Behavior of 129I in the Abukuma River water during two high-flow events in 2018

2021 ◽  
Author(s):  
Yoshifumi Wakiyama ◽  
Masumi Matsumura ◽  
Tetsuya Matsunaka ◽  
Shigekazu Hirao ◽  
Kimikazu Sasa
Keyword(s):  
River Water ◽  
Suspended Sediment ◽  
Activity Concentration ◽  
Environmental Behavior ◽  
Membrane Filter ◽  
Water Discharge ◽  
Temporal Trends ◽  
High Flow ◽  
Activity Concentrations ◽  
Dissolved Form

<p>Radioiodine is one of the most important radionuclides released by the accidents of Fukushima Dai-ichi nuclear power plant (FDNPP). Iodine-131 elevated ambient radiation dose rate immediately after the accident, but it is extinguished due to its short half-life. The long-lived <sup>129</sup>I can be used as a tracer to retrospectively infer the level of <sup>131</sup>I. Understanding of environmental behavior of <sup>129</sup>I is important for preparedness against nuclear disaster. This study presents sampling campaigns on the Abukuma River during two high flow events, and discusses riverine <sup>129</sup>I behavior based on comparisons with that of <sup>137</sup>Cs. The study site was the Kuroiwa site locating at midstream of the Abukuma river. Its catchment area was 2886 km<sup>2 </sup>and mean <sup>129</sup>I inventory in the catchment was 0.041 Bq m<sup>-2</sup>. Five and seven river water samples were taken during high-flow events in July 2018 (JUL18) and October 2018 (OCT18), respectively. Suspended sediment and filtrate samples were obtained by decantation and subsequent filtration with 0.45 μm-mash membrane filter, respectively. The suspended sediment and filtrate samples were measured for <sup>137</sup>Cs activity concentrations with HPGe detector and then measured for <sup>129</sup>I/<sup>127</sup>I ratio with accelerator mass spectrometer and for <sup>127</sup>I concentration with ICP-QQQ-MS. Mean <sup>129</sup>I activity concentration in suspended sediment during JUL18 and OCT18 were 1.0 and 0.43 mBq kg<sup>-1</sup>, respectively. In terms of temporal trends, <sup>129</sup>I activity concentration in suspended sediment lowered in the peak water discharge phase, contrastive to those of <sup>137</sup>Cs which were the highest at peak water discharge phase. Mean dissolved <sup>129</sup>I activity concentrations during JUL18 and OCT18 were 0.18 and 0.067 μBq L<sup>-1</sup>, respectively. Both <sup>129</sup>I and <sup>137</sup>Cs activity concentrations in dissolved form tended to decrease with time during two high-flow events. Mean apparent distribution coefficient (Kd) during JUL18 and OCT18 were 4.3 ×10<sup>4</sup> and 6.1 ×10<sup>3</sup> L kg<sup>-1</sup>, respectively. The Kd values of <sup>129</sup>I were lower than those of <sup>137</sup>Cs and it reveal relatively-high solubility of <sup>129</sup>I. Total exportation of <sup>129</sup>I from the catchment during JUL18 and OCT18 were estimated as 1.0 × 10<sup>4</sup> and 2.3 × 10<sup>4</sup> Bq, respectively. Exported <sup>129</sup>I in dissolved form accounted for 80 and 27% of total exportations, respectively. By contrast, more than 95% of <sup>137</sup>Cs was exported in particulate form in the events. These results indicated an importance of dissolved form for understanding environmental behavior of radioiodine.</p>

Neural networks approached for modelling river suspended sediment concentration due to tropical storms

2013 ◽  
Vol 11 (4) ◽  
pp. 457-466
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Suspended Sediment ◽  
Suspended Sediment Concentration ◽  
Time Series Data ◽  
Water Discharge ◽  
Sediment Concentration ◽  
Series Data ◽  
Generalized Regression Neural Network ◽  
Event Based

Artificial neural networks are one of the advanced technologies employed in hydrology modelling. This paper investigates the potential of two algorithm networks, the feed forward backpropagation (BP) and generalized regression neural network (GRNN) in comparison with the classical regression for modelling the event-based suspended sediment concentration at Jiasian diversion weir in Southern Taiwan. For this study, the hourly time series data comprised of water discharge, turbidity and suspended sediment concentration during the storm events in the year of 2002 are taken into account in the models. The statistical performances comparison showed that both BP and GRNN are superior to the classical regression in the weir sediment modelling. Additionally, the turbidity was found to be a dominant input variable over the water discharge for suspended sediment concentration estimation. Statistically, both neural network models can be successfully applied for the event-based suspended sediment concentration modelling in the weir studied herein when few data are available.

Measured and Modelled Chlorinated Contaminant Distributions in the St. Clair River Water

1986 ◽  
Vol 21 (3) ◽  
pp. 332-343 ◽  
Author(s):  
C.H. Chan ◽  
Y.L. Lau ◽  
B.G. Oliver
Keyword(s):  
River Water ◽  
Suspended Sediment ◽  
Water Samples ◽  
Concentration Distribution ◽  
Suspended Solids ◽  
Industrial Area ◽  
Concentration Profiles ◽  
Detroit River ◽  
Chemical Partitioning ◽  
Transverse Mixing

Abstract The concentration distribution of hexachlorobutadiene (HCBD), pentachloro-benzene (QCB), hexachlorobenzene (HCB) and octachlorostyrene (OCS) in water samples from transects across the upper and lower St. Clair River and the upper Detroit River were determined on four occasions in 1985. The data show a plume of these contaminants from the Sarnia industrial area. The fluxes and concentration profiles of the contaminants at Port Lambton have been modelled success fully using a simple transverse mixing model. A study on the chemical partitioning between the “dissolved” and “suspended sediment” phases shows that an important contaminant fraction is carried in the river by the suspended solids, particularly for lipophilie compounds such as HCB and OCS,

scholarly journals New Approach for the Determination of Radiological Parameters on Hardened Cement Pastes with Coal Fly Ash

Materials ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 475
Author(s):  
Ana María Moreno de los Reyes ◽  
José Antonio Suárez-Navarro ◽  
Maria del Mar Alonso ◽  
Catalina Gascó ◽  
Isabel Sobrados ◽  
...  
Keyword(s):  
Fly Ash ◽  
Activity Concentration ◽  
Gamma Ray ◽  
Coal Fly Ash ◽  
Cementitious Materials ◽  
New Method ◽  
Supplementary Cementitious Materials ◽  
Hardened Cement ◽  
Cement Pastes ◽  
Activity Concentrations

Supplementary cementitious materials (SCMs) in industrial waste and by-products are routinely used to mitigate the adverse environmental effects of, and lower the energy consumption associated with, ordinary Portland cement (OPC) manufacture. Many such SCMs, such as type F coal fly ash (FA), are naturally occurring radioactive materials (NORMs). 226Ra, 232Th and 40K radionuclide activity concentration, information needed to determine what is known as the gamma-ray activity concentration index (ACI), is normally collected from ground cement samples. The present study aims to validate a new method for calculating the ACI from measurements made on unground 5 cm cubic specimens. Mechanical, mineralogical and radiological characterisation of 28-day OPC + FA pastes (bearing up to 30 wt % FA) were characterised to determine their mechanical, mineralogical and radiological properties. The activity concentrations found for 226Ra, 212Pb, 232Th and 40K in hardened, intact 5 cm cubic specimens were also statistically equal to the theoretically calculated values and to the same materials when ground to a powder. These findings consequently validated the new method. The possibility of determining the activity concentrations needed to establish the ACI for cement-based materials on unground samples introduces a new field of radiological research on actual cement, mortar and concrete materials.

scholarly journals Dissolved and particulate nutrient transport dynamics of a small Irish catchment: the River Owenabue

2014 ◽  
Vol 18 (6) ◽  
pp. 2191-2200 ◽  
Author(s):  
S. T. Harrington ◽  
J. R. Harrington
Keyword(s):  
Suspended Sediment ◽  
Water Discharge ◽  
Nutrient Transport ◽  
Sediment Concentration ◽  
Coefficient Of Determination ◽  
Available Phosphorus ◽  
Nitrogen And Phosphorus ◽  
Particulate Nitrogen ◽  
Monitoring Period ◽  
Nitrogen Concentrations

Abstract. The objective of this research was to investigate the relationship between water and sediment discharge on the transport of nutrients: nitrogen and phosphorus. Water discharge, suspended sediment concentration and dissolved and particulate forms of nitrogen and phosphorus were monitored on the 105 km2 River Owenabue catchment in Ireland. Water discharge was found to have an influence on both particulate and dissolved nutrient transport, but more so for particulate nutrients. The particulate portion of N and P in collected samples was found to be 24 and 39%, respectively. Increased particulate nitrogen concentrations were found at the onset of high discharge events, but did not correlate well to discharge. High concentrations of phosphorus were associated with increased discharge rates and the coefficient of determination (r2) between most forms of phosphorus and both discharge and suspended sediment concentrations were observed to be greater than 0.5. The mean TN yield is 4004 kg km−2 yr−1 for the full 29-month monitoring period with a mean PN yield of 982 kg km−2 yr−1, 25% of the TN yield with the contribution to the yield of PN and PP estimated to be 25 and 53% respectively. These yields represent a PN and PP contribution to the suspended sediment load of 5.6 and 0.28% respectively for the monitoring period. While total nitrogen and total phosphorus levels were similar to other European catchments, levels of bio-available phosphorus were elevated indicating a potential risk of eutrophication within the river.

scholarly journals Pertinent spatio-temporal scale of observation to understand suspended sediment yield control factors in the Andean region: the case of the Santa River (Peru)

2013 ◽  
Vol 17 (11) ◽  
pp. 4641-4657 ◽  
Author(s):  
S. B. Morera ◽  
T. Condom ◽  
P. Vauchel ◽  
J.-L. Guyot ◽  
C. Galvez ◽  
...  
Keyword(s):  
Suspended Sediment ◽  
Spatial Data ◽  
Sediment Yield ◽  
Water Discharge ◽  
Daily Rainfall ◽  
Sediment Concentration ◽  
Suspended Sediment Yield ◽  
Control Factors ◽  
Daily Water ◽  
Spatio Temporal

Abstract. Hydro-sedimentology development is a great challenge in Peru due to limited data as well as sparse and confidential information. This study aimed to quantify and to understand the suspended sediment yield from the west-central Andes Mountains and to identify the main erosion-control factors and their relevance. The Tablachaca River (3132 km2) and the Santa River (6815 km2), located in two adjacent Andes catchments, showed similar statistical daily rainfall and discharge variability but large differences in specific suspended-sediment yield (SSY). In order to investigate the main erosion factors, daily water discharge and suspended sediment concentration (SSC) datasets of the Santa and Tablachaca rivers were analysed. Mining activity in specific lithologies was identified as the major factor that controls the high SSY of the Tablachaca (2204 t km2 yr−1), which is four times greater than the Santa's SSY. These results show that the analysis of control factors of regional SSY at the Andes scale should be done carefully. Indeed, spatial data at kilometric scale and also daily water discharge and SSC time series are needed to define the main erosion factors along the entire Andean range.

scholarly journals Artificial Neural Network Model for Estimation of Suspended Sediment Load in Krishna River Basin, India

2020 ◽  
Vol 9 (3) ◽  
pp. 3701-3705
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Water Level ◽  
Suspended Sediment ◽  
River Basin ◽  
Flood Control ◽  
Sediment Load ◽  
Water Discharge ◽  
Suspended Sediment Load ◽  
Artificial Neural

The correct assessment of amount of sediment during design, management and operation of water resources projects is very important. Efficiency of dam has been reduced due to sedimentation which is built for flood control, irrigation, power generation etc. There are traditional methods for the estimation of sediment are available but these cannot provide the accurate results because of involvement of very complex variables and processes. One of the best suitable artificial intelligence technique for modeling this phenomenon is artificial neural network (ANN). In the current study ANN techniques used for simulation monthly suspended sediment load at Vijayawada gauging station in Krishna river basin, Andhra Pradesh, India. Trial & error method were used during the optimization of parameters that are involved in this model. Estimation of suspended sediment load (SSL) is done using water discharge and water level data as inputs. The water discharge, water level and sediment load is collected from January 1966 to December 2005. This approach is used for modelled the SSL. By considering the results, ANN has the satisfactory performance and more accurate results in the simulation of monthly SSL for the study location.

Sign in / Sign up

Export Citation Format

Share Document