[PDF] Top 20 Improving the characterization of initial condition for ensemble streamflow prediction using data assimilation
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Improving the characterization of initial condition for ensemble streamflow prediction using data assimilation
... probabilistic streamflow estimation dur- ing model hindcasts, using Nash-Sutcliffe Efficiency, Rank Probability Skill Score and Normalized Root Mean Square Error for different error ... See full document
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A past discharge assimilation system for ensemble streamflow forecasts over France – Part 2: Impact on the ensemble streamflow forecasts
... of ensemble streamflow forecasts is de- veloping in the international flood forecasting ...semble streamflow forecast systems can provide more accu- rate forecasts and useful information about the ... See full document
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A past discharges assimilation system for ensemble streamflow forecasts over France – Part 1: Description and validation of the assimilation system
... variational data assimilation approach for as- similating streamflows in order to retrieve root-zone soil ...moisture data and improved the simulation of water storage and fluxes in the Mississippi ... See full document
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A new data assimilation approach for improving runoff prediction using remotely sensed soil moisture retrievals
... runoff prediction via the assimilation of remotely- sensed surface soil moisture retrievals into a hydrologic ...the characterization of pre-storm soil moisture conditions in a hydrologic model, and ... See full document
16
Skill of a global forecasting system in seasonal ensemble streamflow prediction
... and initial conditions such as soil moisture, groundwater and snow, but also by meteorological forcing ...of initial hydrologic states through assimilation of independent hydrological observations on ... See full document
12
Performance of ensemble streamflow forecasts under varied hydrometeorological conditions
... to improving the forecasts effectively (Yossef et ...parameters, initial conditions and model structure) are most significant at short lead ...the streamflow category: hydrological model un- ... See full document
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Improving operational flood ensemble prediction by the assimilation of satellite soil moisture: comparison between lumped and semi distributed schemes
... satellite data is likely to be more valu- able than in well-instrumented ...that streamflow has a negligible baseflow component and the surface runoff is generated only when a wetness threshold is ... See full document
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Benchmarking ensemble streamflow prediction skill in the UK
... climate data (precipitation, potential evapotranspiration, and/or temperature) at the time of fore- cast are used to force hydrological models, providing a plau- sible range of representations of the future ... See full document
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An integrated uncertainty and ensemble based data assimilation approach for improved operational streamflow predictions
... Over the past several decades, a variety of uncertainty analysis methods and data assimilation techniques have been developed and reported in the hydrologic literature. Some of the uncertainty analysis ... See full document
17
Evaluation of snow data assimilation using the ensemble Kalman filter for seasonal streamflow prediction in the western United States
... The central motivating aim of this study is thus to as- sess the potential benefits of objective, automated SWE DA against a reference model configuration to identify forecast improvement opportunities. We apply the EnKF ... See full document
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A geostatistical data assimilation technique for enhancing macro scale rainfall–runoff simulations
... open- data products with local observations. We enhanced the streamflow series simulated by macro- and continental-scale rainfall–runoff models at ungauged prediction nodes by as- similating ... See full document
16
A non-Gaussian analysis scheme using rank histograms for ensemble data assimilation
... corrected using a linear regression onto the corrections of observed variables, as in the ...for ensemble data assimi- lation, in the spirit of the method of Reich ...how ensemble analysis ... See full document
17
Monthly hydrometeorological ensemble prediction of streamflow droughts and corresponding drought indices
... of streamflow drought. Figure 3 illustrates the streamflow drought indices drawn from an observed or forecast hydro- graph, with indices being dependent on the choice of the ...low streamflow may be ... See full document
13
ENSO conditioned weather resampling method for seasonal ensemble streamflow prediction
... 50-year ensemble is identical to the original ESP and has a skill score of 0 by ...the ensemble size, the fore- cast skill increases for two of the three test stations (Dwor- shak and Hungry Horse) as a ... See full document
11
Role of forcing uncertainty and background model error characterization in snow data assimilation
... conducted using the Noah land surface model version ...Land Data Assimilation System Phase 2 (NLDAS-2; Xia et ...conducted using the same LSM, but forced with a different meteorology from the ... See full document
11
Quasi-static ensemble variational data assimilation: a theoretical and numerical study with the iterative ensemble Kalman smoother
... Keeping the minimization starting point in a global minimum basin of attraction is constraining because, with a chaotic model, the number of local minima may increase exponen- tially with the data ... See full document
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Optimal adjustment of the atmospheric forcing parameters of ocean models using sea surface temperature data assimilation
... ary condition in ocean general circulation models (hereafter OGCMs) required for operational forecasts, ocean reanal- yses, or hindcast simulations of the recent ocean variabil- ity (the last 50 ...weather ... See full document
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Technical note: Combining quantile forecasts and predictive distributions of streamflows
... In a first step the hydrological modelling errors of all these forecasts will be minimized, using a QR method in com- bination with neural networks (QRNN, Taylor, 2000; Can- non, 2011). This will result in direct ... See full document
10
On deterministic error analysis in variational data assimilation
... the prediction in order to provide some information on the improvement of ...input data to the error of the optimal solution via variational data ...the prediction, involving the case of small ... See full document
10
Diabetes data prediction using data classification algorithm
... not using Random Forest (RF) Classification ...training data and the details of the patient are taken as testing ...training data are classified by using the RF classifier and secondly the ... See full document
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