Characteristics of sediment loads in Ontario streams

1988 ◽  
Vol 15 (6) ◽  
pp. 1067-1079 ◽  
Author(s):  
W. T. Dickinson ◽  
D. R. Green
Keyword(s):  
Suspended Sediment ◽  
Extreme Events ◽  
Surface Soil ◽  
Extreme Values ◽  
Seasonal Pattern ◽  
Soil Conditions ◽  
Rill Erosion ◽  
Spring Period ◽  
Annual Peak ◽  
Sediment Loads

This study has involved a literature review and data analysis regarding suspended stream sediments in southern Ontario, highlighting knowledge and identifying gaps with reference to stream loadings, seasonal and areal variability, extreme events, sources of sediments, and sediment and water quality. The quantity of sediment transported in Ontario streams is generally not of major proportion or of major significance. Daily loads follow a distinctive seasonal pattern, the bulk being transported during the spring period; and sediment transport in the province is an event-oriented process, a large percentage of the load moving in a small percentage of time. Extreme events transport a significant portion of the total suspended load, but so also do annual peak events. The bulk of the load emanates from sheet and rill erosion in cropland areas, and areal variability in loads can be related to land use and surface soil conditions. Suspended sediment has been documented to be both a pollutant carrier or source of contamination and a sink or trap for pollutants such as phosphorus, organic compounds, pesticides, and heavy metals. Key words: suspended sediment, loads, temporal patterns, areal variability, extreme values, sources.

POWER LAW AND STRETCHED EXPONENTIAL EFFECTS OF EXTREME EVENTS IN CHINESE STOCK MARKETS

2010 ◽  
Vol 09 (02) ◽  
pp. 203-217 ◽  
Author(s):  
XIAOJUN ZHAO ◽  
PENGJIAN SHANG ◽  
YULEI PANG
Keyword(s):  
Correlation Analysis ◽  
Power Law ◽  
Extreme Events ◽  
Stock Markets ◽  
Cross Correlation ◽  
Extreme Values ◽  
Cumulative Distribution ◽  
Stretched Exponential ◽  
Cross Correlation Analysis ◽  
Chinese Stock Markets

This paper reports the statistics of extreme values and positions of extreme events in Chinese stock markets. An extreme event is defined as the event exceeding a certain threshold of normalized logarithmic return. Extreme values follow a piecewise function or a power law distribution determined by the threshold due to a crossover. Extreme positions are studied by return intervals of extreme events, and it is found that return intervals yield a stretched exponential function. According to correlation analysis, extreme values and return intervals are weakly correlated and the correlation decreases with increasing threshold. No long-term cross-correlation exists by using the detrended cross-correlation analysis (DCCA) method. We successfully introduce a modification specific to the correlation and derive the joint cumulative distribution of extreme values and return intervals at 95% confidence level.

scholarly journals Daily precipitation records over mainland Spain and the Balearic Islands

2013 ◽  
Vol 13 (10) ◽  
pp. 2483-2491 ◽  
Author(s):  
C. Ramis ◽  
V. Homar ◽  
A. Amengual ◽  
R. Romero ◽  
S. Alonso
Keyword(s):  
Extreme Events ◽  
Extreme Values ◽  
Daily Rainfall ◽  
Rain Gauge ◽  
Balearic Islands ◽  
Precipitation Event ◽  
Similar Distribution ◽  
Major Interest ◽  
Precipitation Records ◽  
Different Characteristics

Abstract. Understanding the spatial distribution of extreme precipitations is of major interest in order to improve our knowledge of the climate of a region and its relationship with society. These analyses inevitably require the use of directly observed values to account for the actual extreme amounts rather than analyzed gridded values. A study of daily rainfall extremes observed over mainland Spain and the Balearic Islands is performed by using records from 8135 rain gauge stations from the Spanish Weather Agency (AEMET). Results show that the heaviest daily precipitations have been observed mainly on the coastal Mediterranean zone from Gibraltar to the Pyrenees. In particular, a record value of 817 mm was recorded in the Valencia region in 1987. The current map of daily records in Spain, which updates the pioneering work of the Spanish meteorologist Font, shows similar distribution of extreme events but with notably higher amounts. Generalized extreme values distributions fit the Mediterranean and Atlantic rain gauge measurements and shows the different characteristics of the extreme daily precipitations in both regions. We identify the most extreme events (above 500 mm per day) and provide a brief description of a typical meteorological situation in which these damaging events occur. An analysis of the low-level circulation patterns producing such extremes – by means of simple indices such as NAO, WeMOi and IBEI – confirms the relevance of local flows in the generation of either Mediterranean or Atlantic episodes. WeMOi, and even more IBEI, are good discriminants of the region affected by the record precipitation event.

scholarly journals Analyses of suspended sediment loads in Slovenian rivers

2016 ◽  
Vol 61 (6) ◽  
pp. 1094-1108 ◽  
Author(s):  
Nejc Bezak ◽  
Mojca Šraj ◽  
Matjaž Mikoš
Keyword(s):  
Suspended Sediment ◽  
Sediment Loads

scholarly journals Curvas-chave de descargas de sedimentos em suspensão no Baixo São Francisco

2020 ◽  
Vol 13 (3) ◽  
pp. 1248 ◽  
Author(s):  
Solange Cavalcanti de Melo ◽  
José Coelho de Araújo Filho ◽  
Renata Maria Caminha Mendes de Oliveira Carvalho
Keyword(s):  
Suspended Sediment ◽  
Suspended Sediment Concentration ◽  
Suspended Sediments ◽  
Sediment Concentration ◽  
Gradual Reduction ◽  
Sao Francisco River ◽  
Sediment Loads ◽  
São Francisco River ◽  
Historical Series ◽  
Suspended Sediment Concentrations

RESUMOO conhecimento da análise quantitativa das concentrações de sedimentos em suspensão transportados pelo rio São Francisco bem como sua relação com as vazões é de muita importância, pois pode auxiliar na identificação dos efeitos da intervenção humana e ou ocasionados pelas condições naturais da região. As regiões a jusante dos barramentos no rio São Francisco apresentam como principal consequência a regularização das vazões e a diminuição das concentrações de sedimentos. O objetivo da pesquisa foi determinar as curvas-chave de sedimentos em suspensão (CCS) nas estações fluviométricas instaladas no Baixo São Francisco (BSF) após a barragem de Xingó. Para o estabelecimento dessas curvas foram utilizados dados de vazão e concentração de sedimentos em suspensão, obtidos do sistema Hidroweb no site da Agência Nacional da Água (ANA) no período de 1999 a 2018. Foram obtidas CCS para todo o trecho do BSF as quais apresentaram bons coeficientes de determinação. Na análise dos dados também foi possível perceber que nos últimos anos, desde 2013 houve redução gradativa das vazões disponibilizadas na barragem de Xingó. Consequentemente, houve também a redução gradativa das cargas de sedimentos em suspensão geradas nas estações de Piranhas, Traipu e Propriá, ou seja, os menores valores já registrados no BSF correspondendo as menores séries históricas tanto de vazão como de sedimentos em suspensão.  Keys curves of sediment discharges in suspension in the Lower São Francisco A B S T R A C TThe knowledge of the quantitative analysis of suspended sediment concentrations carried by the São Francisco River as well as its relation with the flows is of great importance, since it can help in the identification of the effects of human intervention and/or caused by the natural conditions of the region. In the downstream regions of the São Francisco riverbanks, the main consequence was the regularization of flow rates and the reduction of sediment concentrations. The objective of the research was to determine the key curves of suspended sediments (CCS) at the fluviometric stations installed in the lower São Francisco river after Xingó dam. For the evaluation, flow data and suspended sediment concentration were used. These data were obtained from the Hidroweb system on the website of the National Water Agency (ANA) from 1999 to 2018. CCS were plotted for all stretches and presented good coefficients of determination (R2). Based on the analysis of the data it was also possible to notice that in recent years, since 2013 there has been a gradual reduction of the flows available in the Xingó dam. Consequently, there was also a gradual reduction of suspended sediment loads generated at the Piranhas, Traipu and Propriá stations, that is, the lowest values already recorded in lower São Francisco, corresponding to the lower historical series of both discharge and suspended sediments.Keywords: dam, flow, sediments 

scholarly journals Using machine learning to predict extreme events in complex systems

2019 ◽  
Vol 117 (1) ◽  
pp. 52-59 ◽  
Author(s):  
Di Qi ◽  
Andrew J. Majda
Keyword(s):  
Dynamical Systems ◽  
Learning Strategies ◽  
Extreme Events ◽  
Water Waves ◽  
Extreme Values ◽  
Training Data ◽  
Partition Functions ◽  
Grand Challenge ◽  
Natural Systems ◽  
Using Data

Extreme events and the related anomalous statistics are ubiquitously observed in many natural systems, and the development of efficient methods to understand and accurately predict such representative features remains a grand challenge. Here, we investigate the skill of deep learning strategies in the prediction of extreme events in complex turbulent dynamical systems. Deep neural networks have been successfully applied to many imaging processing problems involving big data, and have recently shown potential for the study of dynamical systems. We propose to use a densely connected mixed-scale network model to capture the extreme events appearing in a truncated Korteweg–de Vries (tKdV) statistical framework, which creates anomalous skewed distributions consistent with recent laboratory experiments for shallow water waves across an abrupt depth change, where a remarkable statistical phase transition is generated by varying the inverse temperature parameter in the corresponding Gibbs invariant measures. The neural network is trained using data without knowing the explicit model dynamics, and the training data are only drawn from the near-Gaussian regime of the tKdV model solutions without the occurrence of large extreme values. A relative entropy loss function, together with empirical partition functions, is proposed for measuring the accuracy of the network output where the dominant structures in the turbulent field are emphasized. The optimized network is shown to gain uniformly high skill in accurately predicting the solutions in a wide variety of statistical regimes, including highly skewed extreme events. The technique is promising to be further applied to other complicated high-dimensional systems.

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