Validation of Simulated Runoff From Six Terrestrial Ecosystem Models: Results From Vemap

Vegetation/Ecosystem Modeling and Analysis Project (VEMAP) Phase 2 model experiments investigated the response of biogeochemical and dynamic global veg- etation models (DGVMs) to differences in climate over the conterminous United States. This was accomplished by simulating ecosystem processes using historical climate and atmospheric CO2 records from 1895-1993. We evaluated the behavior of six models (Biome- BGC, Century, GTEC, LPJ, MC1, and TEM) by comparing simulated runoff in 13 water- sheds to gauged streamflow from the Hydro-Climatic Data Network. Metrics used to assess the ''goodness of fit'' between simulated and observed values were: (1) Pearson's r to evaluate the overall data set, (2) Kendall's t to gauge seasonality trends as derived from a time- series analysis of monthly runoff, and (3) three measures of absolute and relative error. We found small differences in performance among the six models over all watersheds. However, the models yielded highly divergent results depending upon the watershed an- alyzed. Performance of the ensemble of models in a watershed was positively correlated with observed streamflow: models in the wettest watersheds in this study were associated with the highest model correlations and largest absolute errors, and models in the driest watersheds were associated with the lowest correlations and smallest absolute errors. Mean relative error was small and nearly constant across watersheds. A bias estimator showed that the models tended to underestimate runoff in wet watersheds and overestimate runoff in dry watersheds. Analysis of long-term trends in runoff using a moving-average approach demonstrated the ability of the models to reproduce temporal variation in observed data, even though quantitative differences among models were large. Models relying on prescribed vegetation (Biome-BGC, Century, and TEM) outper- formed the two DGVMs (LPJ and MC1); GTEC gave the poorest fit to observations due to the absence of an evaporation function and a snow routine. Across all 13 watersheds, TEM ranked the highest in model performance. The validation results presented here suggest that improvements in the simulation of hydrologic processes in land-surface models will come, in part, from a more realistic representation of subgrid-scale soil moisture and from a more detailed understanding and representation of subsurface processes.

[1]  I. C. Prentice,et al.  Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model , 2003 .

[2]  D. C. Lewis,et al.  Hydrology in a California oak woodland watershed: a 17-year study , 2000 .

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

[4]  Walter J. Rawls,et al.  Predicting runoff from Rangeland Catchments: A comparison of two models , 1990 .

[5]  Van Genuchten,et al.  A closed-form equation for predicting the hydraulic conductivity of unsaturated soils , 1980 .

[6]  John L. Monteith,et al.  Accommodation between transpiring vegetation and the convective boundary layer , 1995 .

[7]  D. I. Hawkins,et al.  100 Statistical Tests , 1994 .

[8]  A. Bondeau,et al.  Comparing global models of terrestrial net primary productivity (NPP): overview and key results , 1999 .

[9]  Gregory J. McCabe,et al.  A step increase in streamflow in the conterminous United States , 2002 .

[10]  Charles J Vörösmarty,et al.  Potential evaporation functions compared on US watersheds: Possible implications for global-scale water balance and terrestrial ecosystem modeling , 1998 .

[11]  R. Neilson.  A Model for Predicting Continental‐Scale Vegetation Distribution and Water Balance , 1995 .

[12]  Francisco Olivera,et al.  Global‐scale flow routing using a source‐to‐sink algorithm , 2000 .

[13]  J. M. Landwehr,et al.  Hydro-climatic data network (HCDN); a U.S. Geological Survey streamflow data set for the United States for the study of climate variations, 1874-1988 , 1992 .

[14]  Steven W. Running,et al.  Modeled responses of terrestrial ecosystems to elevated atmospheric CO2: a comparison of simulations by the biogeochemistry models of the Vegetation/Ecosystem Modeling and Analysis Project (VEMAP) , 1998, Oecologia.

[15]  Ramakrishna R. Nemani,et al.  The VEMAP integrated database for modelling United States ecosystem/vegetation sensitivity to climate change , 1995 .

[16]  Taikan Oki,et al.  Assessment of Annual Runoff from Land Surface Models Using Total Runoff Integrating Pathways (TRIP) , 1999 .

[17]  S. Running,et al.  Simulated dry matter yields for aspen and spruce stands in the North American boreal forest , 1992 .

[18]  J. Famiglietti,et al.  Response of the water balance to climate change in the United States over the 20th and 21st centuries: Results from the VEMAP Phase 2 model intercomparisons , 2004 .

[19]  A. McGuire,et al.  Interactions between carbon and nitrogen dynamics in estimating net primary productivity for potential vegetation in North America , 1992 .

[20]  W. Parton,et al.  Contribution of Increasing CO, and Climate to Carbon , 2004 .

[21]  Eric F. Wood,et al.  Application of a macroscale hydrologic model to estimate the water balance of the Arkansas-Red River Basin , 1996 .

[22]  A. McGuire,et al.  Global climate change and terrestrial net primary production , 1993, Nature.

[23]  R. Koster,et al.  The Offline Validation of Land Surface Models: Assessing Success at the Annual Timescale , 1999 .

[24]  H. Tian,et al.  Climatic and biotic controls on annual carbon storage in Amazonian ecosystems , 2000 .

[25]  W. Parton,et al.  Analysis of factors controlling soil organic matter levels in Great Plains grasslands , 1987 .

[26]  Vemap Participants.  Vegetation/ecosystem modeling and analysis project: Comparing biogeography and biogeochemistry models in a continental-scale study of terrestrial ecosystem responses to climate change and CO2 doubling , 1995 .

[27]  J. R. Wallis,et al.  Hydro-Climatological Trends in the Continental United States, 1948-88 , 1994 .

[28]  Eric F. Wood,et al.  Evapotranspiration and runoff from large land areas: Land surface hydrology for atmospheric general circulation models , 1991 .

[29]  I. C. Prentice,et al.  BIOME3: An equilibrium terrestrial biosphere model based on ecophysiological constraints, resource availability, and competition among plant functional types , 1996 .

[30]  J. M. Landwehr,et al.  Temporal variability in the hydrologic regimes of the United States , 1997 .

[31]  W. Post,et al.  Historical variations in terrestrial biospheric carbon storage , 1997 .

[32]  Zong-Liang Yang,et al.  The Project for Intercomparison of Land-surface Parameterization Schemes (PILPS) Phase 2(c) Red–Arkansas River basin experiment:: 1. Experiment description and summary intercomparisons , 1998 .

[33]  W. Parton,et al.  TERRESTRIAL NPP: TOWARD A CONSISTENT DATA SET FORGLOBAL MODEL EVALUATION , 1999 .

[34]  C. Daly,et al.  A Statistical-Topographic Model for Mapping Climatological Precipitation over Mountainous Terrain , 1994 .

[35]  Harry F. Lins,et al.  Streamflow trends in the United States , 1999 .

[36]  F. Woodward,et al.  Global response of terrestrial ecosystem structure and function to CO2 and climate change: results from six dynamic global vegetation models , 2001 .

[37]  Michael T. Coe,et al.  Feedbacks between climate and surface water in northern Africa during the middle Holocene , 1997 .

[38]  E. Rastetter,et al.  Continental scale models of water balance and fluvial transport: An application to South America , 1989 .

[39]  Edward B. Rastetter,et al.  Validating models of ecosystem response to global change , 1996 .

[40]  Robert J. Scholes,et al.  Observations and modeling of biomass and soil organic matter dynamics for the grassland biome worldwide , 1993 .

[41]  Gopal Kanji,et al.  100 Statistical Tests , 1994 .

[42]  I. Watterson,et al.  A comparison of present and doubled CO2 climates and feedbacks simulated by three general circulation models , 1999 .

[43]  T. McMahon,et al.  Identification and explanation of continental differences in the variability of annual runoff , 2001 .

[44]  Robert E. Davis,et al.  Statistics for the evaluation and comparison of models , 1985 .

[45]  Gregory J. McCabe,et al.  Explaining spatial variability in mean annual runoff in the conterminous United States , 1999 .

[46]  J. Monteith,et al.  Principles of Environmental Physics , 2014 .

[47]  Victor Brovkin,et al.  Simulation of an abrupt change in Saharan vegetation in the Mid‐Holocene , 1999 .

[48]  J. Nash,et al.  River flow forecasting through conceptual models part I — A discussion of principles☆ , 1970 .

[49]  Danny Marks,et al.  Characterizing the distribution of observed precipitation and runoff over the continental United States , 1992 .

[50]  Cort J. Willmott,et al.  On the Evaluation of Model Performance in Physical Geography , 1984 .

[51]  Dominique Bachelet,et al.  DYNAMIC SIMULATION OF TREE–GRASS INTERACTIONS FOR GLOBAL CHANGE STUDIES , 2000 .

[52]  G. Bonan.  The Land Surface Climatology of the NCAR Land Surface Model Coupled to the NCAR Community Climate Model , 1998 .

[53]  S. Hagemann,et al.  The influence of rooting depth on the simulated hydrological cycle of a GCM , 1999 .

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

[55]  H. R. Haise,et al.  Estimating evapotranspiration from solar radiation , 1963 .

[56]  R. Grayson,et al.  The use of river runoff to test CSIRO9 land surface scheme in the Amazon and Mississippi River Basins , 2000 .

[57]  J. Hewlett,et al.  A REVIEW OF CATCHMENT EXPERIMENTS TO DETERMINE THE EFFECT OF VEGETATION CHANGES ON WATER YIELD AND EVAPOTRANSPIRATION , 1982 .

[58]  M. Sivapalan,et al.  Climate and landscape controls on water balance model complexity over changing timescales , 2002 .

[59]  Berrien Moore,et al.  Modeling basin-scale hydrology in support of physical climate and global biogeochemical studies: An example using the Zambezi River , 1991 .

[60]  C. W. Richardson.  Stochastic simulation of daily precipitation, temperature, and solar radiation , 1981 .

[61]  S. Running,et al.  8 – Generalization of a Forest Ecosystem Process Model for Other Biomes, BIOME-BGC, and an Application for Global-Scale Models , 1993 .

[62]  W. Parton,et al.  Dynamics of C, N, P and S in grassland soils: a model , 1988 .

[63]  Edward T. Linacre,et al.  A simple formula for estimating evaporation rates in various climates, using temperature data alone , 1977 .

[64]  D. Easterling,et al.  Indices of Climate Change for the United States , 1996 .

[65]  A. Whitmore,et al.  Modelling the fate of nitrogen in crop and soil in the years following application of 15N-labelled fertilizer to winter wheat , 1993, The Journal of Agricultural Science.