scholarly journals Impact of radar-rainfall error structure on estimated flood magnitude across scales: An investigation based on a parsimonious distributed hydrological model

2012 ◽  
Vol 48 (10) ◽  
Author(s):  
Luciana K. Cunha ◽  
Pradeep V. Mandapaka ◽  
Witold F. Krajewski ◽  
Ricardo Mantilla ◽  
Allen A. Bradley
Keyword(s):  
Hydrological Model ◽  
Distributed Hydrological Model ◽  
Radar Rainfall ◽  
Error Structure ◽  
Flood Magnitude

scholarly journals On the potential of variational calibration for a fully distributed hydrological model: application on a Mediterranean catchment

2019 ◽  
Author(s):  
Maxime Jay-Allemand ◽  
Pierre Javelle ◽  
Igor Gejadze ◽  
Patrick Arnaud ◽  
Pierre-Olivier Malaterre ◽  
...  
Keyword(s):  
Hydrological Model ◽  
Weather Forecasting ◽  
Flash Flood ◽  
Estimation Method ◽  
Distributed Hydrological Model ◽  
Initial State ◽  
Ungauged Catchments ◽  
Temporal Dimension ◽  
Radar Rainfall ◽  
Additional Constraints

Abstract. Flash flood alerts in metropolitan France are provided by SCHAPI (Service Central Hydrométéorologique et d’Appui à la Prévision des Inondations) through the Vigicrues Flash service, which is designed to work in ungauged catchments. The AIGA method implemented in Vigicrues Flash is designed for flood forecasting on small- and medium-scale watersheds. It is based on a distributed hydrological model accounting for spatial variability of the rainfall and the catchment properties, based on the radar rainfall observation inputs. Calibration of distributed parameters describing these properties with high resolution is difficult, both technically (in terms of the estimation method), and because of the identifiability issues. Indeed, the number of parameters to be calibrated is much greater than the number of spatial locations where the discharge observations are usually available. However, the flood propagation is a dynamic process, so observations have also a temporal dimension. This must be larger enough to comprise a representative set of events. In order to fully benefit from using the AIGA method, we consider its hydrological model (GRD) in combination with the variational estimation (data assimilation) method. In this method, the optimal set of parameters is found by minimizing the objective function which includes the misfit between the observed and predicted values and some additional constraints. The minimization process requires the gradient of the cost function with respect to all control parameters, which is efficiently computed using the adjoint model. The variational estimation method is scalable, fast converging, and offers a convenient framework for introducing additional constraints relevant to hydrology. It can be used both for calibrating the parameters and estimating the initial state of the hydrological system for short range forecasting (in a manner used in weather forecasting). The study area is the Gardon d’Anduze watershed where four gauging stations are available. In numerical experiments, the benefits of using the distributed against the uniform calibration are analysed in terms of the model predictive performance. Distributed calibration shows encouraging results with better model prediction at gauged and ungauged locations.

scholarly journals Real-Time Analysis and Forecasting of Multisite River Flow Using a Distributed Hydrological Model

2014 ◽  
Vol 2014 ◽  
pp. 1-9
Author(s):  
Mingdong Sun ◽  
Gwangseob Kim
Keyword(s):  
Real Time ◽  
River Flow ◽  
Hydrological Model ◽  
Dynamic State ◽  
Distributed Hydrological Model ◽  
Time Analysis ◽  
Radar Rainfall ◽  
Real Time Analysis ◽  
Nakdong River Basin ◽  
Time Calibration

A spatial distributed hydrological forecasting system was developed to promote the analysis of river flow dynamic state in a large basin. The research presented the real-time analysis and forecasting of multisite river flow in the Nakdong River Basin using a distributed hydrological model with radar rainfall forecast data. A real-time calibration algorithm of hydrological distributed model was proposed to investigate the particular relationship between the water storage and basin discharge. Demonstrate the approach of simulating multisite river flow using a distributed hydrological model couple with real-time calibration and forecasting of multisite river flow with radar rainfall forecasts data. The hydrographs and results exhibit that calibrated flow simulations are very approximate to the flow observation at all sites and the accuracy of forecasting flow is gradually decreased with lead times extending from 1 hr to 3 hrs. The flow forecasts are lower than the flow observation which is likely caused by the low estimation of radar rainfall forecasts. The research has well demonstrated that the distributed hydrological model is readily applicable for multisite real-time river flow analysis and forecasting in a large basin.

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 Influence of Rainfall Data with Different Spatial Resolutions on Flood Forecasting Reliability

10.29007/74bp ◽  
2018 ◽  
Author(s):  
Mamoru Miyamoto ◽  
Kazuhiro Matsumoto
Keyword(s):  
River Discharge ◽  
Hydrological Model ◽  
Radar Data ◽  
Flood Forecasting ◽  
Rainfall Data ◽  
Error Assessment ◽  
Distributed Hydrological Model ◽  
Radar Rainfall ◽  
Convergence Results ◽  
Gauge Data

Recent advancements in precipitation observation technology make it possible to precisely describe the intensity and temporal-spatial distribution of heavy rainfall, which can cause severe floods and inundations. Such technologies have also increased the accuracy of flood forecasting. However, error factors in flood forecasting remain to be solved, originating in not only input data but also model structure and calibration. Thus, this study focused on convergence results of errors in parameter optimization of the PWRI Distributed Hydrological Model and the reproducibility of river discharge. The reliability of ground-gauge and C-band-radar rainfall is compared in terms of flood forecasting under the condition of the minimum error due to calibration. Although the convergence results showed that C-band radar rainfall was superior to ground gauge rainfall, both were equally effective in reproducing river discharge with a high NSE of 0.9 at a station with error assessment. On the other hand, the reproducibility of river discharge with C-band radar data was highly superior to that with ground gauge data at a station without error assessment. This indicates that grid-based high resolution rainfall data is necessary for basin-wide flood forecasting.

Implications of radar rainfall estimates uncertainty on distributed hydrological model predictions

2011 ◽  
Vol 100 (2-3) ◽  
pp. 237-245 ◽  
Author(s):  
Kai Schröter ◽  
Xavier Llort ◽  
Carlos Velasco-Forero ◽  
Manfred Ostrowski ◽  
Daniel Sempere-Torres
Keyword(s):  
Hydrological Model ◽  
Distributed Hydrological Model ◽  
Radar Rainfall ◽  
Model Predictions ◽  
Rainfall Estimates

scholarly journals Methodology for post-event analysis of flash floods - Svacenický Creek case study

2011 ◽  
Vol 41 (3) ◽  
pp. 235-250 ◽  
Author(s):  
Lotta Blaškovičová ◽  
Oliver Horvát ◽  
Kamila Hlavčová ◽  
Silvia Kohnová ◽  
Ján Szolgay
Keyword(s):  
Hydrological Model ◽  
Flash Flood ◽  
Curve Number ◽  
Flash Floods ◽  
Event Analysis ◽  
Distributed Hydrological Model ◽  
Radar Rainfall ◽  
Flood Peak ◽  
Spatially Distributed

Methodology for post-event analysis of flash floods - Svacenický Creek case study In this paper a methodology for a post-event analysis of a flash flood and estimation of the flood peak and volume are developed and tested. The selected flash flood occurred on the 6th of June, 2009 in the Svacenický Creek Basin. To understand rainfall-runoff processes during this extreme flash flood, the runoff response was simulated using the spatially-distributed hydrological model KLEM (Kinematic Local Excess Model). The distributed hydrological model is based on the availability of raster information about the landscape's topography, soil and vegetation properties and radar rainfall data. In the model, the SCS-Curve Number procedure is applied to a grid for the spatially-distributed representation of the runoff-generating processes. A description of the drainage system's response is used to represent the runoff's routing. The simulated values achieved by the KLEM model were comparable with the maximum peak estimated on the basis of the post-event surveying. The consistency of the estimated and simulated values from the KLEM model was evident both in time and space, and the methodology has shown its practical applicability.

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