scholarly journals Effect of radar rainfall time resolution on the predictive capability of a distributed hydrologic model

2011 ◽  
Vol 15 (12) ◽  
pp. 3809-3827 ◽  
Author(s):  
A. Atencia ◽  
L. Mediero ◽  
M. C. Llasat ◽  
L. Garrote
Keyword(s):  
Sensitivity Analysis ◽  
Time Resolution ◽  
Heavy Rainfall ◽  
Flash Flood ◽  
Probabilistic Approach ◽  
Great Influence ◽  
Hydrologic Model ◽  
Radar Rainfall ◽  
Distributed Hydrologic Model ◽  
Correction Technique

Abstract. The performance of a hydrologic model depends on the rainfall input data, both spatially and temporally. As the spatial distribution of rainfall exerts a great influence on both runoff volumes and peak flows, the use of a distributed hydrologic model can improve the results in the case of convective rainfall in a basin where the storm area is smaller than the basin area. The aim of this study was to perform a sensitivity analysis of the rainfall time resolution on the results of a distributed hydrologic model in a flash-flood prone basin. Within such a catchment, floods are produced by heavy rainfall events with a large convective component. A second objective of the current paper is the proposal of a methodology that improves the radar rainfall estimation at a higher spatial and temporal resolution. Composite radar data from a network of three C-band radars with 6-min temporal and 2 × 2 km2 spatial resolution were used to feed the RIBS distributed hydrological model. A modification of the Window Probability Matching Method (gauge-adjustment method) was applied to four cases of heavy rainfall to improve the observed rainfall sub-estimation by computing new Z/R relationships for both convective and stratiform reflectivities. An advection correction technique based on the cross-correlation between two consecutive images was introduced to obtain several time resolutions from 1 min to 30 min. The RIBS hydrologic model was calibrated using a probabilistic approach based on a multiobjective methodology for each time resolution. A sensitivity analysis of rainfall time resolution was conducted to find the resolution that best represents the hydrological basin behaviour.

scholarly journals Extending the Predictability of Hydrometeorological Flood Events Using Radar Rainfall Nowcasting

2006 ◽  
Vol 7 (4) ◽  
pp. 660-677 ◽  
Author(s):  
Enrique R. Vivoni ◽  
Dara Entekhabi ◽  
Rafael L. Bras ◽  
Valeriy Y. Ivanov ◽  
Matthew P. Van Horne ◽  
...  
Keyword(s):  
Lead Time ◽  
Flash Flood ◽  
Spatial Scales ◽  
Surface Characteristics ◽  
Hydrologic Model ◽  
Flood Events ◽  
Catchment Scale ◽  
Radar Rainfall ◽  
Time Operation ◽  
Forecast Lead Time

Abstract The predictability of hydrometeorological flood events is investigated through the combined use of radar nowcasting and distributed hydrologic modeling. Nowcasting of radar-derived rainfall fields can extend the lead time for issuing flood and flash flood forecasts based on a physically based hydrologic model that explicitly accounts for spatial variations in topography, surface characteristics, and meteorological forcing. Through comparisons to discharge observations at multiple gauges (at the basin outlet and interior points), flood predictability is assessed as a function of forecast lead time, catchment scale, and rainfall spatial variability in a simulated real-time operation. The forecast experiments are carried out at temporal and spatial scales relevant for operational hydrologic forecasting. Two modes for temporal coupling of the radar nowcasting and distributed hydrologic models (interpolation and extended-lead forecasting) are proposed and evaluated for flood events within a set of nested basins in Oklahoma. Comparisons of the radar-based forecasts to persistence show the advantages of utilizing radar nowcasting for predicting near-future rainfall during flood event evolution.

scholarly journals Multiobjective sensitivity analysis and optimization of a distributed hydrologic model MOBIDIC

2014 ◽  
Vol 11 (3) ◽  
pp. 3505-3539 ◽  
Author(s):  
J. Yang ◽  
F. Castelli ◽  
Y. Chen
Keyword(s):  
Sensitivity Analysis ◽  
Water Balance ◽  
Surface Runoff ◽  
Hydrologic Model ◽  
Objective Functions ◽  
Analysis Techniques ◽  
Distributed Hydrologic Model ◽  
Conflicting Objectives ◽  
State Dependent Parameter Method ◽  
Initial Starting

Abstract. Calibration of distributed hydrologic models usually involves how to deal with the large number of distributed parameters and optimization problems with multiple but often conflicting objectives which arise in a natural fashion. This study presents a multiobjective sensitivity and optimization approach to handle these problems for a distributed hydrologic model MOBIDIC, which combines two sensitivity analysis techniques (Morris method and State Dependent Parameter method) with a multiobjective optimization (MOO) approach ϵ-NSGAII. This approach was implemented to calibrate MOBIDIC with its application to the Davidson watershed, North Carolina with three objective functions, i.e., standardized root mean square error of logarithmic transformed discharge, water balance index, and mean absolute error of logarithmic transformed flow duration curve, and its results were compared with those with a single objective optimization (SOO) with the traditional Nelder–Mead Simplex algorithm used in MOBIDIC by taking the objective function as the Euclidean norm of these three objectives. Results show: (1) the two sensitivity analysis techniques are effective and efficient to determine the sensitive processes and insensitive parameters: surface runoff and evaporation are very sensitive processes to all three objective functions, while groundwater recession and soil hydraulic conductivity are not sensitive and were excluded in the optimization; (2) both MOO and SOO lead to acceptable simulations, e.g., for MOO, average Nash–Sutcliffe is 0.75 in the calibration period and 0.70 in the validation period; (3) evaporation and surface runoff shows similar importance to watershed water balance while the contribution of baseflow can be ignored; (4) compared to SOO which was dependent of initial starting location, MOO provides more insight on parameter sensitivity and conflicting characteristics of these objective functions. Multiobjective sensitivity analysis and optimization provides an alternative way for future MOBIDIC modelling.

scholarly journals Effect of radar rainfall time resolution on the predictive capability of a distributed hydrologic model

2010 ◽  
Vol 7 (5) ◽  
pp. 7995-8043 ◽  
Author(s):  
A. Atencia ◽  
M. C. Llasat ◽  
L. Garrote ◽  
L. Mediero
Keyword(s):  
Hydrological Model ◽  
Radar Data ◽  
Hydrologic Model ◽  
Rainfall Data ◽  
Distributed Hydrological Model ◽  
Probability Matching ◽  
Radar Rainfall ◽  
Distributed Hydrologic Model ◽  
Surface Data ◽  
Distributed Hydrological Models

Abstract. The performance of distributed hydrological models depends on the resolution, both spatial and temporal, of the rainfall surface data introduced. The estimation of quantitative precipitation from meteorological radar or satellite can improve hydrological model results, thanks to an indirect estimation at higher spatial and temporal resolution. In this work, composed radar data from a network of three C-band radars, with 6-minutal temporal and 2 × 2 km2 spatial resolution, provided by the Catalan Meteorological Service, is used to feed the RIBS distributed hydrological model. A Window Probability Matching Method (gage-adjustment method) is applied to four cases of heavy rainfall to improve the observed rainfall sub-estimation in both convective and stratiform Z/R relations used over Catalonia. Once the rainfall field has been adequately obtained, an advection correction, based on cross-correlation between two consecutive images, was introduced to get several time resolutions from 1 min to 30 min. Each different resolution is treated as an independent event, resulting in a probable range of input rainfall data. This ensemble of rainfall data is used, together with other sources of uncertainty, such as the initial basin state or the accuracy of discharge measurements, to calibrate the RIBS model using probabilistic methodology. A sensitivity analysis of time resolutions was implemented by comparing the various results with real values from stream-flow measurement stations.

scholarly journals Characterization of physically based hydrologic model behaviour with temporal sensitivity analysis for flash floods in Mediterranean catchments

2013 ◽  
Vol 10 (1) ◽  
pp. 1375-1422
Author(s):  
P. A. Garambois ◽  
H. Roux ◽  
K. Larnier ◽  
W. Castaings ◽  
D. Dartus
Keyword(s):  
Sensitivity Analysis ◽  
Flash Flood ◽  
Soil Depth ◽  
Flash Floods ◽  
Hydrologic Model ◽  
Valuable Insight ◽  
Model Output ◽  
Flood Events ◽  
Extreme Flood ◽  
Physically Based

Abstract. This paper presents a detailed analysis of 10 flash flood events in the Mediterranean region using the distributed hydrological model MARINE. Characterizing catchment's response during flash flood events may provide a new and valuable insight into the processes involved for extreme flood response and their dependency on catchment properties and flood severity. The main objective of this study is to analyze hydrologic model sensitivity in the case of flash floods with a new approach in hydrology, allowing model outputs variance decomposition for temporal patterns of parameter sensitivity analysis. Such approaches enable ranking of uncertainty sources for non-linear and non-monotonic mappings with a low computational cost. This study uses hydrologic model and sensitivity analysis as learning tools to derive temporal sensitivity analysis with a variance based method in the case of 10 flash floods that occurred in the French Pyrenees and Cévennes foothills. This constitutes a huge dataset given the scarcity of data about flash flood events. With Nash performances above 0.73 on average for this extended set of validation events, the five sensitive parameters of MARINE distributed physically based model are analyzed. This contribution shows that soil depth explains more than 80% of model output variance when most hydrographs are peaking. Moreover the lateral subsurface transfer is responsible for 80% of model variance for some catchment-flood events' hydrographs during slow declining limbs. The unexplained variance of model output representing interactions between parameters reveals to be very low during modeled flood peaks and informs that model parsimonious parameterization is appropriate to tackle the problem of flash floods. Interactions observed after model initialization or rainfall intensity peaks incite to improve water partition representation between flow components and initialization itself. This paper gives a practical framework for application of this method to other models, landscapes and climatic conditions, potentially helping to improve processes understanding and representation.

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