3. Materials and methods
3.2 Sediment and sediment control parameters
3.2.4 Sediment data
Suspended sediment and bedload data has been gathered in the Farkas Valley and Vadkan Valley since 1996. In the frame of this work, the sediment dataset between the hydrological years 2000 and 2010 has been analysed.
49 Suspended sediment data
Water samples have been manually collected into plastic bottles at the gauging stations with weekly frequency or linked to the flood events. One sample means 1 l water: according to the recommendation of WMO 1981 (Gordon et al. 2004), if suspended sediment concentration (SSC, mg·l-1) exceeds 100 mg·l-1 in the stream, 1 l water sample is sufficient to determine SSC.
The SSC have been quantified by filtering of the water samples. The filter papers containing sediment have been dried in an oven for 24 hours at 90-105 oC and weighed on a precision scale before and after the drying. As the weight of filter papers increases fast due to the air humidity after their removal from the oven, empty filter papers have been applied as control papers to diminish the inaccuracies due to the weight increase. Figure 3.6 shows the process of gathering SSC data.
Figure 3.6. The process of gathering SSC data: water sampling (1), filtering (2-3), drying (3) and weighing (4) of the filter papers
Suspended sediment yield (SSY, mg·s-1 or t·yr-1 after unit conversion) is the total mass that leaves the catchment in a given time and can be estimated by integrating the suspended sediment transport rate over time:
Qt SSC t dt
SSY (Eq. 3.5)
where is the time interval of interest; Q(t) is the stream discharge (l·s-1) at time t; and SSC(t) (mg·l-1) is the suspended sediment concentration at time t.
To calculate SSY on the basis of Eq. 3.5 for every 1 or 2 minute, as having Q values by the automatic water stage recorders in that time resolution, more frequent SSC values are necessary as well. To generate SSC data for the automatic Q time series, regression equations have been developed. For those intervals when
neither SSC nor Q data have been available with high frequency,
no reasonable SSC values have been obtained by the regression equations, SSY have been calculated using average SSC and Q values:
Q SSC dt
SSY average average (Eq. 3.6)
where Qaverage is the normal discharge (l·s-1) and SSCaverage (mg·l-1) is the average suspended sediment concentration for the given season when no continuous data series were available; t in dt refers to the duration of data gap.
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Flow conditions, control factors and time scales for the suspended sediment concentration analyses. Since sediment dynamics has a significant temporal fluctuation according to the literature, this work examines SSC and its control factors at different time scales. Moreover, as the regression analyses, similarly the descriptive statistical assessment of SSC and SSC control factors has been divided into low flow and high flow conditions. Low flow database has been separated on the basis of the number of days elapsed since the previous flood event (antecedent days, AD) resulting in four arbitrary categories:
if AD < 2 (the previous flood event can directly influence the low flow SSC),
if 2 ≤ AD < 8,
if 8 ≤ AD (effect of the in-channel supply processes due to the long dry period may increase).
The high flow database has also been separated according to the rising and falling limb of the hydrograph.
Relations between the sediment variables and control factors have been analysed at different time scales:
for the entire study period – from 1st November 2000 to 31th October 2010,
at seasonal scale – autumn, winter, spring and summer,
and for the hydrological years.
The list below represents the factors controlling SSC and SSY involved in the analyses under high flow conditions:
Relations between hydrological, hydrometeorological and sediment variables have been investigated at the following time resolution:
for the entire study period – from 1st November 2000 to 31th October 2010,
at seasonal scale – autumn, winter, spring and summer,
and at event scale – with especial regard to the flood events on 18th July 2009 and 4th August 2009.
No SumQ and Qmax values are available for the Vadkan Valley.
51 Bedload data
Although the analysis of bedload dynamics is not the objective of the dissertation, the short description of bedload is important to be able
to calculate the total annual sediment yield (TSY) of the Farkas Valley in the weekly using volumetric method, simultaneously to the water stage and/or Q measurement.
Stilling basins are generally open in winter in order to avoid the damages by the frozen water, thus bedload trapping is also limited in winter period. BY of great floods exceed sometimes the 1.5 m3 capacity of the stilling basin causing quantitative underestimation. Organic debris, such as periphyton, leaves and logs may lead to BY overestimation. Suspended sediment may accumulate in the basin at very low Q, while a part of the bedload may behave as suspended sediment at high Q because of the turbulent conditions. To determine the SY leaving the stilling basin, not only the inflow SSC but also the outflow SSC has being sampled since April 2009. The average value of the SSCinflow-SSCoutflow difference has been applied as a correction factor of the BY.
BY has been calculated with a simple summation of the observed data for a longer time period. However, the weekly or longer measuring intervals cause problems in the determination of BY at event scale, because bedload of more flood events and low from period may accumulate in the stilling basin between the measurements. Eq. 3.7 was applied to subtract the BY of the irrelevant high and low flow periods in the cases of the flood event
where BYflood_obs is the bedload yield of the sampled flood event (kg), BY* is the total bedload yield accumulated in the stilling basin between two measurements (kg); BYbf_average is the average baseflow bedload yield (kg·min-1) – it has been determined on the basis of BY values observed in long dry periods when no flood events occurred between two bedload measurements; t is the duration of the low flow periods between two bedload measurements (min); SumQ is the total volume of the sampled flood event (l); SumQhf is the total volume of the high flow periods between two bedload measurements (l) (Csáfordi et al. 2010a).
The method is based on the simplification that there is a direct proportionality between the cumulative Q and BY of the flood events. As this assumption neglect the strong stochasticity in the bedload dynamics due to the sediment availability (breakage of the armoured streambed, sudden outwash of sediment deposits, landslides) and the power law between Q
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and BY, BY values for the sampled flood events have to be recalculated using other methods in the future.
The sum of suspended sediment yield and bedload yield for a given time period is equal to the total sediment yield (TSY, t·yr-1).