scholarly journals Combined risk assessment of nonstationary monthly water quality based on Markov chain and time-varying copula

2016 ◽  
Vol 75 (3) ◽  
pp. 693-704 ◽  
Author(s):  
Wei Shi ◽  
Jun Xia
Keyword(s):  
Water Quality ◽  
Land Cover ◽  
Marginal Distribution ◽  
Dependence Structure ◽  
Time Varying ◽  
Class V ◽  
Marginal Distributions ◽  
Huai River ◽  
Risk Probability ◽  
Class Iv

Water quality risk management is a global hot research linkage with the sustainable water resource development. Ammonium nitrogen (NH3-N) and permanganate index (CODMn) as the focus indicators in Huai River Basin, are selected to reveal their joint transition laws based on Markov theory. The time-varying moments model with either time or land cover index as explanatory variables is applied to build the time-varying marginal distributions of water quality time series. Time-varying copula model, which takes the non-stationarity in the marginal distribution and/or the time variation in dependence structure between water quality series into consideration, is constructed to describe a bivariate frequency analysis for NH3-N and CODMn series at the same monitoring gauge. The larger first-order Markov joint transition probability indicates water quality state Class Vw, Class IV and Class III will occur easily in the water body of Bengbu Sluice. Both marginal distribution and copula models are nonstationary, and the explanatory variable time yields better performance than land cover index in describing the non-stationarities in the marginal distributions. In modelling the dependence structure changes, time-varying copula has a better fitting performance than the copula with the constant or the time-trend dependence parameter. The largest synchronous encounter risk probability of NH3-N and CODMn simultaneously reaching Class V is 50.61%, while the asynchronous encounter risk probability is largest when NH3-N and CODMn is inferior to class V and class IV water quality standards, respectively.

scholarly journals Multivariate hydrologic design methods under nonstationary conditions and application to engineering practice

2019 ◽  
Vol 23 (3) ◽  
pp. 1683-1704 ◽  
Author(s):  
Cong Jiang ◽  
Lihua Xiong ◽  
Lei Yan ◽  
Jianfan Dong ◽  
Chong-Yu Xu
Keyword(s):  
Return Period ◽  
Flood Event ◽  
Exceedance Probability ◽  
Dependence Structure ◽  
Engineering Practice ◽  
Time Varying ◽  
Marginal Distributions ◽  
Hydrologic Design ◽  
The Given ◽  
Nonstationary Conditions

Abstract. Multivariate hydrologic design under stationary conditions is traditionally performed through the use of the design criterion of the return period, which is theoretically equal to the average inter-arrival time of flood events divided by the exceedance probability of the design flood event. Under nonstationary conditions, the exceedance probability of a given multivariate flood event varies over time. This suggests that the traditional return-period concept cannot apply to engineering practice under nonstationary conditions, since by such a definition, a given multivariate flood event would correspond to a time-varying return period. In this paper, average annual reliability (AAR) was employed as the criterion for multivariate design rather than the return period to ensure that a given multivariate flood event corresponded to a unique design level under nonstationary conditions. The multivariate hydrologic design conditioned on the given AAR was estimated from the nonstationary multivariate flood distribution constructed by a dynamic C-vine copula, allowing for time-varying marginal distributions and a time-varying dependence structure. Both the most-likely design event and confidence interval for the multivariate hydrologic design conditioned on the given AAR were identified to provide supporting information for designers. The multivariate flood series from the Xijiang River, China, were chosen as a case study. The results indicated that both the marginal distributions and dependence structure of the multivariate flood series were nonstationary due to the driving forces of urbanization and reservoir regulation. The nonstationarities of both the marginal distributions and dependence structure were found to affect the outcome of the multivariate hydrologic design.

scholarly journals Multivariate hydrologic design methods under nonstationary conditions and application to engineering practice

2018 ◽  
Author(s):  
Cong Jiang ◽  
Lihua Xiong ◽  
Lei Yan ◽  
Jianfan Dong ◽  
Chong-Yu Xu
Keyword(s):  
Return Period ◽  
Flood Event ◽  
Exceedance Probability ◽  
Dependence Structure ◽  
Engineering Practice ◽  
Time Varying ◽  
Marginal Distributions ◽  
Hydrologic Design ◽  
The Given ◽  
Nonstationary Conditions

Abstract. The multivariate hydrologic design under stationary condition is traditionally done through using the design criterion of return period, which theoretically equals to the average inter-arrival time of flood events divided by the exceedance probability of the design flood event. Under nonstationary conditions the exceedance probability of a given multivariate flood event would vary over time. This suggests that the traditional return period concept could not apply to the engineering practice under nonstationary conditions, since by such a definition a given multivariate flood event would correspond to a time-varying return period. In this paper, instead of return period, average annual reliability (AAR) is employed as the criterion for multivariate design, to ensure a given multivariate flood event would correspond to a unique design level under nonstationary conditions. The multivariate hydrologic design conditioned on the given ARR is estimated from the nonstationary multivariate flood distribution constructed by a dynamic C-vine copula, allowing for time-varying marginal distributions and dependence structure. Both the most-likely design event and confidence interval for the multivariate hydrologic design conditioned on the given AAR are identified to provide visual supporting information for designers. The multivariate flood series from the Xijiang River, China are chosen to perform a case study. The results indicate that both the marginal distributions and dependence structure of the multivariate flood series are nonstationary due to the driving force of urbanization and reservoir regulation. The nonstationarities of both the marginal distributions and dependence structure can affect the outcome of the multivariate hydrologic design.

scholarly journals Nonstationary Analysis for Bivariate Distribution of Flood Variables in the Ganjiang River Using Time-Varying Copula

Water ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 746
Author(s):  
Tianfu Wen ◽  
Cong Jiang ◽  
Xinfa Xu
Keyword(s):  
Suspended Sediment ◽  
Flood Event ◽  
Dependence Structure ◽  
Copula Model ◽  
Time Varying ◽  
Bivariate Distributions ◽  
Marginal Distributions ◽  
The Mean ◽  
Water Stage ◽  
Dependence Structures

Nonstationarity of univariate flood series has been widely studied, while nonstationarity of some multivariate flood series, such as discharge, water stage, and suspended sediment concentrations, has been studied rarely. This paper presents a procedure for using the time-varying copula model to describe the nonstationary dependence structures of two correlated flood variables from the same flood event. In this study, we focus on multivariate flood event consisting of peak discharge (Q), peak water stage (Z) and suspended sediment load (S) during the period of 1964–2013 observed at the Waizhou station in the Ganjiang River, China. The time-varying copula model is employed to analyze bivariate distributions of two flood pairs of (Z-Q) and (Z-S). The main channel elevation (MCE) and the forest coverage rate (FCR) of the basin are introduced as the candidate explanatory variables for modelling the nonstationarities of both marginal distributions and dependence structure of copula. It is found that the marginal distributions for both Z and S are nonstationary, whereas the marginal distribution for Q is stationary. In particular, the mean of Z is related to MCE, and the mean and variance of S are related to FCR. Then, time-varying Frank copula with MCE as the covariate has the best performance in fitting the dependence structures of both Z-Q and Z-S. It is indicated that the dependence relationships are strengthen over time associated with the riverbed down-cutting. Finally, the joint and conditional probabilities of both Z-Q and Z-S obtained from the best fitted bivariate copula indicate that there are obvious nonstationarity of their bivariate distributions. This work is helpful to understand how human activities affect the bivariate flood distribution, and therefore provides supporting information for hydraulic structure designs under the changing environments.

Impact of Water Projects on River Flow Regimes and Water Quality in Huai River Basin

2009 ◽  
Vol 24 (5) ◽  
pp. 889-908 ◽  
Author(s):  
Yongyong Zhang ◽  
Jun Xia ◽  
Tao Liang ◽  
Quanxi Shao
Keyword(s):  
Water Quality ◽  
River Basin ◽  
River Flow ◽  
Flow Regimes ◽  
Water Projects ◽  
Huai River Basin ◽  
Huai River

mRNA abundance changes during flagellar regeneration in Chlamydomonas reinhardtii

1984 ◽  
Vol 4 (3) ◽  
pp. 424-434
Author(s):  
J A Schloss ◽  
C D Silflow ◽  
J L Rosenbaum
Keyword(s):  
Chlamydomonas Reinhardtii ◽  
Control Cell ◽  
Beta Tubulin ◽  
Rna Sequences ◽  
Class V ◽  
Alpha Tubulin ◽  
Flagellar Regeneration ◽  
Flagellar Proteins ◽  
Kinetics Of ◽  
Class Iv

Flagellar amputation in Chlamydomonas reinhardtii induces the accumulation of a specific set of RNAs, many of which encode flagellar proteins. We prepared a cDNA clone bank from RNA isolated from cells undergoing flagellar regeneration. From this bank, we selected clones that contain RNA sequences that display several different patterns of abundance regulation. Based on quantitation of the relative amounts of labeled, cloned cDNAs hybridizing to dots of RNA on nitrocellulose filters, the cloned sequences were divided into five regulatory classes: class I RNAs remain at constant abundance during flagellar regeneration; classes II, III, and IV begin to increase in abundance within a few minutes after deflagellation, reach maximal abundance at successively later times during regeneration, and return to control cell levels within 2 to 3 h; and class V RNA abundance decreases during flagellar regeneration. Alpha- and beta-tubulin mRNAs are included in regulatory class IV. The abundance kinetics of alpha-tubulin mRNAs differ slightly from those of beta-tubulin mRNAs. The availability of these clones makes possible studies on the mechanisms controlling the abundance of a wide variety of different RNA species during flagellar regeneration in Chlamydomonas.

A shoreline divided: Twelve-year water quality and land cover trends in Lake Ontario coastal wetlands

2017 ◽  
Vol 43 (6) ◽  
pp. 1005-1015 ◽  
Author(s):  
Melanie V. Croft-White ◽  
Maja Cvetkovic ◽  
Daniel Rokitnicki-Wojcik ◽  
Jonathan D. Midwood ◽  
Greg P. Grabas
Keyword(s):  
Water Quality ◽  
Land Cover ◽  
Coastal Wetlands ◽  
Lake Ontario

Development of Chemical Index as a Measure of In-Stream Water Quality in Response to Land-Use and Land Cover Changes

2006 ◽  
Vol 174 (1-4) ◽  
pp. 161-179 ◽  
Author(s):  
T. Tsegaye ◽  
D. Sheppard ◽  
K. R. Islam ◽  
W. Tadesse ◽  
A. Atalay ◽  
...  
Keyword(s):  
Water Quality ◽  
Land Use ◽  
Land Cover ◽  
Stream Water ◽  
Land Cover Changes ◽  
Stream Water Quality ◽  
Chemical Index
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