scholarly journals Method Consideration of Variation Diagnosis and Design Value Calculation of Flood Sequence in Yiluo River Basin, China

Water ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 2722
Author(s):  
Xinxin Li ◽  
Xixia Ma ◽  
Xiaodong Li ◽  
Wenjiang Zhang
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Human Activities ◽  
Extreme Values ◽  
Frequency Estimation ◽  
Synthesis Method ◽  
Estimation Method ◽  
Stationary Time Series ◽  
Distribution Model ◽  
Design Flood

The conventional approaches of the design flood calculation are based on the assumption that the hydrological time series is subject to the same distribution in the past, present, and future, i.e., the series should be consistent. However, the traditional methods may result in overdesign in the water conservancy project since the series has non-stationary variations due to climate change and human activities. Therefore, it is necessary to develop a new approach for frequency estimation of non-stationary time series of extreme values. This study used four kinds of mutation test methods (the linear trend correlation coefficient, Mann–Kendall test, sliding t-test, and Pettitt test) to identify the trend and mutation of the annual maximum flow series (1950–2006) of three hydrological stations in the Yiluo River Basin. Then we evaluated the performance of two types of design flood methods (the time series decomposition-synthesis method, the mixed distribution model) under the impacts of climate change and human activities on hydro-meteorological conditions. The results showed that (a) the design flood value obtained by the time series decomposition-synthesis method based on the series of the backward restore is larger than that obtained by the decomposition synthesis method based on the series of the forward restore; (b) when the return period is 100 years or less, the design flood value obtained by the mixed distribution model using the capacity ratio parameter estimation method is less than that obtained by the hybrid distribution model with simulated annealing parameter estimation method; and (c) both methods can overcome sequence inconsistency in design frequencies. This study provides insight into the frequency estimation of non-stationary time series of extreme values under the impacts of climate change and human activities on hydro-meteorological conditions.

Extreme Values of Non-stationary Time Series

2021 ◽  
pp. 157-190
Author(s):  
Sylvie Parey ◽  
Thi-Thu-Huong Hoang
Keyword(s):  
Time Series ◽  
Extreme Values ◽  
Stationary Time Series ◽  
Stationary Time

scholarly journals Human and Climate Effects on the Hamoun Wetlands

2019 ◽  
Vol 11 (3) ◽  
pp. 609-622 ◽  
Author(s):  
Saeideh Maleki ◽  
Saeid Soltani Koupaei ◽  
Alireza Soffianian ◽  
Sassan Saatchi ◽  
Saeid Pourmanafi ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Time Series ◽  
Water Stress ◽  
Rural Areas ◽  
Human Activities ◽  
Large Scale ◽  
Upstream Region ◽  
Ecosystem Recovery ◽  
Climate Effects

Abstract Negative impacts of climate change on ecosystems have been increasing, and both the intensification and the mitigation of these impacts are strongly linked with human activities. Management and reduction of human-induced disturbances on ecosystems can mitigate the effects of climate change and enhance the ecosystem recovery process. Here, we investigate coupled human and climate effects on the wetland ecosystem of the lower Helmand basin from 1977 to 2014. Using time series climate-variable data and land-use changes from Landsat time series imagery, we compared changes in ecosystem status between the upstream and downstream regions. Results show that despite a strong and prolonged drought in the region, the upstream region of the lower Helmand basin remained dominated by agriculture, causing severe water stress on the Hamoun wetlands downstream. The loss of available water in wetlands was followed by large-scale land abandonment in rural areas, migration to the cities, and increasing unemployment and economic hardship. Our results suggest that unsustainable land-use policies in the upstream region, combined with synergistic effects of human activities and climate in lower Helmand basin, have exacerbated the effects of water stress on local inhabitants in the downstream region.

Relationship between heating/cooling period and changing temperature conditions in the urban areas of Hungary

2020 ◽  
Author(s):  
Csenge Dian ◽  
Attila Talamon ◽  
Rita Pongrácz ◽  
Judit Bartholy
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Energy Consumption ◽  
Extreme Values ◽  
Building Design ◽  
Temperature Time Series ◽  
Maximum Temperature ◽  
Design Parameters ◽  
Daily Average ◽  
Temperature Time

<p>Climate change, extreme weather conditions, and local scale urban heat island (UHI) effect altogether have substantial impacts on people’s health and comfort. The urban population spends most of its time in buildings, therefore, it is important to examine the relationship between weather/climate conditions and indoor environment. The role of buildings is complex in this context. On the one hand UHI effect is mostly created by buildings and artificial surfaces. On the other hand they account for about 40% of energy consumption on European average. Since environmental protection requires increased energy efficiency, the ultimate goal from this perspective is to achieve nearly zero-energy buildings. When estimating energy consumption, daily average temperatures are taken into account. The design parameters (e.g. for heating systems) are determined using temperature-based criteria. However, due to climate change, these critical values are likely to change as well. Therefore, it is important to examine the temperature time series affecting the energy consumption of buildings. For the analysis focusing on the Carpathian region within central/eastern Europe, we used the daily average, minimum and maximum temperature time series of five Hungarian cities (i.e. Budapest, Debrecen, Szeged, Pécs and Szombathely). The main aim of this study is to investigate the effect of changing daily average temperatures and the rising extreme values on building design parameters, especially heating and cooling periods (including the length and average temperatures of such periods).</p>

scholarly journals Tracking Poisson Parameter for Non-Stationary Discontinuous Time Series with Taylor’s Abnormal Fluctuation Scaling

Stats ◽  
2019 ◽  
Vol 2 (1) ◽  
pp. 55-69 ◽  
Author(s):  
Gen Sakoda ◽  
Hideki Takayasu ◽  
Misako Takayasu
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
State Space Model ◽  
Estimation Method ◽  
Stationary Time Series ◽  
Series Data ◽  
Large Fluctuations ◽  
Taylor’S Law ◽  
Fluctuation Scaling ◽  
Poisson Parameter

We propose a parameter estimation method for non-stationary Poisson time series with the abnormal fluctuation scaling, known as Taylor’s law. By introducing the effect of Taylor’s fluctuation scaling into the State Space Model with the Particle Filter, the underlying Poisson parameter’s time evolution is estimated correctly from given non-stationary time series data with abnormally large fluctuations. We also developed a discontinuity detection method which enables tracking the Poisson parameter even for time series including sudden discontinuous jumps. As an example of application of this new general method, we analyzed Point-of-Sales data in convenience stores to estimate change of probability of purchase of commodities under fluctuating number of potential customers. The effectiveness of our method for Poisson time series with non-stationarity, large discontinuities and Taylor’s fluctuation scaling is verified by artificial and actual time series.

scholarly journals Impact of Climate Change and Human Activities on Streamflow Variations Based on the Budyko Framework

Water ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 2001 ◽  
Author(s):  
Lee ◽  
Yeh
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Human Activities ◽  
Potential Evapotranspiration ◽  
Land Use Changes ◽  
Dominant Factor ◽  
Climate Factors ◽  
The Sustainable Development ◽  
Precipitation Changes ◽  
Northern Taiwan

In recent years, the influence of climate change and human activity on the global environment have become a concern. It is essential to better understand the hydrologic environment to evaluate water availability and related issues. In this study, we perform a trend and breakpoint analysis on streamflow time series in the Lanyang, Keelung, Dahan, Fengshan, Youluo and Shangping River Basins in northern Taiwan. Furthermore, we apply the Budyko–Fu equation and the Budyko–Mezentsev–Choudhury–Yang equation to evaluate the elasticity of streamflow with respect to climate factors and the catchment characteristics parameter. We discuss the sensitivity of streamflow to climate factors (precipitation and potential evapotranspiration), as well as sensitivity to human activities such as land use changes. We detected breakpoints in the streamflow time series for the Lanyang and Keelung rivers in in 1993 and 1990, respectively. The streamflow of Lanyang River increased by 32.50% during the variation period (1993–2017), with 109.00% of the variation caused by non-climate factors. The Keelung River’s streamflow was reduced by 18.11% during the variation period (1990–2017), and the dominant factor was climate change, accounting for 71.53% of the reduction. Sensitivity analysis showed that precipitation changes were the most sensitive factor of streamflow variation. For every 1% increase in precipitation, the streamflow would increase by 1.05% to 1.37%. These results could serve as a reference for the sustainable development of water resources and territorial policies in northern Taiwan.

Extreme Value Analysis of the Response of a Turret-Moored FPSO

2010 ◽  
Author(s):  
Lui´s Volnei Sudati Sagrilo ◽  
Arvid Naess ◽  
Zhen Gao
Keyword(s):  
Time Series ◽  
Extreme Values ◽  
Distribution Model ◽  
Extreme Value Analysis ◽  
Coupled Analysis ◽  
System Response ◽  
Short Term ◽  
Utilization Factor ◽  
Value Analysis ◽  
Extreme Response

One of the standardized procedures used in the design of floating systems and their mooring and production lines is the so-called short-term design approach where the system is analyzed for some specific extreme environmental conditions. Along with this procedure, a nonlinear time-domain coupled dynamic analysis, considering the floater and its risers and mooring lines, is nowadays feasible to be employed in the design practice. One important and challenging aspect of this process is concerned with the estimation of the characteristic short-term extreme values of the system response parameters based on the sampled time-series. In this paper a common procedure used to establish these extreme values for floater system response parameters, which is based on a Weibull distribution model for the time-series peaks, is reviewed in the light of a recently proposed approach based on a general parametric model for the average conditional exceedance rate of peaks. It is shown that the former model corresponds to a particular case of the latter one. Numerical results are presented for the response parameters of a turret-moored FPSO considering a short-term coupled analysis of the whole system under an extreme environmental condition of wind, wave and current. Specifically, the extreme response of surge motion, top tension of the most loaded mooring line and DnV’s utilization factor for the most critical section of a 8″ SLWR (Steel Lazy Wave Riser) are investigated.

Climate change tendencies observable in the rainfall measurements since 1950 in the Federal Land of North Rhine-Westphalia and their consequences for urban hydrology

2011 ◽  
Vol 63 (11) ◽  
pp. 2633-2640
Author(s):  
Th. Einfalt ◽  
M. Quirmbach ◽  
G. Langstädtler ◽  
B. Mehlig
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Extreme Values ◽  
Measurement Data ◽  
Urban Hydrology ◽  
Flexible Design ◽  
Precipitation Regime ◽  
The Past ◽  
Federal Land ◽  
Standard Values

Climate change is present in climatological models – but did we already observe changes in the past measurement data? For the state of North Rhine Westphalia, the rainfall measurements since 1950 have been systematically analysed in order to find out whether there have already been trends and whether the behaviour of rainfall has changed in time. More than 600 station series have been screened for use in the project and quality controlled. Implausible data were discarded. For the analysis, standard values such as yearly sums, half-yearly sums, monthly sums, number of dry days, number of days with precipitation above a threshold, partial time series and extreme values statistics have been calculated and evaluated. Results show that also in the past 50 years, changes in precipitation regime could be observed. These changes have been regionally different. Consequences for urban hydrology include a development of more flexible design approaches.

scholarly journals Multidimensional extremes: joint study of precipitation and temperature time series

2021 ◽  
Author(s):  
Beatrix Izsák ◽  
Tamás Szentimrey ◽  
Mónika Lakatos ◽  
Rita Pongrácz
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Extreme Values ◽  
Standardized Precipitation Index ◽  
Single Element ◽  
Average Temperature ◽  
Temperature And Precipitation ◽  
The Standardized Precipitation Index ◽  
Climatic Time Series ◽  
Precipitation And Temperature

<p>To study climate change, it is essential to analyze extremes as well. The study of extremes can be done on the one hand by examining the time series of extreme climatic events and on the other hand by examining the extremes of climatic time series. In the latter case, if we analyze a single element, the extreme is the maximum or minimum of the given time series. In the present study, we determine the extreme values of climatic time series by examining several meteorological elements together and thus determining the extremes. In general, the main difficulties are connected with the different probability distribution of the variables and the handling of the stochastic connection between them. The first issue can be solved by the standardization procedures, i.e. to transform the variables into standard normal ones. For example, the Standardized Precipitation Index (SPI) uses precipitation sums assuming gamma distribution, or the standardization of temperature series assumes normal distribution. In case of more variables, the problem of stochastic connection can be solved on the basis of the vector norm of the variables defined by their covariance matrix. According to this methodology we have developed a new index in order to examine the precipitation and temperature variables jointly. We present the new index with the mathematical background, furthermore some examples for spatio-temporal examination of these indices using our software MASH (Multiple Analysis of Series for Homogenization; Szentimrey) and MISH (Meteorological Interpolation based on Surface Homogenized Data Basis; Szentimrey, Bihari). For our study, we used the daily average temperature and precipitation time series in Hungary for the period 1870-2020. First of all, our analyses indicate that even though some years may not be considered extreme if only either precipitation or average temperature is taken in to account, but examining the two elements together these years were extreme years indeed. Based on these, therefore, the study of the extremes of multidimensional climate time series complements and thus makes the study of climate change more efficient compared to examining only one-dimensional time series.</p>

scholarly journals Analyzing the Impact of Climate Change and Human Activities on Surface Runoff in the Changbai Mountain Area, Northeast China

Water ◽  
2021 ◽  
Vol 13 (23) ◽  
pp. 3473
Author(s):  
Shanjun Zhang ◽  
Jia Liu ◽  
Chuanzhe Li ◽  
Fuliang Yu ◽  
Lanshu Jing ◽  
...  
Keyword(s):  
Climate Change ◽  
Time Series ◽  
River Basin ◽  
Human Activities ◽  
Surface Runoff ◽  
Northeast China ◽  
Changbai Mountain ◽  
Mountain Area ◽  
Mountainous Regions ◽  
Runoff Changes

Climate change and human activities are two important factors affecting surface runoff. In water resource management and planning, it is generally important to separate the contribution of these factors when assessing runoff changes. The Changbai Mountain area is rich in water resources and is an important hydropower energy base for Northeast China. This study used Sen’s slope estimator to explore trends in runoff precipitation and evapotranspiration from 1960 to 2016, and the results showed a downward trend in runoff and an upward trend in precipitation and evaporation in most areas. The mutation point of the annual time series for the observed runoff was estimated, and the time series was divided into the base period (1960–1975) and impact period (1976–2016). Based on the Budyko framework, we performed attribution analysis of the runoff changes, and analyzed the difference between the mountainous region and the whole basin. We determined that the impacts of climate change and human activities, on average, accounted for decreases in the runoff by 60.15% and 39.85%, respectively, for the Second Songhua River Basin; 73.74% and 26.26%, respectively, for the Tumen River Basin; 84.76% and 15.24%, respectively, for the Yalu River Basin; human activities were the main causes of runoff changes in the Changbai Mountain area; climate change was the main cause of runoff changes in mountainous regions. The results of this study show that the reasons for the change in runoff in mountainous regions and the whole basin in the same area are different, which has some illuminating significance for water resources management of different elevation areas.

scholarly journals Nonparametric and parametric methods of spectral analysis

2019 ◽  
Vol 283 ◽  
pp. 07002 ◽  
Author(s):  
Hangfang Zhao ◽  
Lin Gui
Keyword(s):  
Time Series ◽  
Spectral Analysis ◽  
High Resolution ◽  
Spectral Estimation ◽  
Estimation Method ◽  
Parametric Estimation ◽  
Stationary Time Series ◽  
Estimation Methods ◽  
Practical Applications ◽  
Small Variance

Spectral Analysis is one of the most important methods in signal processing. In practical application, it is critical to discuss the power spectral density estimation of finite data sampled from some stationary time series. A spectral estimator is expected to have good statistical properties such as consistency, high resolution and small variance. For one spectral estimation method, there exists a trade-off between high resolution and small variance. The paper provides a comparison of several popular spectral methods from both theoretical properties and practical applications. We first address several basic nonparametric methods, whose statistical characters are analysed. Then we explain the connections and differences between temporal windowing and lag windowing. Thereafter, the confidence intervals of both windows are given and used to evaluate the estimated results. Besides, several different parametric estimation methods of autoregressive time series are compared, and whose properties and effects are also introduced. Building on our understanding of these studies, we then apply parametric and nonparametric spectral estimation methods on the data of ocean surface wave height.

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