Abstract: On the basis of the structure of alluvial sediments explained by echo sounding data and remote sensing images, the following results can be given: The estuary of Lam river from Ben Thuy Bridge (original word: Bến Thủy) to Cua Hoi (original word: Cửa Hội) is divided into three channels (location is calculated according to the river bank on the Nghe An Province, original word: Nghệ An): i) channel I (from Ben Thuy Bridge to Hung Hoa, original word: Hưng Hòa) is the branching river; ii) channel II (from Hung Hoa to Nghi Thai, original word: Nghi Thái)is a channel develops in a meandering direction with a concave side toward Ha Tinh Province (Hà Tĩnh); iii) channel III (from Nghi Thai to Cua Hoi)is a channel develops in a meandering direction with a concave side toward Nghe An province.This estuary area is formed in the period from after the sea level dropped below 0m (current water level) to the present: i) Channel II developed moving towards Ha Tinh Province; ii) Channel III developed moving towards Nghe An Province; iii) In channel I, a second river branch is formed because the flow of river cuts through the Hong Lam- Hong Nhat mudflat (original word: Hồng Lam -Hồng Nhất),at the same time creating an island.Morphological characteristics of the estuary area of Lam River are the main result of erosion and deposition activities corresponding to two water levels: the water level is about 2 m lower than the current water level and the current water level.Characteristics of the sediment layers on the riverbed in the estuary can be used to determine the sea levels in Late Holocene to the present.
Abstract: The present article discusses design and development of Information System for monitoring ecology within the Black Sea basin of Georgia. Sea parameters, river, estuary, vulnerable district, water sample, etc. were considered as the major parameters of the sea ecosystem. A conceptual schema has been developed for the Black Sea ecosystem based on object-role model. The experimental database for the Black Sea ecosystem has been constructed using Ms SQL Server, while the object-role model NORMA has been developed using graphical instrument Ms Visual Studio within the integrated environment of .NET Framework 4.5. Web portal has been designed based on Ms SharePoint Server. The server database connection with web-portal has been carried out by means of External List of Ms SharePoint Server Designer.
Abstract: Mumbai, being traditionally the epicenter of India's
trade and commerce, the existing major ports such as Mumbai and
Jawaharlal Nehru Ports (JN) situated in Thane estuary are also
developing its waterfront facilities. Various developments over the
passage of decades in this region have changed the tidal flux
entering/leaving the estuary. The intake at Pir-Pau is facing the
problem of shortage of water in view of advancement of shoreline,
while jetty near Ulwe faces the problem of ship scheduling due to
existence of shallower depths between JN Port and Ulwe Bunder. In
order to solve these problems, it is inevitable to have information
about tide levels over a long duration by field measurements.
However, field measurement is a tedious and costly affair;
application of artificial intelligence was used to predict water levels
by training the network for the measured tide data for one lunar tidal
cycle. The application of two layered feed forward Artificial Neural
Network (ANN) with back-propagation training algorithms such as
Gradient Descent (GD) and Levenberg-Marquardt (LM) was used to
predict the yearly tide levels at waterfront structures namely at Ulwe
Bunder and Pir-Pau. The tide data collected at Apollo Bunder, Ulwe,
and Vashi for a period of lunar tidal cycle (2013) was used to train,
validate and test the neural networks. These trained networks having
high co-relation coefficients (R= 0.998) were used to predict the tide
at Ulwe, and Vashi for its verification with the measured tide for the
year 2000 & 2013. The results indicate that the predicted tide levels
by ANN give reasonably accurate estimation of tide. Hence, the
trained network is used to predict the yearly tide data (2015) for
Ulwe. Subsequently, the yearly tide data (2015) at Pir-Pau was
predicted by using the neural network which was trained with the
help of measured tide data (2000) of Apollo and Pir-Pau. The analysis of measured data and study reveals that: The
measured tidal data at Pir-Pau, Vashi and Ulwe indicate that there is
maximum amplification of tide by about 10-20 cm with a phase lag
of 10-20 minutes with reference to the tide at Apollo Bunder
(Mumbai). LM training algorithm is faster than GD and with increase
in number of neurons in hidden layer and the performance of the
network increases. The predicted tide levels by ANN at Pir-Pau and
Ulwe provides valuable information about the occurrence of high and
low water levels to plan the operation of pumping at Pir-Pau and
improve ship schedule at Ulwe.
Abstract: The concentrations of heavy metals in sediments of
Qua Iboe River Estuary (QIRE) were monitored at four different
sampling locations in wet and dry seasons. A preliminary survey to
determine the four sampling stations along the river continuum
showed that the area spanned between
Abstract: High level and high velocity flood flows are
potentially harmful to bridge piers as evidenced in many toppled
piers, and among them the single-column piers were considered as
the most vulnerable. The flood flow characteristic parameters
including drag coefficient, scouring and vortex shedding are built into
a pier-flood interaction model to investigate structural safety against
flood hazards considering the effects of local scouring, hydrodynamic
forces, and vortex induced resonance vibrations. By extracting the
pier-flood simulation results embedded in a neural networks code,
two cases of pier toppling occurred in typhoon days were reexamined:
(1) a bridge overcome by flash flood near a mountain side;
(2) a bridge washed off in flood across a wide channel near the
estuary. The modeling procedures and simulations are capable of
identifying the probable causes for the tumbled bridge piers during
heavy floods, which include the excessive pier bending moments and
resonance in structural vibrations.
Abstract: Sediment and mangrove root samples from Iko River
Estuary, Nigeria were analyzed for microbial and polycyclic
aromatic hydrocarbon (PAH) content. The total heterotrophic
bacterial (THB) count ranged from 1.1x107 to 5.1 x107 cfu/g, total
fungal (TF) count ranged from 1.0x106 to 2.7x106 cfu/g, total
coliform (TC) count ranged from 2.0x104 to 8.0x104cfu/g while
hydrocarbon utilizing bacterial (HUB) count ranged from 1.0x 105 to
5.0 x 105cfu/g. There was a range of positive correlation (r = 0.72 to
0.93) between THB count and total HUB count, respectively. The
organisms were Staphylococcus aureus, Bacillus cereus,
Flavobacterium breve, Pseudomonas aeruginosa, Erwinia
amylovora, Escherichia coli, Enterobacter sp, Desulfovibrio sp,
Acinetobacter iwoffii, Chromobacterium violaceum, Micrococcus
sedentarius, Corynebacterium sp, and Pseudomonas putrefaciens.
The PAH were Naphthalene, 2-Methylnaphthalene, Acenapthylene,
Acenaphthene, Fluorene, Phenanthene, Anthracene, Fluoranthene,
Pyrene, Benzo(a)anthracene, Chrysene, Benzo(b)fluoranthene,
Benzo(k)fluoranthene, Benzo(a)pyrene, Dibenzo(a,h)anthracene,
Benzo(g,h,l)perylene ,Indeno(1,2,3-d)pyrene with individual PAH
concentrations that ranged from 0.20mg/kg to 1.02mg/kg, 0.20mg/kg
to 1.07mg/kg and 0.2mg/kg to 4.43mg/kg in the benthic sediment,
epipellic sediment and mangrove roots, respectively. Total PAH
ranged from 6.30 to 9.93mg/kg, 6.30 to 9.13mg/kg and 9.66 to
16.68mg/kg in the benthic sediment, epipellic sediment and
mangrove roots, respectively. The high concentrations in the
mangrove roots are indicative of bioaccumulation of the pollutant in
the plant tissue. The microorganisms are of ecological significance
and the detectable quantities of polycyclic aromatic hydrocarbon
could be partitioned and accumulated in tissues of infaunal and
epifaunal organisms in the study area.