Simulating the river-basin response to atmospheric forcing by linking a mesoscale meteorological model and hydrologic model system

Abstract The purpose of this article is to test the ability of a distributed meteorological/hydrologic model to simulate the hydrologic response to three single-storm events passing over the Upper West Branch of the Susquehanna River Basin. The high-resolution precipitation fields for three storms are provided by observations and by the Penn State–NCAR Mesoscale Meteorological Model (MM5) with three nested domains. The MM5 simulation successfully captures the storm patterns over the study area, although some temporal and spatial discrepancies exist between observed and simulated precipitation fields. Observed and simulated precipitation data for those storms are used to drive the Hydrologic Model System (HMS). The output from HMS is compared to the measured hydrographic streamflow at the outlet of the Upper West Branch. The Curve Number and Green-Ampt methods of rainfall-runoff partitioning are used in HMS and evaluated for streamflow simulation. The results of the hydrologic simulation compare well with observed data when using the Curve Number partitioning, but underestimate observed data when using the Green-Ampt. The likely cause is the lack of heterogeneity in hydraulic parameters. The simulated streamflow with the MM5-simulated precipitation is lower than the simulated streamflow with observed precipitation. The experiments suggest that the subgrid-scale spatial variability in precipitation and hydraulic parameters should be included in future model development

[1]  D. Lettenmaier,et al.  A simple hydrologically based model of land surface water and energy fluxes for general circulation models , 1994 .

[2]  J. Famiglietti,et al.  Multiscale modeling of spatially variable water and energy balance processes , 1994 .

[3]  Keith Beven,et al.  On hydrologic similarity: 2. A scaled model of storm runoff production , 1987 .

[4]  P. S. Eagleson,et al.  Land Surface Hydrology Parameterization for Atmospheric General Circulation models Including Subgrid Scale Spatial Variability , 1989 .

[5]  Toby N. Carlson,et al.  Initialization of Soil-Water Content in Regional-Scale Atmospheric Prediction Models , 1994 .

[6]  Douglas A. Miller,et al.  A SIMULATION OF RIVER‐BASIN RESPONSE TO MESOSCALE METEOROLOGICAL FORCING: THE SUSQUEHANNA RIVER BASIN EXPERIMENT (SRBEX) 1 , 1998 .

[7]  Keith Beven,et al.  The future of distributed models: model calibration and uncertainty prediction. , 1992 .

[8]  Eric F. Wood,et al.  Evaluating GCM Land Surface Hydrology Parameterizations by Computing River Discharges Using a Runoff Routing Model: Application to the Mississippi Basin , 1994 .

[9]  F. Giorgi,et al.  Development of a Second-Generation Regional Climate Model (RegCM2). Part II: Convective Processes and Assimilation of Lateral Boundary Conditions , 1993 .

[10]  A. Perrier,et al.  HAPEX—MOBLIHY: A Hydrologic Atmospheric Experiment for the Study of Water Budget and Evaporation Flux at the Climatic Scale , 1986 .

[11]  James C. Bathurst,et al.  Physically-based distributed modelling of an upland catchment using the Systeme Hydrologique Europeen , 1986 .

[12]  Zhongbo Yu,et al.  Automated calibration applied to watershed-scale flow simulations , 1999 .

[13]  J. Dudhia A Nonhydrostatic Version of the Penn State–NCAR Mesoscale Model: Validation Tests and Simulation of an Atlantic Cyclone and Cold Front , 1993 .

[14]  B. Yarnal The policy relevance of global environmental change research , 1996 .

[15]  R. Freeze,et al.  Blueprint for a physically-based, digitally-simulated hydrologic response model , 1969 .

[16]  Eric J. Barron,et al.  Global climate model and coupled regional climate model simulations over the eastern United States: GENESIS and RegCM2 simulations , 1997 .

[17]  E. Foufoula‐Georgiou,et al.  Channel network source representation using digital elevation models , 1993 .

[18]  Keith Beven,et al.  Changing ideas in hydrology — The case of physically-based models , 1989 .

[19]  Keith Beven,et al.  Effects of spatial variability and scale with implications to hydrologic modeling , 1988 .

[20]  Murugesu Sivapalan,et al.  Scale issues in hydrological modelling: A review , 1995 .

[21]  Roger A. Pielke,et al.  A parameterization of heterogeneous land surfaces for atmospheric numerical models and its impact on regional meteorology , 1989 .

[22]  Zhongbo Yu,et al.  APPLICATION OF AN INTEGRATED BASIN‐SCALE HYDROLOGIC MODEL TO SIMULATE SURFACE‐WATER AND GROUND‐WATER INTERACTIONS 1 , 1998 .

[23]  A. Pitman,et al.  Land‐surface schemes for future climate models: Specification, aggregation, and heterogeneity , 1992 .

[24]  A. Henderson-Sellers,et al.  An Evaluation of Proposed Representations of Subgrid Hydrologic Processes in Climate Models , 1991 .

[25]  Walter J. Rawls,et al.  Green‐ampt Infiltration Parameters from Soils Data , 1983 .

[26]  K. Mitchell,et al.  Simple water balance model for estimating runoff at different spatial and temporal scales , 1996 .

[27]  Kevin E. Trenberth,et al.  Origins of the 1988 North American Drought , 1988, Science.

[28]  H. Akima,et al.  On estimating partial derivatives for bivariate interpolation of scattered data , 1984 .

[29]  P. E. O'connell,et al.  An introduction to the European Hydrological System — Systeme Hydrologique Europeen, “SHE”, 2: Structure of a physically-based, distributed modelling system , 1986 .

[30]  P. E. O'connell,et al.  An introduction to the European Hydrological System — Systeme Hydrologique Europeen, “SHE”, 1: History and philosophy of a physically-based, distributed modelling system , 1986 .

[31]  Simulating Columbia River flows with data from regional‐scale climate models , 1997 .

[32]  R. Moore The probability-distributed principle and runoff production at point and basin scales , 1985 .

[33]  Douglas A. Miller,et al.  A Conterminous United States Multilayer Soil Characteristics Dataset for Regional Climate and Hydrology Modeling , 1998 .

[34]  Arthur C. Miller,et al.  A spatially distributed hydrologic model utilizing raster data structures , 1997 .

[35]  K. Beven,et al.  A physically based, variable contributing area model of basin hydrology , 1979 .

[36]  G. Grell Prognostic evaluation of assumptions used by cumulus parameterizations , 1993 .

[37]  E. Foufoula‐Georgiou,et al.  Subgrid‐scale rainfall variability and its effects on atmospheric and surface variable predictions , 1997 .

[38]  Shu Tung Chu,et al.  Infiltration during an unsteady rain , 1978 .

[39]  F. Giorgi,et al.  Development of a Second-Generation Regional Climate Model (RegCM2). Part I: Boundary-Layer and Radiative Transfer Processes , 1993 .

[40]  K. Beven,et al.  Similarity and scale in catchment storm response , 1990 .

[41]  A. Henderson-Sellers,et al.  Sensitivity of regional climates to localized precipitation in global models , 1990, Nature.

[42]  Thomas A. McMahon,et al.  Physically based hydrologic modeling: 1. A terrain‐based model for investigative purposes , 1992 .

[43]  Y. Kuo,et al.  Real-time Forecasts for WISP-91 Using the Penn State/NCAR Mesoscale Model , 1992 .

[44]  Jeffrey G. Arnold,et al.  SWRRB; a basin scale simulation model for soil and water resources management. , 1990 .

[45]  G. Grell,et al.  A description of the fifth-generation Penn State/NCAR Mesoscale Model (MM5) , 1994 .

[46]  D. Pollard,et al.  A Global Climate Model (GENESIS) with a Land-Surface Transfer Scheme (LSX). Part I: Present Climate Simulation. , 1995 .

[47]  S. K. Jenson,et al.  Extracting topographic structure from digital elevation data for geographic information-system analysis , 1988 .

[48]  T. Carlson,et al.  Estimating near-surface soil moisture availability using a meteorologically driven soil-water profile model , 1994 .

[49]  Da‐Lin Zhang,et al.  A High-Resolution Model of the Planetary Boundary Layer—Sensitivity Tests and Comparisons with SESAME-79 Data , 1982 .