scholarly journals State updating of a distributed hydrological model with Ensemble Kalman Filtering: effects of updating frequency and observation network density on forecast accuracy

2012 ◽  
Vol 16 (9) ◽  
pp. 3435-3449 ◽  
Author(s):  
O. Rakovec ◽  
A. H. Weerts ◽  
P. Hazenberg ◽  
P. J. J. F. Torfs ◽  
R. Uijlenhoet
Keyword(s):  
Hydrological Model ◽  
Forecast Accuracy ◽  
Markov Property ◽  
Distributed Hydrological Model ◽  
Time Step ◽  
Observation Network ◽  
Physically Based ◽  
Spatially Distributed ◽  
Observation Uncertainty ◽  
The Impact

Abstract. This paper presents a study on the optimal setup for discharge assimilation within a spatially distributed hydrological model. The Ensemble Kalman filter (EnKF) is employed to update the grid-based distributed states of such an hourly spatially distributed version of the HBV-96 model. By using a physically based model for the routing, the time delay and attenuation are modelled more realistically. The discharge and states at a given time step are assumed to be dependent on the previous time step only (Markov property). Synthetic and real world experiments are carried out for the Upper Ourthe (1600 km2), a relatively quickly responding catchment in the Belgian Ardennes. We assess the impact on the forecasted discharge of (1) various sets of the spatially distributed discharge gauges and (2) the filtering frequency. The results show that the hydrological forecast at the catchment outlet is improved by assimilating interior gauges. This augmentation of the observation vector improves the forecast more than increasing the updating frequency. In terms of the model states, the EnKF procedure is found to mainly change the pdfs of the two routing model storages, even when the uncertainty in the discharge simulations is smaller than the defined observation uncertainty.

scholarly journals State updating of a distributed hydrological model with Ensemble Kalman Filtering: effects of updating frequency and observation network density on forecast accuracy

2012 ◽  
Vol 9 (3) ◽  
pp. 3961-3999 ◽  
Author(s):  
O. Rakovec ◽  
A. H. Weerts ◽  
P. Hazenberg ◽  
P. J. J. F. Torfs ◽  
R. Uijlenhoet
Keyword(s):  
Ensemble Kalman Filter ◽  
Hydrological Model ◽  
Forecast Accuracy ◽  
Distributed Hydrological Model ◽  
Observation Network ◽  
Spatially Distributed ◽  
Observation Uncertainty ◽  
The Impact ◽  
Observation Vector ◽  
Ensemble Kalman Filtering

Abstract. This paper presents a study on the optimal setup for discharge assimilation within a spatially distributed hydrological model. The Ensemble Kalman filter (EnKF) is employed to update the grid-based distributed states of the hourly HBV-96 model. Synthetic and real world experiments are carried out for the Upper Ourthe (1600 km2), a quickly responding catchment in the Belgian Ardennes. We assess the impact on the forecasted discharge of (1) various sets of the spatially distributed discharge gauges and (2) the filtering frequency. The results show that the hydrological forecast at the catchment outlet is improved by assimilating interior gauges. This augmentation of the observation vector improves the forecast more than increasing the updating frequency. In terms of the model states, the EnKF scheme is mainly changing the pdf's of the two routing model storages. This also holds for situations, where the uncertainty in the discharge simulations is smaller than the defined observation uncertainty.

scholarly journals Impact of urbanization on flood of Shigu creek in Dongguan city

2018 ◽  
Vol 379 ◽  
pp. 55-60
Author(s):  
Luying Pan ◽  
Yangbo Chen ◽  
Tao Zhang
Keyword(s):  
Hydrological Model ◽  
Peak Flow ◽  
Flood Mitigation ◽  
Distributed Hydrological Model ◽  
Small Watershed ◽  
Rapid Urbanization ◽  
Dongguan City ◽  
Physically Based ◽  
Impact Of Urbanization ◽  
The Impact

Abstract. Shigu creek is a highly urbanized small watershed in Dongguan City. Due to rapid urbanization, quick flood response has been observed, which posted great threat to the flood security of Dongguan City. To evaluate the impact of urbanization on the flood changes of Shigu creek is very important for the flood mitigation of Shigu creek, which will provide insight for flood planners and managers for if to build a larger flood mitigation system. In this paper, the Land cover/use changes of Shigu creek from 1987–2015 induced by urbanization was first extracted from a local database, then, the Liuxihe model, a physically based distributed hydrological model, is employed to simulate the flood processes impacted by urbanization. Precipitation of 3 storms was used for flood processes simulation. The results show that the runoff coefficient and peak flow have increased sharply.

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

2020 ◽  
Vol 24 (11) ◽  
pp. 5519-5538
Author(s):  
Maxime Jay-Allemand ◽  
Pierre Javelle ◽  
Igor Gejadze ◽  
Patrick Arnaud ◽  
Pierre-Olivier Malaterre ◽  
...  
Keyword(s):  
Cost Function ◽  
Variational Approach ◽  
Hydrological Model ◽  
Flash Flood ◽  
Potential Evapotranspiration ◽  
Optimal Solution ◽  
Distributed Model ◽  
Distributed Hydrological Model ◽  
Time Step ◽  
The Impact

Abstract. Calibration of a conceptual distributed model is challenging due to a number of reasons, which include fundamental (model adequacy and identifiability) and algorithmic (e.g., local search vs. global search) issues. The aim of the presented study is to investigate the potential of the variational approach for calibrating a simple continuous hydrological model (GRD; Génie Rural distributed involved in several flash flood modeling applications. This model is defined on a rectangular 1 km2 resolution grid, with three parameters being associated with each cell. The Gardon d'Anduze watershed (543 km2) is chosen as the study benchmark. For this watershed, the discharge observations at five gauging stations, gridded rainfall and potential-evapotranspiration estimates are continuously available for the 2007–2018 period at an hourly time step. In the variational approach one looks for the optimal solution by minimizing the standard quadratic cost function, which penalizes the misfit between the observed and predicted values, under some additional a priori constraints. The cost function gradient is efficiently computed using the adjoint model. In numerical experiments, the benefits of using the distributed against the uniform calibration are measured in terms of the model predictive performance, in temporal, spatial and spatiotemporal validation, both globally and for particular flood events. Overall, distributed calibration shows encouraging results, providing better model predictions and relevant spatial distribution of some parameters. The numerical stability analysis has been performed to understand the impact of different factors on the calibration quality. This analysis indicates the possible directions for future developments, which may include considering a non-Gaussian likelihood and upgrading the model structure.

Evaluation of a Distributed Hydrological Model for the Guishui River Basin

2013 ◽  
Vol 353-356 ◽  
pp. 2511-2514
Author(s):  
Jing Zhang ◽  
Zhen Zheng ◽  
Hui Li Gong
Keyword(s):  
River Basin ◽  
Surface Runoff ◽  
Hydrological Model ◽  
Scientific Basis ◽  
Scale Model ◽  
Distributed Hydrological Model ◽  
Mike She ◽  
Structural Principle ◽  
Physically Based ◽  
The Impact

At present, the application of various hydrological model provides scientific basis for the realization of the water resources management. MIKE SHE model is a classic physically-based watershed-scale model with great advantages in the coupling of surface water and ground water. In the paper, the development history and the present study situation of the distributed hydrological model MIKE SHE and the structural principle of the model is summarized. Furthermore, the ability and applicability of MIKE SHE model was preliminary evaluated for simulating surface runoff in the Guishui river basin in Beijing, China. The impact of different land use practices (the year of 1980 and 2005) on the hydrological response of the selected basin was initially assessed. Overall, the model was able to simulate surface runoff reasonably on annual intervals, representing all the hydrological components adequately.

Toward a Robust Canopy Hydrology Scheme with Precipitation Subgrid Variability

2007 ◽  
Vol 8 (3) ◽  
pp. 439-446 ◽  
Author(s):  
Dagang Wang ◽  
Guiling Wang
Keyword(s):  
Land Surface ◽  
Surface Characteristics ◽  
Hydrological Processes ◽  
Canopy Interception ◽  
Time Step ◽  
Covered Area ◽  
Surface Models ◽  
Physically Based ◽  
Interception Loss ◽  
The Impact

Abstract Representation of the canopy hydrological processes has been challenging in land surface modeling due to the subgrid heterogeneity in both precipitation and surface characteristics. The Shuttleworth dynamic–statistical method is widely used to represent the impact of the precipitation subgrid variability on canopy hydrological processes but shows unwanted sensitivity to temporal resolution when implemented into land surface models. This paper presents a canopy hydrology scheme that is robust at different temporal resolutions. This scheme is devised by applying two physically based treatments to the Shuttleworth scheme: 1) the canopy hydrological processes within the rain-covered area are treated separately from those within the nonrain area, and the scheme tracks the relative rain location between adjacent time steps; and 2) within the rain-covered area, the canopy interception is so determined as to sustain the potential evaporation from the wetted canopy or is equal to precipitation, whichever is less, to maintain somewhat wet canopy during any rainy time step. When applied to the Amazon region, the new scheme establishes interception loss ratios of 0.3 at a 10-min time step and 0.23 at a 2-h time step. Compared to interception loss ratios of 0.45 and 0.09 at the corresponding time steps established by the original Shuttleworth scheme, the new scheme is much more stable under different temporal resolutions.

scholarly journals Inverse distributed hydrological modelling of Alpine catchments

2006 ◽  
Vol 10 (3) ◽  
pp. 395-412 ◽  
Author(s):  
H. Kunstmann ◽  
J. Krause ◽  
S. Mayr
Keyword(s):  
Parameter Estimation ◽  
Hydrological Model ◽  
Model Performance ◽  
Horizontal Resolution ◽  
Nonlinear Parameter ◽  
Model Complexity ◽  
Distributed Hydrological Model ◽  
Nonlinear Parameter Estimation ◽  
Estimated Parameters ◽  
Physically Based

Abstract. Even in physically based distributed hydrological models, various remaining parameters must be estimated for each sub-catchment. This can involve tremendous effort, especially when the number of sub-catchments is large and the applied hydrological model is computationally expensive. Automatic parameter estimation tools can significantly facilitate the calibration process. Hence, we combined the nonlinear parameter estimation tool PEST with the distributed hydrological model WaSiM. PEST is based on the Gauss-Marquardt-Levenberg method, a gradient-based nonlinear parameter estimation algorithm. WaSiM is a fully distributed hydrological model using physically based algorithms for most of the process descriptions. WaSiM was applied to the alpine/prealpine Ammer River catchment (southern Germany, 710 km2 in a 100×100 m2 horizontal resolution. The catchment is heterogeneous in terms of geology, pedology and land use and shows a complex orography (the difference of elevation is around 1600 m). Using the developed PEST-WaSiM interface, the hydrological model was calibrated by comparing simulated and observed runoff at eight gauges for the hydrologic year 1997 and validated for the hydrologic year 1993. For each sub-catchment four parameters had to be calibrated: the recession constants of direct runoff and interflow, the drainage density, and the hydraulic conductivity of the uppermost aquifer. Additionally, five snowmelt specific parameters were adjusted for the entire catchment. Altogether, 37 parameters had to be calibrated. Additional a priori information (e.g. from flood hydrograph analysis) narrowed the parameter space of the solutions and improved the non-uniqueness of the fitted values. A reasonable quality of fit was achieved. Discrepancies between modelled and observed runoff were also due to the small number of meteorological stations and corresponding interpolation artefacts in the orographically complex terrain. Application of a 2-dimensional numerical groundwater model partly yielded a slight decrease of overall model performance when compared to a simple conceptual groundwater approach. Increased model complexity therefore did not yield in general increased model performance. A detailed covariance analysis was performed allowing to derive confidence bounds for all estimated parameters. The correlation between the estimated parameters was in most cases negligible, showing that parameters were estimated independently from each other.

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