Hydrological Research Letters 11(2), 114–120 (2017)
Published online in J-STAGE (www.jstage.jst.go.jp/browse/hrl). DOI: 10.3178/hrl.11.114

Effects of sediment replenishment on riverbed material size distribution
and attached algal biomass in the downstream reaches of a dam
Yukio Miyagawa1,2, Tetsuya Sumi1, Yasuhiro Takemon1 and Sohei Kobayashi1
Disaster Prevention Research Institute, Kyoto University, Japan
Aqua Restoration Research Center, Public Works Research Institute, Japan
1

2

Abstract:
Sediment replenishment is an effective method for
resupplying depleted sediment and detaching overgrownalgae in the downstream reaches of a dam. In this study, weused empirical data to examine the effects of sediment
replenishment on bed material size and algal biomass in thedownstream reaches of the Futase Dam, Chichibu City,
Saitama Prefecture, Japan. Assuming that algae detachfrom bed materials when they are moved by water flow, we
calculated the tractive force on the riverbed (τ) and allotteda threshold bed material size in motion (Dcri) for each given
τ. The resulting bed material in the downstream reaches ofthe dam in any year was typically finer than that in theprevious year when flooding in the rainy season transported
a large volume of sediment. Algal biomass was lower whenmonthly Dcri exceeded 2 mm, versus when it was less than
2 mm. These results suggest that replenishment of fine bed
materials accelerates algal detachment and restricts theaccumulation of algal biomass by reducing bed stability.
KEYWORDS attached algae; sediment deficiency; riverbed disturbance; flow; detachment; tractiveforce

INTRODUCTION
In downstream reaches of a dam, flows are more stable
and sediment transport is more limited than in the upstream
reaches. The downstream reaches often exhibit sediment
deficiency, which causes riverbed degradation (Erskine,
1985; Kondolf, 1997). Under such conditions, the movement of sediment particles and detachment of algae are
reduced, leading to algal overgrowth (Biggs and Close,
1989). Thick mats of algae are for the most part not edibleby grazing animals (e.g. Heptageniid mayflies and Japanese
Ayu fish), because the mats consist of older algae with highsilt content and are of low nutritional quality (Graham,1990).
Bed load and sediment management have been conducted in many Japanese reservoirs to improve the stateof sediment deficiency in downstream reaches. Sediment
replenishment is one such effective management tool. In
this method, a quantity of sediment is excavated from an
upstream reservoir, transported to downstream channels,

and then flushed by the flooding of the channels (Kantoush
et al., 2010). Sediment replenishment supplies sediment to
deficient areas with the added effect of detaching overgrown algae.
There are several principal factors controlling the loss ofalgal biomass in streams (Figure S1). Algal biomass is usually measured using the proxy of the primary photosynthetic pigment, chlorophyll-a (chl-a), the unit for which is
mg/m2 (Stevenson, 1996). Loss can occur via two distinct
pathways: (1) external forces (e.g. hydraulics; Biggs,
1996); and (2) internal activities (e.g. self-generated
detachment; Bouletreau et al., 2006). The sediment replenishment method facilitates algal detachment by exerting an
external force of dynamic friction between bed and saltating particles during bed load transport. A previous study,
which involved experiments using a flume, reported thatsimultaneous velocity elevation and solid addition produced instantaneous algal loss rates approximately double
those with a velocity increase alone (Horner et al., 1990).
An increased quantity of detached algae has also beenreported in situ in the downstream reaches of Managawa
Dam, Fukui Prefecture, Japan after sediment replenishment.
In Japan, replenished sediment typically flows into thedownstream reaches of a dam in the rainy season, whichusually occurs in spring or summer (Figure S2). The total
volume of sediment that flows in depends on several factors, including the volume of replenished sediment, degreeof water discharge, and the location of sediment placement(Ock et al., 2013). Furthermore, the extent of downstream
transport for a set volume of replenished sediment depends
on the distance from the replenished site (Lisle et al.,2001). The combination of these factors complicates theprediction of sediment flow patterns.
The Unified Gravel-Sand (TUGS) model has been developed for simulating sediment transport and bed material
size distribution in gravel-bed rivers (Cui, 2007). However,the downstream interval of the model is very short compared with the downstream reaches of most dams. To analyze the effects of river flow regime and distance from thereplenished site on sediment deposition downstream, several years of data on replenishment sediment volume, dam
discharge, and riverbed material size are needed. However,existing data of this type only span a few years.
Because fine particles are more easily transported by

Correspondence to: Yukio Miyagawa, Aqua Restoration Research Center,
Public Works Research Institute, Kawashima Kasada-machi, Kakamigahara, Gifu 501-6021, Japan. E-mail: y-miyagawa@pwri.go.jp

Received 31 January, 2017
Accepted 11 April, 2017
Published online 19 May, 2017

© The Author(s) 2017. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/
licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s)and the source, provide a link to the Creative Commons license, and indicate if changes were made.

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EFFECTS OF SEDIMENT REPLENISHMENT
river flow than coarser ones (Wilcock et al., 2003), replenishment with fine sediment may disrupt established bed
load transport frequencies and induce algal detachment.
The effects of the dynamic frictional force exerted by sediment grains on attached algae during the rainy season are
not permanent, as algae can recover their biomass within
one month after detachment (Biggs et al., 1999). However,the sediment deficiency may be improved over the longer
term if the replenished sediment particles remain within theriverbed throughout the dry season. To evaluate the extent
of these benefits, the degree of riverbed disturbance must
be observed and quantified daily for one month prior to themeasurement of algal biomass. The algal biomass calculations can then be compared with the degree of disturbanceand the flow regime in the area to determine the factors
responsible for algal detachment. There are, however, few
peer-reviewed investigations that fit this description.
In this study, we examined the effects of sediment
replenishment on the physical characteristics and algal biomass of bed material in the downstream reaches of theFutase Dam, Saitama Prefecture, Japan. We accomplishedthis by quantifying the degree of riverbed disturbancecaused by the supplied sediment and then relating this disturbance metric to the particle size distribution and algal
biomass data measured during annual field surveys.

STUDY AREA AND METHODS
Collection of field monitoring data
We focused on the Futase Dam, an upstream dam on the
Arakawa River in Chichibu City, Saitama Prefecture,
Japan. Sediment from upstream has been deposited in thereservoir here since the dam’s construction in 1961, causing
sediment deficiency in the downstream reaches. To mitigate
degradation of the channel, sediment replenishment has
been carried out once annually in the dry season (FigureS2) by excavating, transporting, and depositing reservoir
sediment downstream. Flooding in the rainy season typically flushes the sediment further downstream (Figure S2).
The volume of replenished sediment has varied annuallyfrom 5,000 m3 to 15,000 m3.
Each year, the replenishing sediment was deposited
0.2 km downstream of the dam. Three survey sites, hereintermed Stations 1, 2, and 3 (St1, St2, and St3, respectively),
were located no further than 4 km downstream of thereplenishment site (0.7, 1.8, and 2.7 km, respectively),
where a tributary, the Nakatsu River, joins the main trunkof the Arakawa River (Figure 1). The volume of sedimentflushed from the sediment replenishment site was estimatedin m3/yr from the difference between the sediment storage
before and after the rainy season. These data were available
from the Ministry of Land, Infrastructure, Transport, andTourism at the Kanto Regional Development Bureau,
Futase Dam Management Office. The water flow at eachsite was estimated based on the outflow discharge of thedam and the Ochiai Gauging Station, located downstream(Ministry of Land, Infrastructure, Transport, and Tourism,
2017). The flows at St1, St3, and St2 were defined as theoutflow discharge of the dam, the outflow discharge of the
Ochiai Gauging Station, and the average of St1 and St3,
respectively. The bed material size distribution was mea-

Figure 1. Map of the study area in the downstream reachesof the Futase Dam
sured at each site once annually, in the dry season (Figure
S2).
Algal biomass was measured up to three times per year
at each site from 2004 to 2013, in the dry season, using theproxy of the primary photosynthetic pigment chl-a in
mg/m2. To measure chl-a, four stones of moderate size
(150–200 mm) were collected from riffles in the river. The
algae were then scraped from the surface of each stone in a
5 × 5 cm quadrat using a nylon brush. The chl-a content ofeach algal sample was measured via high-performance liquid chromatography (HPLC) (Shioi et al., 1983). The dominant species of algae in each sample were determinedusing a microscope to identify any changes in species composition during the overgrowth phase.

Analysis of the relationship between independent anddependent variables
This study aimed to determine the sediment-related
annual changes in the river bed material downstream of theFutase Dam, and the extent to which flood disturbances
contributed to these annual changes between 2003 and2013. To accomplish these goals, we established two independent variables: (1) the annual volume of sedimentflushed from the sediment replenishment site (Sf in m3/yr);and (2) the annual maximum daily flow (Qmax in m3/s), an
index of annual changes in flood disturbance. These variables directly affect the volume of sediment flushed and thedegree of riverbed disturbance (Ock et al., 2013). Variable(1) was collected from annual reports on the Futase Dam(Civil Engineering and Eco-Technology Consultants, from2004 to 2014), and variable (2) was calculated using thedaily flow data at St1, St2, and St3 (Ministry of Land,
Infrastructure, Transport, and Tourism, 2017). We thenestablished various physical characteristics of the bed material as dependent variables. One was representative bed
material size (D60, the 60% passing size of the bed material[mm]). The other was the proportion of particles less than
100 mm in diameter (P<100mm in %), because the size of thereplenished components was less than 100 mm, and weassumed that the proportion of these particles in the riverbed would be changed when replenished materials were
supplied. To identify inter-annual changes in the size distribution of the bed material, differences were calculated—115—

Y. MIYAGAWA ET AL.
between D60 of the present year and D60 of the previous
year, and between P<100mm of the present year and P<100mm ofthe previous year:
cD60 = D60 − D60 previous year(1)

cP<100mm = P<100mm – P<100mm previous year

(2)

In summary, the dependent variables were bed material
characteristics (D60, cD60, P<100mm, cP<100mm), while the independent variables were Qmax and Sf. Annual measurementsof these variables from 2003 to 2013 were analyzed using
Pearson’s correlation coefficient to determine the strengthof linear relationships between the dependent and independent variables. p-values of 0.05 for Pearson’s correlation coefficient were established to indicate statistical significance.

Comparing flow and detachment force with attachedalgal biomass
The tractive force acting on the riverbed (τ) was calculated daily as follows (Wilcock, 1996):
τ=ρ

κu

(3)

ln 10h/D84

where ρ is the density of water (1,000 kg/m3); κ is
Karman’s constant (0.4); u is the average flow velocity(m/s); h is the depth (m); and D84 is the 84% passing size ofthe bed material (m). We assumed that algae detach frombed materials when water flow moves the bed materials.
Sand, with a diameter of around 2 mm (Bain et al., 1985),
is often used as the smallest size category of bed material in
Japan, when measuring bed material size distribution (e.g.
Katano et al., 2009). Because fine particles, and not simply
suspended solids, promote the detachment of algae (Horneret al., 1990), we determined that algae detach when materials with a diameter greater than 2 mm were moved by water
flow. We then calculated the threshold bed material size formotion (Dcri) for a given τ using Equation (4) (Tanaka andFurusato, 2014).
Dcri =

τ
0.045Rs gD0.6
50

2.5

(4)

where Rs is the specific gravity of bed material in water(1.65), g is gravitational acceleration (9.8 m/s2), and D50 is
the 50% passing size of the bed material (m).
Because algal biomass was determined one month after
the flood in most cases (Biggs et al., 1999), algal detaching
events that occurred within a month might be related to themeasured algal biomass. Then Dcri was calculated for one
month prior to the measurement. To determine the degreeof riverbed disturbance for the month, the maximum Dcrivalue for the month (MDcri) was identified. Maximum daily
flows throughout the month (Mdf) were also identified.
Algal biomass measurements were classified into twogroups according to the relative degree of disturbance. Biomass measurements taken when MDcri was below or above
2 mm were classified as G1 or G2, respectively. In a secondclassification scheme, algal biomass measured when Mdf
was below or above 5 m3/s (the average daily flow from2003 to 2013) was classified into R1 or R2, respectively.
Combining the two schemes, algal biomass in G1 and R1(G1R1), in G2 and R1 (G2R1), and in G2 and R2 (G2R2)
were then established (note, there were no algal biomass
measurements in G1 and R2). One-way analysis of variance (ANOVA) was then used to determine whether algal
biomass differed between each of the groups at all levels ofclassification (G1 vs. G2; R1 vs. R2; and G1R1 vs. G2R1
vs. G2R2). The one-way ANOVA was followed by Tukey’s
Honest Significant Difference (HSD) multiple comparison
test to identify differences among the groups (G1R1 vs.
G2R1 vs. G2R2). p-values of 0.05 for the one-way
ANOVA and 0.016 for the Tukey’s HSD test were established to indicate statistical significance.

RESULTS
Relationships between flow, sediment, and bed material
At all sites, D60 decreased and P<100mm increased, especially in 2010, but P<100mm exhibited a sudden decrease in2007 and 2011 (Figure 2). There were several differences
between sites with regard to inter-annual changes. For
example, the bed material size was finer only at St1 in 2009
(Figure 2). Both cD60 and cP<100mm variables exhibited a linear relationship with Qmax (cD60 p < 0.04; cP<100mm p <0.001), while D60 and P<100mm did not (Figure 3a, b, c, and d,respectively). Variable cD60 was the only one to exhibit alinear relationship with Sf (p < 0.003; Figure 3f). Most cD60
values were positive and most cP<100mm values were negative in 2007 and 2011, when Qmax was at its two highest values, and P<100mm exhibited sudden decreases (Figure 2).
These values are termed Group P1 in Figures 3b and 3d.
Most cD60 values were negative and most cP<100mm werepositive in 2004, 2005, 2009 and 2010, when Sf exceeded
10,000 m3/yr. These values are termed Group P2 in Figure
3f and 3h. The remaining data values in 2006, 2008, 2012,
and 2013, when Qmax was not so high and Sf was around
5,000 m3/yr, were termed Group P3.
The rules for whether cD60 or cP<100mm assumed a positiveor negative value were different between groups P1, P2,
and P3. In Group P1, most cD60 were positive and cP<100mm
were negative. That is, the bed materials became coarser
over time (Figure 4). In Group P2, on the other hand, thebed materials became finer over time (Figure 4). Lastly, P3
exhibited an entirely different trend of having positive values for both cD60 and cP<100mm (Figure 4).

Inter-annual comparison of flow and tractive force
with algal biomass
Algal biomass values were typically lower than
100 mg/m2 at all stations in all years, except at St2 and St3
in 2008, which had algal biomass higher than 200 mg/m2(Figure 5). Among the MDcri-classified groups (G1 & G2),
algal biomass was lower in G2 than in G1 (ANOVA p <0.01; Figure 6a). However, among the Mdf-classified
groups (R1 and R2), there was no difference in algal biomass (ANOVA p = 0.11; Figure 6b). A significant difference was, however, seen between G1R1, G2R1, and G2R2
(ANOVA p < 0.05; Figure 6c). Algal biomass was higher in
G1R1 than in G2R2 (Tukey’s HSD p < 0.016; Figure 6c),

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EFFECTS OF SEDIMENT REPLENISHMENT

Figure 2. Annual changes of: (a) Qmax and Sf; (b) D60; and (c) P<100mm relative to daily flow for sampling Stations 1–3
and higher in G1R1 than in G2R1 (Tukey’s HSD 0.016 < p< 0.05; Figure 6c). The dominant algal species did notchange significantly between locations or years, even in
2008, when algal biomass was extremely high.

DISCUSSION
Annual changes of bed material composition after
sediment replenishment
The characteristics of Group P1 indicate that when Qmax
was very high, the bed material size became coarser than in
the previous year (Figure 4). This phenomenon was likely
caused by fine bed materials and replenished sedimentbeing swept away by heavy flooding, which was the case in2007 and 2011. The characteristics of Group P2 indicatethat when Sf exceeded 10,000 m3/yr, the bed material
became finer than in the previous year (Figure 4). In thisgroup, most replenished sediment flowed out of the replenished site during the rainy season. This indicates that if
there is a certain extent of discharge and a large amount ofreplenished sediment placed in the rainy season, sedimentfrom the replenished site will be transported downstream,
contributing to finer bed material in the downstream
reaches. However, if the flow is very low, the sediment will
not be transported as far from the sediment replenishment
site. This scenario was observed in 2009, when Qmax was at
its lowest (27 m3/s; Figure 2), and sediment only reached

the sample station nearest the sediment replenishment site
(i.e. St1).
The characteristics of Group P3 were complex because
D60 was coarser than in the previous year, while P<100mm wasfiner (Figure 4). These observations suggest that at theGroup P3 points, there was a large proportion of particles
smaller than 100 mm in size and only a very small proportion of midsized particles (100–200 mm) in the riverbed. In
this scenario, because flow was low and the riverbeds lessdisturbed, it is possible that only the fine fraction of thereplenished materials reached the downstream areas (Figure4c). In contrast, D60 was finer in Group P2, despite the low
flow (Figure 4). In this case, it is possible that the greater
volume of replenished sediment may have promoted the
movement of the midsized particles. This is likely because
a high volume of fine particles results in greater porosity inthe materials, and thus more air gaps in the sediment(Parker et al., 1982). These fine particles and air gaps act as
lubricant, reducing the friction between moving particles. A
high volume of this low-friction sediment could easilytransport midsized materials downstream and replace themwith finer ones.

The effects of sediment replenishment on the size distribution and attached algae of riverbed material
As indicated by the significant difference in algal biomass between Groups G1 and G2 (Figure 6a), algal growth
may be restricted on moving materials that are larger than—117—

Y. MIYAGAWA ET AL.

Figure 3. Relationships between the annual maximum daily flow (Qmax) and bed material characteristics: (a) representative
size of bed material (D60 in mm); (b) change in D60 from the previous year (cD60); (c) proportion of particles less than
100 mm in diameter (P<100mm); and (d) change in P<100mm from the previous year (cP<100mm). Additionally, relationships
between the annual volume of sediment (Sf) and bed material characteristics: (e) D60; (f) cD60; (g) P<100mm; and (h) cP<100mm(P1: values in 2007 and 2011, years when Qmax was very high (at its highest and second highest) and P<100mm exhibited asudden decrease; P2: values in 2004, 2005, 2009, and 2010, years when Sf was very high (over 10,000 m3/yr); and P3: values in 2006, 2008, 2012, and 2013, years when Qmax was not as high and Sf was around 5,000 m3/yr)
2 mm in diameter. However, since there were no significant
differences between Groups R1 and R2 (Figure 6b), algal
biomass may not be restricted by the force of dischargealone.
Dcri appears to be a more effective criterion than flow ordischarge for the evaluation of river bed disturbance. Thisis likely because Dcri is determined by the characteristics ofboth flow and size distribution of the bed material. Dcri isalways high when the flow is high (as in G2R2), but when
the flow is low, the magnitude of Dcri depends on the size
distribution of the bed material. Because algal biomass was
lower in G2R1 than in G1R1 (Tukey’s HSD 0.016 < p <0.05; Figure 6c), even if flow is low, algal biomass may be
restricted when the bed material is fine and the material iseasily disturbed by the flow.
Algal biomass was extremely high in 2008. It is assumed
that the degree of riverbed disturbance in the rainy seasonof that year must have been low, easing any restriction on
algal growth. This is supported by the results of Group P3,
which showed low values of Sf and Qmax in 2008. In the previous year (2007), heavy flooding removed most of the fine
bed material, so that by 2008 only coarse, difficult to disturb bed materials remained. Interestingly, the flow conditions were similar in 2012, but high algal biomass was notobserved. The average MDcri in winter was higher in 2012(11 mm) than in 2008 (< 1 mm). This evidence suggeststhat algal biomass is affected by the disturbance one monthprior to measurement, rather than by the flow and bed
material size distribution of the preceding rainy season.
This may be because algal biomass grows quickly, requiring only one month to recover after detachment (Biggs etal., 1999). Therefore, we conclude that a monthly disturbance metric is important in evaluating the effect of bed
material disturbance on algal biomass.

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EFFECTS OF SEDIMENT REPLENISHMENT

Figure 5. Algal biomass measured from 2004 to 2013 inautumn, winter, and early spring (N.D. signifies there nodata was measured)
Kanto Regional Development Bureau, Futase Dam Management Office.

SUPPLEMENTS

Figure 4. The average of: (a) cD60; and (b) cP<100mm values
for Groups P1, P2, and P3 derived via One-way ANOVA
and Tukey’s HSD multiple comparisons test (Error bars
signify value of the two standard deviations; P1, P2, and P3
signify same groups as in Figure 3). (c) The general particle
size distribution curves of Groups P1, P2, and P3

ACKNOWLEDGMENTS
The data used in this study were supplied by the Ministryof Land, Infrastructure, Transport, and Tourism at the

Figure S1. The relationships between resources and disturbances related to attached algal biomass in streams andriversFigure S2. Annual schedule of sediment addition and field
monitoring (in Japan, flooding usually occurs in therainy season, and not in the dry season. Sediment addition or monitoring was carried out once during eachperiod indicated by the arrows. Algal biomass was measured one to three times per year.)

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