Morris & Fan. Reservoir Sedimentation Handbook

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CACHÍ HYDROPOWER RESERVOIR, COSTA RICA 19.13

FIGURE 19.8 Discharge hydrograph at La Troya for 1 week. Peak discharges in this

watershed characteristically occur in the evening. Thus, suspended sediment samples collecte

around 10:00 each morning typically correspond to the falling limb of the hydrograph, when

sediment concentrations are lowest (Jansson, 1992a).

alomo gage as an example, hourly discharge data for 1989-1990 were divided into

10 m

/s discharge classes and analyzed to produce the flow-duration graph in Fig. 19.9.

The 10- to 20-m

/s discharge class was represented with the greatest frequency, but the 40-

to 50-m

/s class produced the greatest volume of water discharge.

The three sediment rating curves shown in Fig. 19.9a were applied to the hourly

discharge data to estimate the relative importance of each discharge class with respect to

suspended sediment load, producing the values of sediment load in each class

summarized in Fig. 19.9b. Sediment loads were computed by applying the rating curve

to the mean discharge value within each water discharge class, and then multiplying by

the discharge duration for that class. Despite the large difference in sediment loads at peak

discharges given by the three rating curves, this has relatively little effect on the total

sediment load because the highest flows occur infrequently. Sediment load

computations at Palomo are most sensitive to discharges in the range of 30 to 200 m

/s, and

particular attention must be given to accurately fitting the sediment rating curve within

this range.

19.3.6 Turbidity Measurement

Intensive sampling was conducted during the 1989-1990 inter-flushing period to

generate a representative dataset for computing new sediment rating curves. Given the

difficulty of collecting representative suspended sediment data from small watersheds

CACHÍ HYDROPOWER RESERVOIR, COSTA RICA 19.14

CACHÍ HYDROPOWER RESERVOIR, COSTA RICA 19.15

with fast-rising peaks, turbidimeters were used to continuously record sediment

concentration. Two types of turbidimeters were used, the Hach Surface Scatter 6

turbidimeter and the Monitek Clam 52 LE. Submersible pumps were used to deliver

water to the turbidimeters (Fig. 19.10). Data were collected by data loggers at

intervals of approximately 5 to 6 minutes and analyzed with an electronic

spreadsheet. Both types of turbidimeters experienced problems with clogging by

heavy sediment loads and debris, failure of pumps and transformers, and other

logistical problems. The Hach instrument, with its smaller water delivery tube, was

more prone to clogging by leaves and the husks of coffee beans discarded to the

river during coffee harvest season. The larger interior chamber in the Monitek

instrument was less prone to clogging, but produced low flow velocities that allowed

sediment to settle out at high concentrations (e.g., in measuring sediment concen-

trations downstream of the dam during flushing).

The turbidimeters were calibrated (NTU versus suspended solids) by using

suspended sediment data collected from the stream over a range of discharges while the

turbidimeters were operating. A power function regression was developed for the

Hach instrument having the form:

Concentration = 0.59 NTU

1.30

(19.1)

FIGURE 19.10 Sample collection arrangement for turbidity monitors (Jansson, 1992a).

CACHÍ HYDROPOWER RESERVOIR, COSTA RICA 19.16

The calibration curve for the Monitek instrument was of the form:

Concentration = 1.22 PPM + 71 (19.2)

where PPM is the Monitek instrument reading.

Because the instruments continuously report turbidity values, even though these

values may be spurious, it was necessary to scan the data for reasonableness to search for

periods of clogging. Sudden declines in turbidity, or periods when turbidity remained

essentially stable despite significant changes in discharge, were taken as signals of

clogging. For example, Fig. 19.11a shows a short-duration turbidity spike at Palomo

which produces an open discharge-concentration loop. This could be caused by high

sediment discharge from an area near the gage station (e.g., farms) with little sediment

contribution from the upper watershed. It could also be caused by clogging of the

turbidimeter intake during the event. Because these events with extremely short turbidity

peaks seemed to occur primarily during the coffee processing season, and were otherwise

atypical, it was thought to represent a period of spurious readings due to clogging of the

turbidimeter, and these data were discarded. Figure 19.11b shows a more typical event

at this same gage station.

At La Troya, the turbidity at low flows was affected by waste discharge from an

upstream factory and by in-stream mining, both of which caused turbidity spikes with no

increase in discharge. To avoid the irregular turbidity readings caused by waste

discharges and mining, the sediment rating curve at La Troya was constructed by using

data only from the rising and falling limbs of hydrographs when sediment concentrations

exceeded 1000 mg/L. The resulting dataset at La Troya contained 5763 data points at 6-

min intervals, representing 23 different runoff events between September 1989 and October

1990 (Fig. 19.12). At La Troya gage the discharge peaks typically preceded the turbidity

peak, generating a counter-clockwise loop and a high degree of scatter in the dataset At

Palomo the opposite pattern was observed; the highest turbidities occurred on the rising

limb creating a clockwise loop.

19.3.7 Interpretation of Turbidity Data

The correlation of turbidity data to suspended solids is problematic. The relationship

varies as a function of the monitoring site, stage, type of instrument, calibration, grain

FIGURE 19.11 (Left) Short-duration turbidity spike at Palomo gage station which creates an ope

discharge-concentration loop, probably caused by clogging of the turbidimeter during coffee

harvest season. (Right) More typical discharge-concentration relationship at Palomo outside

of coffee harvest season when clogging is not a problem (Jansson, 1992a).

CACHÍ HYDROPOWER RESERVOIR, COSTA RICA 19.17

FIGURE 19.12 Concentration versus discharge dataset at La Troya based on turbidimeter

measurements and used to construct sediment rating curves. In places the traces of rising or falling

ydrographs from individual events are discernible (Masson, 1992a). h

ze distribution, and other parameters. Furthermore, turbidimeters collect point samples

and the relative depth of the fixed measurement point will vary as a function of stage. It

was intended to continuously measure both streamflow and turbidity, and compute the

sediment load by using a correlation between suspended solids and turbidity. However,

numerous field problems intervened and the turbidity record was far from complete,

making it necessary to construct a rating curve from the turbidity data. Despite

problems and limitations, continuous turbidity measurements were obtained from both

the rising and falling limbs of several hydrographs, and these data provided a more

representative dataset than the water quality sampling program with its population of data

points taken mostly from the falling limb.

To evenly distribute the regression weighting factor across the full range of the

available data, the dataset was divided into 2-m

/s discharge intervals and the mean value

of the concentration data points falling within each discharge class was computed. Three

rating curves were computed from these means. A power regression on the mean values

gave:

(19.3)

91.1

10.4 QL 

The ot

her two equations were developed after discarding the mean value for the highest

discharge class in the dataset, since it contained only one observation. After removing the

highest data point the power regression on the means became:

CACHÍ HYDROPOWER RESERVOIR, COSTA RICA 19.18

(19.4)

51.1

77.28 QL 

A l

og transformation of the means, a log-log regression, gave:

(19.5)

645.1

18.14 QL 

these equations L = sediment load in tons/day and Q = water discharge in m

/s.

The resulting sediment rating curves at La Troya are shown in Fig. 19.13, along with

the mean load values in each water discharge class. Table 19.5 compares the load

computed by each equation against the load computed using the 5763 points in the original

dataset, and also shows the total load for the 1980-1990 period computed by each

equation. This table illustrates the importance of equation-selection on the load

computations.

A similar procedure was followed to develop a rating curve at Palomo which had

6140 data points representing the rising and falling limbs of 22 distinct and significant

runoff events, plus several low-flow intervals between individual events. The longest

continuous record was a 10-day period in October. Data from this station were affected

by periodic releases from the El Macho upstream hydropower station, which increased

discharge with no corresponding increase in turbidity. Two sediment rating equations

were developed from the means, a power function and a log-log regression. The two

equations were first tested by comparing the total sediment load predicted by the

FIGURE 19.13 Sediment rating curves at La Troya based on turbidity data. Each circle is the mean

for a discharge interval (Masson, 1992a).

CACHÍ HYDROPOWER RESERVOIR, COSTA RICA 19.19

TABLE 19.5 Sediment Load Computed by Various Rating Curves Applied to Original

Dataset from which the Equations Were Derived, and for the 1989-1990 Period

Load computed for dataset

Power

[Eq. (19.3)]

Power

[Eq. (19.4)]

Log-log

[Eq. (19.5)]

ICE's

equation

Load for original dataset*:

Tons 47,846 69,132 57,243 78,612

% of ICE equation 61 188 73 100

Load for 1989-1990 inter-flushing period:

Tons 167,241 312,421 238,695 222,047

% of ICE equation 75 141 107 100

*The load computed from the dataset values was 57,667 tons.

equations against the measured load in the dataset. At this station there were some

manually collected water quality data at very high water discharges, which were much

lower than the sediment load values predicted by the rating curves. Therefore, these

additional data points were added to the record obtained by the turbidimeter to augment

the sparse record at high discharges and the regressions were recomputed. The log-log

regression fit the data very well, except that it appeared to overestimate values at higher

discharges. Therefore, an eye-fitted line was used for discharges over 206 m

/s.

19.3.8 Unsampled Area

The soils, drainage density, and land use indicated that the sediment yield from the

unsampled area near the reservoir would probably be similar to the yield from the

watershed tributary to the La Troya gage station. Therefore, the sediment discharge from

the ungaged area was based on the sediment yield at La Troya with a correction for

watershed area.

19.3.9 Conclusions Concerning Sediment Inflow

The original ICE equation provided a reasonable estimate of the sediment load at the La

Troya gage station. However, the load at the Palomo gage was seriously underestimated

at discharges over 100 m

/s, and this was the primary factor responsible for the large

discrepancy in the sediment balance across the reservoir. At Palomo the rating curve had

a clockwise loop, meaning that suspended sediment concentrations on the rising limb

were much higher than on the falling limb, which provided most of the data points for the

original rating curve. The original sediment rating curve had been derived from a

nonrepresentative dataset.

19.4 SEDIMENT DEPOSITION AND EROSION

Various procedures were used to quantify the amount and pattern of sediment deposition

and erosion within the reservoir.

CACHÍ HYDROPOWER RESERVOIR, COSTA RICA 19.20

19.4.1 Sedimentation Plates

In 1976, ICE set out five sedimentation plates in different parts of the reservoir and

returned in subsequent years to measure deposition depth over each plate. From this,

deposition was computed by apportioning the reservoir area among the plates with

Theissen polygons. In 1981, additional plates were set out, for a total of 39 measurement

points. However, as burial depth increased the plates became more difficult to find,

resulting in lost plates and incomplete data.

19.4.2 Topographic Survey

In June 1985, the reservoir was emptied for 15 days and a survey crew mapped the

topography of the flat terraces and measured total sediment depth. It was estimated that

1.03 Mm

of sediment had accumulated on 1.027 km

of terraces in 19 years of

impounding, for an average deposition depth of 1.0 m.

19.4.3 Grain Size Analysis

Twenty-eight samples of surface sediment were collected from the right-hand terraces

when the reservoir was emptied in 1983, and grain size was determined by the

densitometer method (ASTM-D422). The results, summarized in Fig. 19.14, show that

grain size on the terraces declined moving downstream, from an average of 0.70 mm in

the upper basin to less than 0.015 mm near the dam. The main channel was not sampled.

FIGURE 19.14 Elevation and median grain size of sediments on the surface of right-hand terraces

(Ramírez et al., 1992).

CACHÍ HYDROPOWER RESERVOIR, COSTA RICA 19.21

FIGURE 19.15 Preliminary calculated relationship between critical erosion velocity and voi

ratio as a function of grain size (Axelsson, 1992).

19.4.4 X-Ray Analysis

Reservoir sediments were analyzed by x-ray radiographic techniques (Axelsson, 1992)

using 15 shallow cores (0.2 to 0.5 m deep) collected with a valved gravity corer plus nine

surficial grab samples. Rectangular cores, 30 × 60 mm, were collected, since either square or

rectangular cores of uniform thickness are required for quantitative interpretation of

radiographic images. Unextruded cores with adjoining bottom water were transported, stored,

and then irradiated in the upright position at a laboratory in San José, Costa Rica. A

seven-step aluminum wedge was irradiated simultaneously with the cores for density

calibration.

The x-ray image density varies as a function of the density of the material in the core.

Flushing and air drying exposes the soft sediment to desiccation, creating an alternating

sequence of denser surface crusts sandwiched between softer subcrustal material. By

taking cores at intervals of months or years, and by correlating the sedimentary sequences

between cores, it is possible to determine contemporary rates of sedimentation. However,

only one set of cores was available at Cachí, and sediment accumulation rates could not be

determined by radiography because the sediment sequence could not be correlated over

time.

Air drying of the sediment and formation of a surface crust during drawdown sub-

stantially reduces the erodibility of the sediments. Axelsson developed from a variety

of sources a preliminary relationship between critical erosion velocity and void ratio in the

sediments, as related to grain size (Fig. 19.15). Void ratios in Cachí reservoir ranged from

20 in gas-rich organic layers to less than 2 in the hard crusts formed on exposure during

flushing. Newly deposited silt and clays at Cachí had void ratios often exceeding 5.

19.4.5 Side-Scan Sonar

Dual-frequency (104 and 435 kHz) side-scan sonar in conjunction with an electronic

positioning system were used to produce a side-scan sonar mosaic of the entire lower

portion of the reservoir (Erlingsson, 1992a). The survey was accomplished by making

three passes along the axis of the reservoir on three parallel tracks 150 m apart. The

strength of the reflected side-scan sonar signal causes gray-scale differences in the sonar-

CACHÍ HYDROPOWER RESERVOIR, COSTA RICA 19.22

graph images, and the resulting sonargraph is a 16 gray-scale map which reflects both

bottom topography and bottom material. Factors that influence signal strength include

angle of incidence, grain size of the bottom material, mineral composition,

porosity, gas bubbles in the sediment, and bottom flora and fauna. A single track in the

shallow water in the upper portion of the reservoir was made without the positioning

system, but the return signal strength was extremely weak because of the coarse-grain

material.

Hydrogen sulfide (H

S) gas bubbles are formed in the sediments by the

anaerobic decomposition of organic matter. Cachí sediments are relatively high in

organic material, with loss-on-ignition values averaging about 4 percent and reaching

10 percent in soft sediments. These organics are derived primarily from hyacinth and

lake plankton detritus. The warm temperatures in this tropical reservoir accelerate the

rate of organic decomposition and the formation of gas bubbles. The bubbles create

sharp density interfaces within the sediments, strongly scattering acoustic signals. Boat

traffic can also generate acoustic noise that interferes with sonar, and at Cachí (where

there was no boat traffic) the sonar sometimes picked up strong acoustical interference

from the hydropower plant.

The bottom characteristics at a number of locations were known from the sediment

cores, making it possible to correlate the following bottom conditions against gray-scale

units on the sonargraph: median grain size, wet bulk density (related to porosity), and

depth to visible gas in the x-ray films of the cores. Through a series of regression

correlations, it was determined that variation in grain size was the most important

gray-scale parameter, giving a correlation coefficient of R

= 0.71 for an exponential

regression. Finer sediments gave a stronger echo (darker image). Variations in wet

bulk density and gas content were poorly correlated to gray-scale value. Bottom flora

was absent in the reservoir (water hyacinths float on the surface) and tube worms were

present at very few locations, so biotic factors were ignored. Organic detritus caused

low wet bulk density values.

In the sonargraphs, it was found that the thalweg generally became darker in the

downstream direction, interpreted as a decrease in grain size and wet bulk density. The

sonargraph showed a dark gray meander along the thalweg, interpreted as a zone

of deeper sediment deposition by turbidity currents. Despite small grain size,

terraces showed lighter gray-scale values, interpreted as reflection from gas within 15

cm of the sediment-water interface and signal attenuation by deposits overlying the

gas layer.

19.4.6 Subbottom Profiler

The higher frequency sonar is reflected strongly in the immediate vicinity of the water-

sediment interface, thereby registering the bottom of the reservoir. The lower-

frequency (14 kHz) subbottom profiler signal penetrates farther and is reflected

from boundaries within the sediment deposit, plus backscatter within the sediments.

When a subbottom profiler is used in a reservoir, the three principal boundaries of

interest are (1) the sediment-water interface, (2) the boundary between the surface crust

formed by desiccation during the most recent drawdown (flushing) and the overlying

recently deposited material, and (3) the boundary between the original bottom and

the material deposited since impoundment. Deposition depth is determined as the

difference between these boundaries. Because of the presence of gas, the acoustic

signals penetrated to only about 10 cm, even in the thalweg where deposition depth

was known to be much deeper. This abundance of gas made it impossible to obtain

usable readings of deposition depth by acoustic methods.

Morris &amp; Fan. Reservoir Sedimentation Handbook

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Morris & Fan. Reservoir Sedimentation Handbook