scholarly journals Evolution of low flows in Czechia revisited

2015 ◽  
Vol 369 ◽  
pp. 87-95 ◽  
Author(s):  
O. Ledvinka
Keyword(s):  
Trend Analysis ◽  
Autoregressive Process ◽  
Kendall Test ◽  
Test Statistic ◽  
Memory Processes ◽  
Low Flows ◽  
Long Memory Processes ◽  
In Series ◽  
Short Memory ◽  
First Time

Abstract. Although a nationwide study focusing on the evolution of low flows in Czechia was conducted in the past, a need for the revision of the results has arisen. By means of the trend analysis, which specifically considers the presence of significant serial correlation at the first lag, the former study highlighted areas where 7-day low flows increase or decrease. However, taking into account only the lag-one autoregressive process might still have led to the detection of so-called pseudo-trends because, besides short-term persistence, also long-term persistence may adversely influence the variance of the test statistic when the independence among data is required. Therefore, one should carefully investigate the presence of persistence in time series. Before the trend analysis itself, the authors' previous studies aimed at the discrimination between short memory processes and long memory processes employing jointly the Phillips–Perron test and the Kwiatkowski–Phillips–Schmidt–Shin test. This analysis was accompanied by the Hurst exponent estimation. Here, the subsequent identification of trends is carried out using three modifications of the Mann–Kendall test that allow different kinds of persistence. These include the Bayley–Hammersley–Matalas–Langbein–Lettenmaier equivalent sample size approach, the trend-free pre-whitening approach and a block bootstrap with automatic selection of the block length, which was applied for the first time in hydrology. The general results are similar to those presented in the former study on trends. Nevertheless, the divergent minimum discharges evolution in the western part of Czechia is now much clear. Moreover, no significant increasing trend in series incorporating Julian days was found.

scholarly journals Trends in the Maximum, Mean, and Low Flows of Turkish Rivers

2005 ◽  
Vol 6 (3) ◽  
pp. 280-290 ◽  
Author(s):  
H. K. Cigizoglu ◽  
M. Bayazit ◽  
B. Önöz
Keyword(s):  
Trend Analysis ◽  
Kendall Test ◽  
T Test ◽  
Precipitation Trend ◽  
Annual Maximum ◽  
Low Flows ◽  
Time Period ◽  
Southern Turkey ◽  
The Mean ◽  
Maximum Flows

Abstract In this study the existence of trend in maximum, mean, and low flows of Turkish rivers has been investigated. The data consisted of the daily mean flows of nearly 100 flow stations in 24 hydrological regions of Turkey. Trend analysis has been carried out using the parametric t test and nonparametric τ (Mann–Kendall) test. Both tests have been applied to annual maximum, mean, 1-day, and 7-day low flows. Trend existence was detected in the majority of rivers in western and southern Turkey and in some parts of central and eastern Turkey. Trends in mean and low flows were more common compared with maximum flows. Except at a few stations, flows showed a decreasing trend. In the time period of the last 30–60 yr, statistically significant decrease was found especially in the mean and low flows (and in some of the maximum flows) in western, central, and southern parts of Turkey. Such trends were not observed in other regions. These results are in agreement with those of the precipitation trend studies in Turkey.

scholarly journals MEMORY PARAMETER ESTIMATION IN THE PRESENCE OF LEVEL SHIFTS AND DETERMINISTIC TRENDS

2013 ◽  
Vol 29 (6) ◽  
pp. 1196-1237 ◽  
Author(s):  
Adam Mccloskey ◽  
Pierre Perron
Keyword(s):  
Time Series ◽  
Long Memory ◽  
Level Shift ◽  
Finite Sample ◽  
Memory Processes ◽  
Trade Offs ◽  
Level Shifts ◽  
Long Memory Processes ◽  
Short Memory ◽  
Memory Parameter

We propose estimators of the memory parameter of a time series that are robust to a wide variety of random level shift processes, deterministic level shifts, and deterministic time trends. The estimators are simple trimmed versions of the popular log-periodogram regression estimator that employ certain sample-size-dependent and, in some cases, data-dependent trimmings that discard low-frequency components. We also show that a previously developed trimmed local Whittle estimator is robust to the same forms of data contamination. Regardless of whether the underlying long- or short-memory process is contaminated by level shifts or deterministic trends, the estimators are consistent and asymptotically normal with the same limiting variance as their standard untrimmed counterparts. Simulations show that the trimmed estimators perform their intended purpose quite well, substantially decreasing both finite-sample bias and root mean-squared error in the presence of these contaminating components. Furthermore, we assess the trade-offs involved with their use when such components are not present but the underlying process exhibits strong short-memory dynamics or is contaminated by noise. To balance the potential finite-sample biases involved in estimating the memory parameter, we recommend a particular adaptive version of the trimmed log-periodogram estimator that performs well in a wide variety of circumstances. We apply the estimators to stock market volatility data to find that various time series typically thought to be long-memory processes actually appear to be short- or very weak long-memory processes contaminated by level shifts or deterministic trends.

DEVELOPMENT OF STREAMFLOW DROUGHT INDICES IN THE MORAVA RIVER BASIN

2020 ◽  
Author(s):  
Ondrej Ledvinka ◽  
◽  
Pavel Coufal ◽  
Keyword(s):  
Time Series ◽  
Kendall Test ◽  
Drought Indices ◽  
Drought Period ◽  
Left Hand ◽  
Low Flows ◽  
Current Period ◽  
Catchment Size ◽  
Morava River ◽  
The Stability

The territory of Czechia currently suffers from a long-lasting drought period which has been a subject of many studies, including the hydrological ones. Previous works indicated that the basin of the Morava River, a left-hand tributary of the Danube, is very prone to the occurrence of dry spells. It also applies to the development of various hydrological time series that often show decreases in the amount of available water. The purpose of this contribution is to extend the results of studies performed earlier and, using the most updated daily time series of discharge, to look at the situation of the so-called streamflow drought within the basin. 46 water-gauging stations representing the rivers of diverse catchment size were selected where no or a very weak anthropogenic influences are expected and the stability and sensitivity of profiles allow for the proper measurement of low flows. The selected series had to cover the most current period 1981-2018 but they could be much longer, which was considered beneficial for the next determination of the development direction. Various series of drought indices were derived from the original discharge series. Specifically, 7-, 15- and 30-day low flows together with deficit volumes and their durations were tested for trends using the modifications of the Mann– Kendall test that account for short-term and long-term persistence. In order to better reflect the drivers of streamflow drought, the indices were considered for summer and winter seasons separately as well. The places with the situation critical to the future water resources management were highlighted where substantial changes in river regime occur probably due to climate factors. Finally, the current drought episode that started in 2014 was put into a wider context, making use of the information obtained by the analyses.

scholarly journals All-inorganic perovskite quantum dot light-emitting memories

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Meng-Cheng Yen ◽  
Chia-Jung Lee ◽  
Kang-Hsiang Liu ◽  
Yi Peng ◽  
Junfu Leng ◽  
...  
Keyword(s):  
Random Access ◽  
Optoelectronic Device ◽  
Resistive Random Access Memory ◽  
Access Memory ◽  
Light Emitting ◽  
Inorganic Perovskite ◽  
Emission Color ◽  
Perovskite Quantum Dots ◽  
In Series ◽  
First Time

AbstractField-induced ionic motions in all-inorganic CsPbBr3 perovskite quantum dots (QDs) strongly dictate not only their electro-optical characteristics but also the ultimate optoelectronic device performance. Here, we show that the functionality of a single Ag/CsPbBr3/ITO device can be actively switched on a sub-millisecond scale from a resistive random-access memory (RRAM) to a light-emitting electrochemical cell (LEC), or vice versa, by simply modulating its bias polarity. We then realize for the first time a fast, all-perovskite light-emitting memory (LEM) operating at 5 kHz by pairing such two identical devices in series, in which one functions as an RRAM to electrically read the encoded data while the other simultaneously as an LEC for a parallel, non-contact optical reading. We further show that the digital status of the LEM can be perceived in real time from its emission color. Our work opens up a completely new horizon for more advanced all-inorganic perovskite optoelectronic technologies.

scholarly journals A harmonically weighted filter for cyclical long memory processes

2021 ◽  
Author(s):  
Federico Maddanu
Keyword(s):  
Spectral Density ◽  
Long Memory ◽  
Convergence In Probability ◽  
Simulation Methods ◽  
Integrated Process ◽  
Paleoclimatic Data ◽  
Memory Time ◽  
Long Memory Processes ◽  
Short Memory ◽  
Memory Parameter

AbstractThe estimation of the long memory parameter d is a widely discussed issue in the literature. The harmonically weighted (HW) process was recently introduced for long memory time series with an unbounded spectral density at the origin. In contrast to the most famous fractionally integrated process, the HW approach does not require the estimation of the d parameter, but it may be just as able to capture long memory as the fractionally integrated model, if the sample size is not too large. Our contribution is a generalization of the HW model, denominated the Generalized harmonically weighted (GHW) process, which allows for an unbounded spectral density at $$k \ge 1$$ k ≥ 1 frequencies away from the origin. The convergence in probability of the Whittle estimator is provided for the GHW process, along with a discussion on simulation methods. Fit and forecast performances are evaluated via an empirical application on paleoclimatic data. Our main conclusion is that the above generalization is able to model long memory, as well as its classical competitor, the fractionally differenced Gegenbauer process, does. In addition, the GHW process does not require the estimation of the memory parameter, simplifying the issue of how to disentangle long memory from a (moderately persistent) short memory component. This leads to a clear advantage of our formulation over the fractional long memory approach.

scholarly journals Trend analysis of water quality parameters for the Nisava river

2013 ◽  
Vol 11 (3) ◽  
pp. 199-210 ◽  
Author(s):  
Milan Gocic ◽  
Slavisa Trajkovic
Keyword(s):  
Water Quality ◽  
Trend Analysis ◽  
Kendall Test ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Total Hardness ◽  
Significance Level ◽  
Annual Series ◽  
Annual Time Series ◽  
Annual Time

The data of 12 water quality parameters have been daily monitored at the Nis station on the Nisava River during 2000-2004. The trend analysis was performed on monthly, seasonal and annual time series using the Mann-Kendall test, the Spearman?s Rho test and the linear regression at the 5% significance level. The monthly results showed that significant trends were found only in pH, total hardness, Ca and SO4 data. The results in seasonal series indicated that the significant trends were detected in pH, total hardness, Cl, Ca and SO4 data. In annual series, the trends were insignificant at the 5% significance level.

Statistics for Long-Memory Processes

Technometrics ◽  
1997 ◽  
Vol 39 (1) ◽  
pp. 105-106
Author(s):  
Jeffrey Glosup
Keyword(s):  
Long Memory ◽  
Memory Processes ◽  
Long Memory Processes
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