scholarly journals Decreasing uncertainty in flood frequency analyses by including historic flood events in an efficient bootstrap approach

2019 ◽  
Author(s):  
Anouk Bomers ◽  
Ralph Schielen ◽  
Suzanne Hulscher
Keyword(s):  
Bootstrap Method ◽  
River System ◽  
Weather Conditions ◽  
Flood Frequency ◽  
Data Sets ◽  
Rhine River ◽  
Flood Events ◽  
Data Set ◽  
Bootstrap Approach

Abstract. Flood frequency curves are usually highly uncertain since they are based on short data sets of measured discharges or weather conditions. To decrease the confidence intervals, an efficient bootstrap method is developed in this study. The Rhine river delta is considered as a case study. A hydraulic model is used to normalize historic flood events for anthropogenic and natural changes in the river system. As a result, the data set of measured discharges could be extended with approximately 600 years. The study shows that flood events decrease the confidence interval of the flood frequency curve significantly, specifically in the range of large floods. This even applies if the maximum discharges of these historic flood events are highly uncertain themselves.

scholarly journals Decreasing uncertainty in flood frequency analyses by including historic flood events in an efficient bootstrap approach

2019 ◽  
Vol 19 (8) ◽  
pp. 1895-1908
Author(s):  
Anouk Bomers ◽  
Ralph M. J. Schielen ◽  
Suzanne J. M. H. Hulscher
Keyword(s):  
Bootstrap Method ◽  
River System ◽  
Weather Conditions ◽  
Flood Frequency ◽  
Data Sets ◽  
Rhine River ◽  
Flood Events ◽  
Data Set ◽  
Bootstrap Approach

Abstract. Flood frequency curves are usually highly uncertain since they are based on short data sets of measured discharges or weather conditions. To decrease the confidence intervals, an efficient bootstrap method is developed in this study. The Rhine river delta is considered as a case study. We use a hydraulic model to normalize historic flood events for anthropogenic and natural changes in the river system. As a result, the data set of measured discharges could be extended by approximately 600 years. The study shows that historic flood events decrease the confidence interval of the flood frequency curve significantly, specifically in the range of large floods. This even applies if the maximum discharges of these historic flood events are highly uncertain themselves.

Improving Quality and Safety Through Use of Secondary Data: Methods Case Study

2016 ◽  
Vol 39 (11) ◽  
pp. 1477-1501 ◽  
Author(s):  
Victoria Goode ◽  
Nancy Crego ◽  
Michael P. Cary ◽  
Deirdre Thornlow ◽  
Elizabeth Merwin
Keyword(s):  
Research Question ◽  
Secondary Data ◽  
Data Access ◽  
Data Sets ◽  
Complex Data ◽  
Management Skills ◽  
Data Set ◽  
Large Numbers ◽  
Need To Evaluate

Researchers need to evaluate the strengths and weaknesses of data sets to choose a secondary data set to use for a health care study. This research method review informs the reader of the major issues necessary for investigators to consider while incorporating secondary data into their repertoire of potential research designs and shows the range of approaches the investigators may take to answer nursing research questions in a variety of context areas. The researcher requires expertise in locating and judging data sets and in the development of complex data management skills for managing large numbers of records. There are important considerations such as firm knowledge of the research question supported by the conceptual framework and the selection of appropriate databases, which guide the researcher in delineating the unit of analysis. Other more complex issues for researchers to consider when conducting secondary data research methods include data access, management and security, and complex variable construction.

Does development reduce fatalities from natural disasters? New evidence for floods

2013 ◽  
Vol 18 (6) ◽  
pp. 649-679 ◽  
Author(s):  
Susana Ferreira ◽  
Kirk Hamilton ◽  
Jeffrey R. Vincent
Keyword(s):  
Natural Disasters ◽  
Flood Frequency ◽  
Lower Income ◽  
Flood Events ◽  
Data Set ◽  
Flood Magnitude ◽  
Lower Income Countries ◽  
The Impact ◽  
New Evidence ◽  
Large Floods

AbstractWe analyze the impact of development on flood fatalities using a new data set of 2,171 large floods in 92 countries between 1985 and 2008. Our results challenge the conventional wisdom that development results in fewer fatalities during natural disasters. Results indicating that higher income and better governance reduce fatalities during flood events do not hold up when unobserved country heterogeneity and within-country correlation of standard errors are taken into account. We find that income does have a significant, indirect effect on flood fatalities by affecting flood frequency and flood magnitude, but this effect is nonmonotonic, with net reductions in fatalities occurring only in lower income countries. We find little evidence that improved governance affects flood fatalities either directly or indirectly.

Functional Reuse and Intensification of Rural-Urban Context

2016 ◽  
Vol 7 (1) ◽  
pp. 1-27 ◽  
Author(s):  
Tiziano Cattaneo ◽  
Roberto De Lotto ◽  
Elisabetta Maria Venco
Keyword(s):  
Best Practices ◽  
Dynamic Balance ◽  
Methodological Approach ◽  
Data Sets ◽  
Logical Framework ◽  
Urban Context ◽  
Specific Knowledge ◽  
Data Set ◽  
Whole Process

In regional and urban planning such as in design actions they are usually involved different themes and disciplines; especially when the goal is to improve, restore and re-functionalize existing minor settlements in rural-urban context. For this reason it is necessary to define integrated methodologies able to face inter-scalar issues and interdisciplinary themes. Authors propose a framework for a decision support system based on the treatment of geographical data and on the integration of the data sets that have dissimilar origin, diverse formats (they may be not only digital) and different meaning value. This complete data set refers to various disciplines and it is possible to deduce specific knowledge throughout analytical passages and assessment steps. In the paper authors describe: a methodological approach to support planning activities; the technical support to seek a (dynamic) balance between urban density and rural fragmentation; a Best Practices database to support scenarios in rural-urban context. Authors first expose the application field, than the logical framework of the whole process, then describe some related spatial analysis applications and finally they introduce comprehensive case study of the whole procedure.

scholarly journals Evaluation of two precipitation data sets for the Rhine River using streamflow simulations

2011 ◽  
Vol 15 (11) ◽  
pp. 3355-3366 ◽  
Author(s):  
C. S. Photiadou ◽  
A. H. Weerts ◽  
B. J. J. M. van den Hurk
Keyword(s):  
Annual Cycle ◽  
Reanalysis Data ◽  
Data Sets ◽  
Precipitation Data ◽  
Rhine River ◽  
Extended Version ◽  
Data Set ◽  
Rhine Basin ◽  
Temporal Correlations ◽  
Lower Uncertainty

Abstract. This paper presents an extended version of a widely used precipitation data set and evaluates it along with a recently released precipitation data set, using streamflow simulations. First, the existing precipitation data set issued by the Commission for the Hydrology of the Rhine basin (CHR), originally covering the period 1961–1995, was extended until 2008 using a number of additional precipitation data sets. Next, the extended version of the CHR, together with E-OBS Version 4 (ECA & D gridded data set) were evaluated for their performance in the Rhine basin for extreme events. Finally, the two aforementioned precipitation data sets and a meteorological reanalysis data set were used to force a hydrological model, evaluating the influence of different precipitation forcings on the annual mean and extreme discharges compared to observational discharges for the period from 1990 until 2008. The extended version of CHR showed good agreement in terms of mean annual cycle, extreme discharge (both high and low flows), and spatial distribution of correlations with observed discharge. E-OBS performed well with respect to extreme discharge. However, its performance of the mean annual cycle in winter was rather poor and remarkably well in the summer. Also, CHR08 outperformed E-OBS in terms of temporal correlations in most of the analyzed sub-catchment means. The length extension for the CHR and the even longer length of E-OBS permit the assessment of extreme discharge and precipitation values with lower uncertainty for longer return periods. This assessment classifies both of the presented precipitation data sets as possible reference data sets for future studies in hydrological applications.

scholarly journals Comparison of long-term Moscow and Danish NLC observations: statistical results

2006 ◽  
Vol 24 (11) ◽  
pp. 2841-2849 ◽  
Author(s):  
P. Dalin ◽  
S. Kirkwood ◽  
H. Andersen ◽  
O. Hansen ◽  
N. Pertsev ◽  
...  
Keyword(s):  
Weather Conditions ◽  
Noctilucent Clouds ◽  
Characteristic Scale ◽  
Careful Attention ◽  
Data Set ◽  
First Time ◽  
Term Data ◽  
Statistical Results

Abstract. Noctilucent clouds (NLC) are the highest clouds in the Earth's atmosphere, observed close to the mesopause at 80–90 km altitudes. Systematic NLC observations conducted in Moscow for the period of 1962–2005 and in Denmark for 1983–2005 are compared and statistical results both for seasonally summarized NLC parameters and for individual NLC appearances are described. Careful attention is paid to the weather conditions during each season of observations. This turns out to be a very important factor both for the NLC case study and for long-term data set analysis. Time series of seasonal values show moderate similarity (taking into account the weather conditions) but, at the same time, the comparison of individual cases of NLC occurrence reveals substantial differences. There are positive trends in the Moscow and Danish normalized NLC brightness as well as nearly zero trend in the Moscow normalized NLC occurrence frequency but these long-term changes are not statistically significant. The quasi-ten-year cycle in NLC parameters is about 1 year shorter than the solar cycle during the same period. The characteristic scale of NLC fields is estimated for the first time and it is found to be less than 800 km.

Do eel parasites reflect the local crustacean community? A case study from the Rhine river system

2007 ◽  
Vol 81 (2) ◽  
pp. 179-189 ◽  
Author(s):  
Frankie Thielen ◽  
Marcel Münderle ◽  
Horst Taraschewski ◽  
Bernd Sures
Keyword(s):  
Anguilla Anguilla ◽  
River System ◽  
Parasite Fauna ◽  
River Rhine ◽  
Rhine River ◽  
Anguillicola Crassus ◽  
Biogeographic Barrier ◽  
Acanthocephalus Lucii ◽  
Raphidascaris Acus

AbstractIn 2003, the parasite fauna of 197 European eelsAnguilla anguilla, captured at three different locations (Laufenburg, Karlsruhe and Beneeden Leeuwen) in the River Rhine, was analysed. The eels harboured a total of 18 species, among them the protozoa (Myxidium giardi, Myxobolus kotlaniandTrypanosoma granulosum), acanthocephalans (Acanthocephalus anguillae, Acanthocephalus lucii, Echinorhynchus truttae, Pomphorhynchus laevis), nematodes (Paraquimperia tenerrima, Pseudocapillaria tomentosa, Camallanus lacustris, Raphidascaris acus, Spinitectus inermisandAnguillicola crassus), cestodes (Bothriocephalus clavicepsandProteocephalus macrocephalus) and monogeneans (Pseudodactylogyrussp.). The parasite fauna at the different locations is discussed with respect to the crustacean fauna present at these locations. The investigation shows that changes in the composition of the crustacean fauna, due to the anthropogenic breakdown of a biogeographic barrier, are reflected in the composition of the intestinal eel parasite fauna.

scholarly journals Co-registration and bias corrections of satellite elevation data sets for quantifying glacier thickness change

2011 ◽  
Vol 5 (1) ◽  
pp. 271-290 ◽  
Author(s):  
C. Nuth ◽  
A. Kääb
Keyword(s):  
Regional Scale ◽  
Statistical Error ◽  
Data Sets ◽  
Data Set ◽  
Thickness Change ◽  
Aster Gdem ◽  
Digital Elevation ◽  
Elevation Data ◽  
Elevation Changes

Abstract. There are an increasing number of digital elevation models (DEMs) available worldwide for deriving elevation differences over time, including vertical changes on glaciers. Most of these DEMs are heavily post-processed or merged, so that physical error modelling becomes difficult and statistical error modelling is required instead. We propose a three-step methodological framework for assessing and correcting DEMs to quantify glacier elevation changes: (i) remove DEM shifts, (ii) check for elevation-dependent biases, and (iii) check for higher-order, sensor-specific biases. A simple, analytic and robust method to co-register elevation data is presented in regions where stable terrain is either plentiful (case study New Zealand) or limited (case study Svalbard). The method is demonstrated using the three global elevation data sets available to date, SRTM, ICESat and the ASTER GDEM, and with automatically generated DEMs from satellite stereo instruments of ASTER and SPOT5-HRS. After 3-D co-registration, significant biases related to elevation were found in some of the stereoscopic DEMs. Biases related to the satellite acquisition geometry (along/cross track) were detected at two frequencies in the automatically generated ASTER DEMs. The higher frequency bias seems to be related to satellite jitter, most apparent in the back-looking pass of the satellite. The origins of the more significant lower frequency bias is uncertain. ICESat-derived elevations are found to be the most consistent globally available elevation data set available so far. Before performing regional-scale glacier elevation change studies or mosaicking DEMs from multiple individual tiles (e.g. ASTER GDEM), we recommend to co-register all elevation data to ICESat as a global vertical reference system.

scholarly journals A Bayesian approach to exploring the influence of climate variability modes on fire weather conditions and lightning-ignited wildfires

2021 ◽  
Author(s):  
Bryson C. Bates ◽  
Andrew J. Dowdy ◽  
Lachlan McCaw
Keyword(s):  
Climate Variability ◽  
Network Architecture ◽  
Large Scale ◽  
Weather Prediction ◽  
Weather Conditions ◽  
Fire Weather ◽  
Prescribed Burn ◽  
Data Set ◽  
Climate Modes

AbstractUnderstanding the relationships between large-scale, low-frequency climate variability modes, fire weather conditions and lighting-ignited wildfires has implications for fire-weather prediction, fire management and conservation. This article proposes a Bayesian network framework for quantifying the influence of climate modes on fire weather conditions and occurrence of lightning-ignited wildfires. The main objectives are to describe and demonstrate a probabilistic framework for identifying and quantifying the joint and individual relationships that comprise the climate-wildfire system; gain insight into potential causal mechanisms and pathways; gauge the influence of climate modes on fire weather and lightning-ignition relative to that of local-scale conditions alone; assess the predictive skill of the network; and motivate the use of techniques that are intuitive, flexible and for which user‐friendly software is freely available. A case study illustrates the application of the framework to a forested region in southwest Australia. Indices for six climate variability modes are considered along with two hazard variables (observed fire weather conditions and prescribed burn area), and a 41-year record of lightning-ignited wildfire counts. Using the case study data set, we demonstrate that the proposed framework: (1) is based on reasonable assumptions provided the joint density of the variables is converted to multivariate normal; (2) generates a parsimonious and interpretable network architecture; (3) identifies known or partially known relationships between the variables; (4) has potential to be used in a predictive setting for fire weather conditions; and (5) climate modes are more directly related to fire weather conditions than to lightning-ignition counts.

scholarly journals What's in an elevation difference? Accuracy and corrections of satellite elevation data sets for quantification of glacier changes

2010 ◽  
Vol 4 (4) ◽  
pp. 2013-2077 ◽  
Author(s):  
C. Nuth ◽  
A. Kääb
Keyword(s):  
New Zealand ◽  
Regional Scale ◽  
Statistical Error ◽  
Data Sets ◽  
Methodological Framework ◽  
Data Set ◽  
Aster Gdem ◽  
Elevation Data ◽  
Elevation Changes

Abstract. There is an increasing number of DEMs available worldwide for deriving elevation differences over time, including vertical changes on glaciers. Most of these DEMs are heavily post-processed or merged, so that physical error modelling becomes impossible and statistical error modelling is required instead. We propose a three-step methodological framework for assessing and correcting DEMs to quantify glacier elevation changes: remove DEM shifts, check for elevation-dependent biases, and check for higher-order, sensor-specific biases. An analytic, simple and robust method to co-register elevation data is presented in regions where stable terrain is either plentiful (case study New Zealand) or limited (case study Svalbard). The method is exemplified using the three global elevation data sets available, SRTM, ICESat and the ASTER GDEM, and with automatically generated DEMs from satellite stereo instruments of ASTER and SPOT5-HRS. After three-dimensional co-registration, significant biases related to elevation were found in some of the stereoscopic DEMs. Biases related to the satellite acquisition geometry (along/cross track) were detected at two frequencies in the automatically generated ASTER DEMs. The higher frequency bias seems to be related to satellite \\emph{jitter}, most effective in the back-looking pass of the satellite. The origins of the more significant lower frequency bias is uncertain. ICESat-derived elevations are found to be the most consistent globally available elevation data set available so far. Before performing regional-scale glacier elevation change studies or mosaicking DEMs from multiple individual tiles (e.g. ASTER GDEM), we recommend to co-register all elevation data to ICESat as a global vertical reference system. The proposed methodological framework is exemplified for elevation changes on the Fox, Franz Joseph, Tasman and Murchison glaciers of New Zealand and the glaciers of central Spitsbergen, Svalbard.

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