Technical review of large-scale hydrological models for implementation in operational flood forecasting schemes on continental level

Kauffeldt, Anna; Wetterhall, F.; Pappenberger, Florian; Salamon, Peter; Thielen, Joanna

doi:10.1016/j.envsoft.2015.09.009

Cited by 209 publications

(133 citation statements)

References 80 publications

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“…At the same time, it is possible to focus on regionally relevant processes that are usually not included or not well resolved in global models. In South America, for example, several previous studies suggested that lateral water fluxes in large lowland rivers should be resolved using hydrodynamic routing (e.g., Paiva et al, 2011Paiva et al, , 2013Paz et al, 2011Paz et al, , 2014Yamazaki et al, 2011;Pontes et 10 al., 2017;Zhao et al, 2017), while GHMs generally apply methods based on constant/variable velocity or a kinematic simplification of the St. Venant equations (see the overview by Kauffeldt et al, 2016 andBierkens, 2015). Even if LSMs can be offline coupled to more physically based global river routing models (e.g., Yamazaki et al, 2011;Getirana et al, 2017b), calibration in the latter is likely to compensate for errors in runoff generation (Pappenberger et al, 2010;Hodges, 2013) and lack of relevant vertical hydrological processes linked to river-floodplain dynamics (e.g., Pedinotti 15 et al, 2012;Paz et al, 2014;Fleischmann et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Toward continental hydrologic–hydrodynamic modeling in South America

Paiva¹,

Siqueira²,

Fleischmann³

et al. 2018

Preprint

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Abstract. Providing reliable estimates of streamflow and hydrological fluxes is a major challenge for water resources management over national and transnational basins in South America. Global hydrological models and land surface models are a possible solution to simulate the terrestrial water cycle at the continental scale, but issues on parameterization and limitations in representing lowland river systems put into question their utility for basin-scale analysis and to deliver daily 15 discharges to meet local needs. In an attempt to overcome such limitations, we extended a regional, fully coupled hydrologic-hydrodynamic model (MGB) to the continental domain of South America and assessed its performance using daily river discharges, water levels from independent sources (in situ, satellite altimetry), estimates of terrestrial water storage (TWS) and evapotranspiration (ET) from remote sensing and other available global datasets. In addition, river discharges were compared with outputs from global models acquired through the eartH2Observe project (HTESSEL/CaMa-20 Flood, LISFLOOD and WaterGAP3), providing the first cross-scale assessment (regional/continental  global models) that makes use of spatially consistent daily discharge data. A satisfactory representation of discharges and water levels was obtained (NSE > 0.6 in 55 % of the cases) and MGB was able to capture patterns of seasonality and magnitude of TWS and ET especially over the largest basins of South America. Continental-scale modeling significantly improved discharge estimates when compared with global models, which resulted in a large number of gauges with negative (or close to 0) NSE 25 values. Models were largely affected by positive bias mainly over East/Northeast Brazil and Argentina as well as over regions of Sao Francisco and Parnaiba basins, while major issues on flow timing were observed in regions affected by floodplain processes such as the Amazon, La Plata, Tocantins-Araguaia, Orinoco and Magdalena basins. We state that efforts in calibrating rainfall-runoff parameters within large basins are necessary to simulate daily river discharges appropriately in this continent, but implementing a hydrodynamic routing component is also important. We hope that our 30 study provides further insights about hydrological simulation in South America, helping to reduce the gap between global and regional hydrological modeling communities.Hydrol. Earth Syst. Sci. Discuss., https://doi

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Section: Introductionmentioning

confidence: 99%

Toward continental hydrologic–hydrodynamic modeling in South America

Paiva¹,

Siqueira²,

Fleischmann³

et al. 2018

Preprint

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“…Understanding the limitations and uncertainties in hydrological models used for both high and low flow estimations, and associated decision-making processes, has long been a concern but continues to attract important academic research, review and commentary (e.g., Beck et al 2016;Daniell and Daniell 2006;Juston et al 2013;Kauffeldt et al 2016;Salvadore, Bronders, and Batelaan 2015;Wood 1978).…”

Section: Improving the Understanding And Practice Of Hydrological Modmentioning

confidence: 99%

Improving the understanding and practice of hydrological modelling: recent insights and discussion

Daniell

2017

Australasian Journal of Water Resources

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“…For example, past application of a distributed hydrological model for large-watershed flood forecasting is at a resolution coarser than 1 km grid cell (Lohmann et al, 1998;Vieux et al, 2004;Stisen et al, 2008;Rwetabula et al, 2007); the models employed in the panEuropean Flood Awareness System (EFAS; Thielen et al, 2009Thielen et al, , 2010Sood and Smakhtin, 2015;Kauffeldt et al, 2016) are at 1-10 km grid cell, which makes the result only applicable for flood warning.…”

Section: Introductionmentioning

confidence: 99%

“…For this reason, the distributed hydrological model is usually regarded as having the potential to better simulate or forecast the watershed flood (Ambroise et al, 1996;Chen et al, 2016). Employing a distributed hydrological model for watershed food forecasting has been the new trend (Vieux et al, 2004;Chen et al, 2016;Cattoën et al, 2016;Witold et al, 2016;Kauffeldt et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Large-watershed flood forecasting with high-resolution distributed hydrological model

Chen

Wang

et al. 2017

Hydrol. Earth Syst. Sci.

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Abstract. A distributed hydrological model has been successfully used in small-watershed flood forecasting, but there are still challenges for the application in a large watershed, one of them being the model's spatial resolution effect. To cope with this challenge, two efforts could be made; one is to improve the model's computation efficiency in a large watershed, the other is implementing the model on a highperformance supercomputer. This study sets up a physically based distributed hydrological model for flood forecasting of the Liujiang River basin in south China. Terrain data digital elevation model (DEM), soil and land use are downloaded from the website freely, and the model structure with a high resolution of 200 m × 200 m grid cell is set up. The initial model parameters are derived from the terrain property data, and then optimized by using the Particle Swarm Optimization (PSO) algorithm; the model is used to simulate 29 observed flood events. It has been found that by dividing the river channels into virtual channel sections and assuming the cross section shapes as trapezoid, the Liuxihe model largely increases computation efficiency while keeping good model performance, thus making it applicable in larger watersheds. This study also finds that parameter uncertainty exists for physically deriving model parameters, and parameter optimization could reduce this uncertainty, and is highly recom-

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Technical review of large-scale hydrological models for implementation in operational flood forecasting schemes on continental level

Cited by 209 publications

References 80 publications

Toward continental hydrologic–hydrodynamic modeling in South America

Toward continental hydrologic–hydrodynamic modeling in South America

Improving the understanding and practice of hydrological modelling: recent insights and discussion

Large-watershed flood forecasting with high-resolution distributed hydrological model

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