scholarly journals Characterizing the relationship between river branch number and water discharge using distributions of channel belt properties

2021 ◽  
Author(s):  
Tian Dong ◽  
Timothy Goudge
Keyword(s):  
Water Discharge ◽  
Branch Number ◽  
Channel Belt ◽  
The Relationship

scholarly journals LAJU ANGKUTAN SEDIMEN MELAYANG DI SUNGAI WIMBI SUB DAS WIMBI KABUPATEN POSO

2021 ◽  
Vol 9 (1) ◽  
pp. 43
Author(s):  
Herman Harijanto ◽  
Abdul Wahid ◽  
Arief Sudhartono ◽  
Nikteri Perori
Keyword(s):  
River Water ◽  
Cross Section ◽  
Loading Rate ◽  
Water Discharge ◽  
Survey Method ◽  
Water Runoff ◽  
Sediment Loading ◽  
Sediment Discharge ◽  
The Cross ◽  
The Relationship

The research purpose was to determine of floating sediment loading rate which transported along Wimbi river water runoff and analyzed the relationship between water discharge with floating sediment discharge in the Wimbi river. The method used in this study was a survey method, namely by conducting direct measurements in the field, including: measurement of water discharge and water sampling for analysis of floating sediment content. Parameter  measured for the purpose of analyzing the sediment loading rate, namely floating sediment concentration Cs (mg / l), river water discharge Q (m3 / sec) and floating sediment discharge Qs (kg / sec). The relationship between water discharge and sediment discharge was analyzed using a suspended sediment rating curve. The results showed the flow of river water flowing at the cross section of the Wimbi river ranged from 0.88 m3 / sec - 13.7 m3 / sec (average of 6.17 m3 / sec). Furthermore, the height of the water level (H) flowing in the cross section of the Wimbi river ranged from 0.5 to 1.84 m with  average = 1.14m. Sediment loading rates float in the Wimbi river ranged from 2.110 - 99.511kg / sec (average of 35.222 kg / sec). The analyzed results of the relationship between water discharge and floating sediment discharge obtained a positive relationship with a correlation value of 0.96.

scholarly journals Degradation of recalcitrant organic polluants in seafood wastewater by modified TiO2 photocatalysts

2017 ◽  
Vol 1 (T4) ◽  
pp. 241-248
Author(s):  
Loc Cam Luu ◽  
Da Linh Ho ◽  
Phu Chi Hoang ◽  
Tri Nguyen ◽  
Van Thi Thuy Nguyen ◽  
...  
Keyword(s):  
Waste Water ◽  
Water Discharge ◽  
Pure Tio2 ◽  
Reaction Conditions ◽  
Tio2 Photocatalysts ◽  
Processing Plants ◽  
Seafood Processing ◽  
The Relationship

In seafood processing plants, industrial waste water discharge reached virtually the level B (QCVN 11-MT:2015/BTNMT) after using mechanical, physicochemical and biological wastewater treatment methods. However, their COD values (COD = 20-120 mg/L) were not qualified for allowable concentration of discharge requirement - level A (COD ≤ 75 mg/L) in many cases. In this paper, bio-treated seafood waster water was continually treated by TiO2 photocatalyst modified by doping Fe and N to degrade recalcitrant organic pollutants to obtain the A level water which can be resused. TiO2 modified by doping Fe and N were prepared and investigated the physico-chemicalproperties. The results showed that modified TiO2 had a lower band gap and more photoactivity than pure TiO2. Beside that, at the reaction conditions: reaction temperature 25 oC, dissolved oxygen concentration 7.6 mg/L and pH = 7, the optimal concentration of catalysts was determined (1.25 g/L). After 12 hours of treatment, COD removal efficiency on TiO2-Fe and TiO2-N catalysts attained 41.1 % and 64.3 %, respectively, and their COD values reached 49.3 and 29.9 mg/L, correspondingly. After treatment, the quality of waste water discharge met the level A (QCVN 11-MT:2015/BTNMT) and became a safety source for reusing (QCVN 08-MT:2015/BTNMT). In addition, the relationship between the characterization of modifed TiO2 and their activity was characterized.

scholarly journals Erosion rates and sediment yields of glaciers

1996 ◽  
Vol 22 ◽  
pp. 48-52 ◽  
Author(s):  
Jim Bogen
Keyword(s):  
Water Pressure ◽  
Water Discharge ◽  
Drainage System ◽  
Sediment Concentration ◽  
Pressure Drops ◽  
Sediment Yields ◽  
Erosion Rates ◽  
Slow Moving ◽  
The Relationship ◽  
Subglacial Drainage

Sediment yields and glacial erosion rates are evaluated for four Norwegian glaciers during the years 1989-93. Annual erosion rates were determined from measurements of sediment load and water discharge in glacial meltwater rivers. The mean sediment yield and the corresponding erosion rate of the valley glaciers Engabreen and Nigardsbreen were found to be 456 t km−2year−1(0.168 mm year−1) and 210 t km−2year−1(0.078 mm year−1), respectively. A small and slow-moving cirque glacier Øvre Beiarbre yielded a rate of 482 t km−2year−1(0.178 mm year−1), and the sub-polar Svalbard glacier Brøggerbreen yielded 613 t km−2year−1(0.226 mm year−1). The erosion rates are low compared to glaciers elsewhere. There are also considerable variations in sediment yields at each glacier from year to year. However, different factors are found to control the variability on each individual glacier. Analysis of the relationship between water discharge and sediment concentration in meltwater rivers suggests that changes in subglacial drainage systems cause variations in sediment availability and the way sediments are melted out from the ice. When water pressure drops, the drainage system in fast-moving, thick valley glaciers deforms at a more rapid rate than in thin, slow-moving ones. New volumes of debris-laden ice are thus more readily available for melting when water pressure next increases. Beneath the thin, slow-moving Øvre Beiarbre, single years with high transport rates and evacuation of sediment are followed by periods of low availability lasting for 2 years or longer. It is suggested that this pattern results from exhaustion of sediment in a stable drainage system, with more sediment becoming available when the position of the subglacial drainage system is changed.

Experimental investigation on the relationship between sluice caisson shape of tidal power plant and the water discharge capability

2010 ◽  
Vol 35 (10) ◽  
pp. 2243-2256 ◽  
Author(s):  
Dal Soo Lee ◽  
Sang-Ho Oh ◽  
Jin-Hak Yi ◽  
Woo-Sun Park ◽  
Hyu-Sang Cho ◽  
...  
Keyword(s):  
Experimental Investigation ◽  
Power Plant ◽  
Water Discharge ◽  
Tidal Power ◽  
Tidal Power Plant ◽  
The Relationship

scholarly journals Lebegtetett hordalékmérési módszerek összehasonlító vizsgálata balatoni részvízgyűjtőkön

2017 ◽  
Vol 66 (2) ◽  
pp. 317-332 ◽  
Author(s):  
I. Potyó ◽  
I. Kása ◽  
Cs. Farkas ◽  
Gy. Gelybó ◽  
Zs. Bakacsi ◽  
...  
Keyword(s):  
Spatial Heterogeneity ◽  
Suspended Solids ◽  
Measurement Accuracy ◽  
Water Discharge ◽  
Total Suspended Solids ◽  
Monitoring Point ◽  
Handheld Device ◽  
The Relationship ◽  
Small Catchments ◽  
Soil Weight

The present study investigated the quantity of total suspended solids (TSS) in three small catchments and compared the data to turbidity measurements. The TSS data were based on filtration, drying and weight measurements, while the turbidity measurements were retrieved using a handheld device with a turbidity sensor. Water was collected daily at the catchment outlets from November 1, 2016 to May 31, 2017, representing the winter and spring seasons. The lowest quantity of TSS was detected at the catchment outlet of the Esztergályi Stream; however, there were two lakes close to the monitoring point where soil particles may have settled, possibly explaining the low TSS values. The Csorsza and Tetves streams had similar TSS values during winter, but in the spring samples the TSS values were approximately three times higher in the Csorsza Stream than in the Tetves Stream. The relationship between water discharge and TSS values was also investigated for the Tetves Stream, but no significant correlations were observed between them. The results suggested that the labour-intensive TSS measurements (e.g. filtration, soil weight measurements) could be replaced to a good approximation using the handheld device. The spatial heterogeneity within and between the catchments influences the amount of suspended sediment and hence the measurement accuracy. Therefore, the use of the handheld device should also be complemented with other methods, such as the filtration used in the present study, to attain more precise values.

THE RELATIONSHIP BETWEEN ACTIVE CHANNEL AND CHANNEL BELT WIDTHS AND SINUOSITIES, AND HOW IT CHANGES DOWN A MEGAFAN

2018 ◽  
Author(s):  
Stephen D. Newman ◽  
◽  
Gary S. Weissmann ◽  
Louis A. Scuderi
Keyword(s):  
Channel Belt ◽  
The Relationship ◽  
Active Channel

scholarly journals On the Relationship between Suspended Sediment Concentration, Rainfall Variability and Groundwater: An Empirical and Probabilistic Analysis for the Andean Beni River, Bolivia (2003–2016)

Water ◽  
2019 ◽  
Vol 11 (12) ◽  
pp. 2497 ◽  
Author(s):  
Irma Ayes Rivera ◽  
Ana Claudia Callau Poduje ◽  
Jorge Molina-Carpio ◽  
José Max Ayala ◽  
Elisa Armijos Cardenas ◽  
...  
Keyword(s):  
Suspended Sediment ◽  
Suspended Sediment Concentration ◽  
Water Discharge ◽  
Probabilistic Method ◽  
Sediment Concentration ◽  
Sediment Dynamics ◽  
Base Flow ◽  
Flow Index ◽  
The Relationship ◽  
Clockwise Hysteresis

Fluvial sediment dynamics plays a key role in the Amazonian environment, with most of the sediments originating in the Andes. The Madeira River, the second largest tributary of the Amazon River, contributes up to 50% of its sediment discharge to the Atlantic Ocean, most of it provided by the Andean part of the Madeira basin, in particular the Beni River. In this study, we assessed the rainfall (R)-surface suspended sediment concentration (SSSC) and discharge (Q)-SSSC relationship at the Rurrenabaque station (200 m a.s.l.) in the Beni Andean piedmont (Bolivia). We started by showing how the R and Q relationship varies throughout the hydrological year (September to August), describing a counter-clockwise hysteresis, and went on to evaluate the R–SSSC and Q–SSSC relationships. Although no marked hysteresis is observed in the first case, a clockwise hysteresis is described in the second. In spite of this, the rating curve normally used ( SSSC = aQ b ) shows a satisfactory R2 = 0.73 (p < 0.05). With regard to water discharge components, a linear function relates the direct surface flow Qs–SSSC, and a hysteresis is observed in the relationship between the base flow Qb and SSSC. A higher base flow index (Qb/Q) is related to lower SSSC and vice versa. This article highlights the role of base flow on sediment dynamics and provides a method to analyze it through a seasonal empirical model combining the influence of both Qb and Qs, which could be employed in other watersheds. A probabilistic method to examine the SSSC relationship with R and Q is also proposed.

scholarly journals Prediction of water discharge and sediment in teak forested area using artificial neural network model

2017 ◽  
Vol 6 (1) ◽  
pp. 73
Author(s):  
Nining Wahyuningrum
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Water Discharge ◽  
Ann Modeling ◽  
Highly Nonlinear ◽  
Condition Modeling ◽  
Artificial Neural ◽  
Artificial Neural Network Ann ◽  
Relationship Of ◽  
The Relationship

Information on the relationship of rainfall with discharge and sediment are required in watershed management.This relationship is known to be highly nonlinear and complex. Although discharge and sediment has been monitored continuously, but sometimes the information is not or less complete. In this condition, modeling is indispensable.The research objective is to create a model to predict the monthly direct runoff and sediment using Artificial Neural Network (ANN).The model was tested using rainfall data at t-3 and t-4 as input, and discharge and sediment at t+3 and t+4 as output. The data used is the data from 2001 to 2014. The results showed that of some models tested there are two models for the prediction of discharge and two models for sediment.The model was chosen because it has the smallest MSE, the largest R2 and satisfying K (0.5 to 0.65).Thus, these models can be used to predict discharge andsediment for a period of t+3 and t+4. Prediction of discharge of t+3 and t+4 may use Q t+3 = 0,64 Q t-3 + 0,05 and Q t+4 = 0,65 Q t-4 + 0,074 res pectively, while for predicting sediment of t+3 and t+4 may use equations QS t+3 = 0,45 QS t-3 + 0,052 and QS t+4 = 0,45 QS t-4 + 0,052. This ANN modeling can be applied to predict the flow and sediment in other locations with an architecture adapted to the conditions of available data.

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