LANDSLIDES OF THE CINCINNATI, OHIO, AREA

Rapid Water-Level Fluctuations

in a Thin Colluvium Landslide

West of Cincinnati, Ohio

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Rapid Water-Level Fluctuations 

in a Thin Colluvium Landslide 

West of Cincinnati, Ohio

By WILLIAM C. HANEBERG and A. ONDER GOKCE

LANDSLIDES OF THE CINCINNATI, OHIO, AREA

U.S. GEOLOGICAL SURVEY BULLETIN 2059-C

The fluctuations are analyzed using 

analytical and numerical models of 

modified Dupuit hillside flow

UNITED STATES GOVERNMENT PRINTING OFFICE, WASHINGTON : 1994
U.S. DEPARTMENT OF THE INTERIOR 

BRUCE BABBITT, Secretary

U.S. GEOLOGICAL SURVEY 

Gordon P. Eaton, Director

For Sale by U.S. Geological Survey, Map Distribution

Box 25286, MS 306, Federal Center

Denver, CO 80225

Any use of trade, product, or firm names in this publication is for descriptive purposes only and 

does not imply endorsement by the U.S. Government

Library of Congress Cataloging-in-Publication Data

Haneberg, William C.

Rapid water-level fluctuations in a thin colluvium landslide west of Cincinnati, Ohio / by 

William C. Haneberg and A. Onder Gokce.

p. cm. (U.S. Geological Survey bulletin ; 2059-C) (Landslides of the Cincinnati, 

Ohio, area ; ch. C)

1. Landslides Ohio Cincinnati Region. 2. Colluvium Ohio Cincinnati 

Region. 3. Groundwater Ohio Cincinnati Region.

I. Gokce, A. Onder. II. Title. HI. Series. IV. Series: Landslides of the Cincinnati, 

Ohio, area ; ch. C. 

QE75.B9 no. 2059-C 

[QE599.U5]

557.3 s dc20 93-37928 

[551.3'07] CIP
CONTENTS

Abstract........................................................................................................................... Cl

Introduction..................................................................................................................... 1

Acknowledgments................................................................................................ 1

Previous Work................................................................................................................ 2

Subsequent Work............................................................................................................ 2

Geologic Setting and Soil Properties.............................................................................. 2

Hydraulic Conductivity........................................................................................ 4

Grain Size, Atterberg Limits, and Clay Mineralogy............................................. 5

Measurement of Water-Level Fluctuations.................................................................... 5

General Characteristics of P-4 Water-Level Records.......................................... 5

Individual Storms ................................................................................................. 5

A Mathematical Model for Hillside Flow ...................................................................... 6

Modified Dupuit Flow.......................................................................................... 6

The Governing Equation....................................................................................... 8

Dimensional Analysis of the Governing Equation............................................... 10

Finite Difference Formulation.............................................................................. 11

Boundary and Initial Conditions........................................................................... 11

Numerical Results........................................................................................................... 12

Simulation of P-4 Water-Level Records.............................................................. 12

Discussion....................................................................................................................... 14

References Cited............................................................................................................. 15

FIGURES

1. Index map showing location of Cincinnati, Hamilton County, the Ohio River, and the Delhi Pike study area ......... C3

2. Plane table geologic map of the portion of the Delhi Pike landslide complex studied in this paper .......................... 4

3. North-south longitudinal cross section along the trench shown in figure 2 ................................................................ 6

4. Graph showing variation of colluvium hydraulic conductivity with depth ................................................................. 8

5. Schematic drawing of piezometer P-4 at Delhi Pike .................................................................................................. 8

6. Graphs showing rainfall and piezometric level in piezometer P-4 for three rainy periods in the spring of 1980 ...... 9

7. Graph showing change in water level versus rainfall.................................................................................................. 10

8. Idealized sketch of a thin slab atop a sloping substrate and the representative element used to derive the

	governing equation....................................................................................................................................................... 10

9. Graph comparing actual and synthetic water-level records from piezometer P-4 for April 11-12, 1980 ................. 12

10. Graph showing modeled water levels along a sloping aquifer at various time intervals following a rainstorm ........ 13

11. Synthetic water-level records showing projected response to three different patterns of rainfall .............................. 13

TABLE

1. Grain-size distribution of colluvium, Atterberg limits, and clay type in samples from a borehole at Delhi Pike ...... C5

III
IV CONTENTS

	LIST OF SYMBOLS

A0 Amplitude of periodic perturbation to the phreatic surface

c Celerity of a traveling waveform (= sin (3)

D Thickness of a porous slab

H Normalized height of phreatic surface (= h/D)

h Height of phreatic surface measured perpendicular to the substrate

/ Spatial grid index

j Temporal grid index

K Hydraulic conductivity in saturated soil

L Length of a porous slab

O Order

p Effective porosity

R Net recharge to the water table

T Normalized time (= tltr)

t Time

tr Characteristic time (= pDIK)

X Normalized slope-parallel coordinate (= ^/L)

P Slope angle in degrees

X Wavelength of periodic perturbation to the phreatic surface

O Total hydraulic head (h cos P-^ sin P)

a Aspect ratio of porous slab (= DIL)

£, Slope-parallel coordinate on a sloping, porous slab, giving distance

	from upper end of slab to point of measurement 

£ Coordinate normal to slope on a sloping, porous slab, giving distance

	from base of slab to point of measurement
RAPID WATER-LEVEL FLUCTUATIONS IN A

THIN COLLUVIUM LANDSLIDE WEST OF

CINCINNATI, OHIO

By William C. Haneberg 1 ' 2 and A. Onder Gokce 1 ' 3 

ABSTRACT INTRODUCTION

Data from 14 rainstorms between March and May 1980 

show that water levels in colluvium at the Delhi Pike landslide complex, which lies along the Ohio River valley about 

15 km west of downtown Cincinnati, can rise and fall 

quickly during and immediately after storms. Piezometer 

water-level records are characteristically asymmetric, with 

steep rising limbs and flatter, sigmoidal falling limbs. Rainfall intensity, rainfall duration, and effective porosity all 

appear to control the shapes and amplitudes of these waterlevel records. A modified Dupuit hillside flow model shows 

that water levels will fluctuate uniformly along the entire 

slope in response to either an increase or a decrease in net 

recharge (due to either rainfall or evapotranspiration) and 

that wavelike downhill flow can occur only when net 

recharge is negligible. For each storm observed, we divided 

total rainfall by total change in ground water level to derive 

an estimate of pre-storm maximum effective porosity. These 

figures ranged from 1 to 7 percent for all but one of the 

storms. We found, however, that effective porosity values in 

the range of 1 to 3 percent gave a much better simulation of 

actual water-level records when used in a finite-difference 

approximation of modified Dupuit flow, suggesting that the 

hillside must have been at or very near tension saturation 

before the storms of record. Our model is very sensitive to a 

combination of effective porosity, hydraulic conductivity, 

rainfall intensity, and rainfall duration (all of which are 

difficult to characterize in the field), and suggests that caution should be exercised when attempting to predict the 

hydrologic response of hillsides to rainfall.

1 John L. Rich Geomechanics Laboratory, Department of Geology, University of Cincinnati, Cincinnati, OH 45221-0013.

2Current address: New Mexico Bureau of Mines & Mineral Resources, 

New Mexico Institute of Mining & Technology, Socorro, NM 87801.

3Current address: Parsons Brinckerhoff Quade & Douglass, 120 

Boylston St., Boston, MA 02116.

Several years ago, while examining dozens of 

landslides along the Ohio River and its tributaries near 

Cincinnati, Ohio, we began to realize that in some landslides 

destabilizing pore water pressure is artesian, whereas in 

others it is hydrostatic. We selected two study areas, one in 

glacial deposits and another in colluvium, for detailed 

observation and began to monitor movement and water 

levels in both places.

We began exploring the colluvium landslide complex 

in March 1979 by drilling two types of boreholes: on gentle 

slopes, we used a trailer-mounted auger rig to make deep 

boreholes; and on steeper slopes, we used a two-person 

portable auger to make shallow boreholes. We installed 

porous-stone piezometers in all holes and measured 

piezometric levels by hand at 2-week intervals. After 

realizing that piezometric levels in the shallow colluvium 

could change very rapidly in direct response to rainfall 

(Fleming and others, 1981; Gokce, 1989), we installed 

instruments to record both rainfall and piezometric level in 

one piezometer at 15-minute intervals from late March 

through mid-May 1980. In this paper we describe details of 

these rainfall and piezometric-level records and then use a 

simple mathematical model of hillside ground-water flow to 

explain some important characteristics of piezometer waterlevel records.

ACKNOWLEDGMENTS

Most of the work described in this chapter was done 

while the authors were in residence at the University of 

Cincinnati Department of Geology. Fieldwork and data 

analysis by A. Onder Gokce were supported by the U.S. 

Geological Survey (USGS) and the University of Cincinnati. 

Data analysis and modeling by William Haneberg were 

supported by The Hillside Trust, the USGS, and the 

University of Cincinnati. Geotechnical testing was 

performed by personnel of the USGS soil mechanics

Cl
C2 LANDSLIDES OF THE CINCINNATI, OHIO, AREA

laboratory in Golden, Colo., under the direction of Roger 

Nichols. Reviews by Rex Baum, Robert Fleming, Arvid 

Johnson, and David Nash helped to improve many parts of 

this paper.

PREVIOUS WORK

Iverson and Major (1987) describe both annual and 

short-term water-level fluctuations in a long, thin, northern 

California landslide, and note both that high-frequency 

fluctuations due to individual storms attenuate with depth 

and that the events of previous water years control annual 

water-level increases. These results are in line with those of 

two separate field studies by Gillham (1984) and 

Novakowski and Gillham (1988), who concluded that high 

antecedent moisture content resulted in more rapid watertable response to rainfall. Pyles and others (1987) observed 

asymmetric water-level fluctuations similar to those 

described in this paper during their studies of thin landslides 

in western Oregon. Harr (1977) monitored both saturated 

and unsaturated flow in a steeply sloping, forested hillside in 

the same western Oregon experimental forest used by Pyles 

and others (1987), and showed that flow was almost always 

unsaturated except near the foot of the hillside. He used 

measurements of stream and seepage-face discharge to show 

that the lower reaches of the hillside remained saturated due 

to drainage of soil pores farther upslope that had been filled 

during rainstorms. Upper reaches of the hillside became 

saturated at depth from time to time, but only after at least 3 

mm of rain fell within 12 hours, and even then the saturation 

persisted less than 20 hours. Harr attributed these 

intermittent zones of saturation to the accumulation of 

infiltrating water along the contact between soil and 

underlying bedrock, where hydraulic conductivity decreased 

by an order of magnitude. Longitudinal water-table profiles 

from a natural hillside described by Anderson and Burt 

(1977a) show that water accumulates in the lower portion of 

the hillside while water level falls in the upper portions. In a 

related laboratory study, Anderson and Burt (1977b) show 

that a sloping, sand-filled gutter drains from the top down 

and a small saturated wedge remains at the base throughout 

the experiment. Measurements of discharge from the 

laboratory setup agree closely with those predicted using the 

slope of the water table as the hydraulic gradient, but do not 

agree with predictions that factor in the release of water from 

the unsaturated zone, suggesting that gravity drainage of 

unsaturated sand was negligible under the conditions 

investigated by Anderson and Burt (1977b).

SUBSEQUENT WORK

Since the revised manuscript for this chapter was 

returned to the U.S. Geological Survey for publication,

additional work has almost completely superseded the 

mathematical model it describes.

Jackson and Cundy (1992), for example, developed a 

more complicated two-dimensional finite-difference model 

of modified Dupuit flow incorporating topographically 

convergent and divergent flow, which they used to 

successfully reproduce ground-water-level fluctuations 

observed in a steep hillslope hollow in the Cascade Mountains of Washington. Haneberg (199la) (1) described shortterm, predominantly unsaturated pressure-head fluctuations 

that were observed during the spring of 1988 at the Delhi 

Pike landslide complex, (2) presented a dimensional analysis 

of the partial differential equation governing flow through a 

variably saturated sloping layer in order to establish the 

conditions under which slope-normal and slope-parallel flow 

would predominate, (3) used a finite-difference model of 

slope-normal pore-pressure diffusion in an attempt to 

reproduce field measurements collected during the spring of 

1988, and (4) concluded that storm frequency, storm 

intensity, and pre-storm fillable porosity influenced the 

hydrologic response of thin landslides to rainfall. Haneberg 

(1991b) applied the pore-pressure-diffusion model to 

published data from several landslides in order to calculate 

characteristic response times, and discussed how the diffusion model could be used to explain the nonlinear storm 

intensity-duration curves that are common products of 

empirical studies of rainfall thresholds associated with slope 

instability. This chapter was optimistically cited as Haneberg 

and Gokce (1991) in all three of the papers described above.

Finally, Haneberg (1992) presented a simple massbalance model of subsurface flow through hillside soils, and 

compared the results of this model to field data from the 

Delhi Pike landslide. This work showed that the steady-state 

ratio of recharge to discharge at Delhi Pike, estimated using 

spring 1988 precipitation values, was near unity, and that 

simulations of unsteady flow could reproduce average pore 

pressure values observed at Delhi Pike.

GEOLOGIC SETTING AND SOIL 

PROPERTIES

Landslides in the Delhi Pike area (fig. 1) occur in illitic, 

bouldery-silty-clayey colluvium formed along the northern 

side of the Ohio River valley about 15 km west of downtown 

Cincinnati. Colluvium thickness ranges from less than a 

meter near hilltops to more than 10 m at river level, and the 

basal slip surfaces of the slides are generally along the 

contact between colluvium and weathered bedrock. Flatlying, interstratified shale and limestone of the Upper 

Ordovician Kope Formation (approximately 80 percent 

shale and 20 percent limestone) and the overlying Upper 

Ordovician Fairview Formation (approximately 60 percent 

shale and 40 percent limestone) compose the local bedrock 

and are parent material for the overlying colluvium.
WATER-LEVEL FLUCTUATIONS IN LANDSLIDE WEST OF CINCINNATI C3

_ByTLER' COUNTY 

HAMILTON COUNTY

39° 

15'

39°

20 KILOMETERS

Figure 1. Location of Cincinnati, Hamilton County, the Ohio River, and the Delhi Pike study area.

For the most part, landslides in the Delhi Pike area are 

elongate parallel to topographic contours but, in some 

cases, this pattern is broken by narrow U-shaped landslides 

reaching farther uphill. The landslide that we describe is 

one of these U-shaped fingers, as shown in a detailed planetable map (fig. 2). Its topography is generally irregular, with 

many small hummocks and scarps about a meter high, but 

the overall slope of the ground surface range from 20° to 

30°, and the bedrock surface slopes approximately 20° 

across most of the hillside. The main slide mass is bounded 

by a left-lateral strike-slip zone along its entire eastern flank, 

a head scarp to the north, and a right-lateral strike-slip zone 

along the northern half of its western flank. All of these 

boundaries coincide with topographic depressions, in some 

places as much as 1 m deep. The southern half of the western 

flank grades into several east-west scarps and, hence, has no 

distinct boundary. The northern half of the slide mass is 

broken into a number of smaller slides, each of which has a 

subsidiary, U-shaped head scarp reflecting the shape of the 

slide as a whole. The vertical offset along these scarps is 

generally 1 m or less. Subsidiary scarps in the southern half 

of the slide, where the western boundary becomes indistinct, 

tend to be nearly linear and parallel to topographic contours. 

Locally, however, these parallel scarps branch and join to 

form an anastomosing network. The subtle increase in slope

above the +30 m contour (all elevations are relative to an 

arbitrary control point on Delhi Pike) reflects the transition 

from Kope Formation to Fairview Formation bedrock.

The colluvium at Delhi Pike is mapped as Eden silty 

clay loam, a residual soil formed on moderate to steep 

slopes, in the Hamilton County Soil Survey (Lerch and 

others, 1982). It is described as well drained, with slow 

permeability and very rapid runoff (although our field 

observations showed very little runoff during storms). 

Lerch and others further state that excavations in the lower 

parts of slopes commonly have seepage problems and recommend that drains be installed around foundations. We 

had five test trenches excavated, using backhoes and larger 

tracked excavators, and found that within about 0.1 to 0.2 m 

of the surface the colluvium is grayish-brown and commonly breaks into peds, whereas colluvium 0.2 m or more 

below the surface is yellowish and massive. In places, however, brown colluvium is found in isolated lenses within the 

yellow colluvium. Both types of colluvium are composed of 

about 70 percent silty-clayey matrix and 30 percent 

limestone slabs as much as 0.3 m thick and 3 m long, with 

no apparent preferred orientation. The distribution of brown 

colluvium, yellow colluvium, large limestone slabs, and 

slip surfaces exposed in a longitudinal trench is shown in 

figure 3.
C4 LANDSLIDES OF THE CINCINNATI, OHIO, AREA

EXPLANATION

 i Scarp Hachures on downdropped side. 

Dashed where inferred

= Strike-slip boundary Showing relative 

horizontal movement

P8 I Piezometer location

> A Tensiometer location

0 10

CONTOUR INTERVAL 1 METER

20 METERS 

I

Figure 2. Plane-table geologic map of the portion of the Delhi Pike landslide complex studied 

in this paper. All elevations are relative to an arbitrary station on Delhi Pike. Data obtained 

from piezometer P^t during the spring of 1980 

are described in this paper. See Haneberg 

(199la) for a discussion of data from other piezometers and tensiometers shown here. Mapped by W.C. Haneberg and R.L Olson, 1987

HYDRAULIC CONDUCTIVITY

A falling-head permeability test was run on each of nine 

samples taken from different depths in a trench at Delhi Pike, 

and the results were averaged to obtain a single value for 

each sample. These average values range from a high of

2.63xlO~5 m/s to a low of 7.70x10 8 m/s and have an 

arithmetic mean of 1.31xlO~5 m/s and a geometric mean of 

6.67xlO~ 6 m/s (fig. 4); if the solitary value in the 10~8 range 

is excluded, the lowest average value becomes 3.26xlO~6 

m/s and the arithmetic mean becomes 1.47xlO~5 m/s. With 

the exception of two errant values, hydraulic conductivity
WATER-LEVEL FLUCTUATIONS IN LANDSLIDE WEST OF CINCINNATI C5

appears to be very nearly constant with depth. Both horizontal and vertical components of hydraulic conductivity were 

measured for one of the samples from a 1.2 m depth, and the 

average vertical conductivity is 5.11xlO~6 m/s, whereas the 

average horizontal conductivity is 1.03xlO~5 m/s. It is 

difficult to assess the significance of measurements on only 

one sample, but, if accurate, these results suggest that the 

colluvium at Delhi Pike is weakly anisotropic.

for location), approximately halfway up the landslide, to 

monitor piezometric levels at 15-minute intervals between 

late March and mid-April 1980. Our original intent was to 

use these short-term data to estimate piezometer lag time, but 

they also provided the first evidence of rapid water-level 

fluctuations in the Delhi Pike landslide complex. Subsequent 

field work during 1987 and 1988 has shown that P^ often 

contains water when other piezometers are dry, and we have 

limited data to suggest that this was also true during 1980.

GRAIN SIZE, ATTERBERG LIMITS, AND 

CLAY MINERALOGY

Grain size, Atterberg limits, and clay mineralogy were 

determined using four samples taken from different depths in 

an auger hole, approximately 60 m southeast of piezometer 

P 4 but not shown in figure 2. There is very little variation 

in grain size distribution, Atterberg limits, or clay 

mineralogy with depth in the borehole (table 1). Both the 

colluvium and the weathered bedrock samples were 

composed primarily of clay-sized grains with lesser amounts 

of silt-sized grains. Gravel- and sand-sized grains composed 

less than 15 percent of sample weight, in all cases. Liquid 

limits average 46 percent and plastic limits average 24 

percent; both decrease slightly with depth.

MEASUREMENT OF WATER-LEVEL 

FLUCTUATIONS

Our piezometers were cylindrical porous stones, 5 cm 

in diameter and 30 cm long, attached to a 2.5-cm-diameter 

(1-inch O.D.) PVC pipe. Each piezometer hole was backfilled with quartz sand to a level approximately 20 cm above 

the top of the porous stone and sealed with approximately 40 

cm of bentonite (fig. 5). We measured water levels by hand 

in six piezometers at Delhi Pike at least twice a month 

between March 1979 and August 1980. In addition, we 

installed an automatic recorder in piezometer P-4 (see fig. 2

Table 1. Grain-size distribution, Atterberg limits, and clay type 

of colluvium in samples from a borehole at the Delhi Pike landslide 

complex.

Depth 

(m)

1.2

2.1

4.8

6.8

Grain size 

(weight percent)

Gravel

1

4

1

5

Sand

6

7

4

9

Silt

26

29

31

31

Clay

67

60

64

55

Atterberg limits 

(percent)

Liquid

50

48

45

41

Plastic

25

24

24

21

Clay type

Mixed layer, illite.

Mixed layer, illite.

Mixed layer, illite.

Illite, kaolinite.

GENERAL CHARACTERISTICS OF P-4 

WATER-LEVEL RECORDS

We see several common characteristics in the waterlevel records that we describe below, which are typical of all 

our data from P-4. During the summer and early autumn, the 

bottom of P-4 is dry (water level at least 1.20 m below the 

surface), whereas during the late winter and spring of 1980, 

the background water level stood from 0.8 to 0.9 m below the 

surface. This background water level is punctuated by 

distinct increases of several decimeters that correspond to 

individual rainstorms. Short, intense storms generally 

produced sharp peaks, whereas gentle and prolonged rainfall 

generally produced flat-topped peaks. Regardless of rainfall 

intensity and duration, the water-level record peaks are 

asymmetric. In some cases, piezometric level rose virtually 

instantaneously in response to rainfall, and in other cases the 

rise in piezometric level was considerably slower, but 

piezometric levels always fell more slowly than they rose. 

After rainfall had stopped, piezometric levels characteristically fell slowly at first, then more rapidly, and then slowly 

again as the background piezometric level was approached; 

this pattern formed a sigmoidal falling water-level record 

showing that the water level continued to fall very slowly for 

many tens of hours, in the absence of additional rain. When 

more rain fell several hours after a storm, the fall of the water 

table slowed substantially. In some cases a small hump 

appears to be superimposed upon the overall slope of the 

falling water-level record, but in other cases there is no sign 

of a hump. We use specific examples below, in 

chronological order, to illustrate these generalities.

INDIVIDUAL STORMS

March 20 through March 22, 1980. The first P-4 

water-level record that we describe, illustrated in figure 6A, 

is flat-topped and results from a period of intermittent, relatively gentle rainfall distributed over about 17 hours. Base 

level was about 0.83 m beneath ground level both before and 

after the rainfall. Significant features of this water-level 

record are a compound rising limb reflecting two distinct 

storms on the evening of March 20, and a broad, gently 

sloping crest associated with gentle rainfall on the morning
C6 LANDSLIDES OF THE CINCINNATI, OHIO, AREA

65i20

Figure 3 (above and facing page). North-south longitudinal cross section along the trench shown in figure 2. Section shows distribution of 

brown colluvium, yellow colluvium, limestone slabs, slip surfaces, and the contact between colluvium and weathered bedrock. Figure 

reduced from Fleming and Johnson (1994, pl.l).

of March 21. As with all of our records, the falling limb of 

the water-level record is sigmoidal in shape and is, on the 

whole, much flatter than the rising limb.

April 8 through April 18, 1980. The P^ water-level 

record for this 10-day period (fig. 65) contains a closely 

spaced series of four storms and attendant water-level 

increases. All of the water-level-record peaks during these 

ten days were much sharper than the water-level record from 

March 20 through March 22 (fig. 6A), but the rates (slopes of 

the water-level-record limbs) of water-level changes are 

similar. What appears to be missing is the prolonged, 

intermittent rainfall that occurred during March 20 through 

March 22. Base level before and after this series of storms 

was from 1.12 to 1.15m below ground level. During the first 

storm, approximately 11 mm of rain caused a water-level 

increase of only 3 cm, but in subsequent storms the waterlevel increase is much greater. Rainfall amounts totaling 4 

mm on the 9th, 15 mm on the llth, and 14 mm on the 13th 

resulted in water-level increases of 23, 51, and 54 cm, 

respectively. All four of these water-level records are 

distinctly asymmetric, as is typical of our data.

May 12 through 13,1980. We include this water-level 

record (fig. 6C) in our descriptions because it contains the 

most rapid piezometric-level increase (0.54 m/hr), the most 

rainfall in a single storm (40 mm), and the highest piezometric levels (0.30 m below ground level) we recorded at Delhi 

Pike. As shown in figure 6C, the rising water-level record 

limbs for both storms are very nearly vertical, suggesting a 

nearly instantaneous water-level increase.

Effective porosity. We estimated maximum effective 

porosity for each storm as total rainfall divided by total 

change in water level. In doing this, we assume that all 

rainfall entered the soil and contributed to the water-table 

rise, so our estimates are maximum possible values. In all but 

one case, we found maximum effective porosity ranged 

between 1 percent and 7 percent for all of the storms during 

our period of record (fig. 7) and, in general, that the 

magnitude of water-level increase is proportional to the 

amount of rainfall. The lone exception occurred on April 8, 

1980, when rainfall of 11 mm produced a piezometric level 

increase of 25 mm, for a maximum effective porosity of 44 

percent. This storm will be discussed later in the chapter.

A MATHEMATICAL MODEL FOR 

HILLSIDE FLOW

MODIFIED DUPUIT FLOW

The well-known Dupuit approximation of groundwater flow through a phreatic aquifer, drawn from the 

observation that in most phreatic aquifers the water-table 

slope is very small (Bear, 1972, p. 361), incorporates the 

assumptions that flow is horizontal and equipotential lines 

are vertical. Boussinesq (1904) extended the Dupuit model 

to account for unconfined flow above a sloping impervious 

substrate but retained the assumption of horizontal flow, so 

the model works well only for very gentle slopes. Schmid
WATER-LEVEL FLUCTUATIONS IN LANDSLIDE WEST OF CINCINNATI C7

EXPLANATION

Stony clay, dark-brown; pedologic soil formed on colluvium

Y Stony clay, yellow-brown; colluvium derived from subjacent 

bedrock. Contact with bedrock is transitional and locally 

obscure

Still Shale, yellow-brown to olive-gray, soft bedrock

1111111111 En echelon open cracks indicating incipient shear failure 

on surface

Failure surface Continuous shiny surface containing stria - 

tions. May also be a contact between different materials

Open crack with rough irregular surface that apparently 

formed in tension

Limestone fragment in colluvium 

Contact between different materials

Bottom of trench

100

and Luthin (1964) derived an analytic solution for the 

Boussinesq model for steady-state flow and fixed-head 

boundaries, and Guitjens and Luthin (1965) used Hele-Shaw 

models to show that the solution is accurate for slopes as 

steep as 30 percent. Departing from the Boussinesq 

assumption of horizontal flow, Klute and others (1965) 

solved the problem of steady-state, two-dimensional, slopeparallel flow along an incline under fully saturated 

conditions. They found that flow through an inclined soil 

slab that has a length-to-thickness ratio greater than 10:1 

could be accurately represented by a one-dimensional, slopeparallel flow model. Childs (1971) and Towner (1975) give 

analytic solutions for steady-state, unconfined, slopeparallel flow both with and without recharge. Chauan and 

others (1968) and Ram and Chauan (1987) present analytic 

solutions for the problem of transient slope-parallel flow 

between two trenches on a slope with constant recharge. 

Karadi and others (1968) solve the related problem of transient flow between drains resting on a shallow, impermeable

substrate, and Wong (1977) has published nomographs for 

the problem of flow to drains in sandy leachate collection 

layers overlying clay landfill liners. Beven (1977) used a 

two-dimensional finite-element model of saturated and 

unsaturated flow, and predicted that saturated zones, 

controlled by pre-existing pressure heads, would form by 

accumulation of water at the toes of hillsides. More recently, 

Beven (1981, 1982) and Hurley and Pantelis (1985) have 

used linearized, one-dimensional approximations to 

successfully model some aspects of saturated and 

unsaturated hillside discharge hydrographs. Hurley and 

Pantelis show that flow through a thin sloping aquifer is 

indeed one-dimensional to a first approximation, but they 

solve the problem of flow through unsaturated soil in terms 

of total soil moisture flux.

We approximate hillside flow, at least as we have 

observed it, as unconfined flow in a fully saturated aquifer. 

Bear (1979, p. 74-75) discusses limitations of the "fully 

saturated" approach, particularly the error introduced by
C8 LANDSLIDES OF THE CINCINNATI, OHIO, AREA

0.2

0.6

0.8

LU

0 1.0

1.2

1.4

1.6

V H

10" 10~7 10"6 10~

HYDRAULIC CONDUCTIVITY,

IN METERS PER SECOND

10"

Figure 4. Variation of colluvium hydraulic conductivity with 

depth. Points labeled H and V are values for horizontal and vertical 

conductivity of closely spaced samples from a depth of 1.2 m.

25-mm diameter 

(1-inch O.D)

Figure 5. Schematic drawing of piezometer P-4 at Delhi Pike. 

See figure 2 for location.

ignoring the capillary fringe, or zone of tension saturation, 

above the water table. As we will show, however, our model 

has the advantage of predicting water-table height rather 

than total soil moisture flux, as would a more rigorous model 

that considered both saturated and unsaturated zones, and it 

can account for many important characteristics of our field 

data.

THE GOVERNING EQUATION

For a thin, porous slab underlain by a sloping, impervious substrate, we define total hydraulic head, <I>, as:

<&=h cos sin |3 (1)

(compare with Beven, 1981; Hurley and Pantelis, 1985) 

where £ is the slope-parallel coordinate, giving distance 

from the upper end of the slab to the point of measurement 

[in units of length], h is height of the phreatic surface 

[length] measured perpendicular to the substrate (fig. 8), and 

P is slope angle [degrees]. Combining equation 1 with 

Darcy's law, the governing equation for incompressible onedimensional flow through a homogeneous, fully saturated,

unconfined aquifer is:

3/z = dt ~ (2)

where p is effective porosity, K is saturated hydraulic 

conductivity [length/time], R is net recharge (R is positive 

for precipitation and negative for evapotranspiration) to the 

water table [length/time], and t is time. Positive recharge is 

not necessarily the same as rainfall, so the two should not be 

used synonymously unless there is evidence to suggest that 

all rainfall reaches the water table. Because we have not 

observed any runoff at Delhi Pike except in areas where we 

have removed the organic soil and exposed colluvium at the 

surface during fieldwork, we will assume that a large proportion of rain finds its way to the water table and that recharge 

is approximately equal to rainfall when weather is cloudy 

and cool during winter and spring storms. We also use effective porosity, /?, in place of the more common specific yield 

on the assumption that both the water and the soil are incompressible, so that there is no elastic storage (Bear, 1972, p. 

376). For the limiting case of p=0, corresponding to a state 

of tension saturation, the temporal derivative in equation 2
WATER-LEVEL FLUCTUATIONS IN LANDSLIDE WEST OF CINCINNATI C9

0.4 

tr 0.5

LLJ

j| 0.6 

-0-7

LU

m 0.8

1.1

1.2

12 18 

MARCH 21

12 18 

MARCH 22

6 12 18 

APRILS

6 12 18 ' 6 12 18 ' 6 12 18 ' 6 12 18 ' 6 12 18 ' 6 12 18 ' 6 12 18 ' 6 12 18 ' 6 12 18 

APRIL 9 APRIL 10 APRIL 11 APRIL 12 APRIL 13 APRIL 14 APRIL 15 APRIL 16 APRIL 17

,o I

<

8 CC

MAY 13

DATE AND HOUR

Figure 6. Rainfall and piezometric level in piezometer P-4 for 

three rainy periods in the spring of 1980. Vertical bars represent 

cumulative rainfall totals during 15-minute intervals (graphs A 

and Q or during 1-hour intervals (graph B). A, March 19-22, an 

example of a flat-topped record in which water levels remain 

high due to prolonged gentle rain following an initial storm or 

storms. B, April 8-18, an example of a sharp-peaked record in

which water levels rise and fall rapidly following a short-lived 

intense storm. In this record, the slopes of the rising limbs have 

nearly the same absolute values as the maximum slopes of the 

falling limbs. C, May 12-13, another example of a sharp-peaked 

record in which water levels rise and fall rapidly following a 

short-lived intense storm. In this record, the rising limbs are 

nearly vertical and are much steeper than the falling limbs.
CIO LANDSLIDES OF THE CINCINNATI, OHIO, AREA

0.75

- 0.50

0.25

0.00

/ I

i

10 20 30 

RAINFALL, IN MILLIMETERS

40

Figure 7. Change in water level versus rainfall. With one 

exception, maximum effective porosity (p) estimates range from 

0.01 to 0.07, suggesting that the colluvium was nearly saturated 

before rapid water-level increases.

goes to infinity and the piezometric level should rise instantaneously in response to rainfall.

Differentiating equation 1 with respect to \ and substituting the result into equation 2, we arrive at:

or, equivalently: 

dh K[&h

(3)

- (4)

both of which are nonlinear in h and have no known analytic 

solutions for time-variant recharge.

DIMENSIONAL ANALYSIS OF THE 

GOVERNING EQUATION

For a porous slab of length L and thickness D, we introduce the dimensionless variables:

H=hlD

X=^/L 

T=tltr

as well as the scaling factor:

G=D/L 

and then we normalize equation 4 to arrive at:

 .. , ~ i'd#Vl ^ /?

 = //+ r o2 cosB-r OsinB + - (5) ^^ i ^,,-, v -^^y j K 3x A:

REPRESENTATIVE

ELEMENTAL

VOLUME

HORIZONTAL

Figure 8. Idealization of a thin slab of uniform thickness resting 

atop a sloping, impervious substrate and the representative element 

used to derive the governing equation for hillside flow through a 

homogeneous, isotropic, phreatic aquifer.

We chose to use a characteristic time of tr=pDIK because 

we are interested principally in short-term water-level 

changes rather than the long-term fluctuations that would 

occur on a scale of tr =pL IK. Thus for a slab on the order of 

£>=10° m, 1(T2 <p<lQ~l , and K=1Q~5 m/s, typical of the 

hillsides at Delhi Pike, we will be looking at changes that 

occur on a time scale of 103<?r<104 s, or hours to tens of 

hours. For long, thin slabs all terms containing a will be 

negligible; hence, integration to solve equation 5 for H 

yields:

T-,

= l-dT+H, (6)

where HQ is uniform water level along the slope at T\. Equation 6 shows that water levels will rise and fall uniformly 

along the entire slope, with no component of slope-parallel 

flow over the short term. Pre-storm values of/?, which affect 

the magnitude of tr, will change with time, thereby changing 

the magnitude and duration of rainfall necessary to produce
WATER-LEVEL FLUCTUATIONS IN LANDSLIDE WEST OF CINCINNATI Cll

a given water-level increase. Thus prediction of rainfallinduced water-level changes, even using this simple model, 

requires detailed knowledge of pre-storm effective porosity, 

hydraulic conductivity, rainfall intensity, and rainfall 

duration.

One way to produce slope-parallel flow is to redefine 

the characteristic time of the system as tr=pL/K, so that 

typical values of L=102 m, lO~2<p<lQ-1 , and K=1Q~5 m/s 

give a characteristic time of 105<?r<106 s, or about 1 to 10 

days. Using this new definition, equation 4 can be written as 

the nonhomogeneous kinematic-wave equation (Lighthill 

and Whitham, 1955; Miller, 1984):

R

(7)

which will produce slope-parallel, wavelike flow on a time 

scale l/o times as long as the uniform changes predicted by 

equation 6. Another way to produce slope-parallel, wavelike 

flow with the model is to return to our original definition of 

tr=pD/K, set /?=0, and assume that for a nearly saturated 

hillside G~p. To first order in o, then, equation 4 can be 

rewritten as the homogeneous kinematic-wave equation:

the error introduced by letting coefficients lag over large 

temporal increments, we use the alternate method of 

Douglas and Jones (1963, p. 199). This method uses a 

predictor to estimate values of h at time H-(8f/2), which are 

then substituted into a Crank-Nicholson corrector to solve 

for values of h at time t+bt. For interior nodes, the predictor 

form of equation 4 is:

KStMcosfi Kdtcosfi

AW cos P

(10)

where i is the spatial grid index and j is the temporal grid 

index. The corrector form of equation 4 for interior nodes is

h>+l-2\l +

(-1

\_ Tr<£ , Kot n

cosp

i+1

(8)

where

c=sn

is the celerity of the traveling waveform. For a phreatic surface with periodic perturbations of arbitrary wavelength A, 

and amplitude AQ, a general solution to equation 8 is:

T271 I 

= A0 sin (X-cT)

I A, I

(9)

which can be verified by differentiating with respect to X and 

T, and then substituting the results into equation 8. Thus net 

recharge, due to either infiltration or evapotranspiration, 

must be insignificant in order for slope-parallel flow to be 

significant over the short term. It is also possible for waterlevel increases to occur much more quickly than water-level 

decreases (1) if the pre-storm effective porosity is much less 

than the drainable porosity of the colluvium, which is 

essentially a constant for a given soil (Bear, 1972, p. 484), or 

(2) if recharge rates are much higher than evapotranspiration 

rates.

FINITE DIFFERENCE FORMULATION

We assume that spatial grid increments are uniform, 

solve for the second derivative, and linearize by letting 

coefficient h values lag one time increment behind 

(Anderson and others, 1984, p. 337). In order to minimize

(H)

The predictor, equation 10, uses a forward-difference 

temporal derivative and is only first-order accurate in time. 

The Crank-Nicholson corrector, equation 11, uses a centraldifference temporal derivative and is second-order accurate 

in time. Both the predictor and the corrector are second-order 

accurate in space, so the combined accuracy over one entire 

time increment is <9[(5^)2+(5?)3/2] (Douglas and Jones, 

1963).

BOUNDARY AND INITIAL CONDITIONS

We chose to fix water-table height at both the uphill and 

downhill ends of our numerical model to account for the 

steady base flow, represented by relatively constant water 

levels in P-4 between storms that we observed at Delhi Pike, 

and also to ensure that water levels near the lower boundary 

did not exceed soil thickness. As shown in the perturbation 

analysis above (equations 5 and 6), however, boundary 

effects act only near the ends of the problem domain, so the
C12 LANDSLIDES OF THE CINCINNATI, OHIO, AREA

choice of a specific set of boundary conditions will not 

greatly affect the behavior of the model along most of the 

slope. For a fixed piezometric level at spatial node 1, the 

boundary form of the predictor, equation 10, expanded 

around neighboring spatial node 2 is:

-21 + ^

2

2k>2

(hJ _ M

3

and the accompanying form of the corrector, equation 11, is:

J+/2 cosp 4/z; +1/'

+ /2 cos|3

(13)

Both the predictor and the corrector for the downhill 

boundary expanded around the (n-l)th node are similar in 

form to equations 12 and 13.

To solve the model, we used the standard Thomas 

algorithm (Press and others, 1986; Anderson and others, 

1984) for tridiagonal linear systems to solve finite-difference 

approximations of the forms given in equations 10 and 11 

with boundary approximations of the forms given by 

equations 12 and 13, and we verified our algorithm using an 

analytical steady-state perturbation solution of equation 4. 

The computer program and the analytic solution are given in 

appendixes C and E of Haneberg (1989).

NUMERICAL RESULTS

On the basis of our theoretical analyses and field 

observations, we chose representative values for all of the 

constants in equation 2 and then experimented with the 

numerical model in order to produce synthetic water-level 

records similar to those we recorded at Delhi Pike. First, we 

attempted to match actual water-level records with synthetic 

water-level records from our model. Then, after we were 

satisfied that the model could account for our field 

observations, we experimented with different combinations 

of rainfall intensity and duration to see what effect changes 

in these variables would have on water-level record shapes.

0.5

S 0.4

Z0.3

0.2

5 0.1

0.0 I I I I I I I

10 15 20 25 30 35 40 45 50 55

z ii.s

?0v-o ^

Sgi-o

LU Q.

S^

dgo.5

? o

^ S nn

1 1 1 1 1 1 1 1 1 1

IS

fl H nn wL li nn i i i i i i

10 15 20 25 30 35 40 45 50 

ELAPSED TIME, IN HOURS

55

Figure 9. Comparison of actual and synthetic water-level records 

from P-4 on April 11-12,1980. Effective porosity in the numerical 

model was lowered from the estimated maximum effective porosity 

of 0.035 to 0.025, and recharge to the model water table was set 

equal to actual rainfall.

In order to better understand the effects of rainfall patterns 

on water-level record shape, we decided to use relatively 

simple rainfall distributions rather than the more complex 

patterns we recorded at Delhi Pike.

SIMULATION OF P-4 WATER-LEVEL 

RECORDS

By trial and error, we found it difficult to model field 

water-level records that show very abrupt changes or cover a 

period including multiple storms, such as the one we have 

described for May 12 through May 13, 1980 (fig. 6C). 

However, we were able to obtain good results for simple, 

single storms in which water-level records changed gradually.

In general, we found that the model is very sensitive to 

changes in effective porosity, p, hydraulic conductivity, K, 

and recharge, R. For example, figure 9 compares actual and 

calculated water-level records for the storm of April 11 and 

12, 1980. We used values of /?=0.025, K=l.3xW~5 m/s, 

6f=3600 s, 6^=5 m, (3=22°, upslope head fixed at 0.1 m, 

downslope head fixed at 1.2 m, and recharge, R, equal to 

measured rainfall. Except for effective porosity, p, we 

selected these representative values from our field 

observations. Calculated maximum effective porosity for
WATER-LEVEL FLUCTUATIONS IN LANDSLIDE WEST OF CINCINNATI C13

20 30 40 50 60 70 80 

DISTANCE ALONG SLOPE, IN METERS

90 100

(UPHILL) (DOWNHILL)

Figure 10. Model results for drainage of a fully saturated, thin, 

homogeneous aquifer of uniform thickness resting atop a sloping, 

impervious substrate. Water level rises almost uniformly along 

the entire slope, but drains from head to the toe of the hillside. 

Variables used werep=0.01, £=1.3xl(T5 m/s, p=22°, h=2 m, and 

L=100 m. Rainfall intensity was 0.1 um/s for the first hour, 0.5 

|jm/s for the second and third hours, 0.1 um/s for the fourth hour, 

and zero thereafter.

this storm, which assumes that all of the rain contributes to 

the measured water-level increase, was 0.035, but our trials 

showed that/?=0.025 gave better results.

Another variable is location along the slope and, again 

by trial and error, we found that synthetic water-level records 

from the finite difference node at ^=15 m (measured from 

the top of the slope) gave the best match with field data from 

P-4. The synthetic water-level record in figure 9 begins to 

rise steeply as soon as rainfall begins, whereas the actual 

field water-level record begins to rise slowly 2 hours after 

rainfall begins. Furthermore, the synthetic water-level record 

is very sensitive to changes in rainfall intensity, producing an 

irregular curve, whereas the actual water-level record is 

smooth and does not reflect variations in rainfall intensity. 

Both water-level records peak at about 0.50 m and 22 hours 

elapsed time. (Note that we give model results in water-table 

height above the impermeable substrate and elapsed time, as 

compared to water depth beneath the surface and time of day 

for our field data). The synthetic water-level record falls 

more rapidly to its fixed-head boundary base level of 0.10 m, 

whereas the actual water-level record falls to about 0.20 m 

before leveling off and shows several small perturbations on 

its falling limb.

C/D 

LU

o

CD

10 20 30 40 50

10 20 30 40 50 60 

ELAPSED TIME, IN HOURS

Figure 11. Synthetic water-level records showing projected 

response to three different patterns of rainfall. Curves are for finite 

difference nodes located 25 and 50 m from the top of the hillside. 

Shaded bars show pattern of rainfall intensity. R.I. = rainfall 

intensity in micrometers per second. A, Response to a short, intense 

rainstorm providing 4 mm of net recharge to the water table. B, 

Response to gentle rainfall providing 4 mm of net recharge. Note 

the differences between A and B produced by variations in the 

intensity and duration of rainfall, even though net recharge was the 

same. C, Response to a short, intense storm followed by several 

hours of gentle rainfall. Initial storm provided 4 mm of net 

recharge, as in A and B, but the additional recharge significantly 

decreased the rate of decline following the storm.

Simulation of short, intense rainfall. Our numerical 

experiments with short, intense rainfall produced distinctly 

asymmetric water-level records with very steep rising 

limbs. Figures 10 and 11A show that for one simulation of 

this type, water level began to rise almost immediately after 

rainfall began, and peaked shortly after rainfall stopped. 

Although water level rose uniformly at all of the interior
C14 LANDSLIDES OF THE CINCINNATI, OHIO, AREA

finite-difference nodes, it fell much more rapidly near the 

top of the hillside than at its midpoint, and the water-level 

record from ^=50 m is much flatter than the water-level 

record from ^=25 m. Total recharge for the simulation 

shown in figure 11A was 4 mm.

Simulation of prolonged, gentle rainfall. We 

simulated the effects of a prolonged, gentle rainfall 

providing the same amount of recharge as the short, intense 

rainfall simulation that we describe above (4 mm). Figure 

115 shows that the ^=25 m water-level record peaked 

slightly below and before the ^=50 m water-level record. 

Except for this offset of peaks, the falling limbs are virtually 

identical to those in figure 11A. The rising limb, however, is 

much flatter and is no steeper than the steepest portion of the 

falling limb.

Simulation of intense rainfall followed by gentle 

rainfall. We observed that in some cases for example, the 

water-level record of March 19-22, 1980 a small amount 

of rain distributed over several hours seemed to maintain the 

water table at a high level until the rain stopped. So, we 

modeled such a situation using an initial short, intense storm 

identical to that in figure 11A followed by 7 hours of very 

light but continuous rain (0.05 jam/s). The results of our 

simulation (fig. 11C) show that water level first peaked at the 

same level and time as in figure 11A and then began to fall 

slowly when the rain stopped. Before the water level could 

fall very much, however, the light rain began and the slope 

of the falling limb for ^=25 m remained constant until the 

rain stopped, and then fell. The ^=50 m water-level record, 

however, fell only until the second round of rain began, and 

then rose to peak at about 1.75 m while the ^=25 m waterlevel record was falling. Thus, the effect of a small, 

secondary storm differs along the length of the hillside.

DISCUSSION

Our simple, theoretical model accounts for the shapes 

and amplitudes of asymmetric, short-term piezometer 

hydrographs from the Delhi Pike landslide complex 

surprisingly well if we assume that pre-storm effective 

porosity was on the order of a few percent when our field 

data were collected. Most importantly, we have shown that 

rapid water-level fluctuations should occur uniformly along 

the entire slope over the short term if either rainfall or 

evapotranspiration is significant. Slope-parallel, wavelike 

flow is controlled by higher order terms in the governing 

equation that are significant only over the long term. Slopeparallel flow will be significant over the short term only if 

both rainfall and evapotranspiration are negligible, and then 

only because slope-normal flow vanishes.

Although we have developed a conceptually simple 

model, we stress that it is also extremely sensitive to 

variations in all four of the values needed to predict rapid 

water-level fluctuations: rainfall intensity, rainfall duration,

hydraulic conductivity, and pre-storm effective porosity. 

Because these critical values are extremely difficult to assess 

in complex natural hillsides, we are wary of attempts to 

predict sudden hillside failures during rainstorms by 

correlating so-called threshold rainfall with slope instability, 

particularly when such predictions may have a bearing on 

human life and limb (for example, Keefer and others, 1987). 

We recommend that instead of relying solely on statistical 

correlations, any future slope instability warning system 

should include monitoring of prestorm soil moisture 

conditions in areas where sudden failure would have 

significant economic or social consequences.

Numerical solutions of our model, using reasonable 

values for the hillside at Delhi Pike, agree in both shape and 

magnitude with our field data but, like the first-order 

analytical model, the solutions are also sensitive to 

variations in rainfall, conductivity, and porosity estimates. 

Differences between actual and synthetic water-level 

records, produced using the model (fig. 9), give us some 

insight into the hillside hydrologic system. The first major 

difference, a noticeable time lag between the onset of rainfall 

and piezometer response, can be attributed largely to the 

time required for rainwater to infiltrate through the 

unsaturated zone. For example, if we assume that R was 

constant with time and/?=0.03 before the storm of April 11, 

1980, we can solve equation 7 for /?=5xlO~6 m/s, using the 

observed 7200-s time lag, which suggests that the water table 

is being recharged at a rate of about K/2. Examination of 

Murdoch's (1987) laboratory data for colluvium from Delhi 

Pike shows that unsaturated hydraulic conductivity for 

/?=0.03 is about two-thirds to one-half of saturated hydraulic 

conductivity, so a 7200-s time lag for a piezometer tip about 

1 m deep in slightly unsaturated colluvium is reasonable. 

Because the hydraulic conductivity of unsaturated soils is a 

highly nonlinear function of pressure head, both the time lag 

and the slope of the rising hydrograph will vary 

exponentially with pre-storm effective porosity, which is 

also a function of pressure head. Once the soil does become 

saturated, however, water can flow into the piezometer tube, 

and Hvorslev's (1951) method predicts a response time for 

P-4 of about one minute, so the effect of the piezometer tube 

itself on response time should be negligible.

The differences between the falling limbs of the actual 

and synthetic water-level records in figure 9 suggest to us 

that water is being introduced from a source not considered 

in the model, perhaps bedrock seeps. Localized seepage 

from fractured limestone layers in the bedrock would also 

explain the steady base flow observed in P-4 between storms 

and is consistent with observations of weakly artesian 

bedrock springs throughout the Cincinnati area (Baum, 

1983).

There are not enough high-frequency water-level data 

uphill and downhill from P-4 to tell us how well our model, 

or any other model, applies to the entire hillside. The data do 

tell us, however, that sampling frequencies of several days or
WATER-LEVEL FLUCTUATIONS IN LANDSLIDE WEST OF CINCINNATI C15

weeks can be too low to resolve the effects of single storms 

at Delhi Pike. The Hamilton County Soil Survey (Lerch and 

others, 1982) does describe common seepage problems 

along only the lower portions of Eden silty clay loam slopes, 

so there is some evidence for slope-parallel drainage in hillsides such as those at Delhi Pike, and similar results have 

been reported elsewhere.

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Manuscript approved for publication August 25, 1993. 

Published in the Central Region, Denver, Colorado. 

Photocomposition by Mari L. Kauffmann. 

Graphics by Norma J. Maes. 

Edited by Peter L. Martin.

Cover design by Arthur L. Isom, based on an original drawing 

by K. A. Richards, University of Cincinnati.

U.S. GGVERtMENT PRINTING OFFICE: 1994-573-038/86030
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