FIGURE 1
The following sub-hypotheses were statistically tested: 1) Urucurituba
Channel presents higher sediment transport rate than Gurijuba-Igarapé
Novo Channel (> 50%), which causes the hydrological
collapse of Araguari River mouth; 2) the rainy seasonal period, in
combination to the tidal phase, significantly intensifies the solid
discharge contribution coming from the Amazon River, which is later
transported into Araguari River estuary. Therefore, this dynamics favors
erosive events, as well as changes suspended sediment concentrations and
water quality parameters; 3) the new configuration and complexity of the
formed drainage system affects water balance and leads to variations in
water quality parameters; and 4) factors such as location, distance from
the Amazon River, seasonality and tidal phase can explain variations in
suspended solid concentrations and in the quality of the water at
Araguari River mouth.
2 MATERIALS AND METHODS
2.1 Study site
The study site lies between the right bank of lower Araguari River and
the left bank of lower Amazon River, in the coastal-estuarine zone of
Amapá State / Brazil. It is featured as a flat and low coast influenced
by fluvial (North Channel of the Amazon River) and coastal (semidiurnal
tides) processes (Torres et al., 2018) (Figure 1). It has hydromorphic
soil associated with recent geological formations that originated
quaternary plain areas that, in their turn, are naturally vulnerable to
erosion processes (Rabelo, 2006).
The climate in the region is ruled by the Intertropical Convergence Zone
(Schneider et al., 2014). The rainy season goes from December to July,
whereas the dry season goes from August to November. Mean annual air
temperature ranges from 27ºC to 27.5ºC, whereas mean annual rainfall
rate ranges from 2,400 to 2,600 mm.year-1 (Oliveira et
al., 2010).
Araguari River basin covers 1/3 of the total territory of Amapá State.
It shelters important protected areas, from its source in Tumucumaque
Mountains National Park to its low course near Piratuba Lake Biological
Reserve (Dias et al., 2016).
Maximum flow of 3,415.8
m³s-1 (May 2014) and minimum flow of 155.5
m³s-1 (December 2013) were recorded between 2013 and
2015 in middle Araguari River, at Porto Platon station, which is located
270 km away from the original mouth (Cunha et al., 2014). However, the
coastline of lower Araguari River, close to Amazonas, is influenced by
tides whose amplitude is of approximately 3.4 m, in the North Channel of
Amazon River (Figure 1).
Hydroelectric power generation (Coaracy Nunes series of plants - UHECN,
Ferreira Gomes - UHEFG and Cachoeira Caldeirão - UHECC) is the main
economic activity in the middle section of Araguari River basin (Cunha
et al., 2011; Silva et al., 2017). Mining activity (gold, manganese,
iron and pebble extraction) is carried out in its high section (Matta et
al., 2008), whereas extensive buffalo breeding is performed in its low
section, mainly in floodplain areas in the region (Silva et al., 2020).
2.2 Net discharge
Net discharge and current velocity were measured in acoustic Doppler
profiler (Acoustic Doppler Current Profiler - ADCP, RD Instruments, Rio
Grande model, 600 kHz), based on recommendations by Mueller and Wagner
(2009).
Positive flow values (Q
> 0) indicate flow downstream the Amazon River estuary
(ebb), whereas negative flow values (Q < 0) indicate opposite
flow direction – i.e., upstream the hydrographic basin (flood). Q = 0
indicates lack of net flow in the measured section (low or high tide).
Monitoring stations are shown in Figure 1. Measurements were only taken
during spring tide (12.5h cycle), in the dry (October 2017) and rainy
(May 2018) seasons.
2.3 Suspended Sediments
One liter (1 L) of water-sediment mixture was collected on the surface
of the channel (0.30 m deep) at 1-hour intervals, until the end of a
tidal cycle, for suspended sediment (SSC) analysis
purposes - 127 samples were collected in both seasonal campaigns.
SSC was obtained by filtering 250 mL of water samples in
glass fiber membranes (0.45 µm porosity). It was used as dependent
parameter and suspended solids discharge (Qss)
estimator. Qss was used as dependent variable in order
to test the sediment transport hypothesis based on environmental
factors, hydrodynamic variables and water quality.
2.4 Suspended solids discharge
Qss was estimated by only taking into consideration the
SSC load, which represented approximately 80-90% of the
effective total solid discharge (Carvalho et al., 2014). The calculation
was based on the simplified method described by the aforementioned
authors and represented by the following equation:
\(Q_{\text{SS}}=0.0864.\ Q.\text{SSC}\) (1)
wherein: Qss represents the suspended solids discharge
(t tidal cycle-1), Q is net discharge
(m³s-1) and SSC is the suspended
sediment concentration (mgL-1). Factor 0.0864 is the
constant used for conversion into ton per day.
2.5 Water Quality Parameters
Water samples were collected in 2-L sampling bottle, in the middle of
the channel section (surface), at 1-h intervals and throughout the
semidiurnal tide cycle and in the dry (December) and rainy (May)
periods.
Air temperature was measured in
digital thermometer. Parameters such as water temperature, electrical
conductivity, total dissolved solids and pH were measured in
multiparameter probe (HANNA, model HI 9828). Turbidity was analyzed in
AP 2000 IP turbidimeter (Policontrol Analytical Instruments) based on
the nephelometric method. Secchi disk was used to measure water
transparency. Instrutherm oximeter (model MO-900) was used to determine
dissolved oxygen (DO) and DO saturation. Oakton Pcstestr 35 probe was
used to measure salinity level.
2.6 Statistical Analysis
Hydrodynamic and water quality data were subjected to descriptive
analysis and, subsequently, to uni- and multivariate analyses (R
Development Core Team, 2020). After data non-normality were tested
(Shapiro-Wilk test), Spearman correlation analyses were applied to test
correlations between SSC and Qssversus water quality parameters, based on factors such as
distance between collection points and the Amazon River, seasonality and
tidal phase (flow and current velocity, Q and V, respectively).
Non-parametric Kruskal-Wallis test was used to investigate the
spatial-seasonal effects of hydrodynamics and water quality on
Ssc and Qss, based on the aforementioned
factors (Crawley, 2007).
In addition, discriminating principal component analysis (DPCA) was
applied to jointly test hydrodynamic and water quality variables
(MacKinnon et al., 2016). After suitable transformation, DPCA was used
to create normality and to equalize variances (Jombart and Collins,
2015). The goal was to enable the efficient discrimination of water
quality and hydrodynamic groups based on few synthetic variables built
as linear combinations of the original variables, which have the widest
variation between and within groups (α ≤ 0.05) (Supplement).