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Hydrogeology Journal

, Volume 19, Issue 2, pp 289–305 | Cite as

Influences of subsurface heterogeneity and vegetation cover on soil moisture, surface temperature and evapotranspiration at hillslope scales

  • Adam L. Atchley
  • Reed M. Maxwell
Paper

Abstract

Physical processes are at the root of determining hydrologic response at all scales. Here, the physical mechanisms linking (1) subsurface heterogeneities to soil moisture and (2) resulting land-surface energy feedbacks to the atmosphere, are examined at the hillslope scale using a fully coupled surface-subsurface-land-surface model, ParFlow. A hillslope with a heterogeneous subsurface and uniform topography was modeled numerically using summer atmospheric conditions and a single precipitation event under controlled boundary conditions in order to isolate the contribution of hydraulic conductivity to land-surface hydrological processes and energy interactions. Patterns of subsurface hydraulic conductivity are shown to govern soil-moisture distribution at the hillslope scale following precipitation. This variability in soil moisture is closely linked to the variability in land-surface energy feedbacks. The role that vegetation plays in subsurface soil moisture and land energy communications is also examined. Results show that hillslope soil moisture variation is first established by patterns in vertical hydraulic conductivity, while later on in the dry-down period, vegetation exerts greater control on the land-surface energy fluxes and controls the rate of hillslope dry down. Furthermore, as compared to bare-soil simulations, grass-cover simulations show an increase in near-surface soil moisture despite water up-take along the rooting depth.

Keywords

Soil moisture modeling Hydraulic conductivity Heterogeneity Land energy flux USA 

Influence des hétérogénéités de surface et du couvert végétal sur l’humidité du sol, température de surface et évapotranspiration à l’échelle du versant

Résumé

Les processus physiques sont à la base de la réponse hydrologique à toutes les échelles. Ici, les mécanismes physiques reliant (1) les hétérogénéités de subsurface à l’humidité du sol et (2) les pertes par évapotranspiration sont examinés à l’échelle du versant avec un modèle numérique couplant état de surface-surface-subsurface du sol, Parflow. Un versant présentant une subsurface hétérogène et une topographie uniforme a été modélisé en entrant des conditions atmosphériques estivales et un seul épisode pluvieux avec des conditions aux limites fixées, afin de séparer des interactions énergétiques la contribution de la conductivité capillaire aux processus d’évapotranspiration. On montre que la perméabilité capillaire de subsurface contrôle la distribution de l’humidité à l’échelle du versant à la suite d‘une précipitation. Cette distribution de l’humidité du sol est étroitement reliée à la variabilité des pertes par évapotranspiration. Le rôle que la végétation joue sur l’humidité de subsurface et sur l’évapotranspiration est aussi examiné. Les résultats montrent que la variation d’humidité du versant est d’abord conditionnée par la capilarité verticale, alors qu‘en période de sécheresse, la végétation exerce un plus grand contrôle sur l’évapotranspiration et contrôle le taux de dessication du versant. De plus, comparativement à un sol dénudé, les simulations montrent qu’une couverture herbeuse accroît l’humidité de subsurface malgré le prélèvement d’eau radiculaire.

Influencia de la heterogeneidad subsuperficial y de la cobertura de vegetación en la humedad del suelo, temperatura superficial y evapotranspiración a escala de laderas

Resumen

Los procesos físicos están en la raíz de las determinaciones de las respuestas hidrológicas a toda escala. Aquí se examinan los mecanismos físicos que vinculan (1) la heterogeneidad subsuperficial a la humedad del suelo y (2) la retroalimentación de energía de la superficie de la tierra a la atmósfera, a una escala de ladera usando un modelo completamente acoplado superficie – subsuperficie –superficie del terreno, ParFlow. Se modeló numéricamente una ladera con una subsuperficie heterogénea y una topografía uniforme usando condiciones atmosféricas de verano y un solo evento de precipitación bajo condiciones de contorno controladas con el fin de aislar la contribución de la conductividad hidráulica a los procesos hidrológicos de la superficie terrestre y las interacciones energéticas. Se demuestra que los esquemas de conductividad hidráulica subsuperficial gobiernan la distribución de la humedad del suelo a la escala de ladera y posteriormente a la precipitación. Esta variabilidad en la humedad del suelo está estrechamente ligada con la variabilidad en la retroalimentación de energía en la superficie terrestre. También se examinaron el rol que juega la vegetación en la humedad subsuperficial del suelo y en las comunicaciones energéticas en el terreno. Los resultados muestran que la variación de la humedad del suelo en la ladera está establecida en primer lugar por el esquema en la conductividad hidráulica vertical, mientras que posteriormente por el período de secado, en el cual la vegetación ejerce el mayor control sobre los flujos de energía superficial terrestre y controla la ritmo del secado de la ladera. Además, en comparación con las simulaciones de suelo descubierto, las simulaciones de la cubierta vegetal muestra un incremento en la humedad del suelo próxima a la superficie a pesar que el agua es tomada a través de la profundidad del enraizado.

山坡尺度上地下非均质性和植被对土壤水、地表温度和腾发的影响

摘要

在任一尺度上, 物理过程都是研究水文响应的基础。本文在山坡尺度上, 采用完全耦合的地表-地下-陆地-地表模型 (ParFlow) 将物理机制与 (1) 地下非均质性对土壤水分的影响; (2) 陆-地对大气的能量反馈等相联系起来进行研究。对一个地下为非均质介质而地形一致的山坡进行数值模拟, 其控制边界条件限定为夏季大气条件下的一次降水过程, 以区分开渗透系数和陆地水文过程与能量相互作用的不同影响。作出了地下渗透系数特征分布图, 以明确降水后山坡尺度上土壤水分的分布。土壤水分的变化与陆-地能量反馈的变化密切相关。另外, 本文分析了植被在土壤水汽与陆地能量交换中所发挥的作用。结果表明, 山坡尺度上, 土壤水汽的变化首先受到垂向渗透系数的控制, 然后在逐渐变干的过程中, 植被逐渐控制陆地表面能量通量与山坡变干的速率。进一步分析表明, 与裸土模拟相比, 有植被覆盖的模拟表明土壤水汽含量在近地表增加, 尽管根部在向上吸水。

Influências da heterogeneidade subsuperficial e do coberto vegetal na humidade do solo, na temperatura superficial e na evapotranspiração à escala das vertentes de encostas

Resumo

Os processos físicos são a base para determinar a resposta hidrológica a todas as escalas. Aqui, os mecanismos físicos que ligam (1) as heterogeneidades subsuperficiais à humidade do solo e (2) as respostas energéticas resultantes da ligação superfície do terreno à atmosfera, são examinados à escala da vertente de encostas, utilizando o modelo conjunto de superfície-subsuperfície-superfície do terreno, ParFlow. Uma vertente de encosta com uma subsuperfície heterogénea e topografia uniforme foi modelada numericamente, utilizando condições atmosféricas de verão e um evento de precipitação único, sob condições de fronteira controladas, de forma a isolar a contribuição da condutividade hidráulica para os processos hidrológicos da superfície do terreno e para as interacções energéticas. Demonstra-se que os padrões da condutividade hidráulica subsuperficial condicionam a distribuição da humidade do solo à escala da vertente de encosta após a precipitação. Esta variabilidade na humidade do solo está proximamente ligada à variabilidade da resposta energética da superfície do terreno. Examina-se também o papel que a vegetação desempenha na humidade do solo subsuperficial e nas comunicações de energia do terreno. Os resultados demonstram que a variação de humidade das vertentes de encosta se estabelece em primeiro lugar por padrões na condutividade hidráulica vertical, enquanto mais tarde, durante o período de secagem, a vegetação exerce um maior controlo nos fluxos energéticos da superfície do terreno e controla a taxa de secagem da vertente de encosta. Para além disso, quando comparadas com simulações de solo descoberto, as simulações do coberto de relva mostram um aumento na humidade do solo próximo da superfície, apesar de haver absorção de água ao longo da profundidade das raízes.

Notes

Acknowledgements

This research was supported in part by the Golden Energy Computing Organization at the Colorado School of Mines using resources acquired with financial assistance from the National Science Foundation and the National Renewable Energy Laboratory. We wish to thank Salvatore Manfreda and the anonymous reviewer for comments that improved the quality and clarity of our paper.

References

  1. Baldocchi DD, Xu L (2007) What limits evaporation from Mediterranean oak woodlands: the supply of moisture in the soil, physiological control by plants or the demand by the atmosphere? Adv Water Resour 30:2113–2122CrossRefGoogle Scholar
  2. Berndtsson R, Nodomi K, Yasuda H, Persson T, Chen H, Jinno K (1996) Soil water and temperature patterns in an arid desert dune sand. J Hydrol 185:221–240. doi: 101016/jadvwatres.2006.06.013 CrossRefGoogle Scholar
  3. Bhark EW, Small EE (2003) Association between plant canopies and the spatial patterns of infiltration in shrubland and grassland of the Chihuahuan Desert, New Mexico. Ecosystems 6:185–196. doi: 10.1007/s10021-002-0210-9 CrossRefGoogle Scholar
  4. Brooks JR, Barnard HR, Coulombe R, McDonnell JJ (2010) Ecohydrologic separation of water between trees and streams in a Mediterranean climate. Nat Geosci 3:100–104. doi: 10.1038/NGEO722 CrossRefGoogle Scholar
  5. Dai JJ et al (2003) The common land model. Bull Am Meteorol Soc 84:1013–1023. doi: 10.1175/BAMS-84-8-1013 CrossRefGoogle Scholar
  6. D’Odorico P, Laio F, Ridolfi L (2005) Noise-induced stability in dryland plant ecosystems. Natl Acad Sci USA 102(21):10819–10822. doi: 10.1073/pnas.0502884102 CrossRefGoogle Scholar
  7. D’Odorico P, Caylor K, Okin GS, Scanlon TM (2007) On soil moisture–vegetation feedbacks and their possible effects on the dynamics of dryland ecosystems. J Geophys Res 112:G04010. doi: 1029/2006JG000379 CrossRefGoogle Scholar
  8. Famiglietti JS, Rudnicki JW, Rodell M (1998) Variability in surface moisture content along a hillslope transect: Ratlesnake Hill, Texas. J Hydrol 210:259–281. doi: 10.1016/S0022-1694(98)00187-5 CrossRefGoogle Scholar
  9. Ferguson IM, Maxwell RM (2010) The role of groundwater in watershed response and land surface feedbacks under climate change. Water Resour Res 46:W00F02. doi: 10.1029/2009WR008616
  10. Grayson RB, Western AW, Chiew FHS (1997) Preferred states in spatial soil moisture patterns: local and nonlocal controls. Water Resour Res 33(12):2897–2908. doi: 10.1029/97/WR02174 CrossRefGoogle Scholar
  11. Harter T, Zhang D (1999) Water flow and solute spreading in heterogeneous soils with spatially variable water content. Water Resour Res 35:415–426CrossRefGoogle Scholar
  12. Huxman TE, Wilcox BP, Bresherrs DD, Scott RL, Snyder KA, Small EE, Hultine K, Pockman WT, Jackson RB (2005) Ecohydrological implications of woody plant encroachment. Ecology 86(2):308–319. doi: 10.1890/03-583 CrossRefGoogle Scholar
  13. Kim CP, Stricker JNM, Feddes RA (1997) Impact of soil heterogeneity on the water budget of the unsaturated zone. Water Resour Res 33(5):991–999. doi: 10.1029/97WR00364 CrossRefGoogle Scholar
  14. Kollet S (2009) Influence of soil heterogeneity on evapotransporation under shallow water table conditions: transient, stochastic simulations. Environ Res Lett 4. doi: 10.1088/1748-9326/4/3/035007
  15. Kollet SJ, Maxwell RM (2006) Integrated surface–groundwater flow modeling: a free-surface overland flow boundary condition in a parallel groundwater flow model. Adv Water Resour 29(7):945–958CrossRefGoogle Scholar
  16. Kollet SJ, Maxwell RM (2008) Capturing the influence of groundwater dynamics on land surface processes using an integrated, distributed watershed model. Water Resour Res 44:W02402. doi: 1029/2007WR006004 CrossRefGoogle Scholar
  17. Kollet SJ, Cvijanovic I, Schuttemeyer D, Maxwell RM, Moene AF, Bayer P (2009) The influence of rain sensible heat and subsurface energy transport on the energy balance at the land surface. Vadose Zone J 8:846–857. doi: 10.2136/vzj2009.0005 CrossRefGoogle Scholar
  18. Kollet SJ, Maxwell RM, Woodward CS, Smith S, Vanderborght J, Vereecken H, Simmer C (2010) Proof of concept of regional scale hydrologic simulations at hydrologic resolution utilizing massively parallel computer resources. Water Resour Res 46. doi: 10.1029WR008730
  19. Laio F, Poroiorato A, Fernandez-Illescas CP, Rodriguez-Iturbe I (2001) Plants in water-controlled ecosystems: active role in hydrologic processes and response to water stress IV—discussion of real cases. Adv Water Resour 24:745–762. doi: 10.1016/s0309-1708(1)00005-7 CrossRefGoogle Scholar
  20. Maxwell RM, Kollet SJ (2008a) Interdependence of groundwater dynamics and land-energy feedbacks under climate change. Nat Geosi 1:665–669. doi: 10.1038/ngeo315 CrossRefGoogle Scholar
  21. Maxwell RM, Kollet SJ (2008b) Quantifying the effects to three-dimensional subsurface heterogeneity on Hortonian runoff processes using a coupled numerical stochastic approach. Adv Water Resour 31:807–817. doi: 10.1016/j.advwatres.2008.01.020 CrossRefGoogle Scholar
  22. Maxwell RM, Miller NL (2005) Development of a coupled land surface and groundwater model. J Hydrometeorol 6:233–247CrossRefGoogle Scholar
  23. Maxwell RM, Chow FK, Kollet SJ (2007) The groundwater-land-surface-atmospheric connection: soil moisture effects on the atmospheric boundary layer in fully-coupled simulations. Adv Water Resour 30:2447–2466. doi: 10.10/j.advwatres.2007.05.018 CrossRefGoogle Scholar
  24. McDonnell JJ, Sivapalan M, Vache K, Dunn S, Grant G, Haggerty R, Hinz C, Hooper R, Kirchner J, Roderick ML, Selker J, Weiler M (2007) Moving beyond heterogeneity and process complexity: a new vision for watershed hydrology. Water Resour Res 43:W07301. doi: 1029/2006WR005467 CrossRefGoogle Scholar
  25. Nash MS, Wierenga PJ, Gutjahr A (1991) Time series analysis of soil moisture and rainfall along a line transect in arid rangeland. Soil Sci 152:189–198CrossRefGoogle Scholar
  26. Pan YX, Wang XP (2009) Factors controlling the spatial variability if surface soil moisture within revegetated-stabilized desert ecosystems of the Tengger Desert, northern China. Hydrol Process 23:1591–1601. doi: 10.1002/hyp.7287 CrossRefGoogle Scholar
  27. Ridolfi L, D’Odorico P, Porporato A, Rodriguez-Iturbe I (2003) Stochastic soil moisture dynamics along a hillslope. J Hydrol 272:264–275. doi: 10.1016/S0022-1694(02000270-6 CrossRefGoogle Scholar
  28. Rodriguez-Iturbe I, D’Odorico P, Porporato A, Ridolf L (1999) On the spatial and temporal links between vegetation, climate, and soil moisture. Water Resour Res 35(12):3709–3722. doi: 10.1029/1999WR900255 CrossRefGoogle Scholar
  29. Running SW, Loveland TR, Peerce LL (1994) A vegetation classification logic based on remote sensing for using in global scale biogeochemical models. Ambio 23(1):77–81. doi: 10.1016/0034-4257(94)00063-S Google Scholar
  30. Tompson AFB, Ababou R, Gelhar LW (1989) Implementation of the three-dimensional turning bands random field generator. Water Resour Res 25(10):2227–2243. doi: 10.1029/WR025i010p02227 CrossRefGoogle Scholar
  31. Tromp-van Meerveld HJ, McDonnell JJ (2006) On the interrelations between topography, soil depth, soil moister, transpiration rates and species distribution at the hillslope scale. Adv Water Resour 29:293–310. doi: 10.1016/j.advwaters.2005.02.016 CrossRefGoogle Scholar
  32. van Genuchten MT (1980) A closed-form equation for predicting the hydraulic conductivity of unsaturated soils. Soil Sci Soc Am J 44:892–898CrossRefGoogle Scholar
  33. Vereecken H, Kasteel R, Vanderborght J, Harter T (2007) Upscaling hydraulic properties and soil water flow processes in heterogeneous soils: a review. Vadose Zone J 6:1–28. doi: 10.2136/vzj2006.0055 CrossRefGoogle Scholar
  34. Villegas JC, Breshears DD, Zou CB, Law DJ (2009) Ecohydrological controls of soil evaporation in deciduous drylands: how the hierarchical effects of litter, patch and vegetation mosaic cover interact with phenology and season. J Arid Environ 74(5):595–602. doi: 10.1016/j.aridenv.2009.09.028 Google Scholar
  35. Western AW, Grayson RB, Bloschl G, Willgoose GR, McMahon TA (1999) Observed spatial organization of soil moisture and its relation to terrain indices. Water Resour Res 35:797–810. doi: 10.1029/1998WR900065 CrossRefGoogle Scholar
  36. Western AW, Zhou SL, Grayson RB, McMahon TA, Bloschl G, Wilson DJ (2004) Spatial correlation of soil moisture in small catchments and its relationship to dominant spatial hydrological processes. J Hydrol 286:113–134. doi: 10.1016/j.hydrol.2003.09.014 CrossRefGoogle Scholar
  37. Williams CJ, McNamara JP, Chandler DG (2008) Controls on the temporal and spatial variability of soil moisture in a mountainous landscape: the signature of snow and complex terrain. Hydrol Earth Syst Sci 13:1325–1336CrossRefGoogle Scholar
  38. Wood EF (1994) Scaling, soil moisture and evapotranspiration in runoff models. Adv Water Resour 17:25–34. doi: 10.1016/0309-1708(94)90021-3 CrossRefGoogle Scholar
  39. Zhang L, Dawes WR, Walker GR (2001) Response of mean annual evapotranspiration to vegetation changes at catchment scale. Water Resour Res 37(3):701–708. doi: 10.1029/2000WR900325 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  1. 1.Hydrologic Science and Engineering Program, Department of Geology and Geologic EngineeringColorado School of MinesGoldenUSA

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