Improving process representation in conceptual hydrological model calibration using climate simulations

Minville, Marie; Cartier, Dominique; Guay, Catherine; Leclaire, Louis-Alexandre; Audet, Charles; Digabel, Sébastien Le; Merleau, James

doi:10.1002/2013wr013857

Cited by 38 publications

(26 citation statements)

References 61 publications

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“…Calibration is important for both conceptual and physically based hydrological models to provide more accurate runoff estimates, to account for (i) the impossibility of measuring all required model parameters at the model application scale, (ii) lack of process understanding, (iii) possibly overly simplistic process representations, (iv) the spatiotemporal discretization of highly heterogeneous rainfall-runoff processes, and (v) errors in the forcing data (Beven, 1989;Blöschl and Sivapalan, 1995;Duan et al, 2001Duan et al, , 2006McDonnell et al, 2007;Nasonova et al, 2009;Rosero et al, 2011;Minville et al, 2014). Yet, despite the development of numerous calibration techniques over the last 50 years (Dawdy and O'Donnell, 1965;Duan et al, 2004) and the current widespread availability of streamflow observations , macro-scale models generally tend to be uncalibrated (Sooda and Smakhtin, 2015;Bierkens, 2015;Kauffeldt et al, 2016).…”

Section: Are Calibration and Regionalization Important Or Even Essentmentioning

confidence: 99%

Global evaluation of runoff from 10 state-of-the-art hydrological models

Beck

Dijk

Roo

et al. 2017

Hydrol. Earth Syst. Sci.

182

183

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Abstract. Observed streamflow data from 966 medium sized catchments (1000-5000 km 2 ) around the globe were used to comprehensively evaluate the daily runoff estimates of six global hydrological models (GHMs) and four land surface models (LSMs) produced as part of tier-1 of the eartH2Observe project. The models were all driven by the WATCH Forcing Data ERA-Interim (WFDEI) meteorological dataset, but used different datasets for non-meteorologic inputs and were run at various spatial and temporal resolutions, although all data were re-sampled to a common 0.5• spatial and daily temporal resolution. For the evaluation, we used a broad range of performance metrics related to important aspects of the hydrograph. We found pronounced intermodel performance differences, underscoring the importance of hydrological model uncertainty in addition to climate input uncertainty, for example in studies assessing the hydrological impacts of climate change. The uncalibrated GHMs were found to perform, on average, better than the uncalibrated LSMs in snow-dominated regions, while the ensemble mean was found to perform only slightly worse than the best (calibrated) model. The inclusion of less-accurate models did not appreciably degrade the ensemble performance. Overall, we argue that more effort should be devoted on calibrating and regionalizing the parameters of macro-scale models. We further found that, despite adjustments using gauge observations, the WFDEI precipitation data still contain substantial biases that propagate into the simulated runoff. The early bias in the spring snowmelt peak exhibited by most models is probably primarily due to the widespread precipitation underestimation at high northern latitudes.

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Section: Are Calibration and Regionalization Important Or Even Essentmentioning

confidence: 99%

Global evaluation of runoff from 10 state-of-the-art hydrological models

Beck

Dijk

Roo

et al. 2017

Hydrol. Earth Syst. Sci.

182

183

View full text Add to dashboard Cite

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“…All hydrologic models can to some degree benefit from calibration to improve their Q simulations, due to (i) lack of process understanding, (ii) possibly overly simplistic process representations, (iii) the spatiotemporal discretization of highly heterogeneous rainfall‐runoff processes, and (iv) the impossibility of measuring all required model parameters at the model application scale [ Beven , ; Blöschl and Sivapalan , ; Duan et al ., ; McDonnell et al ., ; Nasonova et al ., ; Rosero et al ., ; Minville et al ., ]. Since Q observations are unavailable for the majority of the Earth's land surface [ Sivapalan , ; Hannah et al ., ], hydrologic models often rely on regionalization approaches to transfer information from gauged (donor) to ungauged (receptor) catchments [see He et al ., ; Hrachowitz et al ., ; Razavi and Coulibaly , ; Blöschl et al ., ; Parajka et al ., for reviews].…”

Section: Introductionmentioning

confidence: 99%

Global‐scale regionalization of hydrologic model parameters

Beck

Dijk

Roo

et al. 2016

Water Resources Research

322

284

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Current state-of-the-art models typically applied at continental to global scales (hereafter called macroscale) tend to use a priori parameters, resulting in suboptimal streamflow (Q) simulation. For the first time, a scheme for regionalization of model parameters at the global scale was developed. We used data from a diverse set of 1787 small-to-medium sized catchments (10-10;000 km 2 ) and the simple conceptual HBV model to set up and test the scheme. Each catchment was calibrated against observed daily Q, after which 674 catchments with high calibration and validation scores, and thus presumably good-quality observed Q and forcing data, were selected to serve as donor catchments. The calibrated parameter sets for the donors were subsequently transferred to 0.58 grid cells with similar climatic and physiographic characteristics, resulting in parameter maps for HBV with global coverage. For each grid cell, we used the 10 most similar donor catchments, rather than the single most similar donor, and averaged the resulting simulated Q, which enhanced model performance. The 1113 catchments not used as donors were used to independently evaluate the scheme. The regionalized parameters outperformed spatially uniform (i.e., averaged calibrated) parameters for 79% of the evaluation catchments. Substantial improvements were evident for all major K€ oppen-Geiger climate types and even for evaluation catchments > 5000 km distant from the donors. The median improvement was about half of the performance increase achieved through calibration. HBV with regionalized parameters outperformed nine state-of-the-art macroscale models, suggesting these might also benefit from the new regionalization scheme. The produced HBV parameter maps including ancillary data are available via www.gloh2o.org.

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“…Although accurate ET estimation is essential, ET plays a major compensational role in the hydrological budget and is sacrificed to transform rainfall to runoff for better streamflow simulations (Beven, 2001;Minville et al, 2014). Hydrological models are commonly calibrated against observed discharge and often fail to consider major hydrological components including actual evapotranspiration (AET) and soil moisture (Wanders, Bierkens, de Jong, de Roo, & Karssenberg, 2014).…”

Section: Introductionmentioning

confidence: 99%

Effectiveness of introducing crop coefficient and leaf area index to enhance evapotranspiration simulations in hydrologic models

Birhanu

Kim

Jang

2019

Hydrological Processes

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Evapotranspiration (ET) is an essential component of the hydrological cycle and plays a critical role in water resource management. However, ET is often overlooked in order to transform rainfall to runoff for better streamflow simulation. Hydrological models are commonly used to estimate areal actual evapotranspiration (AET) after calibration against observed discharge. However, classical approaches are often inadequate to appropriately simulate other hydrologic components. Hence, it is important to introduce natural heterogeneity to enhance hydrological processes and reduce water balance errors. In this study, the effectiveness of introducing a constant crop coefficient (Kc), flux tower‐based Kc, and leaf area index (LAI) to three hydrological models (Three‐Parametric Hydrologic Model [TPHM], Génie Rural à 4 paramètres Journalier [GR4J], and Catchment hydrologic cycle Assessment Tool [CAT]) is assessed for the simulation of daily streamflow and AET in a mountainous mixed forest watershed (8.54 km2) in South Korea. The results show that the streamflow simulations after introduction of Kc and LAI to the original models are quite similar. However, the effectiveness of the AET estimation was significantly enhanced after introduction of the flux tower‐based Kc and LAI. The information criterion computed to compare the models reveals that the flux tower‐based Kc‐simulated AET demonstrated better agreement with the observed AET. The Pearson's correlation coefficients (R2) of the TPHM (8%), GR4J (55%), and CAT (55%) models also showed improvements that were greater than the constant based Kc simulation. Similarly, the limitations of the three models with respect to capturing seasonal variation as well as high and low flows were enhanced after the introduction of the flux tower‐based Kc, which adequately reproduced hydrological processes with minimum water balance errors and bias. A regression analysis revealed the potential of estimating Kc as a linear function of LAI (R2 = 0.84). The results of this study indicate that introduction of Kc and LAI to the conceptual rainfall–runoff models can be considered an effective approach to reduce water balance errors and uncertainties in hydrological models and improve the reliability of climate change studies and water resource management.

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Improving process representation in conceptual hydrological model calibration using climate simulations

Cited by 38 publications

References 61 publications

Global evaluation of runoff from 10 state-of-the-art hydrological models

Global evaluation of runoff from 10 state-of-the-art hydrological models

Global‐scale regionalization of hydrologic model parameters

Effectiveness of introducing crop coefficient and leaf area index to enhance evapotranspiration simulations in hydrologic models

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