Channel Form Prediction of Chinda Creek: A Critical Factor to Sustainable Management of Flood Disaster in Port Harcourt, Niger Delta Nigeria
OYEGUN CU1, CHUKWU-OKEAH O1 and NWANKWOALA HO2*
1 Department of Geography & Environmental Management, University of Port Harcourt, Nigeria
2 Department of Geology, University of Port Harcourt, Nigeria
Submission: March 01, 2017; Published: June 28, 2017
*Corresponding author: Nwankwoala HO, Department of Geology, University of Port Harcourt, Nigeria
How to cite this article: OYEGUN C, CHUKWU-OKEAH G, NWANKWOALA H. Channel Form Prediction of Chinda Creek: A Critical Factor to Sustainable Management of Flood Disaster in Port Harcourt, Niger Delta Nigeria. Oceanogr Fish Open Access J. 2017; 3(3): 555612. DOI: 10.19080/OFOAJ.2017.02.555612
Flooding have been identified by different scholars as a major challenge facing communities, hence this study examines the role of water bodies in the control and management of flood. The study was conducted in Chinda Creek in Ogbogoro section of the New Calabar River, Niger Delta Nigeria. Measurement of study variables was done, this was to identify the influence of velocity, sediment yield, depth and discharge on channel morphology. The channel length measured 643.275m and was divided into 30 sample points were measurement of the study variables were taken. The result from the correlation revealed that channel morphology of Chinda Creek is significantly correlated with discharge and depth. Nevertheless, it has positive correlation with velocity, bed load and suspended sediment load but their correlation were not significant. Multiple regression analysis was used and the result showed that only two variables, discharge and velocity provided 94.8% explanation for the variation in channel morphology. Hence the study recommended planned sand mining of the creek to increase its capacity for discharge as well as serve as a flood control mechanism in the study area.
Stream channels have similar forms and processes throughout the world. Water and sediment discharge create channels as they flow through drainage networks. Obstructions and bends formed from resistant material can locally control channel form by influencing flow and sediment deposition . In forest streams where structural elements such as woody debris, bedrock, and boulders are commonly abundant, these effects are particularly important.Sediment load, water discharge, and structural elements, the controlling independent variables of channel morphology determine the shape of the channel along the stream network. The form of any channel cross section reflects a balance between the channel’s capacity to carry sediment away from that point and the influx of sediment to that point. A stable channel is one whose morphology, roughness, and gradient have adjusted to allow passage of the sediment load contributed from upstream . Characteristics of the banks also influence the cross-sectional shape of the channel and help to regulate channel width at any point in the stream.
Chinda Creek which is a tributary of the New Calabar River is an alluvial river, in that it flows through sands, silts, or clays deposited by flowing water . Natural alluvial rivers are usually wide with an aspect ratio (width to depth) of 10 meters or greater  and the boundary can be moulded into various configurations as was demonstrated in the seminal work of Gilbert in Roberts . With alluvial rivers, the channel geometry is influenced not only by the flow of water but by the sediment transported by the water. When the flow discharge changes, the sediment transport changes and, in turn, the channel geometry usually changes.Morphological change in stream channels may be a result of stream side forest harvesting. Millar  developed a model to predict stream channel morphology based on the condition of riparian vegetation. This model was tested on a portion of Slesse Creek (a tributary to the Chilliwack River) downstream of an old-growth area in the headwaters. The riparian area was extensively logged in the 1950s and 1960s, and has subsequently become parkland. The model predicted that in the presence of dense riparian vegetation, Slesse Creek would form meandering channel morphology, and that in the
absence of dense riparian vegetation it would form a braided
channel.These predictions were then confirmed using pre- and
post-logging air photos.
However, corresponding changes in stream morphology may
change stage discharge relationships and thereby increase or
decrease peak flood stages . Thus, predicting changes in base
level and channel morphologies are important steps toward
understanding future stream behaviors and risks.
A few key relationships describe the physics governing
channel processes and illustrate controls on channel response.
Conservation of energy and mass describe sediment transport
and the flow of water through both the channel network and
any point along a channel. Other relationships describe energy
dissipation by channel roughness elements, the influence of
boundary shear stress on sediment transport and the geometry
of the active transport zone.
A common problem faced by geomorphologists is the
identification of the dominant process responsible for creation
of a particular form. Arising from this, it is the interest of the
study to examine the influence of hydraulic parameters such as
depth, discharge, velocity; bed load and suspended sediment
load on channel morphology and also identify the major factors
controlling morphological change in the area. The study therefore
intends to develop a model which predicts channel morphology
from hydraulic parameters with the intent to identify its role in
sustainable flood disaster management.
Changes in channel morphology following large sediment
inputs have been demonstrated in several regions. Lisle 
showed a decrease in pool depths following a large flood and
associated channel aggradation. Madej & Ozaki  quantified
the decreases in both pool depth and frequency associated
with a sediment pulse. The model for predicting morphologic
change developed by Millar  indicated that Narrowlake Creek
is a transitional watershed, but it was not sensitive enough to
accurately predict the apparent shift from a meandering to a
braided morphology.This reinforces the notion that stream side
forest harvesting does affect stream channels in the Central
Interior, though not necessarily in a way that can be readily
predicted from hydrology models or empirical analysis. While it
is impossible to quantify the exact amount of channel widening
in Narrowlake Creek directly associated with forest harvesting,
the cumulative effects of logging and natural disturbance have
led to channel change throughout the logged portions of the
watershed. The predictive model Millar  developed a tool for
Slesse Creek, Canada and will be important for future prescription
development in watersheds. However, for transitional systems
like Narrowlake Creek in Vancouver, model predictions indicate
that cautionary measures for either floodplain protection or
restoration must be undertaken.
The linkages between logging activity and channel
morphology are complicated. Predictive models have great
value as tools that can be used to assist in successful watershed
protection and restoration, but it will be important that they are
not been used without watershed analyses, particularly in the
case of transitional systems. The biological implications of the
Millar (2000) model, as indicated by the Narrow lake Creek and
Slesse Creek case studies in Canada, are profound and worth the
effort of further analyses and adjustment to provide a useful tool
for both watershed protection and restoration.
Similarly, Oyegun  in his study on channel morphology
prediction using urbanization index, discharge and sediment
yield of the upper Ogunpa River discovered that discharge was
a major determinant of channel form and therefore was able
to develop a model for channel morphology prediction using
the above variables. This was also the same in the case of Oku
 whose study revealed a significant correlation between
discharge and channel shape and size of Ntawogba creek in Port
Harcourt where discharge was the main determinant of channel
morphology amidst several other variables.
As cited by Oku , Faniran & Jeje stated that the geology
of a basin is a determining factor of channel shape and size
characteristics, his work of the Rima basin revealed that despite
discharge and other basin shape and size predicting and
determining variables that channel geological characteristics
determines the level of carving and enlargement of a channel.
Various studies carried out by several geomorphologist from
both local and international have an agreement that channel
form prediction as well as determinant variables seem to follow
a trend irrespective of climatic conditions.
The study was conducted in Chinda Creek in Ogbogoro town
in Obio/Akpor Local Government area of Rivers State, which is
located at latitude 4° 50’42.00’’N and longitude 6° 55’44.10’’.
The community is about 1.37 kilometres away from the creek
which lies at latitude 4° 50’2.43’’N and longitude 6° 56’6.26’’E.
The total length of the creek to an adjoining creek called Okolo-
Nbelekwuru is 1.93 kilometres, connecting to the New Calabar
River, the total length is 3.04 kilometres.
Field studies and river measurement of Chinda Creek in
Ogbogoro section of the New Calabar River was done. This was
to enable the examination of the influence of velocity, sediment
yield, depth and discharge on channel morphology. To do this,
measurement of velocity, depth, discharge and sediment yield
of the channel were taken. The length of the channel was
determined with the aid of a measuring tape, and the channel measured 643 meters. This was divided 30 sample points as
data collection points for the entire channel at an interval of
To determine the velocity of flow in the channel, according
to the International Irrigation Management Institute report no
T-7, several methods of velocity measurement were identified,
but in the case of this study the two point method was used.
This implies that instead of taking measurements on the water
surface alone, velocity measurements was taken both on the
surface and beneath, precisely at 0.2m and 0.8m respectively.
This is because the flow depth of the river exceeds 0.76m .
Therefore velocity meter measurements were taken at 0.2
and 0.8m of the flow depth, d. This was done with the use of a
digital water velocity metre. The mean velocity was obtained by
averaging the velocities measured at 0.2 and 0.8m of the flow
depth. Thus, the mean velocity V, in the reach would be:
To determine discharge, the principle to obtain the
discharge per unit width (m2/sec) is to determine the product
of mean velocity in the vertical per unit area. This method
remains the same whether the measurements are carried out
under permanent or non-permanent flow conditions. The total
discharge of the channel was calculated from the measurement
of velocity in the channel, noting that discharge per unit width
q (m2/sec) which is the product of mean velocity in the vertical
(m/sec) and the water depth (d) at the vertical at the moment of
To measure the bed load, the Handheld Bedload- US BLH-84
sediment sampler was used . The reason for the choice is
that it is mechanically simple, and can be used at depths up to
3m. To carry out the measurement, it was done at each sample
point in the channel. To calculate this, the sediment transport
formula been put forward by Chang et al  was used.
To measure the suspended load as well, the Depth-Integrating
Suspended-Sediment Wading Type Sampler Model DH 48 was
used. The sampler container is held in place and sealed against
a rubber gasket in the sampler head, by a hand-operated springtensioned
clamp at the rear of the sampler. This when immersed
into the channel was removed after every 5 minutes and emptied
into separate clean used bottled water containers for the 30
sample points. The content was there after filtered to determine
the weight of the clastic particles in the water sample. since the
sampler have a volume of 470cc, the researcher ensured that the
volume of water collected did not exceed 440cc but fell within the
range of 375cc to 440cc. To achieve this, enough time was given
during submergence of the sampler to ensure that the volume of
the sampled water falls within the acceptable standard.
The ultimate goal of the data collection process was basically
to access the relationships between the various independent
variables of discharge, velocity depth, bedload and suspended
sediment yield on one hand and the channel morphology on the
other hand. The data set of Chinda Creek was collected with the
aid of a calibrated leveling staff and measuring tape. Within the
context of the present study, channel morphology, which is the
shape of the channel, refers to the cross sectional area of the
channel at various sampled points of the basin. In order words,
the average channel width and depths were measured and their
products were stated in square metre. This was done using
Cuencia  formula for estimating cross sectional area.
Area = width x depth (4)
The cross sectional area of the thirty (30) sample points was
However, from the data generated the mean cross sectional
area of the channel was 10.7223 with a standard deviation of
Tables and charts were used in the presentation of data while
in the analysis bivariate and multivariate analytical techniques
(Correlation matrix and multiple regression analysis) were used.
The model equation of the stepwise multiple regression analysis is as follows:
This section examined the predictive capacity of the
hydrological parameters of discharge, velocity, depth, suspended
sediment yield and bed load of channel morphology in Chinda
creek using the SPSS multiple regression (R) statistical tool.
Below is a correlation matrix table which identifies the
relationship between the dependent variable of channel
morphology and the independent variables of velocity, depth,
discharge, bed load and suspended sediment yield (Table 1).
(*0.05 significant level).
The above shows the correlation matrix of five independent
variables of velocity, depth, discharge, bed load and suspended
load on the dependent variable of channel morphology of Chinda
Creek in Ogbogoro. The testing of various relationships are
shown in the summary on Table 1. With the student “t” statistic
at 0.05 significant levels revealed that the channel morphology
of Chinda Creek is significantly correlated with discharge and
depth. Nevertheless, it has positive correlation with velocity, bed
load and suspended sediment load but their correlation are not
The finding of the study is of importance to geomorphological
studies, such that even though velocity, bed load and suspended
sediment load does not significantly correlate with channel
morphology of Chinda Creek, it indirectly contributes to the
existing channel form. In other words, discharge is partly a
function of velocity.
Table 2 above, shows that only two variables discharge
and velocity entered the regression equation. Discharge alone
provided 59% explanation for variation in channel Morphology
for the study creek while velocity accounts for 35.8% of same.
Hence the total explanation provided for the variation in channel
morphology by the independent variables of discharge and
velocity is 94.8%.
Source: SPSS Analysis result
In conclusion, this study has revealed that discharge and
velocity are the predictors of channel morphology in Chinda
Creek. It should also be noted that suspended sediment yield, bed
load and depth are indirect predictors of channel morphology
in Chinda Creek. This is because they correlate positively with
channel morphology and also have positive correlation with
velocity and discharge which are the direct predictors, with net
effect resulting in increased velocity and discharge.
More so, the five independent variables of the study directly
or indirectly affect channel morphology of Chinda Creek. This
shows that channel morphology of Chinda Creek correlates
positively with discharge, velocity, depth, suspended sediment
yield and bed load.
The stepwise multiple regression as shown in Table 3 above
revealed that discharge and velocity explains the change in the
channel morphology. This is because it accounted 94.8% change
in the channel morphology.
Thus, the hypothesized model developed by this study is of the
Y =10.348 + 1.312X1- 0.808X2 ----------- (6)
Y = Channel morphology
X1 = Discharge
X2 = Velocity
In order to determine the significance of this relationship,
Table 4 below was used.
From the Table 4 above, the analysis of variance chart above
shows two independent variables that significantly explain
variation in Chinda Creek morphology, jointly explained about
94.8% of the variation of channel morphology of Chinda Creek.
Given an F calculated value of 246.68 which is greater than the
table value of 3.35, reveals that discharge and velocity influence
channel morphology of Chinda Creek. This therefore implies that
channel morphology is influenced by hydraulic parameters.
The analysis showed a positive correlation between
discharge and channel morphology. The relationship was
statistically significant at 95% level. The multivariate technique
used in the SPSS computer programme of the step-wise multiple
regression analysis revealed that discharge was the most single
predictor of Chinda Creek morphology as it explains 59% of the
variation in the existing channel morphology of Chinda Creek.
From the analysis of the study, the developed a model helped
in predicting channel morphology using suspended sediment
yield, bed load, velocity, discharge and depth, which is of the
Y =10.348 + 1.312X1- 0.808X2 -------------- (7)
Y = dependent variable (channel morphology)
X1 = discharge (independent variable)
X2 = velocity (independent variable)
One of the findings of the study is that the channel has high
discharge. It also revealed that discharge and velocity are the
major predictors of the channel form, with discharge providing
59% of the variation in channel morphology of Chinda Creek.
The implication of this is that discharge has helped in the clearing of the creek a tributary to a major river the New Calabar
River. Velocity also provided 35.8% of the variation in channel
morphology of Chinda Creek, this has contributed immensely
to increasing the rate of flow in the channel and the amount of
water the channel discharges.
The study therefore recommends that a planned sand
mining of the creek should be done, to ensure that it has
more capacity for discharge as well as serve as a flood control
mechanism in Ogbogoro community noting its role in the control
of flood within the rural catchment. This will also allow traffic
flow for water transportation while generating revenue for
the Government and the community through the sand mining
process. With the growing demand for land space especially
within rural catchments, exposure of the earth surface as
well as concretization of the surfaces are possible, hence the
the tendency to increase surface run off of the area. There is
therefore need for annual and bi-annual study of the state of the
streams, creeks and other water bodies within rural catchment
to determine their role in flood control as a means to curb the
menace of flooding which is a major environmental hazard in the
Port Harcourt region.