scholarly journals Diagnostic of a regional distributed hydrological model through hydrological signatures

2020 ◽  
Author(s):  
Flora Branger ◽  
Ivan Horner ◽  
Jean Marçais ◽  
Yvan Caballero ◽  
Isabelle Braud
Keyword(s):  
Hydrological Model ◽  
Performance Criteria ◽  
Land Uses ◽  
Distributed Hydrological Model ◽  
Future Studies ◽  
Distributed Models ◽  
Evaluation Approach ◽  
Model Parameterization ◽  
Parameter Values ◽  
Hydrological Signatures

<p>Distributed models are useful tools for the assessment of water resources in a context of global change. However, due to the high spatial heterogeneity of the corresponding catchments, these models end up being quite complex with a high number of parameters. In particular, it is not easy to obtain good performances and physically sounded parameter values at all points in the catchment. In order to complement the traditional evaluation approach based on performance criteria, we developed a diagnostic approach based on hydrological signatures. A set of hydrological signatures based on precipitation and runoff data was defined and applied to a regional model of the Rhône basin (100 000 km<sup>2</sup>) in France. The comparison of simulated and observed signatures for 45 contrasted sub-basins of various sizes, climates, geologies and land uses, show that performance and ability to reproduce signatures are not always correlated. The analysis of signature results, combined with additional hydrogeology expertise, provided directions to improve the model parameterization, especially in the groundwater compartment. The study also provided feedback on the degree of information contained in the signatures and allows us to make recommendations for future studies.</p>

scholarly journals Effect of length of the observed dataset on the calibration of a distributed hydrological model

2015 ◽  
Vol 368 ◽  
pp. 305-311 ◽  
Author(s):  
X. Cui ◽  
W. Sun ◽  
J. Teng ◽  
H. Song ◽  
X. Yao
Keyword(s):  
Hydrological Model ◽  
Assessment Tool ◽  
Swat Model ◽  
Model Performance ◽  
Hydrological Models ◽  
Distributed Hydrological Model ◽  
Discharge Data ◽  
One Year ◽  
Parameter Values ◽  
Discharge Measurements

Abstract. Calibration of hydrological models in ungauged basins is now a hot research topic in the field of hydrology. In addition to the traditional method of parameter regionalization, using discontinuous flow observations to calibrate hydrological models has gradually become popular in recent years. In this study, the possibility of using a limited number of river discharge data to calibrate a distributed hydrological model, the Soil and Water Assessment Tool (SWAT), was explored. The influence of the quantity of discharge measurements on model calibration in the upper Heihe Basin was analysed. Calibration using only one year of daily discharge measurements was compared with calibration using three years of discharge data. The results showed that the parameter values derived from calibration using one year’s data could achieve similar model performance with calibration using three years’ data, indicating that there is a possibility of using limited numbers of discharge data to calibrate the SWAT model effectively in poorly gauged basins.

scholarly journals Development of a semi-distributed hydrological model on a tidal-affected river: application to the Adour catchment, France.

2020 ◽  
Author(s):  
Valentin Mansanarez ◽  
Guillaume Thirel ◽  
Olivier Delaigue ◽  
Benoit Liquet
Keyword(s):  
Hydrological Model ◽  
Potential Evapotranspiration ◽  
River Mouth ◽  
Model Parameters ◽  
Distributed Hydrological Model ◽  
Natural Systems ◽  
Tidal Influence ◽  
Novel Approach ◽  
Spatio Temporal ◽  
Parameter Values

<p>Streamflow estimation from rain events is a delicate exercise. Watersheds are complex natural systems and their response to rainfall events is influenced by many factors. Hydrological rainfall-runoff modelling is traditionally used to understand those factors by predicting discharges from precipitation data. These models are simplified conceptualisations and thus still struggle when facing some particular processes linked to the catchment. Among those processes, the tide influence on river discharges is rarely accounted for in hydrological modelling when estimating streamflow series at river mouth areas. Instead, estimated streamflow series are sometimes corrected by coefficients to account for the tide effect.</p><p>In this presentation, we explored a semi-distributed hydrological model by adapting it to account for tidal-influence in the river mouth area. This model uses observed spatio-temporal rainfall and potential evapotranspiration databases to predict streamflow at gauged and ungauged locations within the catchment. The hydrological model is calibrated using streamflow observations and priors on parameter values to calibrate each model parameters of each sub-catchments. A drift procedure in the calibration process is used to ensure continuity in parameter values between upstream and downstream successive sub-catchments.</p><p>This novel approach was applied to a tidal-affected catchment: the Adour’s catchment in southern France. Estimated results were compared to simulations without accounting for the tidal influence. Results from the new hydrological model were improved at tidal-affected locations of the catchment. They also show similar estimations in tidal-unaffected part of the catchment.</p>

The limitations of assessing impacts of land use changes on runoff with a distributed hydrological model: case study of the Hron River

Biologia ◽  
2009 ◽  
Vol 64 (3) ◽  
Author(s):  
Kamila Hlavčová ◽  
Ján Szolgay ◽  
Silvia Kohnová ◽  
Oliver Horvát
Keyword(s):  
Land Use ◽  
Hydrological Model ◽  
Land Use Changes ◽  
Annual Runoff ◽  
Distributed Hydrological Model ◽  
Climate Data ◽  
Model Case ◽  
Distributed Models ◽  
Physically Based ◽  
Runoff Regime

AbstractA distributed hydrological model was applied for estimating changes in a runoff regime due to land use changes. The upper Hron river basin, which has an area of 1766 km2 and is located in central Slovakia, was selected as the pilot basin. A physically-based rainfall-runoff model with distributed parameters was used for modelling runoff from rainfall and melting snow. The parameters of the model were estimated using climate data from 1981–2000 and from three digital map layers: a land-use map, soil map and digital elevation model. Several scenarios of changes in land use were prepared, and the runoff under the new land use conditions was simulated. Long-term mean annual runoff components and the design maximal mean daily discharges with a return period from 5 to 100 years under the previous and changed land uses were estimated and compared. The simulated runoff changes were confronted with expert judgments and estimates from the literature. Limitations of the use of distributed models for estimating land use changes are discussed.

Comparing 18 precipitation datasets for large scale distributed hydrological modelling

2020 ◽  
Author(s):  
Luigia Brandimarte ◽  
Maurizio Mazzoleni ◽  
Alessandro Amaranto
Keyword(s):  
High Performance ◽  
Large Scale ◽  
Hydrological Model ◽  
River Basins ◽  
Distributed Hydrological Model ◽  
Distributed Models ◽  
Distributed Modelling ◽  
Human Footprint ◽  
Class 1 ◽  
Precipitation Gauge

<p>Our understanding of the advantages and limitations of satellite derived precipitation datasets as a forcing to hydrological models has made tremendous progress over the past decade. However, most studies have only analysed the performance of one or few datasets, have used global precipitation datasets to force lumped models on regional/large-scale basins, or have adopted more complex distributed models but applied them to small basin scales.</p><p>We aimed at addressing these gaps in the literature: in particular, we compared the performance of 18 different precipitation datasets used as input in a grid-based distributed hydrological model to assess streamflow in large-scale river basins. These datasets are classified as Uncorrected Satellites, Corrected Satellites, and Reanalysis-Gauges based datasets. The hydrological model is applied to 8 large scale river basins (Amazon, Brahmaputra, Congo, Danube, Godavari, Mississippi, Rhine and Volga) with different sizes, presence of hydraulic structures, human footprint, hydrometeorological characteristics, and precipitation gauge network density were selected.</p><p>The results of this study showed that there is not a unique best performing precipitation dataset for all basins and results are very sensitive to the basin characteristics. However, there are few datasets which persistently outperform the others: SM2RAIN-ASCAT for Class 1, CHIRPS V2.0, MSWEP V2.1, and CMORPH-CRTV1.0 for Class 2, GPCC and WFEDEI GPCC for Class 3. The use of a distributed modelling approach rather than lumped is supported by the fact that precipitation datasets showing the highest model result at the basin outlet do not show the same high performance at internal locations of the basin. In addition, precipitation datasets belonging to Class 2 outperform the other datasets in basins with Tropical and Temperate-Arid climate (e.g. Congo, Mississippi and Godavari), while Class 3 datasets show the highest NSE values in Temperate and Temperate-Cold basins (e.g. Danube, Rhine and Volga).</p>

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