scholarly journals Comparison of hydrological model structures based on recession and low flow simulations

2011 ◽  
Vol 8 (4) ◽  
pp. 6833-6866 ◽  
Author(s):  
M. Staudinger ◽  
K. Stahl ◽  
J. Seibert ◽  
M. P. Clark ◽  
L. M. Tallaksen
Keyword(s):  
Hydrological Model ◽  
Lower Layer ◽  
Model Performance ◽  
Low Flow ◽  
Model Structure ◽  
Hydrological Models ◽  
Flow Simulations ◽  
Low Flows ◽  
The Impact ◽  
Model Structures

Abstract. Low flows are often poorly reproduced by commonly used hydrological models, which are traditionally designed to meet peak flow situations. Hence, there is a need to improve hydrological models for low flow prediction. This study assessed the impact of model structure on low flow simulations and recession behaviour using the Framework for Understanding Structural Errors (FUSE). FUSE identifies the set of subjective decisions made when building a hydrological model, and provides multiple options for each modeling decision. Altogether 79 models were created and applied to simulate stream flows in the snow dominated headwater catchment Narsjø in Norway (119 km2). All models were calibrated using an automatic optimisation method. The results showed that simulations of summer low flows were poorer than simulations of winter low flows, reflecting the importance of different hydrological processes. The model structure influencing winter low flow simulations is the lower layer architecture, whereas various model structures were identified to influence model performance during summer.

scholarly journals Comparison of hydrological model structures based on recession and low flow simulations

2011 ◽  
Vol 15 (11) ◽  
pp. 3447-3459 ◽  
Author(s):  
M. Staudinger ◽  
K. Stahl ◽  
J. Seibert ◽  
M. P. Clark ◽  
L. M. Tallaksen
Keyword(s):  
Hydrological Model ◽  
Lower Layer ◽  
Model Performance ◽  
Low Flow ◽  
Model Structure ◽  
Hydrological Models ◽  
Flow Simulations ◽  
Low Flows ◽  
The Impact ◽  
Model Structures

Abstract. Low flows are often poorly reproduced by commonly used hydrological models, which are traditionally designed to meet peak flow situations. Hence, there is a need to improve hydrological models for low flow prediction. This study assessed the impact of model structure on low flow simulations and recession behaviour using the Framework for Understanding Structural Errors (FUSE). FUSE identifies the set of subjective decisions made when building a hydrological model and provides multiple options for each modeling decision. Altogether 79 models were created and applied to simulate stream flows in the snow dominated headwater catchment Narsjø in Norway (119 km2). All models were calibrated using an automatic optimisation method. The results showed that simulations of summer low flows were poorer than simulations of winter low flows, reflecting the importance of different hydrological processes. The model structure influencing winter low flow simulations is the lower layer architecture, whereas various model structures were identified to influence model performance during summer.

scholarly journals The impact of hydrological model structure on the simulation of extreme runoff events

2021 ◽  
Vol 21 (3) ◽  
pp. 961-976
Author(s):  
Gijs van Kempen ◽  
Karin van der Wiel ◽  
Lieke Anna Melsen
Keyword(s):  
Hydrological Model ◽  
Low Flow ◽  
Temperate Climate ◽  
Hydrological Process ◽  
Model Structure ◽  
Hydrological Models ◽  
Climate Zones ◽  
The Impact ◽  
Model Structures ◽  
Runoff Events

Abstract. Hydrological extremes affect societies and ecosystems around the world in many ways, stressing the need to make reliable predictions using hydrological models. However, several different hydrological models can be selected to simulate extreme events. A difference in hydrological model structure results in a spread in the simulation of extreme runoff events. We investigated the impact of different model structures on the magnitude and timing of simulated extreme high- and low-flow events by combining two state-of-the-art approaches: a modular modelling framework (FUSE) and large ensemble meteorological simulations. This combination of methods created the opportunity to isolate the impact of specific hydrological process formulations at long return periods without relying on statistical models. We showed that the impact of hydrological model structure was larger for the simulation of low-flow compared to high-flow events and varied between the four evaluated climate zones. In cold and temperate climate zones, the magnitude and timing of extreme runoff events were significantly affected by different parameter sets and hydrological process formulations, such as evaporation. In the arid and tropical climate zones, the impact of hydrological model structures on extreme runoff events was smaller. This novel combination of approaches provided insights into the importance of specific hydrological process formulations in different climate zones, which can support adequate model selection for the simulation of extreme runoff events.

scholarly journals The impact of hydrological model structure on the simulation of extreme runoff events

2020 ◽  
Author(s):  
Gijs van Kempen ◽  
Karin van der Wiel ◽  
Lieke Anna Melsen
Keyword(s):  
Hydrological Model ◽  
Low Flow ◽  
Temperate Climate ◽  
Hydrological Process ◽  
Model Structure ◽  
Hydrological Models ◽  
Climate Zones ◽  
The Impact ◽  
Model Structures ◽  
Runoff Events

Abstract. Hydrological extremes affect societies and ecosystems around the world in many ways, stressing the need to make reliable predictions using hydrological models. However, several hydrological models can be selected to simulate extreme events. A difference in hydrological model structure results in a spread in the simulation of extreme runoff events. We investigated the impact of different model structures on the magnitude and timing of simulated extreme high- and low-flow events, by combining two state-of-the-art approaches; a modular modelling framework (FUSE) and large ensemble meteorological simulations. This combination of methods created the opportunity to isolate the impact of specific hydrological process formulations at long return periods without relying on statistical models. We showed that the impact of hydrological model structure was larger for the simulation of low-flow compared to high-flow events and varied between the four evaluated climate zones. In cold and temperate climate zones, the magnitude and timing of extreme runoff events were significantly affected by different parameter sets and hydrological process formulations, such as evaporation. The impact of hydrological model structures on extreme runoff events was smaller in the arid and tropical climate zones. This novel combination of approaches provided insights into the importance of specific hydrological processes formulations in different climate zones, which can support adequate model selection for the simulation of extreme runoff events.

Investigating hydrological model versatility to simulate extreme flood events 

2021 ◽  
Author(s):  
Daniela Peredo Ramirez ◽  
Maria-Helena Ramos ◽  
Vazken Andréassian ◽  
Ludovic Oudin
Keyword(s):  
Hydrological Model ◽  
Model Performance ◽  
Original Model ◽  
Model Structure ◽  
Model Adaptation ◽  
Flood Events ◽  
Runoff Generation ◽  
Local Climate ◽  
Extreme Flood ◽  
The Impact

<p><span>High-impact flood events in the Mediterranean region are often the result of a combination of local climate and topographic characteristics of the region. Therefore, the way runoff generation processes are represented in hydrological models is a key factor to simulate and forecast floods. In this study, we adapt an existing model in order to increase its versatility to simulate flood events occurring under different conditions: during or after wet periods and after long and dry summer periods. The model adaptation introduces a dependency on rainfall intensity in the production function. The impact of this adaptation is analysed considering model performance over selected flood events and also over a continuous 10-year period of flows. The event-based assessment showed that the adapted model structure performs better than or equal to the original model structure in terms of differences in the timing of peak discharges, regardless of the season of the year when the flood occurs. The most important improvement was observed in the simulation of the magnitude of the flood peaks. A visualisation of model versatility is proposed, which allows detecting the time steps when the new model structure tends to behave more similarly or differently from the original model structure in terms of runoff production. Overall, the results show the potential of the model adaptation proposed to simulate floods originated by different hydrological processes and the value of increasing hydrological model versatility to simulate extreme events.</span></p>

scholarly journals Replication of ecologically relevant hydrological indicators following a covariance approach to hydrological model parameterisation

2018 ◽  
Author(s):  
Annie Visser ◽  
Lindsay Beevers ◽  
Sandhya Patidar
Keyword(s):  
Goodness Of Fit ◽  
Hydrological Model ◽  
Model Performance ◽  
Rate Of Change ◽  
Hydrological Models ◽  
Hydrologic Alteration ◽  
Output Time ◽  
Complex Indicators ◽  
The Impact

Abstract. Hydrological models can be used to assess the impact of hydrologic alteration on the river ecosystem. However, there are considerable limitations and uncertainties associated with the replication of the required, ecologically relevant hydrological indicators. Vogel and Sankarasubramanian's covariance approach to model parameterisation represents a shift away from the traditional calibration-validation goodness-of-fit paradigm. Using the covariance structures of the observed input and simulated output time-series, the region of parameter space which best captures (replicates) the characteristics of a hydrological indicator may be identified. Through a case study, a modified covariance approach is applied with a view to replicating a suite of seven ecologically relevant hydrological indicators. Model performance and consistency are assessed relative to four comparative studies. The ability of the approach to address the limitations associated with traditional calibration-validation is further considered. Benefits of the approach include an overall reduction in model uncertainty whilst also reducing overall time-demands. Difficulties in the replication of complex indicators, such as rate of change, are in line with prior work. Nonetheless, the study illustrates that consistency in the replication of hydrological indicators is achievable; additionally, the replication of magnitude indices is markedly improved upon.

scholarly journals SHETRAN and HEC HMS Model Evaluation for Runoff and Soil Moisture Simulation in the Jičinka River Catchment (Czech Republic)

Water ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 872
Author(s):  
Vesna Đukić ◽  
Ranka Erić
Keyword(s):  
Soil Moisture ◽  
Czech Republic ◽  
Hydrological Model ◽  
Flash Flood ◽  
Model Performance ◽  
Rainfall Runoff ◽  
The Czech Republic ◽  
River Catchment ◽  
Hydrological Variable ◽  
Model Structures

Due to the improvement of computation power, in recent decades considerable progress has been made in the development of complex hydrological models. On the other hand, simple conceptual models have also been advanced. Previous studies on rainfall–runoff models have shown that model performance depends very much on the model structure. The purpose of this study is to determine whether the use of a complex hydrological model leads to more accurate results or not and to analyze whether some model structures are more efficient than others. Different configurations of the two models of different complexity, the Système Hydrologique Européen TRANsport (SHETRAN) and Hydrologic Modeling System (HEC-HMS), were compared and evaluated in simulating flash flood runoff for the small (75.9 km2) Jičinka River catchment in the Czech Republic. The two models were compared with respect to runoff simulations at the catchment outlet and soil moisture simulations within the catchment. The results indicate that the more complex SHETRAN model outperforms the simpler HEC HMS model in case of runoff, but not for soil moisture. It can be concluded that the models with higher complexity do not necessarily provide better model performance, and that the reliability of hydrological model simulations can vary depending on the hydrological variable under consideration.

Stepwise improvement of hydrological models using satellite-based evaporation and total water storage estimations

2021 ◽  
Author(s):  
Markus Hrachowitz ◽  
Petra Hulsman ◽  
Hubert Savenije
Keyword(s):  
Model Calibration ◽  
Hydrological Model ◽  
Model Development ◽  
Water Storage ◽  
Spatiotemporal Variability ◽  
Model Structure ◽  
Hydrological Models ◽  
Total Water ◽  
Spatiotemporal Model ◽  
Multiple Variables

<p>Hydrological models are often calibrated with respect to flow observations at the basin outlet. As a result, flow predictions may seem reliable but this is not necessarily the case for the spatiotemporal variability of system-internal processes, especially in large river basins. Satellite observations contain valuable information not only for poorly gauged basins with limited ground observations and spatiotemporal model calibration, but also for stepwise model development. This study explored the value of satellite observations to improve our understanding of hydrological processes through stepwise model structure adaption and to calibrate models both temporally and spatially. More specifically, satellite-based evaporation and total water storage anomaly observations were used to diagnose model deficiencies and to subsequently improve the hydrological model structure and the selection of feasible parameter sets. A distributed, process based hydrological model was developed for the Luangwa river basin in Zambia and calibrated with respect to discharge as benchmark. This model was modified stepwise by testing five alternative hypotheses related to the process of upwelling groundwater in wetlands, which was assumed to be negligible in the benchmark model, and the spatial discretization of the groundwater reservoir. Each model hypothesis was calibrated with respect to 1) discharge and 2) multiple variables simultaneously including discharge and the spatiotemporal variability in the evaporation and total water storage anomalies. The benchmark model calibrated with respect to discharge reproduced this variable well, as also the basin-averaged evaporation and total water storage anomalies. However, the evaporation in wetland dominated areas and the spatial variability in the evaporation and total water storage anomalies were poorly modelled. The model improved the most when introducing upwelling groundwater flow from a distributed groundwater reservoir and calibrating it with respect to multiple variables simultaneously. This study showed satellite-based evaporation and total water storage anomaly observations provide valuable information for improved understanding of hydrological processes through stepwise model development and spatiotemporal model calibration.</p>

Hydrological modelling and anthropogenic water use

2021 ◽  
Author(s):  
Ponnambalam Rameshwaran ◽  
Ali Rudd ◽  
Vicky Bell ◽  
Matt Brown ◽  
Helen Davies ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Use ◽  
Hydrological Model ◽  
Model Performance ◽  
River Flows ◽  
Discharge Data ◽  
New Approach ◽  
Water Demands ◽  
The Impact ◽  
Grid Based

<p>Despite Britain’s often-rainy maritime climate, anthropogenic water demands have a significant impact on river flows, particularly during dry summers. In future years, projected population growth and climate change are likely to increase the demand for water and lead to greater pressures on available freshwater resources.</p><p>Across England, abstraction (from groundwater, surface water or tidal sources) and discharge data along with ‘Hands off Flow’ conditions are available for thousands of individual locations; each with a licence for use, an amount, an indication of when abstraction can take place, and the actual amount of water abstracted (generally less than the licence amount). Here we demonstrate how these data can be used in combination to incorporate anthropogenic artificial influences into a grid-based hydrological model. Model simulations of both high and low river flows are generally improved when abstractions and discharges are included, though for some catchments model performance decreases. The new approach provides a methodological baseline for further work investigating the impact of anthropogenic water use and projected climate change on future river flows.</p>

scholarly journals Impact of model structure on flow simulation and hydrological realism: from a lumped to a semi-distributed approach

2017 ◽  
Vol 21 (8) ◽  
pp. 3937-3952 ◽  
Author(s):  
Federico Garavaglia ◽  
Matthieu Le Lay ◽  
Fréderic Gottardi ◽  
Rémy Garçon ◽  
Joël Gailhard ◽  
...  
Keyword(s):  
Hydrological Model ◽  
Snow Water Equivalent ◽  
Flow Simulation ◽  
Evaluation Framework ◽  
Model Structure ◽  
Runoff Simulation ◽  
Snow Cover Area ◽  
Mountainous Regions ◽  
Distributed Approach ◽  
The Impact

Abstract. Model intercomparison experiments are widely used to investigate and improve hydrological model performance. However, a study based only on runoff simulation is not sufficient to discriminate between different model structures. Hence, there is a need to improve hydrological models for specific streamflow signatures (e.g., low and high flow) and multi-variable predictions (e.g., soil moisture, snow and groundwater). This study assesses the impact of model structure on flow simulation and hydrological realism using three versions of a hydrological model called MORDOR: the historical lumped structure and a revisited formulation available in both lumped and semi-distributed structures. In particular, the main goal of this paper is to investigate the relative impact of model equations and spatial discretization on flow simulation, snowpack representation and evapotranspiration estimation. Comparison of the models is based on an extensive dataset composed of 50 catchments located in French mountainous regions. The evaluation framework is founded on a multi-criterion split-sample strategy. All models were calibrated using an automatic optimization method based on an efficient genetic algorithm. The evaluation framework is enriched by the assessment of snow and evapotranspiration modeling against in situ and satellite data. The results showed that the new model formulations perform significantly better than the initial one in terms of the various streamflow signatures, snow and evapotranspiration predictions. The semi-distributed approach provides better calibration–validation performance for the snow cover area, snow water equivalent and runoff simulation, especially for nival catchments.

Sign in / Sign up

Export Citation Format

Share Document