variability in surface moisture content along a hillslope

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TitleVariability in surface moisture content along a hillslope transect: Rattlesnake Hill, Texas

Permalinkhttps://escholarship.org/uc/item/1mp448sv

JournalJournal of Hydrology, 210(1-4)

ISSN0022-1694

AuthorsFamiglietti, JSRudnicki, JWRodell, M

Publication Date1998-09-01

DOI10.1016/s0022-1694(98)00187-5

Copyright InformationThis work is made available under the terms of a Creative Commons Attribution License, availalbe at https://creativecommons.org/licenses/by/4.0/ Peer reviewed

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Variability in surface moisture content along a hillslope transect:Rattlesnake Hill, Texas

J.S. Famiglietti*, J.W. Rudnicki, M. Rodell

Department of Geological Sciences, University of Texas, Austin, TX 78712, USA

Received 2 June 1997; received in revised form 8 July 1998; accepted 8 July 1998

Abstract

Surface soil moisture content exhibits a high degree of spatial and temporal variability. The purpose of this study was (a) tocharacterize variations in moisture content in the 0–5 cm surface soil layer along a hillslope transect by means of intensivesampling in both space and time; and (b) to make inferences regarding the environmental factors that influence this variability.Over a period of seven months, soil moisture content was measured (gravimetric method) on a near-daily basis at 10 mintervals along a 200 m downslope transect at the Rattlesnake Hill field site in Austin, Texas. Results indicate that significantvariability in soil moisture content exists along the length of the transect; that variability decreases with decreasing transect-mean moisture content as the hillslope dries down following rain events; and that the dominant influences on moisture contentvariability are dependent upon the moisture conditions on the hillslope. While topographic and soil attributes operate jointly toredistribute soil water following storm events, under wet conditions, variability in surface moisture content is most stronglyinfluenced by porosity and hydraulic conductivity, and under dry conditions, correlations are strongest to relative elevation,aspect and clay content. Consequently, the dominant influence on soil moisture variability gradually changes from soilheterogeneity to joint control by topographic and soil properties as the transect dries following significant rain events.� 1998 Elsevier Science B.V. All rights reserved.

Keywords: Hydrology; Soil moisture; Field studies; Statistical analysis; Correlation coefficient

1. Introduction

Soil moisture stored near the land surface affects awide variety of earth system interactions over a rangeof spatial and temporal scales. The moisture contentof surface soils exerts a major control on the partition-ing of net radiation into latent and sensible heat and ofrainfall into runoff and infiltration. Through the pro-cess of evapotranspiration, soil moisture provides asignificant source of moisture for the formation of

clouds and precipitation over land. Like the worldoceans, soil moisture provides thermal inertia to theclimate system (though to lesser degree), storing andlater releasing heat, dampening out diurnal andseasonal variations in surface temperatures (Wei,1995).

Given the importance of surface soil moisture toearth system processes, quantification of its spatial–temporal behavior is receiving increased attentionfrom the hydrologic community (e.g. from the scaleof hillslopes and small watersheds (Western et al.,1997) to the global scale (IGPO, 1995)). This task isnot trivial however, since surface soil moisture

Journal of Hydrology 210 (1998) 259–281

0022-1694/98/$ - see front matter � 1998 Elsevier Science B.V. All rights reserved.PII S0022-1694(98)00187-5

* Corresponding author. Tel.: +1 512 471 3824; fax: +1 512 4719425; e-mail: [email protected]

exhibits a high degree of variability in both space andtime. Consequently, high resolution ground-basedmonitoring is required to accurately characterizethese variations, at least until remote sensing (e.g.passive and active microwave) progresses to thepoint of providing routine, reliable, high resolutionobservations of surface soil moisture. Unfortunately,ground-based methods (e.g. gravimetric, neutron ther-malization, gamma attenuation, time domain reflecto-metry) are far too labor or equipment intensive toremain feasible with increasing spatial scale andspace/time sampling frequencies. As a result, a con-sistent picture regarding spatial/temporal soil moist-ure variability and the processes that control it has yetto emerge.

In view of the intensive labor demands of ground-based monitoring, this study was initiated at the hill-slope scale in order to ensure the high samplingfrequencies required for a detailed study of soil moist-ure variability. From 20 September 1995 to 25 April1996, soil moisture content was measured on a neardaily basis at 10 m intervals (0–5 cm, 5–10 cm, and10–15 cm depths) along a 200 m downslope transectat the Rattlesnake Hill field site in Austin, TX. A totalof 4440 samples were collected during this sevenmonth period. Since it was not always possible toretrieve samples from the lower two depths at eachtransect location on each day that samples were col-lected, only the 0–5 cm samples (totaling 1848) areanalyzed in this paper. The purpose of the study was(a) to quantify surface soil moisture variability alongthe hillsope transect by means of intensive monitoringin space and time; and (b) to make inferences regard-ing the environmental factors that influence this varia-bility. Specific objectives of this paper are (a) tocharacterize the transect mean and variance of themoisture content in the 0–5 cm surface soil layer,the downslope moisture content profile in this surfacelayer, and the temporal dynamics of these quantities;and (b) to understand the relative roles of topographicattributes and soil properties in controlling theobserved variability. Variations in vegetation, meteo-rological factors and other significant influences onsoil moisture variability, were observed to be negligi-ble at the hillslope scale.

Although the spatial scale of the study is small, thisresearch has implications for a range of issuesin hydrology. First, a thorough knowledge of

hillslope-scale soil moisture variability will providea foundation for better understanding hillslope hydro-logical, ecological and biogeochemical processes,many of which are nonlinearly related to soil moisturecontent. Second, since hillslopes are fundamentallandscape units, this work will provide a basis forcharacterizing soil moisture variations at larger scales.Consequently, this work will provide insight into theparameterization of soil moisture dynamics in largerscale hydrological models, and into the design oflarger-scale soil moisture monitoring networks.Finally, this study will contribute towards animproved understanding of the representativeness ofpoint soil moisture measurements as indicators oflarger-scale average moisture conditions, and of thevariability of soil moisture within larger-scale remotesensing footprints.

2. Background

Soil moisture variability is influenced by a numberof factors. These include variations in topography,soil properties, vegetation type and density, meanmoisture content, depth to water table, precipitationdepth, solar radiation and other meteorological fac-tors. This section reviews previous studies in whichthe influence of several of these variables, either inde-pendently or in combination, has been investigated.The emphasis of this review is on field investigationsof near-surface (0–15 cm) soil moisture variability atsmall spatial scales (plot to small watershed scale).Table 1 lists the basic attributes of the studies includedin this review.

2.1. Topography

Variations in slope, aspect, curvature, upslope con-tributing area and relative elevation all affect the dis-tribution of soil moisture near the land surface. Slopeangle influences infiltration, drainage and runoff;steeper slopes are likely to be drier than flat areasowing to lower infiltration rates, rapid subsurfacedrainage, and higher surface runoff. Hills andReynolds (1969), Moore et al. (1988) and Nyberg(1996) all found that slope angle influences soil moist-ure variability. Aspect, or slope orientation, influencessolar irradiance and thus evapotranspiration and soil

260 J.S. Famiglietti et al./Journal of Hydrology 210 (1998) 259–281

moisture. Reid (1973) found a significant correlationbetween aspect and soil moisture content.

Curvature is a measure of convexity or concavity ofthe landscape, and thus influences the convergenceof lateral flow. For example, depressions, or areas ofhigh curvature, tend to be wetter than planar areas,where curvature is low. Curvature can be further char-acterized as planform (perpendicular to the slopedirection), profile (in the same direction as theslope), or mean (the average of curvature in all direc-tions). Moore et al. (1988) found a significant correla-tion between profile curvature and moisture content,though the variance accounted for by their regressionswas low.

Specific contributing area, or the upslope surfacearea that drains through a unit length of contour ona hillslope, influences the distribution of soil moistureby controlling the potential volume of subsurfacemoisture flowing past a particular point on the land-scape; hillslope locations with larger contributingareas are likely to be wetter than those with smallercontributing areas. Moore et al. (1988) and Nyberg(1996) found moderate, positive correlation betweenspecific contributing area and soil moisture content.

A number of researchers have demonstrated theinfluence of slope location, or relative elevation, onthe distribution of soil moisture. Relative elevation isoften correlated with various soil and topographicattributes that may influence soil water redistribution(e.g. specific contributing area, clay content).Krumbach (1959), Henninger et al. (1976), Hawleyet al. (1983), Robinson and Dean (1993) and Nyberg(1996) all found that moisture content is inverselyproportional to relative elevation. Crave andGascuel-Odoux (1997) found that a threshold valueof relative elevation distinguished between drier andslowly varying moisture conditions upslope, andwetter, more variable conditions downslope.

2.2. Soil properties

Soil heterogeneity affects the distribution of soilmoisture through variations in texture, organic mattercontent, structure and the existence of macroporosity,all of which affect the fluid transmission and retentionproperties of the soil column. Additionally, soil colorinfluences its albedo and thus the rate of evaporativedrying. Reynolds (1970a,b), Henninger et al. (1976)

and Crave and Gascuel-Odoux (1997) all found thatvariations in soil moisture were related to variations insoil texture. Hawley et al. (1983) noted that differ-ences in soil moisture content due to differences insoil texture were more pronounced under wet condi-tions rather than dry. Niemann and Edgell (1993)found that macroporosity exerted a controlling influ-ence on moisture movement and thus soil moisturevariability.

2.3. Vegetation

Vegetation influences soil moisture variability bythe pattern of throughfall imposed by the canopy; byshading the land surface and affecting the rate ofevaporative drying; by generating turbulence andenhancing evapotranspiration rates; by affecting soilhydraulic conductivity through root activity and theaddition of organic matter to the soil surface layer;and by extracting moisture for transpiration from thesoil profile. The degree to which these factors affectthe soil moisture distribution varies with vegetationtype, density and season. Lull and Reinhart (1955)found that the amount of vegetative cover was oneof the major factors influencing soil moisture varia-bility. They found further that variability increasedwith decreasing, or partial canopy coverage. Similarfindings were made by Reynolds (1970b); Reynolds(1970c). Hawley et al. (1983) and Francis et al. (1986)found significant differences in moisture content dueto differences in vegetative cover, and Hawley et al.(1983) noted further that these differences were oftengreater on wetter days than dry days.

2.4. Mean moisture content

Several investigations have noted that the varianceof soil moisture decreases with decreasing meanmoisture content (Hills and Reynolds, 1969;Reynolds, 1970c; Henninger et al., 1976; Bell et al.,1980; Hawley et al., 1982 and Robinson and Dean,1993). Speculating on temporal dynamics of the var-iance, Reynolds (1970c) proposed that variabilitymight be largest following a rainfall event since theeffects of soil heterogeneity would be at a maximum;and similarly, that the variance would be lowest afteran extended dry period, when the effects of soilheterogeneity would be minimized. Hawley et al.

261J.S. Famiglietti et al./Journal of Hydrology 210 (1998) 259–281

(1983) extended this proposed scenario by suggestingthat the variance might increase with increasing pre-cipitation depth and under extremely dry conditions.Hills and Reynolds (1969) envisioned an alternativescenario in which the variance peaks in the mid-rangeof mean moisture content, when small areas of rapiddrying might co-exist with wet areas, resulting inmore heterogeneous wetness conditions.

Several studies have also observed that near-surface soil moisture is normally distributed (Hillsand Reynolds, 1969; Bell et al., 1980; Hawley et al.,1983; Francis et al., 1986; Loague, 1992 (transectdata; see Table 1) and Nyberg, 1996). Hills andReynolds (1969), Reynolds (1970c) and Bell et al.(1980) all pointed to the need for long-term studiesto fully characterize the time dynamics of soil moist-ure variability.

2.5. Combined influences

A number of previous studies have explored theinfluence of multiple environmental factors on thedistribution of soil moisture (Reynolds, 1970c;Henninger et al., 1976; Hawley et al., 1983; Mooreet al., 1988; Nyberg, 1996; and Crave and Gascuel-Odoux, 1997). Reynolds (1970c) examined the rela-tionship between soil moisture variability, the amountof rainfall and insolation received in the week preced-ing the sampling, and the moisture content and vege-tation cover at the time of sampling. Although noattempt was made to infer the relative influenceof each of these factors, trends were identifiedthat were consistent with the notion that soilmoisture variability increases with increasingmean moisture content. Specifically, it was notedthat low variance was associated with dry periods(low mean moisture content, high insolation andlow precipitation depth) and that high variancewas associated with wet periods (high meanmoisture content, low insolation and high precipi-tation depth). Marked seasonal changes in vegeta-tive cover were also thought partially to explaindifferences in soil moisture variability observedon different sampling dates.

Henninger et al. (1976) found that both relativeelevation along a downslope transect and the internaldrainage properties of soils were important factorsinfluencing soil moisture variability. However, no

effort was made to distinguish between the relativeimportance of each of these factors.

Hawley et al. (1983) examined the influence ofvariations in vegetation, soil properties and topogra-phy on the distribution of soil moisture. Their resultsindicated that relative elevation was the dominantcontrol on soil moisture variability; that the presenceof vegetative cover tended to diminish the variationsexplained by topography; and that minor variations insoil type had minimal impact on the observed soilmoisture variability. They also cautioned that largerdifferences in soil type may exert a more pronouncedinfluence on the soil moisture distribution, but thatbecause these differences are often related to slopelocation, determining the relative importance ofeach is often not possible.

Moore et al. (1988) explored the relationshipbetween surface moisture content and aspect, slope,curvature and specific contributing area. Correlationbetween each of these topographic variables and sur-face moisture content was low, but significant. How-ever, they found that the most statistically-significantregression equation contained both the compoundvariable ln (a/b) (where a is the specific contributingarea and b is the surface slope angle) and aspect.

More recently, Nyberg (1996) explored the relativeimportance of the lateral distribution of roots, thethickness of the soil humus layer, relative elevation,slope, ln (A) (where A was defined as the upslope areadraining through a 5 m grid cell) and the wetnessindex (Beven and Kirkby, 1979) ln (a/tan b), in influ-encing soil moisture variations. No significant corre-lation between the moisture content and either the rootdistribution or the soil thickness was observed. Slopeand elevation were significantly (and negatively) cor-related with soil moisture. The highest correlationsobserved were between moisture content and both ln(A) and ln (a/tan b). The similarity in correlation coef-ficients between ln (A) and ln (a/tan b) versus moist-ure content, and the lower correlation between slopeand moisture content, led Nyberg (1996) to concludethat upslope contributing area (either A or a) was amore important factor than slope in controlling thespatial distribution of soil moisture.

2.6. Contradictions

Although the above summary attempts to provide a


consensus view of the factors that influence surfacesoil moisture variability, enough contradictory find-ings appear in the literature so that our basic under-standing of these processes must be called intoquestion. For example, several of the studies citedabove noted the influence of topography on soil moist-ure variability, yet Charpentier and Groffman (1992),Whitaker (1993) and Niemann and Edgell (1993)found no correspondence between relative elevationand moisture content; Niemann and Edgell (1993)found no relationship between curvature and surfacemoisture content; and Crave and Gascuel-Odoux(1997) found no correlation between moisture contentand ln (a/tan b). Ladson and Moore (1992) investi-gated the relationship between soil moisture andseveral topographic attributes (including relative ele-vation, slope, aspect, curvature and ln (a/tan b) amongothers) and found, with minor exceptions, that no sig-nificant correlations existed.

Although in numerous previous investigations thevariance of soil moisture content has been observed todecrease with decreasing mean moisture content,Hawley et al. (1983) and Charpentier and Groffman(1992) found no systematic relationship between the

variance and the mean moisture content, and Oweet al. (1982) observed that soil moisture variabilitypeaked in the mid-range of mean moisture content.While several previous studies noted that the distribu-tion of surface moisture content is often normal,Charpentier and Groffman (1992) reported that thedaily distributions observed in their study had lowprobabilities of representing normal distributions.Loague (1992) found that surface moisture contentsmeasured along transects were normally distributed,while those measured on a square grid were not.

Some of the differing findings can be explained bydifferences in climate, soils, vegetation, topographyand time and depth of sampling between the variousfield studies. However, close inspection of the litera-ture reveals that a common feature in each of thestudies listed in Table 1 is a low sampling frequencyin space, time, or both. An underlying premise of thiswork is that previous studies have undersampled near-surface soil moisture content in either space or time(or both), so that no consistent picture of soil moisturevariability, its behavior through time, and the pro-cesses that control it, currently exists at the smallspatial scales that are the focus of this research.

Fig. 1. Map view of the Rattlesnake Hill hillslope field site. Sampling locations are located at 10 m intervals along the transect and are shownas black dots. North is at the top of the page. Map dimensions are 220 m east–west and 155 m north–south. Contour interval is 1 m. Theapproximate location of the contact between the two distinct soil types located on the hillslope is shown as a dashed line.


Table 1Characteristics of previous small-scale studies of near-surface soil moisture variability

Study Location Area Number of samples Temporal frequency Samplingdepth

Krumbach, 1959 Mississippi, USA 270 m2 120 twice 15–30 cmHills and Reynolds, 1969 Chew Stoke, UK 2.4 m2 to 6 km2 60 per field/watershed once 0–8 cmReynolds, 1970a; Reynolds, 1970b;Reynolds, 1970c

Somerset, UK 715 5.9 m2 plots 10 per plot monthly for 8 months 0–8 cm

Reid, 1973 Caydell, UK 2 10 000 m2 fields 12 per field weekly for 1 year 0–32.5 cmHenninger et al., 1976 Pennsylvania, USA 560 m transect 57 weekly for 6 months 0–15 cmBell et al., 1980 Arizona, Kansas and

South Dakota, USA62 160 000 m2 fields 9–36 per field 1–5 times per field 0–15 cm

Hawley et al., 1982 Maryland, USA 2 m2 plot 80 3 dates 0–10 cmOwe et al., 1982 South Dakota, USA 160 000 m2 to 2.6 km2 fields 42–69 per field 9 dates in 3 years 0–10 cmHawley et al., 1983 Oklahoma, USA 8 51 000 m2 to 179 000 m2

watersheds16–92 per watershed 4 dates in 1 month 0–15 cm

Francis et al., 1986 Murcia, Spain 5 transects in 3000 m2 plot 23–113 per transect 3 dates in 13 months 0–7.5 cmMoore et al., 1988 New South Wales, Australia 6 190–200 m transects in 7.5 ha

watershed20–21 per transect twice 0–10 cm

Charpentier and Groffman, 1992 Kansas, USA 2 4356 m2 plots 49 per plot twice 0–5 cmLadson and Moore, 1992 Kansas, USA 377 000 m2 watershed 20 9 consecutive days 0–5 cmLoague, 1992 Oklahoma, USA 100 000 m2 watershed 4 90 dates in 4 years 0–15 cm

100 000 m2 watershed 34 84 dates in 4 years 0–15 cm100 000 m2 watershed 157 once 0–10 cm100/250 m transects in100 000 m2 watershed

50 per transect once 0–10 cm

Niemann and Edgell, 1993 British Columbia, Canada 10 000 m2 31 5 dates in 4 months 0–100 cmRobinson and Dean, 1993 Oxford, UK 150 m transect 151 4 dates in 15 months 0–10 cmWhitaker, 1993 Arizona, USA 44 000 m2 134 4 dates in 2 weeks 0–15 cmNyberg, 1996 Gardsjon, Sweden 6300 m2 57–73 monthly for two months 0–30 cmCrave and Gascuel-Odoux, 1997 Brittany, France 10 500 m transects in 1.3 km2

watershed20 per transect 4 dates in 18 months 0–5 cm;

5–10 cm

Listed studies in which sampling depths exceeded 15 cm included sampling intervals in the 0–15 cm range

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3. Site description

The experiment was conducted on a 56 000 m2 hill-slope of Rattlesnake Hill (30� 17�N, 97� 37�W), locatedapproximately seven miles east of Austin on the westernedge of the Black Prairie, a large agricultural region inTexas characterized by gently undulating terrain and siltand clay soils. A contour map of the site (Fig. 1) showsthat the hillslope has an east– southeasterly aspect andapproximately 12 m of relief. It is bounded to the northand east by trees, and to the west and south by roadways.An ephemeral (most often dry) stream runs parallel to theeastern tree line, just east of the site. Native prairie grassuniformly covers the hillslope.

Two distinct soil types are found on the hillslope(Soil Survey of Travis County, Texas, 1974). Theircontact is shown in Fig. 1. The Houston Black grav-elly clay is located on the upper portion of the hill-slope. It is characteristically 30–75% chert gravel,dark gray in appearance, has a surface layer over 0.6 mthick, and a total depth of almost 2 m. The Heiden clayoccupies the lower portion of the hillslope. It is a darkgrayish-brown clay with a surface layer approxi-mately 0.4 m deep and a typical depth of 1 m.

Climate at the site is humid–subtropical, and istypical of the Austin area. This region of centralTexas receives an average of 80 cm of precipitationeach year, most of which falls in the late spring (May–June) and early fall (September–October). Panevaporation averages 185 cm per year, with monthlyaverage depths ranging from 6 to 8 cm in the wintermonths to 22 to 25 cm in the summer months. Aver-age mid-day relative humidity varies from a winterhigh near 60% to a summer low near 50%. Averagedaily maximum temperatures range from 16.4�C inwinter to 34.4�C in summer.

A 200 m transect was established in the maximumdownslope direction along the hillslope (see Fig. 1).Elevations at the top and bottom of the transect are130.1 m and 119.5 m respectively, yielding a total of10.6 m of relief.

4. Methods

4.1. Soil moisture sampling transect

Survey stakes were located at 10 m intervals along

the transect (see Fig. 1) resulting in a total of 21 loca-tions for moisture content sampling. While a largernumber of sampling locations may have been desir-able for statistical purposes, the 10 m spatial resolu-tion was chosen so that sampling time would beminimized, in order that the results would not be sig-nificantly affected by diurnal variations in soil moist-ure content. Elevation at each of the samplinglocations was determined to within 1 cm using differ-ential, kinematic GPS (Global Positioning System).Non-recording raingages were secured to the surveystakes and were monitored daily to determine theoccurrence and variability of precipitation. Elevationat several additional hillslope points was measured toconstruct a digital elevation model (DEM) fromwhich Fig. 1 and several terrain-based attributes(described later) were derived.

4.2. Moisture content sampling

Soil samples were collected almost daily at eachsampling location and at three depth horizons (0–5 cm,5–10 cm and 10–15 cm) using a 3 cm diameter handauger. It was not always possible to collect samples atthe lower two depths at each location on each day,particularly under dry conditions in the gravelly clayon the upper portion of the hillslope. Consequently,the 0–5 cm data represent the most complete data setresulting from the sampling campaign, and are thesubject of the analyses presented in this paper.

Owing to the destructive nature of the gravimetricmethod, soil samples were collected within a 1 mradius of the survey stakes. Each sample had a volumeof approximately 15 cm3. Once extracted from theground, samples were placed in three-ounce metalcans with tight-fitting lids. Shortly thereafter, sampleswere weighed before and after oven-drying for 24 h at105�C. The gravimetric moisture content (in percent)of each sample was then computed as the ratio of themass of the water contained in the soil (g) to the massof the dry soil (g), multiplied by one hundred. Notethat all moisture contents in this study are reported asgravimetric rather than volumetric owing to the inac-curacies associated with the volumetric methodapplied to soils with significant clay fractions.

Samples were collected for several consecutivedays following precipitation events to monitor therapidly changing moisture conditions on the hillslope.


As the rate of change of hillslope surface moisturecontent decreased with time during an interstorm per-iod, samples were collected every other or every thirdday. Over the 217 day period of the experiment thisresulted in 88 days on which samples were collected.

4.3. Soil properties

Particle size distribution, dry bulk density, particledensity and porosity were determined at each of the 21sampling locations along the transect. Particle sizedistributions were measured using traditional sievingmethods to quantify the coarser grains (gravel andsand) and pipette analyses to determine the silt andclay fractions (see Rudnicki, 1996, for more details onthe methodology). Dry bulk density (g/cm3), rb, wascomputed as the ratio of the mass of dry soil (g) to thevolume of the sample (cm3). Particle density (g/cm3),r s, was determined as the ratio of the mass of dry soil(g) to the volume of the dry soil (cm3) with the aid ofgas pycnometry (see Klute, 1986, for details on thegas pycnometer method). Porosity, f, was computedas (1 − rb/r s). Particle size distributions and porositymeasurements are discussed in Section 5. Hillslope-average dry bulk measured 1.1 g/cm3.

5. Results and discussion

5.1. Mean and variance of transect moisture content

The daily transect-mean moisture content and itsvariance are shown versus time in Fig. 2. Alsoshown are the daily precipitation depths. The timeseries is characterized by at least nine distinct ‘drydown’ sequences (beginning on 22 September, 1, 6and 18 November 1995; and 1, 19 and 28 Marchand 8 and 23 April 1996) in which the mean moisturecontent peaks following significant precipitationevents and decays rapidly thereafter. While severalsmaller and trace (unrecorded) rain events occurredbetween these dates (e.g. on 30 October 1995 and 6February , 26 and 30 March, and 13 April 1996), theyserved only to temporarily interrupt more pronounceddrying trends, unless they immediately followed, andwere effectively part of, larger events on the previousday (e.g. 22 September 1995). The longest of the drydowns include the six-week period between 22

September and 31 October 1995, and the 15-weekperiod between 18 November 1995 and 1 March 1996.

In general, the magnitude of the moisture contentpeaks corresponds to the depth of precipitation, withhigher mean moisture contents occurring after heavierrains. Other factors influencing the magnitude of thepeaks include antecedent mean-moisture conditions(wetter pre-existing conditions yield higher meanmoisture contents for storm events with similar char-acteristics), rainfall intensity (higher intensity rainfallmay yield more surface runoff and thus lower meanmoisture contents than storms of lower intensity), andthe timing of precipitation relative to moisture contentsampling (sampling was routinely conducted in theearly afternoon, so that infiltrated storm water wouldhave ample time to drain following rain events thatsignificantly preceded data collection). Since the rain-gauges employed in the study were non-recording, noattempt was made to determine the influence of thesevariables on the transect-mean moisture content otherthan the qualitative description given above.

Important seasonal trends in the mean moisturecontent are also apparent in Fig. 2. First, peaks inthe mean moisture content time series are greater fol-lowing storm events in the fall and spring months thanin the winter, owing to the greater precipitation depthsresulting from those storms. Second, the time requiredto reach a comparatively minimum value of moisturecontent at the end of a dry down is far greater duringthe winter than in the fall or spring. This is likely theresult of lower evapotranspiration rates during thewinter months. Third, the spring months experiencedmore frequent storm events so that more temporalvariability is evident in the time series in March andApril relative to the previous months. Consequently,the spring dry down sequences are brief with gener-ally higher minimum mean moisture contents than theminima observed during the fall and winter months.

The temporal dynamics of the variance are moredifficult to characterize. It is likely that a larger sam-ple size, fixed, rather than random sampling at eachtransect location, and an increased temporal monitor-ing frequency would have resulted in better con-strained estimates of the variance and its behaviorthrough time. However, some general observationscan be made. Fig. 2 shows that the behavior of thevariance loosely mimics that of the mean, peakingafter storm and trace events and decreasing rapidly


during the ensuing days. This is shown most clearly inthe first dry down sequence that follows the stormevent of 21–22 September 1995. Thus, heavier rainsand higher mean moisture contents are often asso-ciated with higher variability, and vice versa. Fig. 3shows that the variance generally decreases withdecreasing mean moisture content (consistent withprevious findings by Hills and Reynolds, 1969;Reynolds, 1970c; Henninger et al., 1976; Bell et al.,1980; Hawley et al., 1982; and Robinson and Dean,1993), but that scatter in the relationship increaseswith increasing wetness. This scatter can be attributedto the above-mentioned factors.

Given the above relationships, seasonal trends inthe variance may be best understood in the contextof seasonal trends in the mean moisture content. Forexample, of the highest peaks in the variance timeseries, several occurred during the fall months (e.g.20, 23 September and 7 November 1995), when trans-ect-mean moisture contents were at their highest for

the study period. Similarly, lower peaks occurred dur-ing the winter (e.g. 21 and 30 December 1995 and 24January 1996), and intermediate magnitude peaks areevident in the spring (e.g. 5 and 19 March 1996). Thefall dry down sequences show the greatest range insoil moisture variability, as the highest and lowestmean moisture contents were observed during thisperiod. Because, owing to the lower evapotranspira-tion rates, transect mean moisture content decreasesmore slowly during the winter dry down (beginningon 18 November 1995) than the fall (beginning on 22September 1995), so too does the variance. Just as thefrequency of spring storms prevents the transect meanmoisture content from decreasing to the minimumvalues observed during the fall and winter months,the variance is prevented from similar decreases.

5.2. Downslope moisture content profiles

Fig. 4 shows along-transect profiles of soil moisture

Fig. 2. Daily transect-mean moisture content (%) in the 0–5 cm soil layer versus time. Also shown are the variance (%2) and dailyprecipitation depth (cm).


content in the 0–5 cm layer for three representativedry down sequences (fall, winter and spring). Alsoshown is the elevation profile for the transect. Severalaspects of the variance and its temporal dynamics areapparent when examining these moisture content pro-files. For example: significant spatial variability inmoisture content exists along the length of the transectregardless of season or wetness conditions; spatialvariability is greatest immediately following a stormevent and decreases with time into the interstormperiod; and the degree of variability apparent in theearly phase of hillslope drying is directly related tothe depth of precipitation falling on the hillslope (seeFig. 2).

The profiles also share the following characteristicswhich have implications for the environmental factorsthat influence moisture content variability along thetransect. Immediately following a precipitation event,variability is greatest on the upper portion of the hill-slope, and decreases towards levels observed on thelower portion of the hillslope with time into a drydown. Also, early in the interstorm period, soil

moisture content appears uncorrelated with relativeelevation, but increasing negative correlation is evi-dent with time into the dry down. Negative correlationis consistent with previous findings by Krumbach(1959), Henninger et al. (1976), Hawley et al.(1983), Robinson and Dean (1993) and Nyberg(1996), all of whom noted an inverse relationshipbetween relative elevation and surface moisturecontent.

Fig. 5 shows the frequency distributions corre-sponding to each of the dates for which downslopemoisture content transects appear in Fig. 4. In eachcase, the progressive hillslope drying with time into adry down sequence is reflected by a translation of thedistribution to the left along the x-axis, towards lowervalues of the moisture content. Larger decreases invariance, such as those associated with the first falldry down, are also apparent in the histograms.

5.3. Correlation analyses

In this section we explore the relative roles of

Fig. 3. Variance of moisture content (%2) in the 0–5 cm soil layer versus mean moisture content (%).


Fig. 4. Moisture content (%) at each sampling location versus distance of sampling location along transect (m), for several dates during thesampling period. Also shown is the vertically-exaggerated relative elevation profile (m) for the transect. Panels a, b and c show progressivedrying along the transect during three separate dry down sequences (fall, winter, spring).


topography and soils in controlling the variability insurface moisture content observed at Rattlesnake Hill.We first present the results of a number of correlationanalyses, in which the time series of correlation

coefficients between surface soil moisture and severaltopographic attributes (relative elevation, specificcontributing area, slope, ln (a/tan b), mean curvature,profile curvature, planform curvature, and aspect) are

Fig. 5. Frequency (number of samples) of moisture content (%) for each of the dates shown in Fig. 4.


interpreted in the context of the vertical and lateralmoisture redistribution processes occurring duringand after storm events.

It is important to note that the presentation of suchtime series is only possible because of the high tem-poral sampling frequency in this work. In fact, none ofthe previous studies cited in Section 2 presented theirresults in this fashion. The benefit of the time seriesapproach is that it elucidates the evolution of correla-tion through time, which enhances our ability tounderstand the factors which influence variations insurface moisture content, and how they changethrough time.

Following the analysis of the role of topographicattributes, we next discuss the results of the particlesize analysis and present additional correlation coeffi-cient time series between moisture content and poros-ity and clay content. Based on these findings, in thenext section we summarize the mechanisms by whichwe believe the along-transect moisture content pro-files shown in Fig. 4 evolve through dry down

sequences, with implications for the factors responsi-ble for the observed variability.

The relationship between surface soil moisture andtopography is first explored via the time history of thecorrelation coefficient between moisture content andrelative elevation (Fig. 6). Relative elevation is aneasily and accurately measured surrogate for a num-ber of topographic and soil attributes which influencelateral redistribution of soil water, and withwhich it varies jointly (e.g. specific contributingarea, ln (a/tan b), aspect, water table elevation, claycontent, etc. (see Table 2)). In general, positive corre-lation increases with the occurrence of precipitationevents, and is followed by a rapid increase in negativecorrelation, towards high values of the correlationcoefficient (near −0.8 at the 95% significance level;note that for the purpose of this discussion, we refer topositive and negative correlation levels between 0 and0.5 as weak, between 0.5 and 0.8 as moderate, andbetween 0.8 and 1.0 as strong). The magnitude of theincrease in positive correlation generally corresponds

Fig. 6. Daily correlation coefficient between relative elevation and moisture content versus date. Also shown is daily precipitation depth (cm).


to the depth of rainfall, with the larger fall rain eventsresulting in the largest increases and smaller winterrain events yielding the smallest increases. Table 3further characterizes the moisture content–relativeelevation correlation coefficient time series (as wellas those of the additional topographic and soilattributes considered in this work) by presenting itsmaximum positive and negative daily values, and anaverage value of the correlation coeffient for the entirestudy period.

Although the correlation between relative elevationand surface moisture content grows increasinglystrong during dry down sequences, on its own, relativeelevation may not act as a significant driving force formoisture redistribution. It may simply reflectthe degree to which the topographic and soil

characteristics shown in Table 2 influence soil watermovement and hence moisture content variability atthe land surface. In order to understand better the rolesof the various topographic and soil attributes listed inTable 2, the time series of their correlation coeffi-cients with moisture content were computed.

Fig. 7 shows these time series for specific contri-buting area, a, the tangent of the slope angle, tan b,and the wetness index, ln (a/tan b). The time series ofthe specific contributing area–moisture content corre-lation coefficient (Fig. 7a) behaves similarly to that ofrelative elevation, though it is opposite in sign, andmaximum correlation levels are somewhat less. Posi-tive correlation decreases with the occurrence ofstorm events and increases towards moderate levels(correlation coefficients between 0.6 and 0.7) with

Table 2

Cross correlation matrix

Relativeelevation

Specificcontributingarea (a)

Slope(tan b)

ln (a/tan b) Meancurvature

Profilecurvature

Planformcurvature

cos(aspect)

Porosity Claycontent

Relative elevation 1 − 0.81 0.05 − 0.67 0.46 0.52 0.38 − 0.98 0.77 − 0.86Specific contributingarea (a)

1 − 0.56 0.93 − 0.68 − 0.61 − 0.69 0.82 − 0.51 0.48

Slope (tan b) 1 − 0.70 0.59 0.40 0.71 − 0.09 − 0.16 0.33ln (a/tan b) 1 − 0.84 − 0.71 − 0.87 0.69 − 0.41 0.34Mean curvature 1 0.95 0.97 − 0.49 0.28 − 0.24Profile curvature 1 0.84 − 0.52 0.36 − 0.37Planform curvature 1 − 0.43 0.18 − 0.11cos(aspect) 1 − 0.75 0.85Porosity 1 − 0.82Clay content 1

Table 3

Maximum positive, negative and time series-average correlation coefficients (95% significance level) between surface moisture content andtopographic and soil characteristics (20 September 1995–25 April 1996)

Attribute Maximum negative correlationcoefficient

Maximum positivecorrelation coefficient

Average correlation coefficient

Relative elevation − 0.83 0.48 − 0.37Specific contributing area (a) − 0.34 0.70 0.36Slope (tan b) − 0.64 0.23 − 0.12ln (a/tan b) − 0.36 0.62 0.29Mean curvature − 0.66 0.33 − 0.34Profile curvature − 0.70 0.35 − 0.40Planform curvature − 0.63 0.28 − 0.27cos(aspect) − 0.49 0.83 0.39Porosity − 0.73 0.62 − 0.19Clay content − 0.56 0.86 0.36


Fig. 7. Daily correlation coefficient between moisture content and (a) specific contributing area; (b) tan b; and (c) ln (a/tan b). All versus date.Also shown is daily precipitation depth (cm).


time into a dry down sequence. Note that positivecorrelation between specific contributing area and sur-face moisture content is in agreement with previousfindings by Moore et al. (1988) and Nyberg (1996).

Decorrelation with specific contributing area dur-ing storms is explained by the fact that the 0–5 cm soillayer is relatively thin. During a significant precipita-tion event, the storage capacity of the thin surfacelayer is quickly satisfied, in particular along thelower porosity, lower half of the transect (describedlater), so that no correlation with topography is evi-dent. However, owing to the wetness of the soil, lat-eral and vertical hydraulic conductivities are high,resulting in active moisture redistribution downslope and to greater depths in the soil profile. As dry-ing of the surface soil layer progresses, the correlationbetween moisture content and specific contributingarea increases, as downslope transect locations, withgreater specific contributing areas and thus a greaterinflux of moisture from upslope sources, remain wet-ter than upslope locations, in part due to the redistri-bution of soil water from upslope to downslopelocations. These mechanisms will be discussed furtherin the next section.

As shown in Fig. 7b, moisture content and slopeexhibit weak negative correlation during and imme-diately following storm events (maximum negativecorrelation between −0.3 and −0.6). With increasingtime into a dry down sequence, the correlation coeffi-cient tends to zero. The concentration of correlationaround precipitation events is indicative of a mechan-ism that only operates during storms. One possibleexplanation is that during precipitation events, loca-tions with higher slopes yield more infiltration excessrunoff, and thus less infiltrated water and lower moist-ure contents than those with lesser slopes. An alter-native explanation is that greater slopes foster rapiddrainage, and hence relatively lower moisture con-tents under the wet conditions following storm events.However, if this were the case, correlation would beexpected to persist, if not increase with time, as in thecase of specific contributing area. Weak correlationbetween surface moisture content and slope has alsobeen noted by Moore et al. (1988) and Nyberg (1996).

Fig. 7c shows the wetness index–moisture contentcorrelation coefficient time series. It behaves similarlyto that between moisture content and specific contri-buting area, approaching moderate levels of

correlation (between 0.5 and 0.6) with increasingtime into a dry down sequence. However, overall cor-relation levels are somewhat less than those shown inFig. 7a, owing to the combined impact of incorporat-ing slope, with which moisture content is only weaklycorrelated, and taking the natural logarithm of thecombined quantity a/tan b. The moderate level ofcorrelation reported on here is consistent with pre-vious findings by both Moore et al. (1988) and Nyberg(1996).

The correlation coefficient time series of moisturecontent with mean curvature, planform curvature andprofile curvature is shown in Fig. 8. All three timeseries behave similarly. As in the case of relative ele-vation, negative correlation tends to decrease withstorm events and increase with time into interstormperiods. The strength of the correlation for all threecurvature measures hovers in the weak to moderaterange, with profile curvature displaying the strongestrelationship to moisture content (approaching maxi-mum correlation levels between −0.4 and −0.7).Moore et al. (1988) have previously reported a weakcorrelation between surface moisture content and pro-file curvature.

As in the case of specific contributing area, thedecorrelation of curvature with moisture content dur-ing storm events is likely due to the fact that the thin,near-surface soil layer wets up quickly, and thereforeshows little relationship to topography. Only after thethin layer begins to dry, and soil water has had suffi-cient time to travel laterally, does the impact of cur-vature on moisture redistribution become evident.

While our results indicate that moisture content ismore strongly correlated to profile curvature thanplanform or mean curvature, it is important to notethat in this study, profile curvature was better resolvedthan planform curvature, owing to the manner inwhich elevation measurements were collected.Hence, correlation of moisture content with planformand mean curvature may in reality be stronger thanour results indicate. It should be noted further that thetransect is located along primarily divergent terrain,so that in general, variations in curvature are under-sampled with respect to this experiment.

The time series of the correlation coefficientbetween the cosine of aspect and moisture content isshown in Fig. 9. It is nearly identical to that betweenrelative elevation and moisture content, though opposite


in sign. In fact, Table 2 indicates that cos(aspect) andrelative elevation are highly correlated, with a corre-lation coefficient of −0.98. Consequently, the beha-vior of the time series shown in Fig. 9 mimics thatof the relative elevation–moisture content correlationcoefficient: positive correlation decreases duringstorm events; the strength of the decorrelation ofmoisture content with cos(aspect) generally corre-sponds to the depth of rainfall; and positive correla-tion increases following storm events, oftenapproaching strong levels (maximum values of thecorrelation coefficient near 0.8) late into dry downsequences. Positive correlation between surfacemoisture content and aspect is consistent with pre-vious findings by Reid (1973).

The progressively increasing correlation of cos(aspect) with moisture content during dry downsmost likely reflects the influence of topographic varia-bility on evapotranspiration, and thus surface soil

moisture. As seen in Fig. 1, aspect varies systemati-cally moving upslope, from east–southeast at the footof the transect, to south at the transect head. Conse-quently, downslope locations receive less daily solarradiation than upslope. This variation in solar radia-tion input along the transect implies lower rates ofevaporative drying downslope and greater ratesupslope. This effect would become more pronouncedwith time into a dry down sequence, as the differencein cumulative evapotranspiration losses increasesbetween upslope and downslope locations.

While the various topographic attributes consideredin this study work to redistribute moisture under thewet conditions associated with storms and early inter-storm periods, taken together, Figs. 4, 6–9 show thatmost of these attributes (with the exception of slope)are increasingly correlated with moisture content laterinto a dry down sequence. This suggests that someother environmental factor (e.g. soil properties,

Fig. 8. Daily correlation coefficient between moisture content and planform curvature, profile curvature and mean curvature. All versus date.Also shown is daily precipitation depth (cm).


vegetation, meteorology) influences variability ear-lier in a dry down. These results suggest further thatthe greater the precipitation depth and the resultingsurface wetness, the stronger the decorrelation withtopography, and the more important other environ-mental factors become in influencing moisture contentvariability early in an interstorm period.

At least two factors suggest that heterogeneity insoils is the dominant influence on soil moisture varia-bility under wet conditions. The first is that no sig-nificant variations in vegetation and precipitationwere observed along the transect. However, two dis-tinct soil types are found along the transect, and thetransition between the two, which occurs between60 m and 100 m from the transect origin (see Fig. 1),directly coincides with the transition between themore variable moisture conditions upslope and theless variable conditions downslope observed underwet conditions (see Fig. 4). Second, the tendencytowards positive correlation between relative eleva-tion and moisture content after heavy rain events

(see Fig. 6) is indicative of an environmental controlthat varies jointly with topography, such as soil prop-erties. For example, under saturated conditions, apositive correlation between relative elevation andmoisture content would be expected if porositydecreased systematically downslope.

The relationship between soil heterogeneity andmoisture content variability was further explored bymeans of particle size analysis and porosity measure-ments at each of the 21 sampling locations. Results ofthese analyses (Fig. 10) indicate that particle size dis-tributions are highly variable upslope and relativelyconstant downslope. These textural differences can beexpected to yield large variations in hydraulic conduc-tivity, which would be maximized under wet con-ditions (owing to the nonlinear relationship betweenmoisture content and hydraulic conductivity in theunsaturated zone), thus explaining the differences inupslope versus downslope moisture content variationsand the higher degree of soil moisture variabilityunder wet conditions than dry. Unfortunately, we

Fig. 9. Daily correlation coefficient between cos(aspect) and moisture content versus date. Also shown is daily precipitation depth (cm).


were unable to obtain reliable estimates of hydraulicconductivity along the transect, so that no correlationbetween surface moisture content and hydraulic con-ductivity was possible.

Like the particle size distributions, porosity(Fig. 10) shows a systematic (decreasing) trend down-slope, which explains the increasing positive correla-tion between moisture content and relative elevationwith increasing precipitation depth described above.In fact, the relationship between porosity and surfacemoisture content is shown more clearly in the timeseries of their correlation coefficient, shown inFig. 11a. As expected, positive correlation is at amaximum (moderate level) following rain events;and the wetter the soil, the stronger the correlation.

Fig. 11a also shows that the correlation betweenmoisture content and porosity becomes increasinglynegative, approaching moderate levels (correlationcoefficients between −0.6 to −0.7) as dry downsequences progress, so that the influence of soil

heterogeneity on surface moisture content variabilityis not strictly limited to early in dry down sequences.The downslope decrease in porosity (and the othersystematic textural variations shown in Fig. 10) islikely associated with coincident decreases in hydrau-lic conductivity, so that negative correlation wouldarise due to slower drainage and evapotranspirationrates, and thus higher surface moisture contents at thefoot of the transect.

This point is further supported by the time series ofthe correlation coefficient between clay content andsurface moisture content shown in Fig. 11b. In gen-eral, positive correlation increases with time in a drydown sequence, and reaches high levels (correlationcoefficients greater than 0.8) during the wintermonths. This increase in positive correlation is con-sistent with the increasingly negative correlationshown in Fig. 11a, since increasing clay contentdownslope likely results in decreasing hydraulic con-ductivity, slower drainage and evapotranspiration

Fig. 10. Particle size distribution (%) and porosity (%) at each sampling location versus distance of sampling location along transect (m).


rates, and hence higher moisture retention along thelower portion of the transect.

5.4. Summary of mechanistic controls on surface soilmoisture variability at Rattlesnake Hill

Because both topographic and soil characteristicsvary systematically in the downslope direction, dis-tinguishing between the relative roles of topographicand soil attributes in influencing surface moisture con-tent variability would require intensive field monitor-ing that is beyond the scope of this work.Additionally, since only a limited range of theseattributes are observed along the single transect,their influence on surface moisture content variations

may be over or underestimated with respect to thelarger hillslope area. With these caveats in mind, weoffer a conceptual model of the mechanistic controlson surface soil moisture variability along the Rattle-snake Hill transect.

Under the wettest conditions, the surface layer willbe saturated, and consequently, we propose that var-iations in moisture content are strongly influenced bythe spatial distribution of porosity. Although topogra-phy is playing an important role in driving lateralredistribution under saturated and wet conditions, itsimpact on moisture content variability may not yet beevident while the thin soil layer is at or near satura-tion. Our results indicate that under the wettest con-ditions encountered during the study (22 September

Fig. 11. Daily correlation coefficient between moisture content and (a) porosity; (b) clay content. Both versus date. Also shown is dailyprecipitation depth (cm).


and 1 November 1995), at which time the surface soillayer along the lower half of the transect was satu-rated, surface moisture content is moderately corre-lated to porosity, clay content, relative elevation andaspect. Correlation to relative elevation has been pre-viously explained in the context of its covariance withporosity; correlation with clay content and aspect canbe similarly explained, since they are each highlycorrelated with relative elevation (see Table 2). Cor-relation between surface moisture content and all ofthe remaining topographic indices is weak.

The high moisture contents following significantstorm events result in active vertical and lateral redis-tribution. Under wet, but not saturated conditions, soilmoisture variability is likely controlled by variationsin hydraulic conductivity, the heterogeneity in whichwill have a greater impact on moisture movement, andthus moisture content variations, under wet conditionsthan dry. Unfortunately, as previously mentioned, noreliable measurements of hydraulic conductivity wereobtained in this study. However, we believe that theincreased variability in the along-transect moisturecontent profiles under wet versus dry conditions is adirect result of the measured variations in particle sizedistribution and porosity (Fig. 10), which serve asindirect measures of hydraulic conductivity.

As the hillslope dries, soil properties and topogra-phy continue to jointly influence moisture movement,and the impact of topography on soil moisture varia-bility becomes more apparent. Results of the particlesize size analysis indicate that clay content increasesand porosity decreases in the downslope direction.Both of these are consistent with a systematicdecrease in hydraulic conductivity along the transect.This would result in more rapid drainage upslope,more moisture retention downslope, and the emer-gence of along-transect moisture content profiles inwhich moisture content increases downslope.

Topography also contributes to the downslopeincrease in moisture content, in at least two ways.First, topographically-driven lateral flow redistributesmoisture towards areas of topographic convergence,and from upslope to downslope areas. Consequently,in addition to draining more slowly than upslopeareas, downslope locations receive more lateral moist-ure inputs from (at least while lateral redistribution isactive), and thus remain wetter than, their upslopeneighbors. Second, as shown in Fig. 1, aspect changes

systematically along the transect, from south upslopeto east–southeast downslope, and as a result, upslopeareas receive greater daily total solar radiation inputthan those downslope. This likely encourages greaterevaporative drying upslope than down, further contri-buting to the increasingly negative correlation ofmoisture content with relative elevation seen in thetime series of hillslope moisture content transectsshown in Fig. 4. Our results show that with progres-sive drying, for example, by the end of the fall andwinter dry down sequences, correlation with moisturecontent is strong for relative elevation, clay contentand cos(aspect); is moderate for specific contributingarea, porosity, ln (a/tan b), and profile curvature; isweak for planform and mean curvature, and is essen-tially zero for slope.

5.5. Implications for surface soil moisture estimation

The results of this study have the following impli-cations for modeling and predicting variations in sur-face soil moisture content at Rattlesnake Hill. Theseimplications may also have relevance to soil moistureestimation in different geographical and climatologi-cal regimes. First, small scale variations in both soiland topographic properties control the evolution ofsurface moisture content variability along the transect.Hence, in hillslope-scale applications, these variousattributes must be incorporated at high resolutioninto distributed hydrological models, or into the deri-vation of other predictive measures of surface moist-ure content.

Second, the topographic and soil attributes withwhich variability in surface moisture content is mostcorrelated, change with the degree of hillslope wet-ness, from porosity and hydraulic conductivity underwet conditions, to relative elevation, cos(aspect) andclay content under drying conditions. This suggeststhat no one predictive index (e.g. the wetnessindex), can be expected accurately to predict surfacemoisture content throughout an entire dry downsequence. Rather, different predictive indices forwet versus dry conditions may be required. Westernet al. (1997) reached a similar conclusion, but for the30 cm surface soil layer, rather than the 5 cm layerconsidered in this study.

Third, it is worth noting that under drying condi-tions, several other topographic and soil attributes


were better correlated with surface moisture contentthan ln (a/tan b) (relative elevation, clay content,cos(aspect), specific contributing area and porosity).This is likely due to the fact that the wetness indexwas developed to predict the soil water deficit in theentire unsaturated zone profile, not just the upper 5 cmsoil layer. In spite of this theoretical mismatch, thewetness index is often invoked as a predictor of sur-face moisture content, and this research suggests thatother topographic and soil attributes are better suitedat Rattlesnake Hill and perhaps elsewhere.

A final and related point for discussion is the highcorrelation of relative elevation with moisture contentunder dry conditions. At Rattlesnake Hill, several ofthe topographic and soil attributes investigated in thiswork vary systematically with relative elevation, andare consequently strongly or moderately correlatedwith it (Table 2). As such, we believe that its strongcorrelation to moisture content results because it inte-grates along-transect variability in important controls(e.g. porosity, hydraulic conductivity, aspect, claycontent, specific contributing area, wetness index,curvature) into one easily and accurately measuredvariable. Because of the ease with which relative ele-vation is measured (i.e. it does not need to be derivedfrom a high resolution DEM, which may not exist in alocation of interest) we suggest that its utility as apredictive index of surface moisture content beexplored beyond the context of Rattlesnake Hill.

6. Summary

Variability in surface soil moisture content wasstudied along a 200 m downslope transect on a hill-slope in central Texas. For the seven-month periodbeginning on 20 September 1995, soil samples werecollected on a near-daily basis at 10 m intervals alongthe transect, and gravimetric moisture contents weredetermined. Results for the 0–5 cm surface soil layerindicate that significant variability in moisture contentexists along the length of the transect; that followingrain events, variability is greater upslope than down-slope; that these differences decrease with time; andthat in general, moisture content variability decreaseswith time between rain events as the transect-meanmoisture content decreases.

The dominant influences on soil moisture

variability were inferred by correlation analyses.Though cross-correlation between soil and topo-graphic attributes complicated identification of caus-ality, results suggest that the dominant influences onsoil moisture variability along the transect are depen-dent upon the status of surface moisture content.Under wet conditions, variation in soil properties(porosity, hydraulic conductivity) exerts a controllinginfluence on surface moisture content variability.Under dry conditions, surface soil moisture contentis most strongly related to relative elevation, aspectand clay content. Consequently, the dominant influ-ence on soil moisture variability gradually changesfrom soil heterogeneity to joint influence by topogra-phy and soil properties as the transect dries followingrain events.

Acknowledgements

This work was supported in part by the GeologyFoundation of the Department of Geological Sciencesat the University of Texas at Austin, and by NASAgrants NAGW-4087 and 5240, and NAG5-3773 and6395. The authors wish to acknowledge the AustinParks and Recreation Department for access to theRattlesnake Hill site; Philip Bennett for the use ofhis laboratory facilities; Roberto Gutierrez for hisefforts with GPS and his help in constructing theDEM; and David Martineau for his assistance withgas pycnometry. The comments of Jack Sharp,Bridget Scanlon and two anonymous reviewersgreatly improved the quality of this paper.

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