scholarly journals Generation of monthly synthetic streamflow series based on the method of fragments

2011 ◽  
Author(s):  
A. T. Silva ◽  
M. M. Portela
Keyword(s):  
Method Of Fragments ◽  
Synthetic Streamflow

scholarly journals A regional similarity-based approach for sub-daily rainfall nonparametric generation

RBRH ◽  
2020 ◽  
Vol 25 ◽  
Author(s):  
Milena Guerra de Aguilar ◽  
Veber Afonso Figueiredo Costa
Keyword(s):  
Daily Rainfall ◽  
High Temporal Resolution ◽  
Rainfall Time Series ◽  
Storm Events ◽  
Runoff Simulation ◽  
K Nearest Neighbors ◽  
Method Of Fragments ◽  
Block Maxima ◽  
Regional Similarity ◽  
Doce River

ABSTRACT Rainfall time series with high temporal resolution are required for estimating storm events for the design of urban drainage systems, for performing rainfall-runoff simulation in small catchments and for modeling flash-floods. Nonetheless, large and continuous sub-daily rainfall samples are often unavailable. For dealing with the limited availability of high-resolution rainfall records, in both time and space, this paper explored an alternative version of the k-nearest neighbors algorithm, coupled with the method of fragments (KNN-MOF model), which utilizes a state-based logic for simulating consecutive wet days and a regionalized similarity-based approach for sampling fragments from hydrologically similar nearby stations. The proposed disaggregation method was applied to 40 rainfall gauging stations located in the São Francisco and Doce river catchments. Disaggregation of daily rainfall was performed for the durations of 60, 180 and 360 minutes. Results indicated the model presented an appropriate performance to disaggregate daily rainfall, reasonably reproducing sub-daily summary statistics. In addition, the annual block-maxima behavior, even for low exceedance probabilities, was relatively well described, although not all expected variability in the quantiles was properly summarized by the model. Overall, the proposed approach proved a sound and easy to implement alternative for simulating continuous sub-daily rainfall amounts from coarse-resolution records.

Vibrations of a Cage-like Molecule, P4S3: Some Theoretical Aspects

1981 ◽  
Vol 36 (7) ◽  
pp. 774-777 ◽  
Author(s):  
S. J. Cyvin ◽  
B. N. Cyvin ◽  
M. Somer ◽  
W. Brockner
Keyword(s):  
Potential Energy ◽  
Energy Distribution ◽  
Force Field ◽  
Normal Modes ◽  
Potential Energy Distribution ◽  
Symmetry Coordinates ◽  
Method Of Fragments ◽  
Compliance Matrices

Abstract Two independent symmetry coordinate sets for P4S3 are developed, starting from the "method of fragments". A simple, approximate force field is expressed in terms of the two sets of symmetry coordinates, and the corresponding compliance matrices are given. The invariance of compliants is demonstrated. The potential energy distribution (PED) is discussed. An example is shown where the PED terms are clearly inadequate for the description of normal modes. A general warning against the interpretation of the PED in terms of such descriptions for cage-like structures seems to be warranted. V ib r a tio n s o f a C a g e -lik e M o le c u le , P 4S3 : S o m e T h e o r e tic a l A sp e c ts

Adaptation of Method of Fragments to Axisymmetric Cofferdam Seepage Problem

2017 ◽  
Vol 17 (9) ◽  
pp. 06017012 ◽  
Author(s):  
Thushara Asela Madanayaka ◽  
Nagaratnam Sivakugan
Keyword(s):  
Seepage Problem ◽  
Method Of Fragments

scholarly journals Downsizing parameter ensembles for simulations of extreme floods

2020 ◽  
Author(s):  
Anna E. Sikorska-Senoner ◽  
Bettina Schaefli ◽  
Jan Seibert
Keyword(s):  
Time Series ◽  
Computational Cost ◽  
Hydrologic Model ◽  
Extreme Floods ◽  
Continuous Simulation ◽  
Modelling Uncertainty ◽  
Extreme Flood ◽  
Simulation Based ◽  
Flood Estimation ◽  
Synthetic Streamflow

Abstract. For extreme flood estimation, simulation-based approaches represent an interesting alternative to purely statistical approaches, particularly if hydrograph shapes are required. Such simulation-based methods are adapted within continuous simulation frameworks that rely on statistical analyses of continuous streamflow time series derived from a hydrologic model fed with long precipitation time series. These frameworks are, however, affected by high computational demands, particularly if floods with return periods > 1000 years are of interest or if modelling uncertainty due to different sources (meteorological input or hydrologic model) is to be quantified. Here, we propose three methods for reducing the computational requirements for the hydrological simulations for extreme flood estimation, so that long streamflow time series can be analysed at a reduced computational cost. These methods rely on simulation of annual maxima and on analyzing their simulated range to downsize the hydrological parameter ensemble to a small number suitable for continuous simulation frameworks. The methods are tested in a Swiss catchment with 10 000 years of synthetic streamflow data simulated with a weather generator. Our results demonstrate the reliability of the proposed downsizing methods for robust simulations of extreme floods with uncertainty. The methods are readily transferable to other situations where ensemble simulations are needed.

scholarly journals Stochastic generation of annual, monthly and daily climate data: A review

2001 ◽  
Vol 5 (4) ◽  
pp. 653-670 ◽  
Author(s):  
R. Srikanthan ◽  
T. A. McMahon
Keyword(s):  
Climate Change ◽  
Historical Data ◽  
Southern Oscillation ◽  
Daily Rainfall ◽  
Annual Rainfall ◽  
Model Parameters ◽  
Annual Data ◽  
Climate Data ◽  
Time Step ◽  
Method Of Fragments

Abstract. The generation of rainfall and other climate data needs a range of models depending on the time and spatial scales involved. Most of the models used previously do not take into account year to year variations in the model parameters. Long periods of wet and dry years were observed in the past but were not taken into account. Recently, Thyer and Kuczera (1999) developed a hidden state Markov model to account for the wet and dry spells explicitly in annual rainfall. This review looks firstly at traditional time series models and then at the more complex models which take account of the pseudo-cycles in the data. Monthly rainfall data have been generated successfully by using the method of fragments. The main criticism of this approach is the repetitions of the same yearly pattern when only a limited number of years of historical data are available. This deficiency has been overcome by using synthetic fragments but this brings an additional problem of generating the right number of months with zero rainfall. Disaggregation schemes are effective in obtaining monthly data but the main problem is the large number of parameters to be estimated when dealing with many sites. Several simplifications have been proposed to overcome this problem. Models for generating daily rainfall are well developed. The transition probability matrix method preserves most of the characteristics of daily, monthly and annual characteristics and is shown to be the best performing model. The two-part model has been shown by many researchers to perform well across a range of climates at the daily level but has not been tested adequately at monthly or annual levels. A shortcoming of the existing models is the consistent underestimation of the variances of the simulated monthly and annual totals. As an alternative, conditioning model parameters on monthly amounts or perturbing the model parameters with the Southern Oscillation Index (SOI) result in better agreement between the variance of the simulated and observed annual rainfall and these approaches should be investigated further. As climate data are less variable than rainfall, but are correlated among themselves and with rainfall, multisite-type models have been used successfully to generate annual data. The monthly climate data can be obtained by disaggregating these annual data. On a daily time step at a site, climate data have been generated using a multisite type model conditional on the state of the present and previous days. The generation of daily climate data at a number of sites remains a challenging problem. If daily rainfall can be modelled successfully by a censored power of normal distribution then the model can be extended easily to generate daily climate data at several sites simultaneously. Most of the early work on the impacts of climate change used historical data adjusted for the climate change. In recent studies, stochastic daily weather generation models are used to compute climate data by adjusting the parameters appropriately for the future climates assumed.

Study of Drainage Through Hydraulic Fill Stopes using Method of Fragments

2006 ◽  
Vol 24 (1) ◽  
pp. 79-89 ◽  
Author(s):  
N. Sivakugan ◽  
K. J. Rankine ◽  
K. S. Rankine
Keyword(s):  
Hydraulic Fill ◽  
Method Of Fragments
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