Development of a Conceptual Deterministic Rainfall-Runoff Model

Bergström, Sten; Forsman, Arne

doi:10.2166/nh.1973.0012

Cited by 369 publications

(248 citation statements)

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“…The HBV model is a semi-distributed conceptual model and was originally developed at the Swedish Meteorological and Hydrological Institute (SMHI) (Bergström and Forsman, 1973). The area to be modeled is divided into a number of subcatchments and each subcatchment is further divided into a number of zones based on elevation, land use or soil type or combinations of them.…”

Section: Model and Methodsmentioning

confidence: 99%

Influence of rainfall observation network on model calibration and application

Bàrdossy

Das

2008

Hydrol. Earth Syst. Sci.

182

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Abstract. The objective in this study is to investigate the influence of the spatial resolution of the rainfall input on the model calibration and application. The analysis is carried out by varying the distribution of the raingauge network. A meso-scale catchment located in southwest Germany has been selected for this study. First, the semi-distributed HBV model is calibrated with the precipitation interpolated from the available observed rainfall of the different raingauge networks. An automatic calibration method based on the combinatorial optimization algorithm simulated annealing is applied. The performance of the hydrological model is analyzed as a function of the raingauge density. Secondly, the calibrated model is validated using interpolated precipitation from the same raingauge density used for the calibration as well as interpolated precipitation based on networks of reduced and increased raingauge density. Lastly, the effect of missing rainfall data is investigated by using a multiple linear regression approach for filling in the missing measurements. The model, calibrated with the complete set of observed data, is then run in the validation period using the above described precipitation field. The simulated hydrographs obtained in the above described three sets of experiments are analyzed through the comparisons of the computed Nash-Sutcliffe coefficient and several goodness-of-fit indexes. The results show that the model using different raingauge networks might need re-calibration of the model parameters, specifically model calibrated on relatively sparse precipitation information might perform well on dense precipitation information while model calibrated on dense precipitation information fails on sparse precipitation information. Also, the model calibrated with the complete set of observed precipitation and run with incomplete observed data associated with the data estimated using multiple linear regressions, at the locations treated as missing measurements, performs well.

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Section: Model and Methodsmentioning

confidence: 99%

Influence of rainfall observation network on model calibration and application

Bàrdossy

Das

2008

Hydrol. Earth Syst. Sci.

182

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“…This is an asset because the prediction of long-term land use is unrealistic. The hydrological models used are: ModHyPMA (Hydrological Model based on Least Action Principe [27]), HBV (Hydrologiska Byråns Vattenbalansavdelning, Bergström and Forsman [28]), AWBM (Australian Water Balance Model, [29,30]), and SimHyd [31].…”

Section: Hydrological Modelsmentioning

confidence: 99%

Assessment of Future Water Resources Availability under Climate Change Scenarios in the Mékrou Basin, Benin

2017

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Abstract:This work aims to evaluate future water availability in the Mékrou catchment under climate change scenarios. To reach this goal, data from Regional Climate Models (RCMs) were used as the input for four rainfall-runoff models which are ModHyPMA (Hydrological Model based on Least Action Principe), HBV (Hydrologiska Byråns Vattenbalansavdelning), AWBM (Australian Water Balance Model), and SimHyd (Simplified Hydrolog). Then the mean values of the hydro-meteorological data of three different projected periods (2011-2040, 2041-2070 and 2071-2100) were compared to their values in the baseline period. The results of calibration and validation of these models show that the meteorological data from RCMs give performances that are as good as performances obtained with the observed meteorological data in the baseline period. The comparison of the mean values of the hydro-meteorological data of the baseline period to their values for the different projected periods indicates that for PET there is a significantly increase until 2100 for both Representative Concentration Pathway 4.5 (RCP4.5) and RCP8.5 scenarios. Therefore, the rate's increase of potential evapotranspiration (PET) under the RCP8.5 scenario is higher than that obtained under the RCP8.5 scenario. Changes in rainfall amounts depend on the scenario of climate change and the projected periods. For the RCP4.5 scenario, there is a little increase in the annual rainfall amounts over the period from 2011 to 2040, while there is a decrease in the rainfall amounts over the other two projected periods. According to the RCP8.5 scenario, the contrary of changes observed with the RCP4.5 scenario are observed. At a monthly scale, the rainfall amounts will increase for August and September and decrease for July and October. These changes in rainfall amounts greatly affect yearly and monthly discharge at the catchment outlet. Over the three projected periods and for both RCP4.5 and RCP8.5, the mean annual discharge will significantly increase related to the baseline periods. However, the magnitude of increases will depend on the projected period and the RCP scenario. At a monthly scale, it was found that runoff increases significantly from August to November for all projected periods and the climate change scenario.

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“…In this study, we will focus on the bucket-type models, which are among the simplest. These models, such as VIC (Wood et al, 1992), HBV (Bergström and Forsman, 1973) and Sacramento (Burnash, 1995), describe various conceptualizations of the hydrological processes at the catchment scale. Their parsimony…”

Section: On the Need For An Adequate Mathematical And Computational Hmentioning

confidence: 99%

State-space representation of a bucket-type rainfall-runoff model: a case study with State-Space GR4 (version 1.0)

Santos¹,

Thirel²,

Perrin³

2017

Preprint

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Abstract. In many conceptual rainfall-runoff models, the water balance differential equations are not explicitly formulated.These differential equations are solved sequentially by splitting the equations into terms that can be solved analytically with a technique called "operator splitting". As a result, only the resolutions of the split equations are used to present the different models. This article provides a methodology to make the governing water balance equations of a bucket-type rainfall-runoff model explicit. This is done by setting up a comprehensive state-space representation of the model. By representing it in this 5 way, the operator splitting, which complexifies the structural analysis of the model, is removed. In this state-space representation, the lag functions (unit hydrographs), which are frequent in this type of model and make the resolution of the representation difficult, are replaced by a so-called "Nash cascade". This substitution also improves the lag parameter consistency across time

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Development of a Conceptual Deterministic Rainfall-Runoff Model

Cited by 369 publications

References 1 publication

Influence of rainfall observation network on model calibration and application

Influence of rainfall observation network on model calibration and application

Assessment of Future Water Resources Availability under Climate Change Scenarios in the Mékrou Basin, Benin

State-space representation of a bucket-type rainfall-runoff model: a case study with State-Space GR4 (version 1.0)

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