostatistics in a sequence stratigraphic framework. J Hydrol 226:48–65CrossRefGoogle Scholar
  41. Weissmann GS, Carle SF, Fogg GE (1999) Three-dimensional hydrofacies modeling based on soil surveys and transition probability geostatistics. Water Resour Res 35:1761–1770CrossRefGoogle Scholar
  42. Weissmann GS, Mount JF, Fogg GE (2002) Glacially driven cycles in accumulation space and sequence stratigraphy of a stream dominated alluvial fan, San Joaquin Valley, California, USA. J Sediment Res 72:270–281CrossRefGoogle Scholar
  43. Weissmann GS, Bennett G, Lansdale AL (2005) Factors controlling sequence development on Quaternary fluvial fans, San Joaquin Basin, California, USA. In: Harvey A, Mather A, Stokes M (eds) Alluvial fans: geomorphology, sedimentology, dynamics. Geol Soc Lond Spec Publ 251, pp 169–186Google Scholar
  44. Wentworth CM, Fisher GR, Levine P, Jachens RC (1995) The surface of crystalline basement, Great Valley and Sierra Nevada, California: a digital map database. US Geol Surv Open-File Rep 95-0096, 16 ppGoogle Scholar
  45. Williamson AK, Prudic DE, Swain LA (1989) Ground-water flow in the Central Valley, California: US Geol Surv Prof Pap 1401-D, 127 ppGoogle Scholar

Copyright information

© Springer-Verlag 2009

Authors and Affiliations

  • Claudia C. Faunt
    • 1
  • Kenneth Belitz
    • 1
  • Randall T. Hanson
    • 1
  1. 1.US Geological SurveyCalifornia Water Science Center, San Diego Projects OfficeSan DiegoUSA

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