scholarly journals Stationarity analysis of historical flood series in France and Spain (14th–20th centuries)

2003 ◽  
Vol 3 (6) ◽  
pp. 583-592 ◽  
Author(s):  
M. Barriendos ◽  
D. Coeur ◽  
M. Lang ◽  
M. C. Llasat ◽  
R. Naulet ◽  
...  
Keyword(s):  
Land Use Planning ◽  
Temporal Trends ◽  
Critical Evaluation ◽  
Data Series ◽  
Data Generation ◽  
Flood Events ◽  
Management Of Resources ◽  
Methodological Aspects ◽  
Scientific Fields ◽  
Past 1000 Years

Abstract. Interdisciplinary frameworks for studying natural hazards and their temporal trends have an important potential in data generation for risk assessment, land use planning, and therefore the sustainable management of resources. This paper focuses on the adjustments required because of the wide variety of scientific fields involved in the reconstruction and characterisation of flood events for the past 1000 years. The aim of this paper is to describe various methodological aspects of the study of flood events in their historical dimension, including the critical evaluation of old documentary and instrumental sources, flood-event classification and hydraulic modelling, and homogeneity and quality control tests. Standardized criteria for flood classification have been defined and applied to the Isère and Drac floods in France, from 1600 to 1950, and to the Ter, the Llobregat and the Segre floods, in Spain, from 1300 to 1980. The analysis on the Drac and Isère data series from 1600 to the present day showed that extraordinary and catastrophic floods were not distributed uniformly in time. However, the largest floods (general catastrophic floods) were homogeneously distributed in time within the period 1600–1900. No major flood occurred during the 20th century in these rivers. From 1300 to the present day, no homogeneous behaviour was observed for extraordinary floods in the Spanish rivers. The largest floods were uniformly distributed in time within the period 1300–1900, for the Segre and Ter rivers.

Application de la fonction bêta et des polynômes de Jacobi à l'analyse des valeurs extrêmes

1994 ◽  
Vol 21 (6) ◽  
pp. 1074-1080 ◽  
Author(s):  
J. Llamas ◽  
C. Diaz Delgado ◽  
M.-L. Lavertu
Keyword(s):  
Frequency Estimation ◽  
Probabilistic Method ◽  
Beta Function ◽  
Real Data ◽  
Flood Frequency ◽  
Data Series ◽  
Data Generation ◽  
Practical Applications ◽  
Flood Probability ◽  
Probable Maximum Flood

In this paper, an improved probabilistic method for flood analysis using the probable maximum flood, the beta function, and orthogonal Jacobi’s polynomials is proposed. The shape of the beta function depends on the sample's characteristics and the bounds of the phenomenon. On the other hand, a serial of Jacobi’s polynomials has been used improving the beta function and increasing its convergence degree toward the real flood probability density function. This mathematical model has been tested using a sample of 1000 generated beta random data. Finally, some practical applications with real data series, from important Quebec's rivers, have been performed; the model solutions for these rivers showed the accuracy of this new method in flood frequency estimation. Key words: probable maximum flood, beta function, orthogonal polynomials, distribution function, flood frequency estimation, data generation, convergency.

scholarly journals Trend Analysis of Annual and Seasonal River Runoff by Using Innovative Trend Analysis with Significant Test

Water ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 95
Author(s):  
Yilinuer Alifujiang ◽  
Jilili Abuduwaili ◽  
Yongxiao Ge
Keyword(s):  
Time Series ◽  
Trend Analysis ◽  
River Runoff ◽  
Temporal Trends ◽  
Temporal Distribution ◽  
Trend Test ◽  
Data Series ◽  
Mk Test ◽  
Comparison Results ◽  
Innovative Trend Analysis

This study investigated the temporal patterns of annual and seasonal river runoff data at 13 hydrological stations in the Lake Issyk-Kul basin, Central Asia. The temporal trends were analyzed using the innovative trend analysis (ITA) method with significance testing. The ITA method results were compared with the Mann-Kendall (MK) trend test at a 95% confidence level. The comparison results revealed that the ITA method could effectively identify the trends detected by the MK trend test. Specifically, the MK test found that the time series percentage decreased from 46.15% in the north to 25.64% in the south, while the ITA method revealed a similar rate of decrease, from 39.2% to 29.4%. According to the temporal distribution of the MK test, significantly increasing (decreasing) trends were observed in 5 (0), 6 (2), 4 (3), 8 (0), and 8 (1) time series in annual, spring, summer, autumn, and winter river runoff data. At the same time, the ITA method detected significant trends in 7 (1), 9 (3), 6(3), 9 (3), and 8 (2) time series in the study area. As for the ITA method, the “peak” values of 24 time series (26.97%) exhibited increasing patterns, 25 time series (28.09%) displayed increasing patterns for “low” values, and 40 time series (44.94%) showed increasing patterns for “medium” values. According to the “low”, “medium”, and “peak” values, five time series (33.33%), seven time series (46.67%), and three time series (20%) manifested decreasing trends, respectively. These results detailed the patterns of annual and seasonal river runoff data series by evaluating “low”, “medium”, and “peak” values.

scholarly journals Spatial and temporal drivers of wildfire occurrence in the context of rural development in northern Wisconsin, USA

2012 ◽  
Vol 21 (2) ◽  
pp. 141 ◽  
Author(s):  
Brian R. Miranda ◽  
Brian R. Sturtevant ◽  
Susan I. Stewart ◽  
Roger B. Hammer
Keyword(s):  
Linear Regression ◽  
Land Use Planning ◽  
Temporal Trends ◽  
Point Pattern Analysis ◽  
Annual Number ◽  
Point Pattern ◽  
Linear Regression Models ◽  
Housing Density ◽  
Spatial And Temporal Scales ◽  
Wildfire Occurrence

Most drivers underlying wildfire are dynamic, but at different spatial and temporal scales. We quantified temporal and spatial trends in wildfire patterns over two spatial extents in northern Wisconsin to identify drivers and their change through time. We used spatial point pattern analysis to quantify the spatial pattern of wildfire occurrences, and linear regression to quantify the influence of drought and temporal trends in annual number and mean size of wildfires. Analyses confirmed drought as an important driver of both occurrences and fire size. When both drought and time were incorporated in linear regression models, the number of wildfires showed a declining trend across the full study area, despite housing density increasing in magnitude and spatial extent. Fires caused by campfires and debris-burning did not show any temporal trends. Comparison of spatial models representing biophysical, anthropogenic and combined factors demonstrated human influences on wildfire occurrences, especially human activity, infrastructure and property values. We also identified a non-linear relationship between housing density and wildfire occurrence. Large wildfire occurrence was predicted by similar variables to all occurrences, except the direction of influence changed. Understanding these spatial and temporal drivers of wildfire occurrence has implications for land-use planning, wildfire suppression strategies and ecological goals.

scholarly journals Spatial-temporal trends analysis of flood events in the Republic of Armenia in the context of climate change

2020 ◽  
Vol 11 (S1) ◽  
pp. 289-309 ◽  
Author(s):  
Hrachuhi Galstyan ◽  
Shamshad Khan ◽  
Hovik Sayadyan ◽  
Artur Sargsyan ◽  
Tatevik Safaryan
Keyword(s):  
Climate Change ◽  
Flood Hazard ◽  
Methodological Approach ◽  
Temporal Trends ◽  
Geographical Information ◽  
Trend Test ◽  
Flood Events ◽  
Temperature And Precipitation ◽  
The Republic ◽  
Events Data

Abstract The primary goal of the study is to analyze the spatial-temporal trends and distribution of flood events in the context of climate change in Armenia. For that purpose, some meteorological parameters, physical-geographical factors and the flood events data were studied for the 1994–2019 period. The linear trends demonstrate an increasing tendency of air temperature and precipitation. Those trends expressed increased flood occurrences, especially for the 2000s, whereas the Mann–Kendall (MK) trend test reveals no significant change. The number of flood events reaches its maximum in 2011 with its peak in May. Out of 191 flood events, half of the occurrences are recorded in the flat areas and southern aspects of the mountains (22% of the country's territory). There is a certain clustering of flood events in the areas with up to 5° slopes (66% of flood events). The most flood vulnerable areas were analyzed and mapped via Geographical Information System (GIS). The GIS-based mapping shows the location of flood vulnerable areas in the central, northern parts of the country, and the coastal areas of Lake Sevan. Our methodological approach elaborates the localization of flood-prone sites. It can be used for the flood hazard assessment mapping and risk management.

scholarly journals Quantifying Landscape Structure of the Kelantan River Basin Before and After a Major Flood Event Using Landscape Metrics

2021 ◽  
pp. 61-67
Author(s):  
H.Y. Abdul
Keyword(s):  
River Basin ◽  
Land Use Planning ◽  
Landscape Structure ◽  
Monsoon Season ◽  
Integrated Approach ◽  
Flood Event ◽  
Northeast Monsoon ◽  
Flood Events ◽  
Kelantan River Basin ◽  
The Impact

Over the years, flood is one of the natural hazards which occur all over the world and it is critical to be controlled through proper management. Flood in Kelantan is mainly caused by heavy rainfall brought by the Northeast monsoon starting from November to March every year. It is categorized as annual flood as it occurs every year during the Monsoon season. Severe flood events in Kelantan, Malaysia cause damage to both life and property every year and understanding landscape structure changes is very important for planners and decision makers for future land use planning and management. This research aims to quantify the landscape structure near to Kelantan River basin during the flood event using integrated approach of remote sensing (RS), geographic information system (GIS) technique and landscape ecological approach. As a result, this study provide new knowledge on landscape structure that contributes to understand the impact of flood events and provide the best ways to mitigate flooding for helping to protect biodiversity habitat and dwellers. As conclusions, this kind of study will give more benefits to various stakeholders such as Department of Irrigation and Drainage, Department of Environment, state government, fisherman and communities.

scholarly journals The rising impact of mathematical modelling in epidemiology: antibiotic resistance research as a case study

2007 ◽  
Vol 136 (3) ◽  
pp. 289-298 ◽  
Author(s):  
L. TEMIME ◽  
G. HEJBLUM ◽  
M. SETBON ◽  
A. J. VALLERON
Keyword(s):  
Public Health ◽  
Antibiotic Resistance ◽  
Mathematical Modelling ◽  
Citation Impact ◽  
Temporal Trends ◽  
Public Health Decision ◽  
Health Decision Making ◽  
Health Decision ◽  
Scientific Fields

SUMMARYMathematical modelling of infectious diseases has gradually become part of public health decision-making in recent years. However, the developing status of modelling in epidemiology and its relationship with other relevant scientific approaches have never been assessed quantitatively. Herein, using antibiotic resistance as a case study, 60 published models were analysed. Their interactions with other scientific fields are reported and their citation impact evaluated, as well as temporal trends. The yearly number of antibiotic resistance modelling publications increased significantly between 1990 and 2006. This rise cannot be explained by the surge of interest in resistance phenomena alone. Moreover, modelling articles are, on average, among the most frequently cited third of articles from the journal in which they were published. The results of this analysis, which might be applicable to other emerging public health problems, demonstrate the growing interest in mathematical modelling approaches to evaluate antibiotic resistance.

scholarly journals Rainfall and runoff regime trends in mountain catchments (Case study area: the upper Hron River basin, Slovakia)

2015 ◽  
Vol 63 (3) ◽  
pp. 183-192 ◽  
Author(s):  
Andrea Blahušiaková ◽  
Milada Matoušková
Keyword(s):  
River Basin ◽  
Kendall Test ◽  
Winter Period ◽  
Data Series ◽  
Flood Events ◽  
Mann Kendall Test ◽  
Runoff Regime ◽  
Simple Mass ◽  
Hydroclimatic Variables

Abstract This paper presents an analysis of trends and causes of changes of selected hydroclimatic variables influencing the runoff regime in the upper Hron River basin (Slovakia). Different methods for identifying trends in data series are evaluated and include: simple mass curve analysis, linear regression, frequency analysis of flood events, use of the Indicators of Hydrological Alteration software, and the Mann-Kendall test. Analyses are performed for data from two periods (1931-2010 and 1961-2010). The changes in runoff are significant, especially in terms of lower QMax and 75 percentile values. This fact is also confirmed by the lower frequency and extremity of flood events. The 1980s are considered a turning point in the development of all hydroclimatic variables. The Mann-Kendall test shows a significant decrease in runoff in the winter period. The main causes of runoff decline are: the considerable increase in air temperature, the decrease in snow cover depth and changes in seasonal distribution of precipitation amounts.

scholarly journals Flash floods in Catalonia: a recurrent situation

2010 ◽  
Vol 26 ◽  
pp. 105-111 ◽  
Author(s):  
M. C. Llasat ◽  
M. Llasat-Botija ◽  
A. Rodriguez ◽  
S. Lindbergh
Keyword(s):  
Social Impact ◽  
Flash Flood ◽  
Temporal Trends ◽  
Temporal Distribution ◽  
Flood Events ◽  
The Social ◽  
Flood Effects ◽  
Data Flood ◽  
Insurance Data

Abstract. This work focuses on the analysis and characterization of the flash flood events occurring during summer in Catalonia. To this aim, a database with information about the social impact produced by all flood events recorded in Catalonia between 1982 and 2007 has been built. The social impact was obtained systematically on the basis of news press data and, occasionally, on the basis of insurance data. Flood events have been classified into ordinary, extraordinary and catastrophic floods, following the proposal of Llasat et al.~(2005). However, bearing in mind flash flood effects, some new categories concerning casualties and car damage have also been introduced. The spatial and temporal distribution of these flood events has been analyzed and, in an effort to better estimate the social impact and vulnerability, some indicators have been defined and analyzed for a specific region. These indicators allow an analysis of spacial and temporal trends as well as characterization of the events. Results show a flash-flood increase in summer and early autumn, mainly due to inter-annual and intra-annual changes in population density.

scholarly journals Analysis of Trends in the FireCCI Global Long Term Burned Area Product (1982–2018)

Fire ◽  
2021 ◽  
Vol 4 (4) ◽  
pp. 74
Author(s):  
Gonzalo Otón ◽  
José Miguel C. Pereira ◽  
João M. N. Silva ◽  
Emilio Chuvieco
Keyword(s):  
Time Series ◽  
Temporal Trends ◽  
European Space Agency ◽  
Eastern Africa ◽  
Burned Area ◽  
Data Series ◽  
Short Term ◽  
The Impact ◽  
Term Data

We present an analysis of the spatio-temporal trends derived from long-term burned area (BA) data series. Two global BA products were included in our analysis, the FireCCI51 (2001–2019) and the FireCCILT11 (1982–2018) datasets. The former was generated from Moderate Resolution Imaging Spectroradiometer (MODIS) 250 m reflectance data, guided by 1 km active fires. The FireCCILT11 dataset was generated from Land Long-Term Data Record data (0.05°), which provides a consistent time series for Advanced Very High Resolution Radiometer images, acquired from the NOAA satellite series. FireCCILT11 is the longest time series of a BA product currently available, making it possible to carry out temporal analysis of long-term trends. Both products were developed under the FireCCI project of the European Space Agency. The two datasets were pre-processed to correct for temporal autocorrelation. Unburnable areas were removed and the lack of the FireCCILT11 data in 1994 was examined to evaluate the impact of this gap on the BA trends. An analysis and comparison between the two BA products was performed using a contextual approach. Results of the contextual Mann-Kendall analysis identified significant trends in both datasets, with very different regional values. The long-term series presented larger clusters than the short-term ones. Africa displayed significant decreasing trends in the short-term, and increasing trends in the long-term data series, except in the east. In the long-term series, Eastern Africa, boreal regions, Central Asia and South Australia showed large BA decrease clusters, and Western and Central Africa, South America, USA and North Australia presented BA increase clusters.

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