Hydropedology and Surface/Subsurface Runoff Processesudel.edu/~inamdar/BREG667/Lin2008.pdf · Hydropedology and Surface/Subsurface Runoff Processes HENRY LIN1, ERIN BROOKS 2, PAUL

Hydropedology and Surface/Subsurface RunoffProcesses

HENRY LIN1, ERIN BROOKS2, PAUL McDANIEL3 AND JAN BOLL2

1Department of Crop and Soil Sciences, Pennsylvania State University, University Park, PA, US2Department of Biological and Agricultural Engineering, University of Idaho, Moscow, ID, US3Department of Plant, Soil, and Entomological Sciences, University of Idaho, Moscow, ID, US

The role of soils has long been recognized as critical to rainfall–runoff processes in watersheds. Hydropedologyis an emerging interdisciplinary field that integrates pedology, hydrology, geomorphology, and other relatedbio- and geosciences to study interactive pedologic and hydrologic processes and the landscape–soil–hydrologyrelationships across space and time. This article presents an overview of hydropedology’s contributions to theunderstanding and modeling of surface/subsurface runoff processes, especially the diagnosis of soil features thatcan help answer “why-type” questions in watershed hydrology and the ubiquitous nature of preferential flow andits networks. We highlight two bottlenecks for advancing watershed hydrology and hydropedology: a conceptualbottleneck of modeling subsurface preferential flow networks and a technological bottleneck of nondestructivelymapping or imaging subsurface architecture. Quantification of “soil architecture” at various scales and theidentification of “hydropedologic functional units” in different landscapes offer promising potentials to advancehydrologic modeling. We present the information of linking surface/subsurface runoff processes to pedologicunderstanding at three scales of microscopic (macropores and aggregates), mesoscopic (horizons and pedons),and macroscopic (hillslopes and catchments) levels. Various examples from the literature are synthesized toillustrate the key points. Further research needs are suggested in the end.

INTRODUCTION

The role of soils (soil properties and their distributionover the landscape) has long been recognized as criti-cal to rainfall–runoff processes in a watershed. Hydrope-dology, as an intertwined branch of soil science andhydrology, embraces multiscale studies of interactive pedo-logic and hydrologic processes and their properties in thevariably saturated and unsaturated surface and subsurfaceenvironments, and therefore possesses significant potentialin enhancing the understanding and prediction of rain-fall–runoff processes (Lin, 2003; Lin et al., 2006a).

The traditional view of surface runoff generation hasbeen based on the infiltration excess, or Hortonian, conceptof runoff production (Horton, 1940), where surface runoff isthe result of rainfall intensity exceeding infiltration capacityat the soil surface. This surface runoff, sometimes alsocalled unsaturated overland flow, occurs more commonly

in arid and semiarid regions, where rainfall intensities arehigh and soil infiltration capacity is reduced because ofsurface sealing or pavement. The primary motivation formany of the early studies was to determine the magnitudeand return period of extreme events, as in many areas of theworld these extreme events have been caused by infiltration-excess runoff.

An alternative runoff generation paradigm, called vari-able source area (VSA) hydrology, has been suggestedover four decades ago (Hewlett and Hibbert, 1967). TheVSA approach to watershed response suggests that runoffcontributing to a storm hydrograph is generated from local-ized (typically near-stream) areas of the landscape. Thecontrolling mechanism is termed saturation-excess runoffgeneration because of precipitation falling on soils that havelittle or no available storage (typically high soil moisturecontent or groundwater level), thereby precluding infiltra-tion. This “saturated overland flow” occurs more frequently

Encyclopedia of Hydrological Sciences. Edited by M G Anderson. 2008 John Wiley & Sons, Ltd.

2 RAINFALL–RUNOFF PROCESSES

in riparian zones, valley bottoms, or local depressional areasin humid or semihumid regions. As a consequence, water-shed hydrologists must consider not only soil properties andtheir spatial distributions, but also the interactive roles oftopography, land use/land cover, geology, and other compo-nents of the hydrologic cycle besides precipitation (Gbureket al., 2006).

Another runoff, called subsurface return flow (or reflow ),occurs after water infiltrates the soil on an upslope por-tion of a hillslope and then flows laterally through the soiland exfiltrates (resurfaces) in the toeslope area or closer tostream channel (Whipkey, 1965; Dunne et al., 1975). Thisoverland flow is related to subsurface stormflow (also calledsubsurface runoff, interflow, throughflow, lateral flow, tran-sient groundwater, or some other names) (see Chapter 112,Subsurface Stormflow, Volume 3). Subsurface stormflowis another runoff-producing mechanism operating in mostupland terrains, especially in humid environment and steepterrain with conductive soils or soils with a water-restrictinglayer. While some studies have documented subsurfacestormflow as unsaturated flow in the vadose zone, moststudies have shown that subsurface stormflow is saturated(or near-saturated) – due to either the rise of an existingwater table into more transmissive soil above (with ensuinglateral flow) or the transient saturation above an impedinglayer, soil–bedrock interface, or some zone of reduced per-meability (e.g. fragipan, argillic horizon, and other denselayers in the soil profile).

Field investigations conducted in various humid forestedcatchments throughout the world have also revealed the sig-nificance of subsurface preferential flow at multiple spatialand temporal scales. While overland flow is limited in theseforested catchments, evidence of subsurface preferentialrunoff is ubiquitous (Sidle et al., 2001; McDonnell, 2003;Lin, 2006). Growing evidence suggests that the subsur-face flow network is a key to understanding rainfall–runoffprocesses including threshold behavior (Sidle et al., 2001;Weiler et al., 2005; McDonnell et al., 2007; Lin and Zhou,2008), and that flow pathways often determine the hot spotsand moments of biogeochemical processes (Band et al.,2001; McClain et al., 2003; Boyer et al., 2006). This sug-gests that a new thinking beyond the VSA paradigm isneeded (Sidle et al., 2000; McDonnell, 2003; McDonnellet al., 2007). The dynamic origin of network structures insoils and hydrologic systems and recurrent patterns of self-organization are the subjects of recent research and modeldevelopment (Rinaldo et al., 2006; James and Roulet, 2007;Weiler and McDonnell, 2007; Lehmann et al., 2007).

There are significant questions remaining in hillslopehydrology and rainfall–runoff prediction. For example,McDonnell et al. (2007) raised a number of such ques-tions in their new vision of watershed hydrology: Why doesheterogeneity exist? Why is there preferential, networklikeflow at all scales? Why are hydrological connections at the

hillslope and watershed scale so thresholdlike when the soil,climate, vegetation, and water appear so tightly coupled?This article attempts to shed light on some of these ques-tions from a hydropedologic perspective. In particular, twobottlenecks are identified and discussed, where hydropedol-ogy can make a unique contribution to advancing watershedhydrology, including the quantification of soil architectureat various scales and the identification of hydropedologicfunctional units (HFUs) in different landscapes.

The article provides an overview of the current under-standing of hydropedology’s role in rainfall–runoff pro-cesses, especially the diagnosis of soils that can help answer“why-type” questions in watershed hydrology. We illustratevarious aspects that show the diagnostic importance of soilsin rainfall–runoff processes at three scales – microscopic(macropores and aggregates), mesoscopic (horizons andpedons), and macroscopic (hillslopes and catchments) lev-els. Some research needs for the future are suggested in theend.

HYDROPEDOLOGY AND ITS FUNDAMENTALQUESTIONS

Hydropedology, as an emerging interdisciplinary field, inte-grates pedology, hydrology, geomorphology, and otherrelated bio- and geosciences to study interactive pedo-logic and hydrologic processes and the landscape–soil–hydrology relationships across space and time (Lin, 2003;Lin et al., 2005a, 2006a). It aims to understand pedologiccontrols on hydrologic processes and properties (e.g. soilas a central link in the hydrologic cycle and as a founda-tion for rainfall–runoff processes) and hydrologic impactson soil formation, variability, and functions (e.g. hydrologyas a critical driving force of soil formation and functionaldynamics). Essentially, hydropedology seeks to answer thefollowing two fundamental questions:

1. How the structure and distribution of soils over thelandscape exert a first-order control on landscape wateracross spatiotemporal scales in the surface and thesubsurface?

2. How landscape water (and associated transport ofchemicals and energy by flowing water) impacts soilevolution, variability, and functions?

Landscape water here encompasses the source, storage,availability, flux, pathway, residence time, and spatiotem-poral distribution of water (and the transport of chemicalsand energy by flowing water) in the variably saturatedand unsaturated surface and subsurface (Lin et al., 2006a).While source, storage, availability, and flux of water havebeen studied extensively in the past, attention to flowpathways (especially flow networks), residence time (ageof water), and spatiotemporal pattern of flow dynamics

HYDROPEDOLOGY AND SURFACE/SUBSURFACE RUNOFF PROCESSES 3

Soils(root zone)

Deep vadose zone(pores partially

filled with water)

Ground water zone(pores entirely

filled with water)

Hydropedologyrealm

Hydrogeologyrealm

1 m

1 dm

Ped

Basic structure

Microscopic scale

Mesoscopic scale

1 µm

Hydrologicprocesses

(water)

Geomorphicprocesses

(landscape)

Pedologicprocesses

(soil)

The landscapeparadigm

The landscapeparadigm

The pedonparadigm

The pedonparadigm

The Critical Zone

Hydroecology

TheCriticalZone

TheCriticalZone

Precipitation

Transpiration

Solarenergy

InfiltrationGround water flow

Evaporation

Human use

1 km

Macroscopic scale

Pedosphere

Runoff

Subsurfa

ce flo

w

Soils

Deep vadose zone

Ground water zone

Water table

Figure 1 Hydropedology as an interdisciplinary science that promotes integrated studies of hydrologic, pedologic, andgeomorphic processes across spatial and temporal scales. It connects the pedon and landscape paradigms throughlinking phenomena occurring at the microscopic (e.g. pores and aggregates) to the mesoscopic (e.g. horizons andpedons) and the macroscopic (e.g. catenas and watersheds) levels, and eventually to the megascopic (e.g. regional andglobal) scales

(and its underlying organizing principles) has been limited(McDonnell et al., 2007).

Hydropedology distinguishes itself from vadose zonehydrology (or soil hydrology) in the following aspects:

• Hydropedology emphasizes in situ soils in the land-scape, where distinct pedogenic features (e.g. aggre-gation, horizonation, and redox features) and soil–landscape relationships (e.g. catena, soil distributionpatterns, HFUs) are essential in understanding interac-tive pedologic and hydrologic processes, hence requir-ing adequate attention to soil architecture, soil layering,soil mapping, soil morphology, soil geomorphology,and stratigraphy.

• Hydropedology deals with the variably saturated andunsaturated zone in the surface and near-surface envi-ronments, including shallow root zone, deep vadosezone, temporally saturated zone, capillary fringe, wet-lands, and even subaqueous soils (i.e. soils that form in

sediment found in shallow permanently flooded envi-ronments such as in an estuary).

• Hydropedology is not just about soils’ impacts onhydrology; equally important is hydrologic feedbacks topedogenesis, why subsurface heterogeneity exists, andhow that impacts soil variability and soil functions.

As illustrated in Figure 1, hydropedology attempts toconnect the pedon and landscape paradigms through linkingphenomena occurring at microscopic (e.g. pores and aggre-gates) to mesoscopic (e.g. horizons and pedons) and macro-scopic (e.g. catenae and watersheds) levels, and eventuallyto megascopic (e.g. regional and global) scales. Hydrope-dology, combined with hydrogeology, promotes an inte-grated systems approach to study the interactions of waterwith solid earth (i.e. soils, rocks, and anything in between)beneath the earth’s surface. Above the ground, hydropedol-ogy interfaces with hydroecology and hydrometeorologyto understand the feedback mechanisms between climate,


Molecular

Mixture

Ped (aggregate)

Profile horizon

Field (catena)

Pedon

Landscape (watershed)

Region

Globe

Mesoscopic

Macroscopic

Microscopic

Model scale

i

i + 1

i + 2

i + 3

i + 4

i − 1

i − 2

i − 3

i − 4

Upscaling(larger area)

Downscaling(smaller area)

Soil processand parameters

Pedon

Components

SSURGO

STATSGO

NATSGO

World soil map

Map scale

1:1

<1:1

2 00

01:

24 0

001:

250

000

1:7

500

000

1:10

0 00

0 00

0

Larg

e

Sm

allG

reat

Little

Order 5+

Order 5

Order 4

Order 3, O

rder 2O

rder 1

Local

Aggregation(larger area)

Disaggregation(smaller area)

(a) (b)

Degree of generalizationof soil distribution

Point

Figure 2 Hierarchical framework for bridging forms (soil distribution) and functions (soil processes) in hydropedology:(a) soil mapping hierarchy for depicting soil spatial distributions at different scales. The SSURGO, STATSGO, andNATSGO are county-, state-, and national-level soil maps, respectively, generated from different orders of soil surveys;(b) soil modeling hierarchy for understanding dynamic soil processes across scales. The pedon is the base level (ithscale), and other levels are defined with reference to it, with i+ levels for upscaling and i – levels for downscaling. Thesescale numbers (i’s), however, do not reflect quantitative relationships among scales; rather, they are used to aid inconceptual understanding

vegetation, and soils. In the temporal dimension, hydrope-dology deals with both short- and long-term changes of thelandscape–soil–hydrology relationships, including the useof pedogenesis and soil micro- and macromorphology asa signature of soil change and soil hydrology in the pastand/or current conditions.

Hierarchical Frameworks for Bridging Forms

and Functions in Hydropedology

Two hierarchical frameworks were suggested to bridge theforms and functions in hydropedology (Lin and Rathbun,2003): one is soil mapping hierarchy that deals withsoil spatial heterogeneity, and the other is soil modelinghierarchy that addresses temporal dynamics (Figure 2). Thesoil mapping hierarchy relates to the “forms” of soilsthat depict the spatial pattern of soil types or specificsoil properties over the landscape of varying sizes, whilethe soil modeling hierarchy relates to the “functions” ofsoils that portray soil’s physical, chemical, and biologicalprocesses at different scales. Explicit links between these

two hierarchies, however, have not yet been established.This is in part due to the mismatch of scales used inmapping and modeling. In a spatial sense, “aggregation”and “disaggregation” are used for mapping soil distribution,which are defined irrespective of a process-based model(Figure 2a). In contrast, “upscaling” and “downscaling” areused in modeling soil processes and/or quantifying modelinputs/outputs, and thus are defined in the context of aspecific model (Figure 2b). The meaning of “scale” alsocarries different meanings between mapping and modeling:in cartography, map scale refers to a ratio of map to reality,and the scale becomes smaller as spatial information isaggregated for a larger area; whereas in the modeling arena,scale is often used in a colloquial sense (without a specificquantifier), so large scale loosely refers to a large areaextent.

Another constraint in connecting the forms and functionsof soils for hydrologic modeling is the gap betweenscales used in either mapping or modeling hierarchies.Although there are approximations that might be taken


to connect the scales of attribute-based mapping (suchas spatial interpolation from point observations to arealcoverages) or the scales of process-based modeling (suchas extrapolation of smaller-area model parameters to larger-area values), significant knowledge gaps remain, and directtranslation from one scale to another is still lacking. Sincedifferent factors or processes may dominate at differentscales, and emerging new phenomena may occur as scalechanges, a hierarchical set of models – based on availablemapped attributes – may be constructed. As we focus onsystem patterns and filter out unimportant details, we mightalso begin to see emergent features that could serve asa natural skeleton to connect descriptions of soil andhydrologic responses across scales (Sivapalan, 2003). Thiscould then form the basis of models that are inherentlysimpler at the macroscales, but with sufficient links toessential detailed heterogeneity and complexity observedat the microscales (McDonnell et al., 2007). Such an ideais somewhat similar to a hierarchy of identifiable dynamicalpatterns of processes, called successive dynamical levels, assuggested by Baveye and Boast (1999).

Jenny (1941) suggested the union of soil maps and soilfunctions to provide the most effective means of pedo-logical research. At least two aspects hydropedology cancontribute uniquely to such needed bridging of “forms” and“functions” and of different scales: One is through definingand quantifying soil architecture at various scales, and theother is through defining and identifying HFUs in differentlandscapes. Both efforts can advance hydrologic model-ing via appropriate causal relationships and soil–landscapedatasets of comparable resolutions.

Defining a Broad Concept of ‘‘Soil Architecture’’and its Quantification at Different Scales

Ped (a naturally formed unit of soil aggregate such as ablock, column, granule, plate, or prism) is a unique termin soil science. Pedology (a branch of soil science thatintegrates and quantifies the morphology, formation, distri-bution, and classification of soils as natural or anthropogeni-cally modified landscape entities) captures that uniquenesswell. The natural soil architecture is of essence in under-standing soil physical, chemical, and biological processesas well as rainfall–runoff processes. It has been suggestedthat most that can be learned from sieved and repacked soilsamples has already been done, so whatever we do with soilphysics/hydrology should be done on intact, undisturbedsoils, and preferably in situ in the field. A new era of soilsresearch will have to rely on “structure-focused” – passingthe stage of “texture-focused” – to achieve better ways ofquantifying flow pathways, residence times, and spatiotem-poral patterns of landscape water.

The term soil structure has been used in the US SoilSurveys, and elsewhere, to refer to the natural organizationof soil particles into individual units (peds) separated

by planes of weakness (Figure 3). Three attributes – pedgrade, shape, and size – are used together to describe a soilstructure. For example, “strong fine granular soil structure”means a soil that separates almost entirely into discrete unitsof peds (i.e. strong grade) that are loosely packed, roughlyspherical (i.e. granular), and mostly between 1 and 2 mm indiameter (i.e. fine size). Some soils have simple pedality,each unit being an entity without component smaller unit;others have compound pedality, in which large units arecomposed of smaller units separated by persistent planes ofweakness (Figure 3c).

Besides the shape, size, and grade of peds, the internalsurface features of peds are also described in soil surveys,consisting of (i) coats of a variety of substances unlikethe adjacent soil material and covering part or all of thesurfaces, (ii) concentration of material on surfaces causedby the removal of other materials, and (iii) stress formationsin which thin layers at the surfaces have undergonereorientation or packing by stress or shear (Soil SurveyDivision Staff, 1993). The kinds of structural surfacefeatures include clay films, clay bridges, sand or silt coats,other coats, stress surfaces, and slickensides (see examplesin Figure 3). All of them have significant impacts on flowand transport processes in field soils.

Pores are considered separately in the U.S. Soil Survey’sconcept of soil structure; however, in Europe, Canada,Australia, and some other countries, pore-related features(e.g. pore-size distribution, connectivity, and tortuosity) arean integral part of soil structure (e.g. Brewer, 1976). Thus,the US concept of soil structure is better termed pedality.Pedality and soil pore space are interrelated. But manysoils have interpedal, intrapedal, and/or transpedal poresthat are not necessarily represented by pedality. Thesepores, formed by biological activities (e.g. root channelsand worm borrows), physical processes (e.g. desiccationcracking and freezing–thawing), or chemical reactions (e.g.dissolution or binding of soluble chemicals and organicmatter) are critical in determining flow and transport in fieldsoils. Therefore, in hydropedology, the term soil structureis used to encompass both pedality and pore space (Linet al., 2005a).

Since soil structure generally refers to a specific soilhorizon, a broader term of soil architecture is suggestedhere to also include the overall organization of a soil profile(e.g. horizonation), a soil’s relationship with the landscape(e.g. catena), and the overall hierarchical levels of soilstructural complexity (Lin et al., 2005a).

Soil horizonation or layering is ubiquitous in nature, soit must be adequately addressed when measuring, model-ing, and interpreting hydrologic processes in watersheds.Various kinds and thicknesses of soil horizons and howthey organize in soil profiles reflect long-time pedogene-sis and the past and current landscape processes. The factthat natural soils are layered has at least two significant


Granular Prismatic Blocky Platy

Crack

Interpedalpore

Rootchannel

Livingroots

Infiltrationintakearea

Slickenside

Secondaryped

Secondaryped

Soil matrix

Clay coating

0.8 mm

(a)

(b)

Tertiaryped

Primarypeds

Primarypeds

Cutans(argillans)

Cutans

(c)

Figure 3 (a) Conceptual understanding of the effects of various shapes of soil structure on water flow (Courtesy of theUSDA-NRCS). (b) Illustrations of preferential water flow paths (blue- or red-dyed areas) in structured clay soils. (c) Atertiary ped and a zoom-in illustration of clay coating (Cutan) on the face of a ped

implications for hydrology: (i) interface between soil layersof contrasting textures and/or structures would slowdownwater downward movement, which often leads to some kindof preferential flow (e.g. fingering flow, macropore flow, orfunnel flow) and (ii) soil layering or discontinuity in soilhydraulic properties between layers would promote lateralflow or perched water table (PWT), especially in slopinglandscapes with a water-restricting layer underneath.

A catena (also called toposequence) is a chain of relatedsoil profiles along a hillslope with about the same age,similar parent material, and similar climatic condition,but differs primarily in relief that leads to differences indrainage and soil thickness. Catenary soil developmentoften occurs in response to the way water runs down thehillslope and recognizes the interrelationship between soiland geomorphic processes (Hall and Olson, 1991; Mooreet al., 1993; Thompson et al., 1997; Lin et al., 2005a,b). Catenae are thus also often called hydrosequences ofrelated soils, especially in depositional landscapes. Anotherimportant aspect of soil architecture along the hillslopeis related to preferential flow network, which is furtherdiscussed later in this article.

While the importance of soil architecture across scaleshas long been recognized in soil science and hydrology, itsquantification and incorporation into models have notori-ously lagged behind. This problem is due to many factors,including those highlighted below:

• Inconsistent and fragmented concepts of soil structure,as described above and further elaborated by Letey(1991), Bronick and Lal (2005), Baveye et al. (2006),and many others. One critical point is illustrated here:“No art historian would attempt to characterize thearchitecture of buildings erected in France in the highMiddle Ages by cataloging the nature of the stonesused, the size of the stones, the types of materialsused to bind the stones together, or the geometry ofthe portions of walls into which the buildings breakwhen they are knocked down. With these parametersalone, it might be somewhat difficult to distinguish NotreDame’s cathedral in Paris from stone houses in the Alps,for example. Clearly, a different perspective is needed,emphasizing the openings (window frames, doorways,rooms, etc.) that the stones allow to create in one case


or another. In the same manner, a focus on voids in soilsmight be a more fruitful way to look at soil architecture”(Letey, 1991; Young et al., 2001; Baveye et al., 2006).

• Overemphasis on ground-sieved soil materials and soiltexture in the past, thus ignoring or downplaying theimportance of the soil’s “natural architecture.” It hasbeen said that a crushed or pulverized sample of thesoil is related to the soil formed by nature in the sameway as a pile of debris is related to a demolishedbuilding (Kubiena, 1938). Lin (2007) also suggestedthat a crushed sample of the soil is as akin to a naturalsoil profile as a bulk of ground beef is to a livecow. The fundamental difference between in situ soilsand disturbed soil materials lies in soil architecture. Infact, soil is a living entity, with many dynamic forcesacting upon it, so its internal architecture forms andevolves to serve various soil functions. That naturalsoils are structured to various degrees at different scalesis the rule; whereas the existence of a macroscopichomogeneity is the exception (Vogel and Roth, 2003).

• Lack of appropriate techniques and devices to quantifysoil architecture directly, especially in situ noninva-sively. Traditionally, soil structure has been evaluatedby pedologists in the field using morphological descrip-tions or thin section observations, while soil physicistshave employed wet and dry sieving, elutriation, and sed-imentation to conduct aggregate analysis. In the absenceof direct quantification, soil structure has been fre-quently evaluated by methods that correlate it to theproperties or processes of interest (such as water reten-tion, saturated hydraulic conductivity or Ksat, infiltrationrate, and gas diffusion rate). In recent years, noninva-sive methods that permit soils to be investigated withoutundue disturbance of their natural architecture havebecome increasingly attractive, which allow 3-D visu-alization of internal soil structure and its interactionswith water. These methods include X-ray computingtomography, soft X-ray, nuclear magnetic resonance,γ -ray tomography, ground penetrating radar, and oth-ers (e.g. Anderson and Hopmans, 1994; Perret et al.,1999). Image analysis has brought new opportunitiesfor analyzing soil structure, especially that of the pores,their sizes, shapes, connectivity, and tortuosity (e.g.Vogel et al., 2002; Vervoort and Cattle, 2003). How-ever, although numerous attempts have been made tofind either statistical relations or deterministic linksbetween soil structural data and hydraulic properties,a significant gap remains between in situ soil struc-ture/architecture and field-measured soil hydraulic prop-erties at different scales.

• Lack of a comprehensive theory of soil structure/architecture formation, evolution, quantification, andmodeling that can bridge orders of magnitude in scale

and integrate physical, chemical, biological, and anthro-pogenic impacts. Although a hierarchical organizationof soil aggregates has been well recognized (Tisdall andOades, 1982; Vogel and Roth, 2003) and fractal char-acterization of soil structure has been proposed (Perrieret al., 1999; Bartoli et al., 1998), there is still a lackof means of representing field soil structure in differ-ent scales in a manner that can be coupled into modelsof flow, transport, and rate processes (Lin, 2003; Linet al., 2005a).

Quantifying soil architecture in the field across scalesand at desirable spatial and temporal resolutions has beentechnologically limited. While landforms (e.g. digital ele-vation models or DEMs) and vegetation (e.g. land use/landcover) can now be mapped with high resolution (e.g.using Light dection and ranging or LIDAR and IKONOSearth observation satellite, respectively), there is a “bot-tleneck” phenomenon for in situ high-resolution (e.g. sub-meter to centimeter) and spatiotemporally continuous andnoninvasive mapping or imaging of subsurface architectureincluding flow networks. This technological bottleneck hasconstrained our predictive capacity of many soil and hydro-logic functions.

Defining ‘‘Hydropedologic Functional Unit (HFU)’’and its Quantification in Different LandscapesAt the hillslope scale, in the absence of detailed field inves-tigations, much of soil information needed for hydrologicmodeling is obtained from soil survey reports. However,the minimum size of soil map unit delineation in a standardsoil survey is ∼1.6 ha (Buol et al., 2003), which is oftentoo coarse for most hillslope-scale studies. Consequently,many soil map units are associations and complexes, wheredifferent soil types are mapped together as a matter ofnecessity dictated by the map scale (Soil Survey DivisionStaff, 1993). Furthermore, polygon-based mapping in tra-ditional soil surveys has resulted in soil variation beingportrayed spatially as a step function that appears onlywhen crossing from one polygon to another (Zhu et al.,2001). This does not allow the continuum of variability insoil attributes on a hillslope or within a catchment to berepresented as it should. Future development of digital soilmaps with greater spatial accuracy and resolution is neededto provide a better interface with other digital databases andto facilitate spatially distributed hydrologic modeling.

Traditional 3-D block diagrams used in soil surveysto show soil–landscape relationships can be enhancedto develop conceptual models of the landscape–soil–hydrology relationships (Figure 4). Enhanced 3-D blockdiagrams with added information of water table dynam-ics, water flow paths, hydric soils, restrictive layers, andother relevant information could significantly increase thevalues of soil survey products. As illustrated in Figure 4,classical block diagrams of soil–landscape relationships


Typichapludalffayette

Typicargiudoll

tama

Verticcumulic

endoaquollwabash

Typicargiudolldinsdale

Aquichapludollmuscatine

Typicendoaquoll

garwin

Ground waterrecharge area

(leached)

Ground waterdischarge area

(calcareous)

Glacial till

Pella

Catena

Dodgesilt loam

Pella silt loam

Lamartinesilt loam

Dodgesilt loam

Flow lines of percolating water CSLL Loached loess covering over calcareous glacial till

Calcareous siltPosition of water table in springPosition of water table in summer

Lamartine

Elevation (n)

silt loam

Mollichapludalf

downs

Alfisols Mollisols

"Edge effect" solublesalt accumulations

Hydric soil

LL

CS

Clarion

Clarion

Nicollet

Nicollet

Clarion

Okobaji

Webster

Okobaji

Harpst

Canisteo

Storden

Leached glacial till

Leached glacial

sediments

Calcareous glacial till

Calcareous glacial till or sedimentsLe

ache

d gl

acia

l till

or s

edim

ents

0 1/2 Mile

920

900

880

860

840

Intermittent pond

(a)

(b)

(c)

Muscatine1–3%

Tama2–15%

Tama2–15%

Downs2–15%

Fayette2–30%

Floodplain

Stream

Dinsdale2–15%

Wabash0–1%

Loess

Garwin0–1%

Alluvium Glacial till

Ochric Ochric Mollic Mollic Mollic Mollic Mollic

AlbicAlbic

Btargillic

Btargillic

Btargillic

Btargillic

Cg Cg

Glacialtill

Bgcambic

Bgcambic

Bgcambic

C C C

Carlislemuck muck

Figure 4 (a) Classical block diagrams used in soil surveys to show soil mapping units and catenae in relation tothe landscape (From Brady and Weil, 2004). Also illustrated are two contrasting landscape hydrology in relationto the soilscape: (b) A soil catena on a drumlin and adjacent lowlands in Dodge Co., WI, illustrating water flowdirection and seasonal water table dynamics (From Hole, 1976); (c) Pattern of soil catena and parent materials in theClarion–Nicollet–Canisteo association in Kossuth Co., IA, illustrating water and solutes in the uplands moving downinto the Clarion soil profile where they either enter the groundwater or move laterally until they are discharged furtherdownslope as return flow (Courtesy of L. Steffen, USDA-NRCS)

could be used to indicate landscape hydrology, illustratingwater flow direction and water-table dynamics. These blockdiagrams could be further linked to watersheds or physio-graphic regions to provide valuable conceptual frameworksof water movement over the landscape in different regions(USDA-NRCS, 1997).

New ways of mapping soils in greater detail andwith higher precision are desirable for precision researchand management. The concept of HFU, defined as asoil–landscape unit having similar pedologic and hydro-logic functions, has been suggested as a means ofcartographically representing important landscape–soil–hydrology functions (Lin et al., 2008). The goal of theHFU is to subdivide the landscape into similarly functioninghydropedologic units by grouping various geomorphic unitsthat have similar storage, flux, pathway, and/or residence

time of water in various soil–landscape units. These unitscan be identified and delineated using traditional soil surveymethods and data in conjunction with various digital datasources (e.g. DEM), geophysical investigations, and in situmonitoring (Lin et al., 2008). Essentially, soil map units arebetter considered as landscape units rather than individualsoil types (Wysocki et al., 2000). It is also desirable to gobeyond the pure description of soil taxonomic classifica-tions on a soil map (as traditional soil surveys did); rather,it would serve diverse applications much better by depict-ing soil functions, particularly those hydrologic functionscritical to various local land uses. Hall and Olson (1991)have challenged traditional soil mapping: “Much effort hasbeen expended on taxonomic classification of soils duringthe last few years but the importance of proper representa-tion of landscape relations within and between soil mapping


units has been virtually ignored. The same mapping unitis often delineated on convex, concave and linear slopes.This mapping results in the inclusion of areas of moistureaccumulation, moisture depletion and uniform moisture flowwithin a given mapping unit.”

Zhu et al. (2008) has proposed an approach towardprecision soil mapping through integrating the existingsecond-order digital soil map with high-resolution terrainindices and site-specific geophysical surveys. Their refinedsoil map obtained for a 19-ha agricultural landscape hada considerably reduced variability within mapping unitsand an increased precision in soil boundaries. Such amap provided a basis for specific soil property mappingthrough addition of soil coring, or monitoring, or othermeans of soil sensing/mapping. On the basis of twosoil properties important to hydrologic functions – surfacesoil texture and depth to clay layer, Lin et al. (2008)developed a map of HFUs for this agricultural landscapeand tested this map for soil moisture dynamics and nitrogenfertilizer management. Their results showed that the threebasic components making up an HFU (i.e. soil seriesor its variant, surface texture, and depth to clay layer)displayed significant differences in soil moisture. They alsoshowed that an optimal combination of hydrology (bothsoil moisture storage and drainage) and nutrient supply(nitrogen fertilizer application rate) was required to obtainoptimal growth of corn.

The HFU of different landscapes is a useful concept tobe further developed. Such a mapping of HFUs can serveas a cartographic building block to increase the knowledgetransfer and the bridging of “forms” and “functions” of soilsat different scales. This is consistent with the flexible boxmodels suggested by McDonnell (2003) and would facili-tate the prediction of ungaged basins (Sivapalan, 2003).

There is a conceptual bottleneck that needs to be resolvedfor developing a new generation of hydrologic models.That is, should a continuous field or discrete objects beused to model surface and subsurface flow? Traditionally,hydrologic processes are generally conceptualized withinthe field domain (e.g. the Navier–Stokes equation and theDarcy’s law) (Goodchild et al., 2007). Classical hydrologyhas applied findings from fluid mechanics, together withthe necessary constitutive relations, to develop sets of gov-erning equations (much the same as atmospheric and oceansciences have done). However, heterogeneities in land sur-face, hierarchical structures of soils, channel geometries,and preferential flow networks all make the land surfaceand subsurface different from the continuous-field assump-tion (Consortium of Universities for the Advancement ofHydrologic Science, Inc. (CUAHSI), 2007). It is becomingmore and more recognized that solid earth is not a con-tinuous fluid; rather, it poses hierarchical heterogeneitieswith discrete flow networks embedded in both the surfaceand the subsurface. As McDonnell et al. (2007), Kirchner

(2006), Beven (2002), and many others have noted, currentmodels in watershed hydrology are based on well-knownsmall-scale physics or theories such as the Darcy’s lawand the Richards equation built into coupled mass balanceequations. It has been observed that the dominant processgoverning unsaturated flow in soils may change from matrixflow to preferential flow under different conditions whenmoving from the pore scale to the pedon scale (Bloschl andSivapalan, 1995; Hendrickx and Flury, 2001). When mov-ing from the pedon scale to the landscape/watershed scale,our knowledge for extrapolating the Darcy–Buckingham’slaw and the Richards equation to large heterogeneous areais further constrained (Weiler and Naef, 2003). Further dis-cussion on subsurface flow network is provided later in thisarticle.

LINKING SURFACE/SUBSURFACE RUNOFFPROCESSES TO PEDOLOGICUNDERSTANDING

In a new vision for watershed hydrology, McDonnell et al.(2007) urged a paradigm shift from merely gauging the nethydrograph at the outlet of a catchment (or at the trench ofa hillslope) and using small-scale theories to model water-shed hydrology to a new one that emphasizes diagnosis(i.e. diagnosis of soil–landscape patterns and watershedfunctional traits), classification (i.e. watershed classifica-tion based on similarity indices or dominant processes),evolution (i.e. why watershed heterogeneity exists), andflow network (i.e. underlying optimality principles) acrossscales. We believe pedology has significant potential tocontribute to this new vision for watershed hydrology andto help answer “why-type” questions, as mentioned in theIntroduction. In the following, we review various aspectsof diagnostic soil–landscape features that are importantto understanding and modeling surface/subsurface runoffprocesses at the three hierarchical scales of microscopic,mesoscopic, and macroscopic levels.

Aggregate and Macropore Scale

Pedality

Through aggregation, pedality alters a soil’s pore-size dis-tribution and pore continuity/connectivity. Notably, theformation of peds creates interpedal pores that have sizeand shape different from intrapedal pores (Figure 3). Dye-tracing studies have clearly demonstrated that preferentialflow often occurs along interpedal pores in structured soils(e.g. van Stiphout et al., 1987; Lin et al., 1996). Concep-tually, we would expect the following trend of increasingcapacity to transmit water vertically among different shapesof peds: platy < blocky, prismatic < granular (Figure 3a).Higher Ksat has been reported for prismatic soil than its


blocky counterpart in silty clay loam (Bouma and Ander-son, 1977a, b). Lin et al. (1999a) showed that, dependingon texture and initial moisture, soils with prismatic pedshad either higher or lower steady-state infiltration rates thansimilar soils with blocky peds. For fine-textured soils (clayand clay loam), prismatic pedality had higher flow ratesthan blocky pedality because of common occurrence ofinterprism macropores; whereas in medium-textured soils(sandy clay loam and silt loam), interprism pores wereless significant in soils with prismatic pedality, leading toa lower water flow rate than in blocky soils (Lin et al.,1999a). The hydraulic distinctions between blocky and pris-matic ped shapes can therefore be addressed through theassociated difference in macroporosity and texture.

Conceptual understanding of pedality’s impacts on soilhydrology is intuitive, including flow pathway and flux(Figure 3). However, quantification of such impacts isless straightforward, in part because of the lack of aproper means for quantifying pedality. Pedality is usuallyexpressed strongest at the surface and decreases with depth,resulting in a general trend of increasing ped size anddecreasing ped grade with soil depth. We would also expectthat the smaller the ped size, the higher the amount ofinterpedal pores, and that the stronger the ped grade (i.e. thedistinctness or strength of ped units), the more significantthe interpedal pores. However, tillage and other human andbiological activities could significantly alter this generaltrend. Changing soil moisture also changes the expressionof soil structure (especially in shrink–swell soils) andthe relative volumes of peds and pores, adding to thecomplexity of finding mathematical solutions for modelingwater movement in structured soils.

Spherical and blocklike pedality is most commonly seenin surface soils, while subsoils generally display blocklikeor prismlike pedality. Platelike pedality is associated withsurface sealing, compacted soil layer (such as plowpan),or sedimentation-inherited C horizon. Two structurelesscases – massive (commonly associated with heavy clayeysoils) or single grains (associated with sands) – are alsoobserved in soils. Often, a soil horizon’s pedality is amixture of several ped sizes (especially with compoundpedality), with one dominant ped shape and grade. How-ever, field qualitative descriptions of pedality often containsome degree of subjectiveness, leading to possible incon-sistency among individuals who describe it.

In soils with compound pedality, Lin et al. (1999a) foundthat primary pedality had limited impact on infiltration atwater potential of > −0.03 m. Quisenberry et al. (1993)and Nortcliff et al. (1994) also reported that in a soil withboth primary and secondary peds, preferential flow occurredmostly along secondary ped faces.

MacroporesSoil macropores encompass many types of structural open-ings in soils, such as desiccation cracks, pore space in

between peds, animal burrows, and channels formed byliving and dead roots. From a hydrologic functional pointof view, these features often lead to preferential flow orbypass flow (Figure 3b). The definition of macropores,especially their size range, however, remains diverse. Someresearchers have defined the size range of macropores onthe basis of flow function: that is, whether flow is subjectedto capillary force or not. Others have used morphologi-cal approach to define macropore size. It appears that bothfunctional and morphological approaches should be com-bined to define macropore so that meaningful interpretationscan be made in a comparable manner. As suggested by theSoil Science Society of America (SSSA, 1997), the minimalsize of macropores is 0.075 mm in diameter. Macroporesare also commonly defined as the pores correspondingto ≥ −0.03-m water potential, that is, ≥0.5 mm in radiusfor cylindrical pores or ≥ 0.5 mm in width for planar pores.Most channels formed by the main roots of annual cropsand earthworms have a minimal radius of about 0.5 mm.However, soil pipes formed by tree roots or animal burrowsare often much larger, with pore diameter often greater thanseveral centimeters.

Among various types of macropores, the general trendof increasing capacity to transmit water is (Lin et al.,1999a): vugh (isolated large void, usually irregular and notnormally interconnected with other voids of comparablesize) < channel (tubular-shaped void) < fracture (planarvoid between aggregates) < packing-void (void formed byrandom packing of single skeletal grains or peds that do notaccommodate each other). Such a trend is supported by dye-tracing studies of Bouma et al. (1977) and Lin et al. (1996);both found the similar order as evidenced by dye-stainedareas in soils with these types of macropores.

On the basis of steady infiltration rates measured on 96soil horizons in Texas, Lin et al. (1999b) demonstrated thatsoil structure was crucial in characterizing hydraulic prop-erties in macropore flow region, whereas texture had majorimpact on those hydraulic properties controlled by microp-ores. Lin et al. (1997) showed that steady-state infiltrationrates at zero tension (i0) were greatest for clay-textured soilswith well-developed structure and macroporosity, whileclayey soils with poorly developed structure had low infil-tration rates, leading to high variability in i0 for clayey soils.At more negative supply water potential, where macroporeswere less active, infiltration rates were greatest for soilsdominated by sand.

Soil Hydromorphology and Hydric Soil FieldIndicators

Actions of water on soils often result in the formationof distinctive morphological features that are indicative offield water movement. Soil horizons, for instance, oftendevelop in response to water movement (such as leach-ing or accumulation of certain materials). Even without the


Mnd/Fed---Bt

<0.06

0.065–0.10

>0.1010

0

Elevation (m)

140 m

210 m

Figure 5 Landscape distribution of dithionite-extractableMn/Fe ratio (Mnd/Fed) in the Bt soil horizon in a 3-hafield in the Peidmont region of North Carolina. The mapwas generated by kriging 60 sampling points occupyinga variety of geomorphic positions. Dash lines indicate thecenter of topographic low areas

formation of visible morphological features, soil chemistryand biology may provide clues regarding field-scale watermovement. For example, difference in mobility betweenredox-sensitive Mn and Fe in acid soil systems allowssecondary Mn/Fe ratios to be used as pedochemical indi-cators of field-scale throughflow (McDaniel et al., 1992)(Figure 5). A subset of soil morphological characteristics,known as hydric soil indicators (USDA-NRCS, 1998), isdirectly related to a specific set of hydrologic conditions.Soil morphology is also the testimony of long-term per-sistent flow and transport processes that result in visiblepedological features such as clay films, tonguing, plinthites,and diverse soil structures that are of hydrologic sig-nificance (Figure 3). Soil macro- and micromorphologythus have long been used to infer soil moisture regimes,hydraulic properties, and landscape hydrologic processes(e.g. Bouma, 1992; Lilly and Lin, 2004; Lin et al., 2005a).

Soil hydromorphology deals with soil morphologi-cal features (especially redoximorphic features or redox)caused by water and their relations with soil hydrology.Redox features (formerly called mottles and low chromacolors) are formed by the processes of alternating reduc-tion–oxidation due to saturation–desaturation and the sub-sequent translocation or precipitation of Fe and Mn com-pounds in the soil (Soil Survey Staff, 1999). Types of redoxfeatures include (i) redox concentrations as accumulationsof Fe/Mn oxides (e.g. nodules, concretions, masses, andpore linings), (ii) redox depletions as low-chroma (≤2)features formed by removal of Fe oxides (including Fedepletions and clay depletions), (iii) reduced matrix thatchanges color upon exposure to air due to Fe(II) oxidationto Fe(III), and (iv) a reaction to an α,α-dipyridyl solu-tion if the soil has no visible redox features (Vepraskas,

1992; Soil Survey Staff, 1999). Redox features, which areusually considered hydric soil indicators, exclude thosehydric soil indicators composed of C and S (USDA-NRCS, 1998).

Hydric soils are defined as soils that formed under con-ditions of saturation, flooding, or ponding that lasted longenough during the growing season (repeated periods ofmore than a few days) to develop anaerobic conditions inthe upper part (usually 0.15–0.3 m) of soil profiles (USDA-NRCS, 1998). Hydric soils are one of the three requirements(along with hydrophytic vegetation and wetland hydrology)for identifying jurisdictional wetlands in the United States.Hydric soil field indicators include a variety of features thatare regional and texture-based, but all are formed predom-inantly by the accumulation or loss of Fe, Mn, C, or Scompounds (USDA-NRCS, 1998). While indicators relatedto Fe/Mn concentrations or depletions are the most com-mon, other features (e.g. sulfide and various combinationsof carbon accumulations) have been used in specific kindsof soils that do not develop redox features. There are alsoso-called problem soils that are seemly hydric soils butwhose morphologies are difficult to interpret or seem incon-sistent with the current landscape, vegetation, or hydrology(Veneman et al., 1998). These include soils formed in gray-ish or reddish colored parent materials, soils with high pHor low organic matter, Mollisols with thick dark A horizon,Vertisols with shrink–swell, soils with relict redox features,and disturbed soils such as cultivated soils and filled areas(USDA-NRCS, 1998; Rabenhorst et al., 1998). Relict redoxfeatures do not reflect contemporary or recent hydrologicconditions of saturation and anaerobiosis; rather, they werelikely formed during past geological wetter climates. Typ-ically, contemporary and recent hydric soil morphologieshave diffuse boundaries, while relict redox features haveabrupt boundaries (USDA-NRCS, 1998).

Certain redox patterns occur as a function of the pat-terns in which the ion-carrying water moves through thesoil and as a function of the location of aerated zones inthe soil. Characteristic color patterns are thus created bythe reduced Fe and Mn ions removed from a soil if ver-tical or lateral water flow occurs, or the oxidized Fe andMn precipitated in a soil if lack of sufficient water flux.Consequently, the spatial relationships of redox depletionsand redox concentrations may be used to interpret waterand air movement in soils (Vepraskas, 1992). Interpretingdirections of water movement from redox patterns is easi-est when the features have a consistent relationship withsoil structure including macropores. For example, whenredox depletions occur around macropores and redox con-centrations occur within matrix, it would suggest that waterinfiltration has occurred along macropores and reducingcondition has developed there because of perched saturatedlayers (Vepraskas, 1992). As another example, when redox


concentrations occur around macropores and redox deple-tions occur within matrix, it would indicate that soil matrixis wet for periods long enough for reducing condition tobe maintained while macropores become aerated becauseof faster drainage or plant roots (such as in rice plant) thattransport air to macropores when the soil is still flooded(Vepraskas, 1992).

Infiltration-excess RunoffA number of processes can cause the reduction in the soil’sinfiltration capacity, leading to infiltration-excess runoff.These include surface sealing, soil freezing, hydrophobicity,and others. Infiltration-excess runoff events, however, canbe minimized by proper management of the soil surfacesuch as mulching and crop residue cover. The followingelaborates each of these aspects.

• A surface seal or crust is caused by the breakdownof soil aggregates through raindrop impact or througha slaking process under saturated conditions (Ellisonand Slater, 1945; Tackett and Pearson, 1965). Finesoil particles are dislodged from soil aggregates andare deposited as a thin layer over the soil surface.Through this process, large soil pores which would havebeen available for infiltration are “sealed” with the finesoil particles because the slaked clay particles are gel-like. Surface sealing and crusting occurs in virtually allarable soils during ponded infiltration or flood irrigation.The abrupt contact of the soil surface with excess watercauses weak aggregates to disintegrate and slake. Themigrating smaller particles can quickly form a seal onthe soil surface within a short period of time.

• The infiltration capacity of a soil can also be greatlyreduced when the soil freezes (seasonally or perma-nently). Concrete frost is often nearly impermeable andcan be found most often in fine-textured soils (Zuzelet al., 1982; Dunne and Black, 1971). In agriculturalareas, erosion from a partially thawed soil surface canbe excessive. However, the infiltration capacity throughsoils that are initially dry or have large macropores isoften minimally affected by soil freezing (Harris, 1972).The thick litter layer and large macropores found intypical forest soils minimize the potential effects of soilfreezing on infiltration (Lutz and Chandler, 1946). Oftenin mountainous areas the deep snow cover insulates theground and prevents soil freezing. Crawford and Legget(1957) observed that the frost depth was reduced about0.3 m for every 0.3 m of undisturbed snow cover.

• Extensive field studies have shown that many soilsare susceptible to hydrophobicity under dry condi-tions (Dekker and Ritsema, 2003). Many forest soilscan become seasonally hydrophobic through leachingof the hydrocarbons in the litter layer and subse-quent drying on the mineral soil; however, these soilsbecome hydrophilic when soil moisture levels exceed

12–25% (Huffman et al., 2001). A hydrophobic soillayer is often developed after intense wild fires. Burn-ing organic matter in a hot fire releases hydrocarbonsinto the atmosphere as a gas, which penetrates intosoil aggregates at the mineral soil surface, condenses,and covers the aggregates with waxy substance after itcools (DeBano et al., 1970). This waxy coating repelswater and greatly reduces the infiltration of the soil.Often, erosion from steep forested hillslopes after ahot-burning fire can be excessive. The thickness andpersistence of hydrophobic layers varies primarily withburn severity; however, vegetation type, soil texture,and soil moisture are also important. Thick hydropho-bic layers (i.e. >0.03 m) often persist for more than ayear (Huffman et al., 2001).

• Additional complicating factors may also reduce a soil’sinfiltration capacity, including soil swelling, soil insta-bility, entrapped air, and soil layering. For example,infiltration into layered soil is always slowed down atthe layer interface because of the hydraulic discontinu-ity (either different hydraulic conductivity or moistureholding capacity at a given soil water potential). In thecase of a fine-textured layer overlying a coarse-texturedlayer, “fingers” may develop after infiltrating water porepressure overcomes the hydraulic discontinuity, form-ing fingering flow that may enhance the subsequentinfiltration. Given the right condition, infiltration intostructured, or macroporous, or cracking soil takes placein only a fraction of total soil surface, called fractionalwetting (i.e. the fraction of total surface area that is wet-ted), thus vitiating the classical assumption of uniformadvancement of the wetting front. Such fractional wet-ting may either reduce or accelerate infiltration depend-ing on the initial and boundary conditions.

Horizon and Profile Scale

Soil Profile Architecture and Water-restricting SoilLayers

Soil profile is a vertical section of the soil through all itshorizons and extending into the C horizon, while soil solumrefers to only the portion of a soil profile above the Chorizon. All materials above fresh, unweathered bedrock arealso referred to as regolith, which is generally equivalentto a soil profile.

In the US Soil Taxonomy, a total of 8 diagnostic surfacehorizons (called epipedons) and 23 diagnostic subsurfacehorizons (called endopedons) have been identified, alongwith 30 additional diagnostic features for mineral soils(Soil Survey Staff, 2006). The presence or absence of thesehorizons plays the major role in determining which class asoil falls in Soil Taxonomy.

Numerous water-restricting subsurface soil horizons andfeatures have been identified in Soil Taxonomy, including


the following, with their major distinguishing characteris-tics, highlighted (genetic symbols are also shown in paren-thesis for diagnostic horizons) (Soil Survey Staff, 2006):

• Duripan (Bqm): hardpan, strongly cemented by silica.• Fragipan (Bx): dense pan, seemingly cemented when

dry, brittle when moist, and slake when submerged inwater. Typically has redox features and bleached prismped faces.

• Glacic layer (Bf or Cf): massive ice or ground ice inthe form of ice lenses or wedges.

• Ortstein (Bhm): cemented by humus and aluminum.• Permafrost: a perennially frozen soil horizon that

remains below 0 ◦C for ≥2 years in succession.• Petrocalcic (Ckm): carbonate cemented horizon.• Petrogypsic (Cym): gypsum cemented horizon.• Placic (Csm): thin pan cemented by iron (or iron and

manganese) and organic matter.• Anhydrous conditions: a soil layer of cold deserts and

other areas with permafrost (often dry permafrost) andlow precipitation.

• Aquic conditions: continuous or periodic saturation andreduction, with redox features.

• Cryoturbation: frost churning on permafrost table, ori-ented rock fragments, and silt caps on rock fragments.

• Densic contact: a contact between soil and densicmaterials, without cracks or with ≥10 cm crack spacing

• Densic materials: relatively unaltered but noncementedmaterials that roots cannot enter except in cracks(including till, volcanic mudflows, mine spoils, or othermechanically compacted materials).

• Fragic soil properties: essential properties of a fragipan,but lacks layer thickness and volume requirement fora fragipan.

• Gelic materials: materials that show cryoturbationand/or ice segregation in the active layer (seasonal thawlayer) and/or upper part of the permafrost.

• Lamellae: thin layer of oriented silicate clay accumula-tion.

• Lithic contact: boundary between soil and a coherent(often indurated) underlying material.

• Lithologic discontinuities: stone lines and others.• Paralithic contact: contact between soil and paralithic

materials, without cracks or with ≥10-cm crack spacing.• Paralithic materials: partially weathered bedrock or

weakly consolidated bedrock (such as sandstone, silt-stone, or shale).

• Petroferric contact: boundary between soil and a thinironstone sheet.

• Plinthite: dark red redox concentrations that changesirreversibly to ironstone on exposure to repeated wettingand drying.

Other subsoil horizons might also act as an aquitard oraquiclude to downward moving water, ultimately resulting

in seasonal PWT and water moving laterally within the soilas subsurface throughflow (Busacca, 1989; Kemp et al.,1998). These include the following diagnostic subsurfacesoil horizons (with their genetic symbols indicated inparenthesis):

• Agric (A or B): silt, clay, and humus accumulationunder cultivation just below plow layer.

• Argillic (Bt): silicate clay accumulation.• Glossic (E): tongue resulting from the degradation of

an argillic, kandic, or natic horizon.• Kandic (Bt): argillic, kaolinite clays (low activity).• Natric (Btn): argillic, high in sodium, columnar, or

prismatic structure.• Oxic (Bo): highly weathered, primarily mixture of Fe,

Al oxides and nonsticky-type silicate clays.• Spodic (Bh, Bs): organic matter, Fe and Al oxides

accumulation.

In addition, stratified or dense geological materials (C orR horizons) also often develop a hydrologically restrictivelayer that leads to PWT and lateral water movement.The importance of soil–bedrock interface and bedrocktopography to subsurface stormflow has been recentlyrecognized (e.g. Onda et al., 2001; Freer et al., 2002;McGlynn et al., 2002).

Fragipan as an Example: Its Extent, Formation,and Impacts on Perched Water Table (PWT) andHillslope/Catchment Runoff

A query into the US Department of Agriculture(USDA) national soils database indicated that there are∼16.5 million ha fragipan soils in the United States, mostlydistributed in the east and southeast (Figure 6). Othercountries, such as New Zealand, Scotland, and Italy, havealso reported fragipan soils (Soil Survey Staff, 1999).This very slowly permeable pan is one of the manywater-restricting soil layers that frequently cause PWTsand control VSA hydrology. Soils having PWTs occupy∼82 million ha in the United States (McDaniel et al., 2008).

The processes that produce fragipans are imperfectlyknown, variously attributed to physical ripening, the weightof glaciers, permafrost processes, and other events duringthe Pleistocene (Smeck and Ciolkosz, 1989; Soil SurveyStaff, 1999). Some of the properties of fragipans areinherited from buried paleosols. Fragipans most commonlyoccur in soils that formed under forest vegetation. Theupper boundary of most fragipans has a narrow depthrange of about 0.5–1 m below the surface, if the soil isnot eroded. It is interesting to note that fragipans formonly in soils in which water moves downward throughthe profile and they are commonly at depths that rarelyfreeze (Soil Survey Staff, 1999). The polygonal networkof bleached materials in fragipans is formed by reduction


Geographic extent of soils where:classification similar to '*fragi*'

Acres per soil survey area (total = 40 683 703)

Acres notreported

Less than5472

5487 to24 162

24 209 to61 411

61 541 to598484

WA

WY

ND

MN

WI

IA

IL IN

GA

FL

MI

ME

RL

ID

SD

NE

KS

OK

TX

ORID

MT

NV

CA

AZNM

COUT

Fragipan

Figure 6 A general distribution map of soils with fragipans in the United States, including all soil series that have ‘‘fragi’’anywhere in their taxonomic classification string (such as Fragiaqualfs, Fragiudalfs, Fragixeralfs, Fragiboralfs, Fragiudults,Fragiaquults, Fragiaquods, Fragiorthods, Fragiaquepts, Fragiochrepts, and others). The map was generated using theSeries Extent Mapping tool (available at http://www.cei.psu.edu/soiltool/semtool phase3.html), which usesthe SSURGO database. The inset shows a soil profile from east-central Pennsylvania, where the fragipan starts at ∼0.5 mdepth and extends to over 1.2 m

of free iron after water has saturated the cracks (Figure 6inset).

Dense, slowly permeable fragipans are important control-ling factors in VSA hydrologic processes in heterogeneouswatersheds (Gburek et al., 2006). Needelman et al. (2004)showed that hillslopes with fragipan-containing soils pro-duced considerably more runoff than did those withoutfragipans. Even within a relatively homogeneous catch-ment comprising one fragipan-containing soil series, thevariable depth to the fragipan also gives rise to VSAhydrology, which in turn influences the spatial pattern ofrunoff generation (Figure 7). Many years’ monitoring in thePalouse Region of northern Idaho and eastern Washingtonby McDaniel et al. (2008) showed that the spatial distri-bution of saturation-excess runoff is largely controlled bythe distribution of fragipan and its varying depth from thesurface (Figure 7). Areas of the catchment where fragipansare relatively close to the surface tend to become saturatedmore quickly and generate more saturation-excess runoff.Subsurface lateral flow on top of the fragipan accounts forredistribution of up to 90% of the precipitation receivedon site during late winter and early spring in the studyby McDaniel et al. (2008). The combination of low drain-able porosity, relatively shallow depth to the fragipan, and

relatively high lateral Ksat in surface soil layers create avery “flashy” hydrologic system (McDaniel et al., 2008).

Saturation-excess RunoffStrictly speaking, the term saturation means 100% porespace filled with water. In reality, field soil saturation ismore a “satiation,” meaning <100% pore space filled withwater (because of air bubbles etc.), but with free waterpresent. Three types of soil saturation/satiation are definedin soil survey (Figure 8) (Soil Survey Staff, 2006):

• Endosaturation: The soil is saturated with water in alllayers from the upper boundary of saturation to a depthof 2 m or more from the mineral soil surface.

• Episaturation: The soil is saturated with water in one ormore layers within 2 m of the mineral soil surface andalso has one or more unsaturated layers with an upperboundary above a depth of 2 m, below the saturatedlayer(s). This is commonly associated with PWT ontop of a relatively impermeable layer. The gleying byepisaturation is sometimes called pseudo-gley or falsegley, in contrast to true gley caused by endosaturation.

• Anthric saturation: This is a special kind of saturationthat occurs in cultivated and irrigated (flood irrigation)soils.


P1

P2

XWCR2XWCR1

Flume

1.21.11.00.90.80.70.60.50.40.3

WA

OR ID

20

020

4060

80

100

0

020

40

6080

100

120

140

160

180

2040

6080

100

120

140

160

180

120

140

160

180

10

00

2040

6080

100

120140

160180

180 160 140 120 100 80 60 40 20 0S

WE

N

160180

180

180 160 140 120 100 80 60 40 20 0

160 140 120 100 80 60 40 20 0

140 120 100 80 60 40 20 0

100

75

50

25

0

100

75

50

25

0

100

75

50

25

0

20

20

10

0

10

20

10

0

0

3/13/01 - 12:00

3/13/01 - 18:00

3/14/01 - 12:00

0

20

40

60

DEC JAN FEB MAR APR MAY JUN

PW

T h

eigh

t (cm

)

Top offragipan

Soilsurface

(b)

(c)

(a)

Figure 7 A case study showing the fragipan’s control on the spatial distribution of soil profile saturation in the PalouseRegion of northern Idaho and eastern Washington: (a) The study site location (inset) and a block diagram showing depthto fragipan in meters WCR1 and WCR2 are locations of soil water content probes; P1 and P2 are locations of pedonsampling pits; dashed white line shows location of hydraulic conductivity sampling transect; black dotted rectangleshows location of the hydrologically isolated of the hydrologically isolated hillslope plot (see MCdaniel et al., 2008,for more details). Black circles indicate location of monitoring wells. Block distances are in meters; (b) An example ofperched water table dynamics recorded by pressure transducer above the fragipan; (c) Shading indicates the percentageof the soil profile above the fragipan that was saturated. Sequence represents a 24 h period coinciding with peak runoffgeneration

Depending on the duration of saturation and whether ornot reduction occurs, two conditions are associated withsoil saturation (Soil Survey Staff, 2006):

• Aquic conditions: continuous or periodic saturation andreduction occur, leading to redox features (gleying).

• Oxyaquic conditions: saturated but not reduced and thusno redox features. This may be related to transient watertable or flashy soil hydrologic conditions.

A combination of topography, soil architecture below thesurface, and vegetation largely determines the location andfrequency of saturation-excess runoff. Key soil attributescritical to understanding the processes leading to saturation-excess runoff include (i) depth to a hydraulically restrictivesoil or bedrock layer, (ii) change in Ksat and drainableporosity with soil depth, (iii) change in bulk density

and saturated moisture content with soil depth, (iv) soilhorizonation and effective vertical versus lateral Ksat, and(v) preferential flow in soil profiles. Each of these factorsis further discussed in the following:

• The depth to a hydrologically restrictive layer is oneof the most critical parameters in understanding VSAhydrology. This depth, which could be either thedistance from the soil surface to a soil horizon that limitsvertical water movement or a bedrock, is often referredto as the soil depth in VSA hydrology. Obviously,for the same amount of water input, a shallow soilwill reach saturation leading to runoff sooner and morefrequently than a deeper soil. The soil depth not onlydetermines the maximum water volume that a soilprofile can hold before runoff is generated, but also


Regional water table

(e.g., clay lense)

Spring

Endoaquic

Soils with poornatural drainage

Epiaquic

Stream

Well-drained soil

Perched water table

Impermeable layer

Figure 8 An illustration of the difference between episaturation and endosaturation: episaturation is from the top andendosatuation is from the side or bottom. This cross section of a landscape also shows the regional versus perchedwater tables in relation to three soils, one well drained and two with poor internal drainage. The soil containing theperched water table is wet in the upper part, but unsaturated below the impermeable layer, and therefore is said to beepiaquic, while the soil saturated by the regional water table is said to be endoaquic. This cross section also illustratesthe importance of subsurface architecture for understanding hillslope hydrology (From Brady and Weil, 2004)

directly relates to the water volume that a soil profilewill hold before a PWT is developed. At this point,large macropores become active leading to downslopelateral flow or subsurface stormflow (Whipkey, 1965).Once this subsurface stormflow is generated, waterfollows the topography of this impeding layer. Recentstudies have provided clear evidence that water oftenfollows bedrock topography rather than the soil surfacetopography as assumed in many hydrologic models(Burns et al., 1998; Freer et al., 2002). Although soildepth and the topography of water-impeding layer areclearly important factors for understanding hillslope andcatchment hydrology, there are few tools available toreliably map these features over large areas.

• Soil Ksat and drainable porosity are commonly assumedto have exponential decline with soil depth in hydro-logic models (Beven and Kirkby, 1979; McDonnell,2003; Weiler et al., 2005). This holds in many solumsfrom organic-rich top layers to more compacted restric-tive subsoil layers (Kendall et al., 1999; Brooks et al.,2004, 2007). For example, Beven (1982) demonstratedusing experimental data taken from hillslope hydrol-ogy experiments on 24 soils in predominantly forestedlandscapes that both Ksat and soil porosity decreasedexponentially with depth below the soil surface. Theseexponential decay functions, however, were not as con-sistent when later examining 38 soils from the broader

database presented by Holtan et al. (1968), (Beven,1984). When deeper soil profiles are considered, thatis, including C horizons and soil layers beneath water-restrictive layers (Figure 8), then such an exponentialdecay function is misleading. As illustrated by Westet al. (2008) for soils in the Southern Piedmont of Geor-gia, five of ten sites had a lower soil horizon’s Ksat

being higher than the overlying horizons. When all siteslumped together, mean Ksat in C horizons was 2.5 timeshigher than the overlying BC and Bt2 horizons (Westet al., 2008). Lin (1995) also documented that field Ksat

(approximated by steady-state infiltration rates at zerotension) in many of the 18 soil profiles measured inTexas did not follow exponential decline trend from thesoil surface to ∼2 m depth. Drainable porosity in deep,freely draining soils is often defined as the differencebetween saturated moisture content and field capacity.In soils dominated by saturation-excess runoff due to arestrictive layer, however, free drainage does not occuras it would in deep soils. During the wet season a PWTforms, which on sloping ground drains primarily by lat-eral flow or has very little drainage on relatively flatground. At equilibrium soil water above the water tableis held under pressures equivalent to the elevation abovethe water table. Thus, the drainable porosity for shallowsoils is the difference between saturated moisture con-tent and the moisture content at the soil surface, which


is higher than field capacity. PWT fluctuations in soilshaving a small drainable porosity can be very dynamic,and surface runoff will be more “flashy” relative to soilshaving a larger drainable porosity (Dunne et al., 1975).

• Saturated soil moisture (which can be derived frombulk density) has a similar effect on the generationof surface runoff as soil depth, because it determinessoil water storage capacity. Soils having low saturatedmoisture content can store less overall water, causingmore frequent and greater amounts of saturation-excessrunoff. Like Ksat, saturated moisture content typicallydecreases with solum depth from organic-rich top layersto compacted restrictive layers, resulting in less overallwater storage at greater soil depths (Beven, 1982, 1984;Brooks et al., 2007). The bulk density of the soil is alsothe most widely used parameter to estimate the amountof open pore space. Pedotransfer functions have usedbulk density along with soil texture to incorporate vari-ability in soil structure into effective Ksat measurements.However, these parameters by themselves are oftenmore appropriate for explaining micropore flow ratesrather than macropore flow as macropores are often notwell represented by small soil cores used to determinebulk density (Beven, 1984; Lin et al., 1999b).

• Soil horizonation impacts the overall effective verticalversus lateral Ksat in a soil profile. The depth distri-bution of vertical Ksat is important in defining wherein the soil profile will begin to saturate (i.e. definingthe depth to a restrictive layer) and the relative magni-tude of lateral Ksat will determine runoff patterns ina catchment dominated by VSA hydrology. Surfacerunoff will be confined primarily to toe slopes or atsharp breaks in the slope from steep to flat in soils hav-ing large lateral Ksat. Surface runoff patterns will bemore widespread and correlated with variability in soildepth in areas with low lateral Ksat (Dunne et al., 1975).The challenge for hydrologists trying to predict subsur-face lateral flow or stormflow at the hillslope scale is todetermine representative lateral Ksat. Using small soilcores it is relatively easy to measure Ksat in the labora-tory but these measurements may not represent the Ksat

at larger scales. Without a method to physically charac-terize soil architecture at the hillslope scale, especiallylarge macropores and their network, Ksat becomes a cal-ibration parameter in most hydrologic models (Graysonet al., 1992; Wigmosta et al., 1994). Most likely, thecalibrated Ksat values will not be able to adequatelyrepresent the flow of water through a hillslope withoutaccounting for differences in soil structure in soil pro-files and how macropores are distributed within eachsoil layer. Tracer and isotope studies often reveal thatsimplified representations of how water flows through ahillslope are inadequate to represent the true flow path

(Vache and McDonnell, 2006). A hillslope-scale exper-iment conducted by Brooks et al. (2004) showed thatthe hillslope-scale Ksat was 15, 5, and 2 times greaterthan the small-scale measurements in the A, Bw, and Esoil horizons, respectively.

Preferential Flow in Soil Profiles

Preferential flow is the process whereby water and dis-solved chemicals move by preferred pathways at an accel-erated speed through a fraction of a porous medium.Vervoort et al. (1999) suggested that preferential flow insoil profiles is related to soil structural differences (e.g.macropore flow and fractional flow) or textural differ-ences (e.g. fingering flow and funnel flow). Differentpedological features are indicative of possible preferen-tial flow in various field soils, especially if combinedwith landscape observations. These include: (i) soil struc-tural features (such as pedality, coatings, macropores,and slickensides); (ii) redox features (indicating water-restricting layer and nonuniform water movement); (iii)water-restrictive soil layers (such as sloping lamellae indi-cating the likely occurrence of funnel flow); and (iv)lithologic discontinuities (indicating significant changesin particle-size distribution and thus possible fingeringflow or other types of preferential flow). A simple fieldtechnique was devised by Bouma (1997) to measure pref-erential flow in clay soils as a function of rain inten-sity/quantity and initial soil moisture content. Derivingcracking patterns from theoretical soil swell–shrink char-acteristics turned out to be difficult, and very small pores(such as slickenside fissures shown in Figure 3) witha volume that cannot be measured with existing phys-ical methods can conduct large volumes of water (Linet al., 1996).

Fluhler et al. (1996) have suggested three regimes offlow and transport within a soil profile during a preferentialflow process: (i) lateral distribution flow in the attractorzone where preferential flow is initiated; (ii) downwardpreferential flow in the transmission zone where watermoves along preferential flow pathways and bypasses aconsiderable portion of the soil matrix; and (iii) lateraland downward dispersive flow in the dispersion zone wherepreferential flow pathways are interrupted and water flowbecomes more or less uniform again. This model appearsto capture the general characteristics of vertical preferen-tial flow in many soil profiles, and is also consistent withthe depth function of soil hydraulic conductivity discussedearlier.

On the basis of a review of studies documentingsoil microbial biomass distributions with soil depth (e.g.Van Gestel et al., 1992; Dodds et al., 1996; Richter andMarkewitz, 2001; Blume et al., 2002; Taylor et al., 2002;Fierer et al., 2003), the system of Fluhler et al. (1996) canbe applied. Previous studies have demonstrated a consistent


pattern of changing microbial biomass size and activity dis-tribution, characterized by three broad zones with distinctbiogeochemical potentials that correspond to the three flowzones of Fluhler et al. (1996): (i) attractor zone, equiva-lent to the A horizon and representing high-biomass surfacesoils under the strong influence of plant roots, moisture, andtemperature; (ii) transmission zone, equivalent to B and Chorizons and representing lower more spatially heteroge-neous biomass than in the attractor zone (Konopka andTurco, 1991; Rodrıguez-Cruz et al., 2006); and (iii) dis-persion zone, representing higher-biomass, water-capturezones at the soil–bedrock interface or right above a water-restricted soil layer because of moisture and more nutrient-rich conditions resulting from impeded or lateral flow (Busset al., 2006). These three zones are distinguished from“deep-subsurface” aquifers and geologic materials, manyof which have extremely low biomass (Kieft et al., 1995).

Catena and Catchment Scale

Topography: Linking Hydrology with Pedology

The topography of a landscape is responsible for providingthe overall direction of water flow and hydraulic gradientfor downslope subsurface stormflow (Dunne et al., 1975;see also Chapter 112, Subsurface Stormflow, Volume 3).In VSA hydrology, the spatial variability of soil moisturebefore an event and of subsurface stormflow during theevent dictates where saturation-excess runoff will occur onthe landscape. Topographically convergent toe slopes oftenare the wettest locations leading to saturation-excess runoff.

In addition to largely controlling the distribution andmagnitude of water flow through a landscape, topographyis also considered one of the five major factors controllingsoil formation. In the classic work by Russian geologistV.V. Dokuchaev and later extended by Jenny (1941), thefive major soil-forming factors include climate, organisms,topography, parent material, and time. Topographic patternsdictate the way in which mass and energy are distributedwithin a landscape. The orientation of a hillslope also dic-tates the amount of solar radiation received, and thereforelargely controls the rates of evaporation, transpiration, andsnow ablation. The topography controls wind fields leadingto variability in evaporation, snow drift, and deposition.The topography also greatly influences rates of soil ero-sion and deposition. The combination of these effects leadsto spatial patterns of vegetation diversity, biomass produc-tion, and soil variability (see Chapter 12, Co-evolution ofClimate, Soil and Vegetation, Volume 1).

There is a close feedback between hydrology and soildevelopment within a landscape that is driving by differ-ences in topography. Topography drives the distributionand transport of water and sediment, which in turn influ-ences soil development (e.g. the development of restrictivelayers through elluviation/illuviation processes). This soil

development can then feedback to the variability in waterdistribution and transport over the landscape.

With the ever-increasing numeric processing power avail-able today and the availability of spatially detailed eleva-tion maps, hydrologists have been able to better representlandscape processes using various means from simple topo-graphic indices to detailed simulation models. Geographicinformation system (GIS) models can use detailed elevationmaps to describe topographic influences on water fluxesthroughout a landscape. For example, Moore et al. (1991)summarized a wide range of topographic attributes that canbe used to map various hydrologic, geomorphic, and bio-logical processes. The most well known static topographicindex for representing the influence of topography on thespatial distribution of saturation-excess runoff that utilizesthe upslope catchment area and local slope was incorporatedinto TOPMODEL (Beven and Kirkby, 1979). This simplewetness index utilizing only topography has been success-ful in describing areas generating saturation-excess runoffpatterns during wet seasons. However, growing evidencehas pointed out the critical importance of the topography ofunderlying bedrock or water-restricting soil layer in defin-ing water flow paths and hence soil wetness distribution(e.g. Onda et al., 2001; Freer et al., 2002; McGlynn et al.,2002; McDonnell, 2003).

Catena

Spatial distribution of topographic attributes that charac-terize water flow also capture spatial variability of soilattributes at the hillslope scale. Because of the processesthat occur along a hillslope, soils may be quite differentin different portions of a landscape, but these processesand relationships may be similar across a larger area, par-ticularly if geomorphology and stratigraphy are similar.Numerous investigations of catenae have been completedin order to address this phenomenon (e.g. Veneman andBodine, 1982; Evans and Franzmeier, 1986; Pennock andde Jong, 1990; Stolt et al., 1993; Khan and Fenton, 1994;Thompson et al., 1998). It is now believed that the greatestvariability in certain soil properties within a physiographicregion may occur along a hillslope rather than from oneside of the region to the other (e.g. Pennock and de Jong,1990; Lin et al., 2005b). This warrants a careful investi-gation and understanding of hillslope soil variability andcatenae before making broad generalizations about soil vari-ability within a physiographic region.

Water table depth (drainage condition) and fluxes ofwater, solutes, and sediments typically differ in soilsalong a catena (Schaetzl and Anderson, 2005). However,catenae in different climatic and physiographic regions mayexhibit markedly different relationships between soil andhydrologic properties. In many low-relief landscapes ofhumid regions, proximity of a water table to the soil surfaceincreases with distance away from stream or drainage way.


An example of this can be seen on the broad, flat, low-relief Atlantic coastal plain in the southeastern UnitedStates. The most poorly drained soils are found toward thecenters of the broad interstream divides, while the mostwell-drained soils are restricted to the edges of the flatsand slopes closest to the streams and estuaries (Danielset al., 1971; Daniels et al., 1984). The opposite trend isseen in the higher-relief landscapes associated with thenearby Piedmont region. Water table proximity to the soilsurface decreases with increasing distance away from thestreams or drainage ways. As a result, the well-drainedsoils occupy the uplands and the more poorly drained soilsoccupy the lower slope positions near the streams (Danielset al., 1984). Similarly, fluxes associated with overlandflow, subsurface lateral flow, percolation, capillary rise,and return flow will also vary along a catena in differentclimatic and physiographic regions (Schaetzl and Anderson,2005; Sommer and Schlichting, 1997). These fluxes willvary spatially and temporally, resulting in VSA hydrologicprocesses.

Two opposite trends of soil depth and soil wetnessdistribution along steeply sloped catenae are illustratedhere. In the humid forested catchment developed from shaleon the ridge of central Pennsylvania (within the Ridge andValley physiographic region), soil thickness and wetnessgenerally increase in concave hillslopes from hilltop tovalley floor, while that of the convex and planar hillslopeswithin the same catchment shows no clear difference fromthe hilltop to the hill bottom (Lin et al., 2006b). In contrast,in the rugged Hill Country of central Texas with stair–steptopography developed from limestone (part of the EdwardsPlateau physiographic region), soil thickness and infiltrationcapacity decrease from the hilltop (upper riser with steeperslopes) to the hill bottom (tread with flatter slope) (Wilcoxet al., 2007). Wilcox et al. (2007) also found that the upperriser subsoils were saturated or very wet for extendedperiods, and surface runoff was generated from lower partof the hillslopes (lower risers and treads) during periodsof high rainfall. Therefore, runoff and erosion increasedfrom upper riser to tread. Despite the opposite trends, bothcatenae described above demonstrate the controls of soil,topography, and geology on runoff generation (Lin et al.,2006b; Wilcox et al., 2007).

Subsurface Preferential Flow Networksin Hillslopes and Catchments

Uhlenbrook (2006) claimed that catchment hydrology is ascience in which all processes are preferential. It has beenwell recognized that preferential flow can occur in justabout any soil, leading to spatial concentrations of waterand chemicals that are not well described by the classicalapproach based on uniform flow assumption (Vervoortet al., 1999; Hendrickx and Flury, 2001). A large body ofresearch on preferential flow and on hillslope hydrology has

been accumulated in the past decades (e.g. Kirby, 1978;Beven and Germann, 1982; Gish and Shirmohammadi,1991; Germann and Hensel, 2006). However, because ofthe complex and dynamic nature of preferential flow indifferent geographic regions and at different space- andtimescales, our ability to predict landscape variability inwater flow and solute transport has been limited (Jury,1999; Lin et al., 2005a, 2006a). This, in part, is dueto the fragmented knowledge of quantitative relationshipsbetween preferential flow and soil structure, soil layering,landscape features, precipitation inputs, and antecedentmoisture conditions at different scales. It is interesting tonote that most preferential flow studies by the soil sciencecommunity has focused on the pore to pedon scales andvertical flow, while the hydrology community seems tohave focused more on the hillslope to catchment scales andlateral flow. A more concerted and integrated effort willadvance our predictive capacity in truly 3-D flow system.

There is an emerging recognition of a paradigm shiftfrom a “continuum”-based approach to a “network”-basedview of hillslope and watershed hydrology (Rinaldo et al.,2006; Uhlenbrook, 2006; Sidle et al., 2001; McDonnellet al., 2007). A “3F” (form, function, and feedback) isneeded to characterize various watershed networks, whichwould lead to a better understanding, modeling, and predic-tion of hillslope hydrology and ungauged basins. It remainsto be further tested, though, whether an internal networkstructure exists in the subsurface of many hillslopes, whichappears to govern vertical and lateral preferential flowdynamics and the threshold-like hydrologic response undervarying precipitation, soil, and antecedent moisture condi-tions (e.g. Weiler et al., 2005; Tromp-van Meerveld andMcDonnell, 2006; Lin and Zhou, 2008). These issues areimportant because without a clear understanding of the ini-tiation, connectivity, and persistence of preferential flownetworks across space and time, we are unable to effec-tively predict rainfall–runoff for the right reasons.

Analogous to stream branching networks, a hillslope/landscape network is a set of linkages among differ-ent reservoirs and pathways with varying conductanceof flow. During storms with wet soil conditions, such anetwork often provides preferred pathways for water toflow downgradient with high velocities (Nimmo, 2007).Threshold phenomena may occur at critical “nodes,” orjunctions of a network (i.e. hot spots), where significantchanges may occur within a short period of time (i.e.hot moments). Threshold behavior of subsurface storm-flow has been observed in many hillslopes and landscapes(Whipkey, 1965; Mosley, 1979; Peters et al., 1995; Weileret al., 2005; Tromp-van Meerveld and McDonnell, 2006;Lin and Zhou, 2008). Thus, the concept of subsurfacepreferential flow networks could provide a strong scien-tific advance in our understanding of seemingly complex


Interaction of macropore withthe surrounding or adjacent soil

matrix resulting in expandedpreferential flow path

Bedrock

Mineral soil

Organic-rich horizon

Wet

Wet

Macropore flowUneven bedrock

topography

Preferential flow

Matrix flow

Fractured flow

Downslope direction

Resultant direction

Vertical direction

Preferential flowthrough living and

decayed roots

Some macroporesconnecting to the bedrock

fractures

Formation of aperched water table

above bedrock

Water movementthrough humus and

loose soil zones

Impeding layer butsome water flow intocracks and fractures

Hetrogeneity causedby preferential flow

pathways

Highly permeable relative tothe mineral soil and very

high density of roots

Formation of a perched watertable temporary between organic-

rich and mineral soil horizons

Water emergingfrom fractured

bedrock into soil

Figure 9 Interconnected preferential flow pathways along a hillslope in a forested catchment in Japan, illustrating theimportance of subsurface preferential network (From Noguchi et al., 1999)

hydrologic (and biogeochemical) phenomena across land-scapes. Sidle et al. (2001); Gish et al. (2005); Lin (2006),and many others have reported evidence of preferentialflow self-organization in forested hillslopes and agriculturallandscapes, where individual short preferential flow path-ways are linked via a series of “nodes” in a network, whichmay be switched on or off, or expand or shrink dependingon local soil moisture conditions and landscape locations(Figure 9). Sidle et al. (2001) suggested different levels ofnodes in a network to approximate the preferential move-ment of water and solutes over the landscape, including(i) those that are easily activated under various conditions(including critical landscape locations such as topographicdepressions, contrasting soil layers and soil–bedrock inter-faces, and direct physical linkages between mesopores andmacropores), (ii) those that require very wet conditions toactivate (such as disconnected large macropores, buriedpockets of organic matter, and discontinuous animal bur-rows and soil pipes), and (iii) those that do not promotepreferential flow (such as soil matrix and dead-end macro-pores with no connecting nodes). This conceptual modelcould lead to a new way of modeling preferential flow net-works across multiple scales.

SUMMARY AND FUTURE OUTLOOK

It is clear that synergies can be generated by bridging classi-cal pedology with soil physics, hydrology, and geomorphol-ogy to advance the mechanistic understanding and process-based modeling of rainfall–runoff processes. The challengeof getting the right answer for the right reason in hydrologic

modeling and prediction (Grayson et al., 1992; Kirchner,2003; McDonnell et al., 2007) calls for contributions fromhydropedology and other related disciplines to enhance theunderstanding of interactive pedologic and hydrologic pro-cesses and the complex landscape–soil–hydrology relation-ships across space and time. This article has illustrated thathydropedology can make unique contributions to advancinghillslope and watershed hydrology in many ways, amongwhich are the following key areas that require furtherresearch:

• Better understanding and quantification of soil archi-tecture from the pore to the catchment scales, and itsrelationships to preferential flow dynamics across spaceand time;

• Defining and mapping hydropedologic functional unit(HFU) in different landscapes and its incorporation intospatially distributed hydrologic modeling;

• Breakthroughs in two bottlenecks – a new concep-tual/theoretical framework for modeling preferentialflow networks (which is different from the continuous-field assumption) and a technological advance-ment in nondestructively mapping/imaging subsurfacearchitecture;

• Pattern recognition and prediction of the “forms” and“functions” of soils and watersheds across scales,which could offer comprehensive insights regardingheterogeneity and the underlying processes leading toheterogeneity;

• Use of various tracers, including isotopes and microbes,in combination with advanced sensor networks, long-term environmental monitoring, and a new generationof computer models, to gain insights into optimality


principles underlying the watershed functional traits(McDonnell et al., 2007; also see Chapter 12, Co-evolution of Climate, Soil and Vegetation, Volume1, Chapter 13, Pattern, Process and Function: Ele-ments of a Unified Theory of Hydrology at theCatchment Scale, Volume 1).

Acknowledgments

The fragipan map of the United States (Figure 6) wasgenerated with help from Sharon Waltman of the USDA-NRCS and Steven Crawford of Penn State University. Theparagraph on the summary of soil microbial distributionswith soil depth and its possible relationships with the threezones of preferential flow was assisted by Mary Ann Brunsof Penn State.

REFERENCES

Anderson S.H. and Hopmans J.W. (Eds.) (1994) Tomographyof Soil-Water-Root Processes. SSSA Special Pub. #36, SoilScience Society of America, Inc.: Madison, WI.

Band L.E., Tague C.L., Groffman P. and Belt K. (2001) Forestecosystem processes at the watershed scale: hydrological andecological controls of nitrogen export. Hydrological Processes,15, 2013–2028.

Bartoli F., Dutartre Ph, Gomendy V., Niquet S., Dubuit M. andVivier H. (1998) Fractals and soils structure. In Fractals inSoil Science. Advances in Soil Science, Baveye P., Parlange J.-Y. and Stewart B.A. (Eds.), CRC Press: Boca Raton, FL, pp.203–232.

Baveye P. and Boast C.W. (1999) Physical scales and spatialpredictability of transport processes in the environment. InCorwin D.L., Loague K. and Ellsworth T.R. (Eds.), Assessmentof Non-Point Source Pollution in the Vadose Zone, GeophysicalMonograph 108, American Geophysical Union: Washington,DC, pp. 261–280.

Baveye P., Bronick C.J. and Lal R. (2006) Comment on“soil structure and management: a review”. Geoderma, 134,231–232.

Beven K.J. (1982) On subsurface stormflow: an analysis ofresponse times. Hydrological Sciences Journal, 27, 505–521.

Beven K.J. (1984) Infiltration into a class of vertically non-uniform soils. Hydrological Sciences Journal, 29, 425–434.

Beven K. (2002) Towards an alternative blueprint for aphysically based digitally simulated hydrologic responsemodelling system. Hydrological Processes, 16, 189–206,DOI:10.1002/hyp.343.

Beven K. and Germann P. (1982) Macropores and water flow insoils. Water Resources Research, 18, 1311–1325.

Beven K.J. and Kirkby M.J. (1979) A physically based variablecontributing area model of basin hydrology. HydrologicalSciences Bulletin, 24, 43–69.

Bloschl G. and Sivapalan M. (1995) Scale issues in hydrologicalmodeling – a review. Hydrological Processes, 9(3–4),251–290.

Blume E., Bischoff M., Reichert J., Moorman T., Konopka A.and Turco R. (2002) Surface and subsurface microbial biomass,community structure and metabolic activity as a function of soildepth and season. Applied Soil Ecology, 592, 1–11.

Bouma J. (1992) Effects of soil structure, tillage, and aggregationupon soil hydraulic properties. In Interacting Processes in SoilScience, Wagenet R.J., Bavege P. and Stewart B.A. (Eds.),Lewis Publishers: pp. 1–36.

Bouma J. (1997) Long-term characterization: monitoring andmodelling. In Methods for the Assessment of Soil Degradation,Lal R., Blum W.H., Valentin C. and Stewart B.A. (Eds.),Advances in Soil Science, pp. 337–358.

Bouma J. and Anderson J.L. (1977a) Water movement throughpedal soils. I. Saturated flow. Soil Science Society of AmericaJournal, 41, 413–418.

Bouma J. and Anderson J.L. (1977b) Water movement throughpedal soils. II. Unsaturated flow. Soil Science Society of AmericaJournal, 41, 419–423.

Bouma J., Jongerius A., Boersma O., Jager A. andSchoonderbeek D. (1977) The function of different types ofmacropores during saturated flow through four swelling soilhorizons. Soil Science Society of America Journal, 41, 945–950.

Boyer E.W., Alexander R.B., Parton W.J., Li C., Butterbach-Bahl K., Donner S.D., Skaggs R.W. and Del Grosso S.J. (2006)Modeling denitrification in terrestrial and aquatic ecosystems atregional scales. Ecological Applications, 16(6), 2123–2142.

Brady N.C. and Weil R.R. (2004) The Nature and Properties ofSoils, Fourth Edition , Prentice Hall: Upper Saddle River, NJ.

Brewer R. (1976) Fabric and Mineral Analysis of Soils, Robert E.,Krieger Publishing Company: Huntington, NY.

Bronick C.J. and Lal R. (2005) Soil structure and management: areview. Geoderma, 124, 3–22.

Brooks E.S., Boll J. and McDaniel P.A. (2004) A hillslope-scale experiment to measure lateral saturated hydraulicconductivity. Water Resources Research, 40, W04208,DOI:10.1029/2003WR002858.

Brooks E.S., Boll J. and McDaniel P.A. (2007) Distributed andintegrated response of a GIS-based hydrologic model in theeastern Palouse region, Idaho. Hydrological Processes, 21,110–122.

Buol S.W., Southard R.J., Graham R.C. and McDaniel P.A. (2003)Soil Genesis and Classification, Fifth Edition , Blackwell/IowaState Press: Ames, IA.

Burns D., Hooper R., Kendall C., Freer J., McDonnell J. andBeven K. (1998) Base cation concentrations in subsurface flowfrom a forested hillslope: the role of flushing frequency. WaterResources Research, 34(12), 3535–3544.

Busacca A.J. (1989) Long quaternary record in easternWashington, USA, interpreted from multiple buried paleosolsin loess. Geoderma, 45, 105–122.

Buss H.L., Bruns M.A., Schultz M.J., Moore J., Mathur C.F. andBrantley S.L. (2006) The coupling of biological iron cyclingand mineral weathering during saprolite formation, LuquilloMountains, Puerto Rico. Geobiology, 3, 247–260.

Consortium of Universities for the Advancement of HydrologicScience, Inc. (CUAHSI) (2007) Hydrology of a DynamicEarth – A decadal research plan for hydrologic science,Washington, DC.


Crawford C.B. and Legget R.F. (1957) Ground temperatureinvestigation in Canada. Engineering Journal, 40, 1–8.

Daniels R.B., Gamble E.E. and Nelson L.A. (1971) Relationsbetween soil morphology and water-table levels on a dissectedNorth Carolina coastal plain surface. Soil Science Society ofAmerica Proceedings, 35, 781–784.

Daniels R.B., Kleiss H.J., Buol S.W., Byrd H.J. and PhillipsJ.A. (1984) Soil systems in North Carolina, North CarolinaAgricultural Research Service: Raleigh, North Carolina.Bulletin 467.

DeBano L.F., Mann L.D. and Hamilton D.A. (1970) Translocationof hydrophobic substances into soil by burning organic litter.Soil Science Society of America Proceedings, 34, 130–133.

Dekker L.W. and Ritsema C.J. (2003) Wetting patterns in waterrepellent Dutch soils. In Soil Water Repellency, Ritsema C.J.and Dekker L.W. (Eds.), Elsevier: Amsterdam, pp. 151–166.

Dodds W.K., Banks M.K., Clenan C.S., Rice C.W., Sotomayor D.,Strauss E.A. and Yu W. (1996) Biological properties of soil andsubsurface sediments under abandoned pasture and cropland.Soil Biology and Biochemistry, 28, 837–846.

Dunne T. and Black R.D. (1971) Runoff processes duringsnowmelt. Water Resources Research, 7, 1160–1172.

Dunne T., Moore T.R. and Taylor C.H. (1975) Recognitionand prediction of runoff-producing zones in humid regions.Hydrological Sciences Bulletin, 20(3), 305–327.

Ellison W.D. and Slater C.S. (1945) Factors that affect surfacesealing and infiltration of exposed soil surface. AgriculturalEngineering, 26, 156–157.

Evans C.V. and Franzmeier D.P. (1986) Saturation, aeration,and color patterns in a toposequence of soils in North-centralIndiana. Soil Science Society of America Journal, 50, 975–980.

Fierer N., Schimel J.P. and Holden P.A. (2003) Variations inmicrobial community composition through two soil depthprofiles. Soil Biology and Biochemistry, 35, 167–176.

Fluhler H., Durner W. and Flury M. (1996) Lateral solute mixingprocesses – a key for understanding field-scale transport ofwater and solutes. Geoderma, 70, 165–183.

Freer J., McDonnell J.J., Beven K.J., Peters N.E., Burns D.A.,Hooper R.P., Aulenbach B. and Kendall C. (2002) The role ofbedrock topography on subsurface storm flow. Water ResourcesResearch, 38(12), 1269, DOI:10.1029/2001WR000872.

Gburek W.J., Needelman B.A. and Srinivasan M.S. (2006)Fragipan controls on runoff generation: hydropedologicalimplications at landscape and watershed scales. Geoderma, 131,330–344.

Germann P.F. and Hensel D. (2006) Poiseuille flow geometryinferred from velocities of wetting fronts in soils. Vadose ZoneJournal, 5, 867–876.

Gish T.J. and Shirmohammadi A. (Eds.) (1991) Preferential Flow:Proceedings of the National Symposium. Dec. 16–17, 1991,American Society of Agricultural Engineers: Chicago, IL.

Gish T.J., Walthall C.L., Daughtry C.S.T. and Kung K.-J.S.(2005) Using soil moisture and spatial yield patterns to identifysubsurface flow pathways. Journal of Environmental Quality,34, 274–286.

Goodchild M.F., Yuan M. and Cova T.J. (2007) Towards a generaltheory of geographic representation in GIS. InternationalJournal of Geographical Information Science, 21, 239–260.

Grayson R.B., Moore I.D. and McMahon T.A. (1992) Physicallybased hydrologic modeling. 1. A terrain-based model forinvestigative purposes. Water Resources Research, 28(10),2639–2658.

Hall G.F. and Olson C.G. (1991) Predicting variability of soilsfrom landscape models. In Spatial Variabilities of Soils andLandforms, Mausbach M.J. and Wilding L.P. (Eds.), SoilScience Society of America: Madison, WI, pp. 9–24. SpecialPublication 28.

Harris A.R. (1972) Infiltration rate as affected by soil freezingunder three cover types. Soil Science Society of AmericaProceedings, 36, 489–492.

Hendrickx J.M.H. and Flury M. (2001) Uniform and preferentialflow mechanisms in the vadose zone. In Conceptual Modelsof Flow and Transport in the Fractured Vadose Zone, NationalResearch Council, National Academy Press: Washington, DC,pp. 149–187.

Hewlett J.D. and Hibbert A.R. (1967) Factors affecting theresponse of small watersheds to precipitation in humid regions.In Forest Hydrology, Sopper W.E. and Lull H.W. (Eds.),Pergamon Press: Oxford, pp. 275–290.

Hole F.D. (1976) Soils of Wisconsin. Wisconsin Geological andNatural History Survey Bulletin 87, Soils Series 62. Universityof Wisconsin Press: Madison, WI.

Holtan H.N., England C.B., Lawless G.P. and SchumakerG.A. (1968) Moisture-Tension Data for Selected Soils onExperimental Watersheds . USDA, ARS, Publication RS 41–144.

Horton R.E. (1940) An approach toward a physical interpretationof infiltration capacity. Soil Science Society of America Journal,5, 399–417.

Huffman E.L., MacDonald L.H. and Stednick J.D. (2001)Strength and persistence of fire-induced soil hydrophobicityunder ponderosa and lodgepole pin, Colorado Front Range.Hydrological Processes, 15, 2877–2892.

Hurt G.W., Whited P.M. and Pringle R.F. (Eds.), USDA-NRCS(1998) Field Indicators of Hydric Soils in the United States. Ver.4.0, USDA-NRCS, Ft. Worth, TX.

James A.L. and Roulet N.T. (2007) Investigating hydrologicconnectivity and its association with threshold change inrunoff response in a temperate forested watershed. HydrologicalProcesses, 21, 3391–3408.

Jenny H. (1941) Factors of Soil Formation – A System ofQuantitative Pedology, McGraw-Hill: New York.

Jury W.A. (1999) Present directions and future research in vadosezone hydrology. In Vadose Zone Hydrology – Cutting acrossdisciplines, Parlange M.B. and Hopmans J.W. (Eds.), OxfordUniversity Press: New York, pp. 433–441.

Kemp R.A., McDaniel P.A. and Busacca A.J. (1998) Genesisand relationship of macromorphology and micromorphology tocontemporary hydrological conditions of a welded Argixerollfrom the Palouse. Geoderma, 83, 309–329.

Kendall K.A., Shanley J.B. and McDonnell J.J. (1999)A hydrometric and geochemical approach to test thetransmissivity feedback hypothesis during snowmelt. Journalof Hydrology, 219(3–4), 188–205.

Khan F.A. and Fenton T.E. (1994) Saturated zones and soilmorphology in a Mollisol catena of Central Iowa. Soil ScienceSociety of America Journal, 58, 1457–1464.


Kieft T.L., Fredrickson J.K., McKinley J.P., Bjornstad B.N.,Rawson S.A., Phelps T.J., Brockman F.J. and PfiffnerS.M. (1995) Microbiological comparisons within and acrosscontiguous lacustrine, paleosol, and fluvial subsurfacesediments. Applied and Environmental Microbiology, 61,749–757.

Kirby M.J. (1978) Hillslope Hydrology, John Wiley & Sons Ltd:Chichester.

Kirchner J.W. (2003) A double paradox in catchment hydrologyand geochemistry. Hydrological Processes, 17, 871–874.

Kirchner J.W. (2006) Getting the right answers for the rightreasons: linking measurements, analyses, and models toadvance the science of hydrology. Water Resources Research,42, W03S04, DOI:10.1029/2005WR004362.

Konopka A. and Turco R. (1991) Biodegradation of organiccompounds in vadose zone and aquifer sediments. Applied andEnvironmental Microbiology, 57, 2260–2268.

Kubiena W.L. (1938) Micropedology, Collegiate Press: Ames, IA.Lehmann P., Hinz C., McGrath G., Tromp-van Meerveld H.J. and

McDonnel J.J. (2007) Rainfall threshold for hillslope outflow:an emergent property of flow pathway connectivity. Hydrologyand Earth System Science, 11, 1047–1063.

Letey J. (1991) The study of soil structure – science or art.Australian Journal of Soil Research, 29, 699–707.

Lilly A. and Lin H.S. (2004) Using soil morphological attributesand soil structure in pedotransfer functions. In Development ofPedotransfer Functions in Soil Hydrology, Pachepsky Y. andRawls W. (Eds.), Elsevier, pp. 115–142.

Lin H.S. (1995) Hydraulic Properties and Macropore Flow ofWater in Relation to Soil Morphology . Ph.D. dissertation.Texas A&M University: College Station, TX. (Diss. Abstr.9534383).

Lin H.S. (2003) Hydropedology: bridging disciplines, scales, anddata. Vadose Zone Journal, 2, 1–11.

Lin H.S. (2006) Temporal stability of soil moisture spatial patternand subsurface preferential flow pathways in the Shale HillsCatchment. Vadose Zone Journal, 5, 317–340.

Lin H.S. (2007) Cattle vs. ground beef: what is the difference?Soil Survey Horizons, 48, 9–10.

Lin H.S., Bouma J., Pachepsky Y., Western A., Thomp-son J., van Genuchten M.Th., Vogel H. and Lilly A.(2006a) Hydropedology: synergistic integration of pedologyand hydrology. Water Resources Research, 42, W05301,DOI:10.1029/(2005)WR004085.

Lin H.S., Bouma J., Wilding L., Richardson J., Kutilek M. andNielsen D. (2005a) Advances in hydropedology. Advances inAgronomy, 85, 1–89.

Lin H.S., Kogelmann W., Walker C. and Bruns M.A. (2006b) Soilmoisture patterns in a forested catchment: a hydropedologicalperspective. Geoderma, 131, 345–368.

Lin H.S. and Rathbun S. (2003) Hierarchical frameworks formultiscale bridging in hydropedology. In Scaling Methods inSoil Physics, Pachepsky Y., Radcliffe D. and Selim H.M. (Eds.),CRC Press: Boca Raton, pp. 353–371.

Lin H.S., McInnes K.J., Wilding L.P. and Hallmark C.T. (1996)Effective porosity and flow rate with infiltration at low tensionsinto a well-structured subsoil. Transactions of the ASAE, 39,131–135.

Lin H.S., McInnes K.J., Wilding L.P. and Hallmark C.T. (1997)Low tension water flow in structured soils. Canadian Journalof Soil Science, 77, 649–654.

Lin H.S., McInnes K.J., Wilding L.P. and Hallmark C.T.(1999a) Effects of soil morphology on hydraulic properties:I. Quantification of soil morphology. Soil Science Society ofAmerica Journal, 63, 948–954.

Lin H.S., McInnes K.J., Wilding L.P. and Hallmark C.T.(1999b) Effects of soil morphology on hydraulic properties:II. Hydraulic pedotransfer functions. Soil Science Society ofAmerica Journal, 63, 955–961.

Lin H.S., Wheeler D., Bell J. and Wilding L. (2005b) Assessmentof soil spatial variability at multiple scales. EcologicalModelling, 182, 271–290.

Lin H.S. and Zhou X. (2008) Evidence of subsurface preferentialflow using soil hydrologic monitoring in the Shale Hillscatchment. European Journal of Soil Science, 59, 34–49.

Lin H.S., Zhu Q. and Schmidt J. (2008) Precision Soil Mappingfor Hydropedologic Functional Units and Its Application in SoilMoisture Monitoring and Nitrogen Management. Proceedingsof the 1st Global Workshop on High-resolution Soil Sensing andMapping , University of Sydney: Australia.

Lutz H.J. and Chandler R.F. (1946) Forest Soils, John Wiley &Sons, Inc.: New York.

McClain M.E., Boyer E.W., Dent C.L., Gergel S.E., GrimmN.B., Groffman P.M., Hart S.C., Harvey J.W., Johnston C.A.and Mayorga E. (2003) Biogeochemical hot spots and hotmoments at the interface of terrestrial and aquatic ecosystems.Ecosystems, 6, 301–312, DOI:10.1007/s10021-003-0161-9.

McDaniel P.A., Bathke G.R., Buol S.W., Cassel D.K. and FalenA.L. (1992) Secondary Mn/Fe ratios as pedochemical indicatorsof field-scale throughflow water movement. Soil Science Societyof America Journal, 56, 1211–1217.

McDaniel P.A., Regan M.P., Brooks E., Boll J., Barndt S.,Falen A., Young S.K. and Hammel J.E. (2008) Linking fragi-pans, perched water tables, and catchment-scale hydrologicalprocesses. Catena, DOI:10.1016/j.catena.2007.05.011.

McDonnell J.J. (2003) Where does water go when itrains? Moving beyond the variable source area conceptof rainfall– runoff response. Hydrological Processes, 17,1869–1875.

McDonnell J.J., Sivapalan M., Vache’ K., Dunn S., Grant G.,Haggerty R., Hinz C., Hooper R., Kirchner J. and RoderickM.L. (2007) Moving beyond heterogeneity and process com-plexity: a new vision for watershed hydrology. Water ResourcesResearch, 43, W07301, DOI:10.1029/(2006)WR005467.

McGlynn B.L., McDonnell J.J. and Brammer D.D. (2002) Areview of the evolving perceptual model of hillslope flowpathsat the Maimai catchments, New Zealand. Journal of Hydrology,257, 1–26.

Mosley M.P. (1979) Streamflow generation in a forestedwatershed. Water Resources Research, 15, 795–806.

Moore I.D., Gessler P.E., Nielsen G.A. and Peterson G.A. (1993)Soil attribute prediction using terrain analysis. Soil ScienceSociety of America Journal, 57, 443–452.

Moore I.D., Grayson R.B. and Ladson A.R. (1991) Digital terrainmodeling: a review of hydrological, geomorphological, andbiological applications. Hydrological Processes, 5, 3–30.


Needelman B.A., Gburek W.J., Petersen G.W., Sharpley A.N. andKleinman P.J.A. (2004) Surface runoff along two agriculturalhillslopes with contrasting soils. Soil Science Society ofAmerican Journal, 68, 914–923.

Nimmo J.R. (2007) Simple predictions of maximum transport ratein unsaturated soil and rock. Water Resources Research, 43,W05426, DOI:10.1029/(2006)WR005372.

Noguchi S., Tsuboyama Y., Sidle R.C. and Hosoda I.(1999) Morphological characteristics of macropores and thedistribution of preferential flow pathways in a forestedslope segment. Soil Science Society of America Journal, 63,1413–1423.

Nortcliff S., Quisenberry V.L., Nelson P. and Phillips R.E. (1994)The analysis of soil macropores and the flow of solutes. InSoil Micromorphology: Studies in Management and Genesis,Ringrose-Voase A.J. and Humpherys G.S. (Eds.), Elsevier:Amsterdam, The Netherlands, pp. 601–612.

Onda Y., Komatsu Y., Tsujimura M. and Fujihara J. (2001)The role of subsurface runoff through bedrock on storm flowgeneration. Hydrological Processes, 15, 1693–1706.

Pennock D.J. and de Jong E. (1990) Regional and caternaryvariations in properties of Borolls of southern Saskatchewan,Canada. Soil Science Society of America Journal, 54,1697–1701.

Perret J., Prasher S.O., Kantzas A. and Langford C. (1999)Three-dimensional quantification of macropore networks inundisturbed soil cores. Soil Science Society of America Journal,63, 1530–1543.

Perrier E., Bird N. and Rieu M. (1999) Generalizing thefractal model of soil structure: the pore-solid fractal approach.Geoderma, 88, 137–164.

Peters D.L., Buttle J.M., Taylor C.H. and LaZerte B.D. (1995)Runoff production in a forested, shallow soil. Canadian Shieldbasin. Water Resources Research, 31(5), 1291–1304.

Quisenberry V.L., Smith B.R., Phillips R.E., Scott H.D. andNortcliff S. (1993) A soil classification system for describingwater and chemical transport. Soil Science, 156, 306–315.

Rabenhorst M.C., Bell J.C. and McDaniel P.A. (1998) QuantifyingSoil Hydromorphology, Soil Science Society of America, Inc:Madison, WI. SSSA Special Pub. #54.

Richter D.D. Jr and Markewitz D. (2001) Understanding SoilChange, Cambridge University Press: Cambridge, UK, pp.94–96.

Rinaldo A., Banavar J.R. and Maritan A. (2006) Trees, networks,and hydrology. Water Resources Research, 42, W06D07,DOI:10.1029/(2005)WR004108.

Rodrıguez-Cruz M.S., Jones J.E. and Bending G.D. (2006) Field-scale study of the variability in pesticide biodegradation withsoil depth and its relationship with soil characteristics. SoilBiology and Biochemistry, 38, 2910–2918.

Schaetzl R. and Anderson S. (2005) Soils: Genesis andgeomorphology, Cambridge University Press: New York.

Sidle R., Noguchi S., Tsuboyama Y. and Laursen K.(2001) A conceptual model of preferential flow systems inforested hillslopes: evidence of self-organization. HydrologicalProcesses, 15, 1675–1692.

Sidle R., Tsuboyama Y., Noguchi S., Hosoda I., Fujieda M.and Shimizu T. (2000) Stormflow generation in steep forested

headwaters: a linked hydrogeomorphic paradigm. HydrologicalProcesses, 14, 369–385.

Sivapalan M. (2003) Process complexity at hillslope scale, processsimplicity at the watershed scale: is there a connection?Hydrological Processes, 17, 1037–1041.

Smeck N.E. and Ciolkosz E.J. (1989) Fragipans: Theiroccurrence, classification, and genesis, Soil Science Society ofAmerica, Inc.: Madison, WI. SSSA Special Publication #24.

Soil Science Society of America (SSSA) (1997) Glossary of SoilScience Terms, Soil Science Society of America, Inc.: Madison,WI.

Soil Survey Division Staff (1993) Soil Survey Manual, U.S.Department of Agriculture Handbook No. 18, U.S. GovernmentPrinting Office: Washington, DC.

Soil Survey Staff (1999) Soil Taxonomy – A Basic System of SoilClassification for Making and Interpreting Soil Surveys, SecondEdition , USDA-NRCS Agricultural Handbook No. 436, U.S.Government Printing Office: Washington, DC.

Soil Survey Staff (2006) Keys to Soil Taxonomy, Tenth Edition ,United States Department of Agriculture – Natural ResourcesConservation Service: Washington, DC.

Sommer M. and Schlichting E. (1997) Archetypes of catenasin respect to matter: a concept for structuring and groupingcatenas. Geoderma, 76, 1–33.

van Stiphout T.P.J., van Lanen H.A.J., Boersma O.H. andBouma J. (1987) The effect of bypass flow and internalcatchment of rain on the water regime in a clay loam grasslandsoil. Journal of Hydrology, 95, 1–11.

Stolt M.H., Baker J.C. and Simpson T.W. (1993) Soil-landscaperelationships in Virginia: I. Soil variability and parent materialuniformity. Soil Science Society of America Journal, 57,414–421.

Tackett J.L. and Pearson R.W. (1965) Some characteristics of soilsurface seals formed by simulated rainfall. Soil Science, 99,407–412.

Taylor J.P., Wilson B., Mills M.S. and Burns R.G. (2002)Comparison of microbial numbers and enzymatic activities insurface soils and subsoils using various techniques. Soil Biologyand Biochemistry, 34, 387–401.

Thompson J.A., Bell J.C. and Butler C.A. (1997) Quantitativesoil-landscape modeling for estimating the areal extent ofhydromorphic soils. Soil Science Society of America Journal,61, 971–980.

Thompson J.A., Bell J.C. and Zanner C.W. (1998) Hydrologyand hydric soil extent within a Mollisol catena in SoutheasternMinnesota. Soil Science Society of America Journal, 62,1126–1133.

Tisdall J.M. and Oades J.M. (1982) Organic matter and water-stable aggregates in soils. Journal of Soil Science, 33,141–163.

Tromp-van Meerveld H.J. and McDonnell J.J. (2006) Thresh-old relations in subsurface stormflow 2: the fill and spillhypothesis: an explanation for observed threshold behav-ior in subsurface stormflow. Water Resources Research,DOI:10.1029/2004WR003800.

Uhlenbrook (2006) Catchment hydrology – a science in which allprocesses are preferential. HP Today. Hydrological Processes,20, 3581–3585.


USDA-NRCS (1997) Land Resource Regions and Major LandResource Areas. National Soil Survey Handbook, U. S.Government Printing Office: Washington, DC.

Van Gestel M., Ladd J.N. and Amato M. (1992) Microbial biomassresponses to seasonal change and imposed drying regimes atincreasing depths of undisturbed topsoil profiles. Soil Biologyand Biochemistry, 24, 103–111.

Vache K.B. and McDonnell J.J. (2006) A process-basedrejectionist framework for evaluating catchment runoffmodel structure. Water Resources Research, 42, W02409,DOI:10.1029/(2005)WR004247.

Veneman P.L.M. and Bodine S.M. (1982) Chemical andmorphological soil characteristics in a New England drainage-toposequence. Soil Science Society of America Journal, 46,359–363.

Veneman P.L.M., Lindbo D.L. and Spokas L.A. (1998) Soilmoisture and redoximorphic features: A historical perspective.In Quantifying Soil Hydromorphology, Rabenhorst M.C., BellJ.C. and McDaniel P.A. (Eds.), Soil Science Society ofAmerica, Inc: Madison, WI, pp. 1–23. SSSA Special Pub. #54.

Vepraskas M.J. (1992) Redoximorphic Features for IdentifyingAquic Conditions, North Carolina Agricultural ResearchService Technical Bulletin No. 301, North Carolina AgriculturalResearch Service: North Carolina.

Vervoort R.W. and Cattle S.R. (2003) Linking hydraulicconductivity and tortuosity parameters to pore space geometryand pore size distribution. Journal of Hydrology, 272, 36–49.

Vervoort R.W., Radcliffe D.E. and West L.T. (1999) Soil structuredevelopment and preferential solute flow. Water ResourcesResearch, 35, 913–928.

Vogel H.J., Cousin I. and Roth K. (2002) Quantification of porestructure and gas diffusion as a function of scale. EuropeanJournal of Soil Science, 53, 465–473.

Vogel H.J. and Roth K. (2003) Moving through scales of flow andtransport in soil. Journal of Hydrology, 272, 95–106.

Weiler M., McDonnell J.J., Tromp-van Meerveld I. and Uchida T.(2005) Subsurface stormflow runoff generation processes. InEncyclopedia of Hydrological Sciences, Anderson M.G. (Ed.),John Wiley& Sons Ltd, pp. 1719–1732.

Weiler M. and Naef F. (2003) An experimental tracer studyof the role of macropores in infiltration in grassland soils.Hydrological Processes, 17, 477–493.

Weiler M. and McDonnell J.J. (2007) Conceptualizing lateralpreferential flow and flow networks and simulating the effectson gauged and ungauged hillslopes. Water Resources Research,43, W03403, DOI:10.1029/2006WR004867.

West L.T., Abreu M.A. and Bishop J.P. (2008) Saturated hydraulicconductivity of soils in the Southern Piedmont of Georgia,USA: field evaluation and relation to horizon and landscapeproperties. Catena, 73, 174–179.

Whipkey R.Z. (1965) Subsurface storm flow from forested slopes.Bulletin of the International Association of Scientific Hydrology,2, 74–85.

Wigmosta M.S., Vail L.W. and Lettenmaier D.P. (1994) Adistributed hydrology-vegetation model for complex terrain.Water Resources Research, 30, 1665–1642.

Wilcox B.P., Wilding L.P. and Woodruff C.M. Jr (2007) Soil andtopographic controls on runoff generation from stepped land-forms in the Edwards Plateau of Central Texas. GeophysicalResearch Letters, 34, L24S24, DOI:10.1029/2007GL030860.

Wysocki D., Schoeneberger P. and LaGarry H. (2000)Geomorphology of soil landscapes. In Handbook of SoilScience, Sumner M.E. (Ed.), CRC Press: Boca Raton, FL, pp.E-5–E-39.

Young I.M., Crawford J.W. and Rappoldt C. (2001) New methodsand models for characterising structural heterogeneity of soil.Soil and Tillage Research, 61, 33–45.

Zhu A.X., Hudson B., Burt J., Lubich K. and Simonson D. (2001)Soil mapping using GIS, expert knowledge, and fuzzy logic.Soil Science Society of America Journal, 65, 1463–1472.

Zhu Q., Lin H.S. and Doolittle J. (2008) Functional soil mappingfor soil moisture and crop management in an agriculturallandscape. Agronomy Journal, In review.

Zuzel J.F., Allmaras R.R. and Greewalt R. (1982) Runoff and soilerosion on frozen soils in northeastern Oregon. Journal of Soiland Water Conservation, 37(6), 351–354.

Documents

Hydropedology and Surface/Subsurface Runoff Processesudel.edu/~inamdar/BREG667/Lin2008.pdf · Hydropedology and Surface/Subsurface Runoff Processes HENRY LIN1, ERIN BROOKS 2, PAUL