Assessing the impact of land use change on hydrology by ensemble modeling (LUCHEM). I: Model intercomparison with current land use

Breuer, Lutz; Huisman, Johan Alexander; Willems, Patrick; Bormann, Helge; Bronstert, Axel; Croke, Barry; Frede, Hans‐Georg; Gräff, Thomas; Hubrechts, Lode; Jakeman, Anthony J.; Kite, Geoff; Lanini, J; Leavesley, George H.; Lettenmaier, Dennis P.; Lindström, Göran; Seibert, Jan; Sivapalan, Murugesu; Viney, Neil R.

doi:10.1016/j.advwatres.2008.10.003

Cited by 196 publications

(130 citation statements)

References 77 publications

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“…Such experiments have been helpful for exploring model simulation performance of lumped (e.g., Duan et al, 2006;Breuer et al, 2009), semi-distributed (e.g., Duan et al, 2006;Holländer et al, 2009) and distributed (e.g., Henderson-Sellers et al, 1993;Reed et al, 2004;Holländer et al, 2009;Smith et al, 2012;Nijzink and Savenije, 2016) models in a consistent way using the same input data. To go beyond specific analyses and provide general conclusions, multi-catchment experiments have been proposed by several authors (e.g., Perrin et al, 2001;Gupta et al, 2014) and are now used extensively.…”

Section: Introductionmentioning

confidence: 99%

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

Garavaglia

Lay

Gottardi

et al. 2017

Hydrol. Earth Syst. Sci.

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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 MOR-DOR: 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.

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Section: Introductionmentioning

confidence: 99%

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

Garavaglia

Lay

Gottardi

et al. 2017

Hydrol. Earth Syst. Sci.

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“…LUCHEM: Breuer et al, 2009;PILPS: Cornwell and Harvey, 2007;GSWP: Dirmeyer et al, 2006;WaterMIP: Haddeland et al, 2011;Prudhomme et al, 2011;Gudmundsson et al, 2012a). Some studies suggest that the ensemble mean (of all models) provides a more accurate estimate than any single model (Guo et al, 2007;Gudmundsson et al, 2012a).…”

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confidence: 99%

Filling the white space on maps of European runoff trends: estimates from a multi-model ensemble

Stahl

Tallaksen

Hannaford

et al. 2012

Hydrol. Earth Syst. Sci.

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Abstract. An overall appraisal of runoff changes at the European scale has been hindered by "white space" on maps of observed trends due to a paucity of readily-available streamflow data. This study tested whether this white space can be filled using estimates of trends derived from model simulations of European runoff. The simulations stem from an ensemble of eight global hydrological models that were forced with the same climate input for the period 1963-2000. The derived trends were validated for 293 grid cells across the European domain with observation-based trend estimates. The ensemble mean overall provided the best representation of trends in the observations. Maps of trends in annual runoff based on the ensemble mean demonstrated a pronounced continental dipole pattern of positive trends in western and northern Europe and negative trends in southern and parts of eastern Europe, which has not previously been demonstrated and discussed in comparable detail. Overall, positive trends in annual streamflow appear to reflect the marked wetting trends of the winter months, whereas negative annual trends result primarily from a widespread decrease in streamflow in spring and summer months, consistent with a decrease in summer low flow in large parts of Europe. High flow appears to have increased in rain-dominated hydrological regimes, whereas an inconsistent or decreasing signal was found in snow-dominated regimes. The different models agreed on the predominant continental-scale pattern of trends, but in some areas disagreed on the magnitude and even the direction of trends, particularly in transition zones between regions with increasing and decreasing runoff trends, in complex terrain with a high spatial variability, and in snow-dominated regimes. Model estimates appeared most reliable in reproducing observed trends in annual runoff, winter runoff, and 7-day high flow. Modelled trends in runoff during the summer months, spring (for snow influenced regions) and autumn, and trends in summer low flow were more variableboth among models and in the spatial patterns of agreement between models and the observations. The use of models to display changes in these hydrological characteristics should therefore be viewed with caution due to higher uncertainty.

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“…The most recent comparison of Glob-HMs was conducted within the frame-4 work of ISI-MIP and described by Schewe et al 2014, Dankers et al 2014, Prudhomme et al 2014, Had-5 deland et al 2014, Davie et al 2013, Wada et al 2013and Portmann et al 2014 for the regional scale are described in Breuer et al 2009, Bosshard et al 2013, Chen et al 2013and Vetter 7 et al 2014 This article first presents a comparison of the model validation runs for the reference period 9 using re-analysis climate data from the WATCH project (Weedon et al 2011) as driving data, and observed 10 discharge. Secondly, the comparison is extended to impacts under climate change scenarios until 2099.…”

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confidence: 99%

Cross‐scale intercomparison of climate change impacts simulated by regional and global hydrological models in eleven large river basins

et al. 2017

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Ideally, the results from models operating at different scales should agree in trend direction and magnitude of impacts under climate change. However, this implies that the sensitivity to climate variability and climate change is comparable for impact models designed for either scale. In this study, we compare hydrological changes simulated by 9 global and 9 regional hydrological models (HM) for 11 large river basins in all continents under reference and scenario conditions. The foci are on model validation runs, sensitivity of annual discharge to climate variability in the reference period, and sensitivity of the long-term average monthly seasonal dynamics to climate change. One major result is that the global models, mostly not calibrated against observations, often show a considerable bias in mean monthly discharge, whereas regional models show a better reproduction of reference conditions. However, the sensitivity of the two HM ensembles to climate variability is in general similar. The simulated climate change impacts in terms of long-term average monthly dynamics evaluated for HM ensemble medians and spreads show that the medians are to a certain extent comparable in some cases, but have distinct differences in other cases, and the spreads related to global models are mostly notably larger. Summarizing, this implies that global HMs are useful tools when looking at large-scale impacts of climate change and variability. Whenever impacts for a specific river basin or region are of interest, e.g. for complex water management applications, the regional-scale models calibrated and validated against observed discharge should be used. © 2017 Springer Science+Business Media Dordrech

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Assessing the impact of land use change on hydrology by ensemble modeling (LUCHEM). I: Model intercomparison with current land use

Cited by 196 publications

References 77 publications

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

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

Filling the white space on maps of European runoff trends: estimates from a multi-model ensemble

Cross‐scale intercomparison of climate change impacts simulated by regional and global hydrological models in eleven large river basins

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