scholarly journals Extremeness of recent drought events in Switzerland: dependence on variable and return period choice

2019 ◽  
Vol 19 (10) ◽  
pp. 2311-2323 ◽  
Author(s):  
Manuela I. Brunner ◽  
Katharina Liechti ◽  
Massimiliano Zappa
Keyword(s):  
Soil Moisture ◽  
Frequency Analysis ◽  
Return Period ◽  
Threshold Level ◽  
Low Flow ◽  
Drought Event ◽  
Return Periods ◽  
Event Identification ◽  
Groundwater Drought ◽  
Drought Frequency Analysis

Abstract. The 2018 drought event had severe ecological, economic, and social impacts. How extreme was it in Switzerland? We addressed this question by looking at different types of drought, including meteorological, hydrological, agricultural, and groundwater drought, and at the two characteristics deficit and deficit duration. The analysis consisted of three main steps: (1) event identification using a threshold-level approach, (2) drought frequency analysis, and (3) comparison of the 2018 event to the severe 2003 and 2015 events. In Step 2 the variables precipitation, discharge, soil moisture, and low-flow storage were first considered separately in a univariate frequency analysis; pairs of variables were then investigated jointly in a bivariate frequency analysis using a copula model for expressing the dependence between the two variables under consideration. Our results show that the 2018 event was especially severe in north-eastern Switzerland in terms of soil moisture, with return periods locally exceeding 100 years. Slightly longer return periods were estimated when discharge and soil moisture deficits were considered together. The return period estimates depended on the region, variable, and return period considered. A single answer to the question of how extreme the 2018 drought event was in Switzerland is therefore not possible – rather, it depends on the processes one is interested in.

scholarly journals Extremeness of recent drought events in Switzerland: dependence on variable and return period choice

2019 ◽  
Author(s):  
Manuela I. Brunner ◽  
Katharina Liechti ◽  
Massimiliano Zappa
Keyword(s):  
Soil Moisture ◽  
Frequency Analysis ◽  
Return Period ◽  
Threshold Level ◽  
Low Flow ◽  
Drought Event ◽  
Return Periods ◽  
Event Identification ◽  
Groundwater Drought ◽  
Drought Frequency Analysis

Abstract. The 2018 drought event had severe ecological, economic, and social impacts. How extreme was it in Switzerland? We addressed this question by looking at different types of drought, including meteorological, hydrological, agricultural, and groundwater drought, and at the two characteristics deficit and deficit duration. The analysis consisted of three main steps: (1) event identification using a threshold-level approach, (2) drought frequency analysis, and (3) comparison of the 2018 event to the severe 2003 and 2015 events. In Step 2 the variables precipitation, discharge, soil moisture, and low-flow storage were first considered separately in a univariate frequency analysis; pairs of variables were then investigated jointly in a bivariate frequency analysis using a copula model for expressing the dependence between the two variables under consideration. Our results show that the 2018 event was especially severe in north-eastern Switzerland in terms of soil moisture, with return periods locally exceeding 100 years. Slightly longer return periods were estimated when discharge and soil moisture deficits were considered together. The return period estimates depended on the region, variable, and return period considered. A single answer to the question of how extreme the 2018 drought event was in Switzerland is therefore not possible – it rather depends on the processes one is interested in.

scholarly journals Joint return periods in hydrology: a critical and practical review focusing on synthetic design hydrograph estimation

2012 ◽  
Vol 9 (5) ◽  
pp. 6781-6828 ◽  
Author(s):  
S. Vandenberghe ◽  
M. J. van den Berg ◽  
B. Gräler ◽  
A. Petroselli ◽  
S. Grimaldi ◽  
...  
Keyword(s):  
Frequency Analysis ◽  
Return Period ◽  
Three Dimensional ◽  
Distribution Functions ◽  
Return Periods ◽  
Design Variables ◽  
Joint Return ◽  
Design Values ◽  
Multivariate Frequency Analysis ◽  
Joint Return Period

Abstract. Most of the hydrological and hydraulic studies refer to the notion of a return period to quantify design variables. When dealing with multiple design variables, the well-known univariate statistical analysis is no longer satisfactory and several issues challenge the practitioner. How should one incorporate the dependence between variables? How should the joint return period be defined and applied? In this study, an overview of the state-of-the-art for defining joint return periods is given. The construction of multivariate distribution functions is done through the use of copulas, given their practicality in multivariate frequency analysis and their ability to model numerous types of dependence structures in a flexible way. A case study focusing on the selection of design hydrograph characteristics is presented and the design values of a three-dimensional phenomenon composed of peak discharge, volume and duration are derived. Joint return period methods based on regression analysis, bivariate conditional distributions, bivariate joint distributions, and Kendal distribution functions are investigated and compared highlighting theoretical and practical issues of multivariate frequency analysis. Also an ensemble-based method is introduced. For a given design return period, the method chosen clearly affects the calculated design event. Eventually, light is shed on the practical implications of a chosen method.

scholarly journals A maximum entropy copula-based frequency analysis method for assessing bivariate drought risk: a case study of the Kaidu River Basin

2021 ◽  
Author(s):  
X. Yang ◽  
Y. P. Li ◽  
G. H. Huang
Keyword(s):  
Maximum Entropy ◽  
River Basin ◽  
Frequency Analysis ◽  
Return Period ◽  
Drought Risk ◽  
Return Periods ◽  
Drought Frequency ◽  
Joint Return ◽  
Joint Return Period ◽  
Kaidu River

Abstract In this study, a maximum entropy copula-based frequency analysis (MECFA) method is developed through integrating maximum entropy, copulas and frequency analysis into a general framework. The advantages of MECFA are that the marginal modeling requires no assumption and joint distribution preserves the dependence structure of drought variables. MECFA is applied to assessing bivariate drought frequency in the Kaidu River Basin, China. Results indicate that the Kaidu River Basin experienced 28 drought events during 1958–2011, and drought inter-arrival time is 10.8 months. The average duration is 6.2 months (severity 4.6), and the most severe drought event lasts for 35 months (severity 41.2) that occurred from June 1977 to March 1980. Results also disclose that hydrological drought index (HDI) 1 is suitable for drought frequency analysis in target year of return periods of 5 and 10, HDI 3, HDI 6 and HDI 12 are fit for the target year of return periods of 20, 50 and 100. The joint return period can be used as the upper bound of the target return period, and the joint return period that either duration or severity reaches the drought threshold can be used as the lower bound of the target return period.

Bias introduced in rainfall risk assessment by a rain gauges network

1998 ◽  
Vol 37 (11) ◽  
pp. 97-104
Author(s):  
L. Neppel ◽  
M. Desbordes ◽  
J. M. Masson
Keyword(s):  
Risk Assessment ◽  
Frequency Analysis ◽  
Return Period ◽  
Return Periods ◽  
Rainfall Events ◽  
Rain Gauges ◽  
Spatial Approach ◽  
Rainfall Depth ◽  
Rain Gauges Network

When large periods of observation are considered, the densest information are often a collection of the daily rain gauges network. As this information is scattered in space, the stochastic results and specially the rainfall risk assessment, are biased because of the rainfall events that are not ‘observed’ by the network. Rainfall risk can be assessed using a punctual approach with the estimation of regional return period of a punctual rainfall depth exceeding a given value, or using a spatial approach with the frequency analysis of the areas of isohyets defined at a given rain threshold τ. This last approach consists, for a given τ, in estimating the return period of isohyet areas. Using simulation, a method of unbiased rainfall risk assessment is proposed for the Languedoc-Roussillon region (France). It has been shown that the bias influence is negligible for the regional return periods of isohyet areas, for 24-hour and 48-hour duration, when compared to their confident limits. On the contrary the return periods of punctual rainfall depths above a given value are more sensitive: for values above 170 mm/24h and 270 mm/48h, the biased return periods could be up to 3 times overestimated.

scholarly journals Assessment of probability distributions and analysis of the minimum storage draft rate in the equatorial region

2021 ◽  
Vol 21 (1) ◽  
pp. 1-19
Author(s):  
Hasrul Hazman Hasan ◽  
Siti Fatin Mohd Razali ◽  
Nur Shazwani Muhammad ◽  
Firdaus Mohamad Hamzah
Keyword(s):  
Water Supply ◽  
Frequency Analysis ◽  
Hydrological Cycle ◽  
Equatorial Region ◽  
Low Flow ◽  
Drought Event ◽  
Rapid Urbanization ◽  
Frequency Distributions ◽  
Drought Characteristics ◽  
Flow Frequency

Abstract. Rapid urbanization in the state of Selangor, Malaysia, has led to a change in the land use, physical properties of basins, vegetation cover and impermeable surface water. These changes have affected the pattern and processes of the hydrological cycle, resulting in the ability of the basin region to store water supply to decline. Reliability on water supply from river basins depends on their low-flow characteristics. The impacts of minimum storage on hydrological drought are yet to be incorporated and assessed. Thus, this study aims to understand the concept of low-flow drought characteristics and the predictive significance of river storage draft rates in managing sustainable water catchment. In this study, the long-term streamflow data of 40 years from seven stations in Selangor were used, and the streamflow trends were analyzed. Low-flow frequency analysis was derived using the Weibull plotting position and four specific frequency distributions. Maximum likelihood was used to parameterize, while Kolmogorov–Smirnov tests were used to evaluate their fit to the dataset. The mass curve was used to quantify the minimum storage draft rate required to maintain the 50 % mean annual flow for the 10-year recurrence interval of low flow. Next, low-flow river discharges were analyzed using the 7 d mean annual minimum, while the drought event was determined using the 90th percentile (Q90) as the threshold level. The inter-event time and moving average was employed to remove the dependent and minor droughts in determining the drought characteristics. The result of the study shows that the lognormal (2P) distribution was found to be the best fit for low-flow frequency analysis to derive the low-flow return period. This analysis reveals September to December to be a critical period in river water storage to sustain the water availability during low flow in a 10-year occurrence interval. These findings indicated that hydrological droughts have generally become more critical in the availability of rivers to sustain water demand during low flows. These results can help in emphasizing the natural flow of water to provide water supply for continuous use during low flow.

scholarly journals Flood Frequency Analysis Using Participatory GIS and Rainfall Data for Two Stations in Narok Town, Kenya

Hydrology ◽  
2019 ◽  
Vol 6 (4) ◽  
pp. 90 ◽  
Author(s):  
Houessou-Dossou ◽  
Gathenya ◽  
Njuguna ◽  
Gariy
Keyword(s):  
Frequency Analysis ◽  
Return Period ◽  
Computational Modelling ◽  
Flood Frequency ◽  
Meteorological Station ◽  
Distribution Functions ◽  
Rainfall Data ◽  
Flood Frequency Analysis ◽  
Return Periods ◽  
Participatory Gis

Flood management requires in-depth computational modelling through assessment of flood return period and river flow data in order to effectively analyze catchment response. The participatory geographic information system (PGIS) is a tool which is increasingly used for collecting data and decision making on environmental issues. This study sought to determine the return periods of major floods that happened in Narok Town, Kenya, using rainfall frequency analysis and PGIS. For this purpose, a number of statistical distribution functions were applied to daily rainfall data from two stations: Narok water supply (WS) station and Narok meteorological station (MS). The first station has a dataset of thirty years and the second one has a dataset of fifty-nine (59) years. The parameters obtained from the Kolmogorov–Smirnov (K–S) test and chi-square test helped to select the appropriate distribution. The best-fitted distribution for WS station were Gumbel L-moment, Pareto L-moment, and Weibull distribution for maximum one day, two days, and three days rainfall, respectively. However, the best-fitted distribution was found to be generalized extreme value L-moment, Gumbel and gamma distribution for maximum one day, two days, and three days, respectively for the meteorological station data. Each of the selected best-fitted distribution was used to compute the corresponding rainfall intensity for 5, 10, 25, 50, and 100 years return period, as well as the return period of the significant flood that happened in the town. The January 1993 flood was found to have a return period of six years, while the April 2013, March 2013, and April 2015 floods had a return period of one year each. This study helped to establish the return period of major flood events that occurred in Narok, and highlights the importance of population in disaster management. The study’s results would be useful in developing flood hazard maps of Narok Town for different return periods.

scholarly journals Application of Frequency Analysis on Peak River Discharge toward the Cumulative Floatable Litter Load at Log Boom Sungai Batu

2019 ◽  
Vol 266 ◽  
pp. 02002
Author(s):  
Nur Khaliesah Abdul Malik ◽  
Nor Rohaizah Jamil ◽  
Latifah Abd Manaf ◽  
Mohd Hafiz Rosli ◽  
Zulfa Hanan Ash’aari ◽  
...  
Keyword(s):  
Frequency Analysis ◽  
Return Period ◽  
River Discharge ◽  
Linear Regression Analysis ◽  
Gumbel Distribution ◽  
Environmental Issues ◽  
Decision Making Process ◽  
Rapid Urbanization ◽  
Distribution Method ◽  
Period 2

The accumulation of floatable litter in the river is mainly influenced by the increasing number of human population, rapid urbanization and development which indirectly lead to the changes of hydrological processes in river discharge, decreasing the water quality and aesthetical value of the river. The main objective of this paper is to determine the cumulative floatable litter load captured at the log boom during the extreme events by using the Gumbel distribution method for frequency analysis in river discharge of Sungai Batu. The annual maximum river discharge for a period of 35 years (1982 to 2016) was used in Gumbel distribution method to obtain the discharge for different return period (2, 5, 10, 25, 50, 100, and 200). The result shows that the estimated discharge (103.17 m³/s) can estimate the cumulative floatable litter load (53267.27 kg/day) at 50 years return period. The R2 value obtained from non – linear regression analysis is 0.9986 indicate that Gumbel distribution is suitable to predict the expected discharge of the river. This study is very crucial for the related agencies in highlighting this environmental issues for their future references which can be used as a guidelines during the decision making process in making better improvement.

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