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Shuzhou Wang and Yaoming Ma

parameterization scheme in this study. Table 1. Flux parameterization schemes for kB −1 . The Prandtl number Pr = 0.71, k = 0.4, ν is the fluid kinematical viscosity, α = 0.52, β = 7.2, and Re * = z 0m u * / ν . b. Determination of excess resistance to heat transfer The excess resistance to heat transfer kB −1 is used to parameterize the sensible heat exchange between the land surface and atmosphere. In past decades, the parameterization of kB −1 has attracted a number of theoretical and

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Riccardo Rigon, Giacomo Bertoldi, and Thomas M. Over

models ( Beven 2000 ) have been implemented to predict the lateral distribution of water, ranging from more conceptualized descriptions (e.g., Beven and Kirkby 1979 ; Franchini and Pacciani 1991 ) to fully distributed approaches, such as the Système Hydrologique Européen (SHE; Abbott et al. 1986 ), topographic kinematic approximation and integration model (TOPKAPI; Ciarapica and Todini 2002 ), THALES ( Grayson et al. 1992 ), and others ( Vertessy et al. 1993 ; Garrote and Bras 1995 ; Bronstert

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Barbara Turato, Oreste Reale, and Franco Siccardi

peaks occur at the end of October), but they could be concurring agents of a complex synergistic mechanism. 3. Moisture sources for the Piedmont 2000 flood event a. Method To investigate surface evaporative sources contributing to the flood event, we adopt a kinematic quasi-isentropic trajectory technique documented in Dirmeyer and Brubacker (1999) ; used by Reale et al. (2001) , Brubacker et al. (2001) , and Burde and Zangvil (2001a , b ); and based on the fully implicit isentropic algorithm of

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Timothy J. Lang, Steven A. Rutledge, and Robert Cifelli

.1175/1520-0493(2000)128<2687:TRBPAL>2.0.CO;2 Cetrone, J. , and Houze R. A. , 2006 : Characteristics of tropical convection over the ocean near Kwajalein. Mon. Wea. Rev. , 134 , 834 – 853 . 10.1175/MWR3075.1 Cifelli, R. , Petersen W. A. , Carey L. D. , Rutledge S. A. , and da Silva Dias M. A. F. , 2002 : Radar observations of kinematic, microphysical, and precipitation characteristics of two MCSs in TRMM LBA. J. Geophys. Res. , 107 , 8077 . doi:10.1029/2000JD000264 . 10.1029/2000JD000264 Cifelli, R

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Sheng Wang, Suxia Liu, Xingguo Mo, Bin Peng, Jianxiu Qiu, Mingxin Li, Changming Liu, Zhonggen Wang, and Peter Bauer-Gottwein

include 1) a multilayer canopy radioactive transfer module; 2) a two-source soil–canopy energy balance module; 3) a multiple-layer soil water and energy transfer module; 4) a modified variable infiltration capacity scheme for runoff generation; 5) the degree-day factor method for snow and ice melt computation; and 6) the kinematic wave scheme for streamflow routing. The VIP model has been applied and validated extensively in basins across China ( Mo and Liu 2001 ; Mo et al. 2004 , 2014 ; Liu et al

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Jonathan J. Gourley, Scott E. Giangrande, Yang Hong, Zachary L. Flamig, Terry Schuur, and Jasper A. Vrugt

-RDHM The model concepts used in this study originate from the Sacramento model ( Burnash et al. 1973 ). This model was subdivided into grid cells having 4.76-km resolution, in accordance with the NWS Hydrologic Rainfall Analysis Project (HRAP) grid. Each grid cell has a water balance component as well as kinematic overland and channel routing components ( Koren et al. 2004 ). The water balance component of the model, referred to as the Sacramento Soil Moisture Accounting model (SAC-SMA), considers

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Efthymios I. Nikolopoulos, Emmanouil N. Anagnostou, and Marco Borga

( Ivanov et al. 2004a , b ; Vivoni et al. 2007 ). The tRIBS model is a distributed physics-based model that explicitly accounts for the spatial variability of land surface descriptors (terrain, soil, and vegetation), soil moisture, and atmospheric forcing. Infiltration is simulated in a sloped heterogeneous and anisotropic soil based on a kinematic approximation for unsaturated flow ( Cabral et al. 1992 ; Garrote and Bras 1995 ). An adaptive multiple resolution approach based on TINs ( Vivoni et al

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Luis Gimeno, Raquel Nieto, Ricardo M. Trigo, Sergio M. Vicente-Serrano, and Juan Ignacio López-Moreno

. 2006 ), numerical water vapor tracers ( Joussame et al. 1984 ; Koster et al. 1986 ), and algorithms that use quasi-isentropic back trajectories in combination with model-derived surface fluxes to determine evaporation sources along back trajectories ( Dirmeyer and Brubaker 1999 ; Reale et al. 2001 ; Dirmeyer and Brubaker 2007 ). Most of the earlier-mentioned Lagrangian studies, however, have been limited by methodological (no kinematic trajectories) and conceptual (e.g., assumptions about how

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William Amponsah, Lorenzo Marchi, Davide Zoccatelli, Giorgio Boni, Marco Cavalli, Francesco Comiti, Stefano Crema, Ana Lucía, Francesco Marra, and Marco Borga

) Spatially distributed rainfall–runoff model A distributed hydrologic model is used to examine hydrologic response associated with space–time radar rainfall variability and to check consistency with postflood indirect peak flow estimates. The Kinematic Local Excess Model (KLEM; Marchi et al. 2010 ) combines a grid-based runoff-generation model and a network-based hillslope and channel transport model. Runoff generation is simulated by applying the Soil Conservation Service Curve Number (SCS-CN) approach

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Masahiro Ryo, Oliver C. Saavedra Valeriano, Shinjiro Kanae, and Tinh Dang Ngoc

the four precipitation datasets. The DHM employed is the geomorphology-based hydrological model (GBHM; developed by Yang et al. 2002 ; see Fig. 3 and appendix for details). Hydrological processes such as precipitation, canopy interception, evapotranspiration, infiltration, percolation, and groundwater flow are simulated. The discharge is computed with the kinematic wave equation. The computational grid size was set to 500 m and the unit time step was set to 6 h in order to include the

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