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This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and education use, including for instruction at the authors institution and sharing with colleagues. Other uses, including reproduction and distribution, or selling or licensing copies, or posting to personal, institutional or third party websites are prohibited. In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier’s archiving and manuscript policies are encouraged to visit: http://www.elsevier.com/copyright Author's personal copy Advances in Water Resources 32 (2009) 129–146 Contents lists available at ScienceDirect Advances in Water Resources journal homepage: www.elsevier.com/locate/advwatres Assessing the impact of land use change on hydrology by ensemble modeling (LUCHEM). I: Model intercomparison with current land use L. Breuer a,*, J.A. Huisman b, P. Willems c, H. Bormann d, A. Bronstert e, B.F.W. Croke f, H.-G. Frede a, T. Gräff e, L. Hubrechts g, A.J. Jakeman f, G. Kite h, J. Lanini i, G. Leavesley j, D.P. Lettenmaier i, G. Lindström k, J. Seibert l, M. Sivapalan m,1, N.R. Viney n a Institute for Landscape Ecology and Resources Management, Justus-Liebig-University Giessen, Heinrich-Buff-Ring 26, 35392 Giessen, Germany b ICG-4 Agrosphere, Forschungszenrum Jülich, Germany c Hydraulics Laboratory, Katholieke Universiteit Leuven, Belgium d Institute for Biology and Environmental Sciences, Carl von Ossietzky University, Oldenburg, Germany e Institute for Geoecology, University of Potsdam, Germany f The Fenner School of Environment and Society, The Australian National University, Australia g Afdeling Ecologie en Water, Lisec NV, Genk, Belgium h Hydrologic Solutions, Pantymwyn, Flintshire, United Kingdom i Department of Civil and Environmental Engineering, University of Washington, USA j Denver Federal Center, US Geological Survey, Denver, USA k SMHI, Norrköping, Sweden l Department of Physical Geography and Quarternary Geology, Stockholm University, Sweden m Centre for Water Research, University of Western Australia, Australia n CSIRO Land and Water, Canberra, Australia article info abstract Article history: This paper introduces the project on ‘Assessing the impact of land use change on hydrology by ensemble Received 18 July 2007 modeling (LUCHEM)’ that aims at investigating the envelope of predictions on changes in hydrological Received in revised form 1 October 2008 fluxes due to land use change. As part of a series of four papers, this paper outlines the motivation and Accepted 3 October 2008 setup of LUCHEM, and presents a model intercomparison for the present-day simulation results. Such Available online 18 October 2008 an intercomparison provides a valuable basis to investigate the effects of different model structures on model predictions and paves the ground for the analysis of the performance of multi-model ensembles Keywords: and the reliability of the scenario predictions in companion papers. In this study, we applied a set of Hydrological modeling 10 lumped, semi-lumped and fully distributed hydrological models that have been previously used in Ensemble modeling Land use land use change studies to the low mountainous Dill catchment, Germany. Substantial differences in Model structure model performance were observed with Nash–Sutcliffe efficiencies ranging from 0.53 to 0.92. Differences Catchment model performance in model performance were attributed to (1) model input data, (2) model calibration and (3) the physical basis of the models. The models were applied with two sets of input data: an original and a homogenized data set. This homogenization of precipitation, temperature and leaf area index was performed to reduce the variation between the models. Homogenization improved the comparability of model simulations and resulted in a reduced average bias, although some variation in model data input remained. The effect of the physical differences between models on the long-term water balance was mainly attributed to dif- ferences in how models represent evapotranspiration. Semi-lumped and lumped conceptual models slightly outperformed the fully distributed and physically based models. This was attributed to the auto- matic model calibration typically used for this type of models. Overall, however, we conclude that there was no superior model if several measures of model performance are considered and that all models are suitable to participate in further multi-model ensemble set-ups and land use change scenario investigations. Ó 2008 Elsevier Ltd. All rights reserved. * Corresponding author. Tel.: +49 641 9937395; fax: +49 641 9937389. E-mail address: [email protected] (L. Breuer). 1 Now at: Department of Geography and Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA. 0309-1708/$ - see front matter Ó 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.advwatres.2008.10.003 Author's personal copy 130 L. Breuer et al. / Advances in Water Resources 32 (2009) 129–146 1. Introduction tive by the International Association of Hydrological Sciences (IAHS) [75]. Climate change and its impact on hydrological fluxes 1.1. Hydrological modeling of land use changes are of growing concern and have also resulted in a set of research initiatives. These include the Global Energy and Water Cycle Exper- Evaluating the impact of land use change on water and matter iment (GEWEX) and the Program for Climate Model Diagnosis and fluxes is a major challenge in hydrological research. Changes in Intercomparison (PCMDI). No such research initiatives have been land surface properties ultimately modify the energy and water ex- developed to approach the problem of land use change and its im- change of the soil–vegetation–atmosphere system. A large number pact on hydrology. of field studies exist where the influence of land use changes Despite this growing knowledge, a high degree of uncertainty (mainly afforestation and deforestation) is investigated in either remains in all model approaches. This global model uncertainty paired site studies or single catchment experiments (see the re- stems from stochastic and structural model uncertainty. Stochastic views of [11,19,79]). Hydrological modeling of such changes has model uncertainty is introduced by measurement errors of model been conducted since the 1970s [10,21,64,81]. One of the chal- input and output data, problems in the observation of physically lenges in hydrological modeling is to account for the changes in based model parameters, parameter estimates, and spatial as well land surface properties by altering (at least some of) the model as temporal parameter heterogeneity. Numerous techniques to parameters. Therefore, it is commonly argued that process-based investigate stochastic model uncertainty have been published in fully distributed models are best suited to simulate land use the field of hydrology (e.g. [25,57,84] amongst many others). These change effects [8]. Since in most cases only parts of the land use techniques are based on Monte Carlo simulations [31], Latin within a catchment changes, it is further argued that spatially dis- Hypercube sampling [25], General Likelihood Uncertainty Estima- tributed models depict these changes more precisely as compared tion GLUE [8], or the Shuffled Complex Evolution Metropolis to lumped modeling approaches [9]. Following this philosophy, (SCEM-UA) technique [84]. several complex models have been developed that are capable of The validity of a given model depends on the scientifically simulating land use changes, such as DHSVM [75,88], MIKE-SHE acceptable explanation of the cause–effect relationships within [3,70], RHESSys [5,6], SHETRAN ([32], a modeling system based the model [72]. The structural model uncertainty results from un- on the SHE model [1]), TAC-D [65], TOPLATS [33,67] and WASIM known, simplified, incomplete or incorrect process descriptions [61,73]. However, these fully distributed process-based modeling within the model. Models are always abstractions of real systems. approaches are often criticized because an a priori estimation of Hence, not all processes can be included, may it be on purpose to model parameters is difficult [9,32]. As an alternative, physically keep the model structure simple or due to the lack of knowledge. based, semi-distributed models with less complex spatial repre- Several approaches have been suggested recently to deal with this sentation have been proposed. This group of models simulates all structural model uncertainty by using a set of different models. A hydrological processes within spatially non-explicit Hydrological simple method of combining several model structures (and further Response Units (HRU). Results for each HRU are lumped within evaluation techniques) was suggested in the model protocol by subcatchments and routed downstream. Models following this ap- Refsgaard et al. [71], Vrugt et al. [83] and Duan et al. [29] presented proach are SWAT [4,86],SWIM[50,51], PRMS [53], HYLUC [20] and approaches for the investigation of structural and stochastic model SLURP [48,49]. HRUs can be defined based on soil units, land use or uncertainty simultaneously. However, the basis for using such a set a combination of both. Although the impact of land use change is of different models is a detailed evaluation of the performance of not simulated