JOURNAL OF HYDROLOGICAL PROCESSES OFFLINE
Similar offline simulations using CLM4 with its dynamic vegetation submodel are also conducted to investigate how dynamic vegetation feedback, a more » process that is being added to more earth system models, may amplify or moderate the intermodel variations of projected future changes. In our study, the contribution of land surface models to the inter-GCM variation of projected future changes in land surface energy and water fluxes are assessed based on output from 19 global climate models (GCMs) and offline Community Land Model version 4 (CLM4) simulations driven by meteorological forcing from the 19 GCMs. (PNNL), Richland, WA (United States) Sponsoring Org.: USDOE Office of Science (SC), Biological and Environmental Research (BER) National Natural Science Foundation of China (NSFC) National Key Research and Development Program of China OSTI Identifier: 1390426 Alternate Identifier(s): OSTI ID: 1550124 Report Number(s): PNNL-SA-127005 Journal ID: ISSN 0022-1694 KP1702030 Grant/Contract Number: AC05-76RL01830 91225302 2016YFC0402404 2016YFC0402406 AC05-76RLO1830 Resource Type: Journal Article: Accepted Manuscript Journal Name: Journal of Hydrology Additional Journal Information: Journal Volume: 551 Journal Issue: C Journal ID: ISSN 0022-1694 Publisher: Elsevier Country of Publication: United States Language: English Subject: 54 ENVIRONMENTAL SCIENCES Eco-hydrological modeling Model coupling Vegetation dynamics Regional hydrological = ,Īssessing and quantifying the uncertainties in projected future changes of energy and water budgets over land surface are important steps toward improving our confidence in climate change projections. Publication Date: Research Org.: Pacific Northwest National Lab. Chinese Academy of Sciences (CAS), Beijing (China).We conclude this result suggests that both natural and anthropogenic factors should be incorporated in dynamic vegetation models to better simulate the eco-hydrological cycle. Compared with a simulation using remotely sensed vegetation cover, the simulation with a dynamic vegetation model more » that considers only climate-induced change showed a 10.3% increase in evapotranspiration, a 47.8% decrease in runoff, and a 62.7% and 71.3% deceleration in changing trend of the outlet river discharge before and after the year 2000, respectively. The CLM-GBHM simulations with static, remotely sensed and model-predicted vegetation conditions showed that the vegetation in the WRB began to recover in the 2000s due to the Grain for Green Program but had not reached the same level of vegetation cover as regions in natural eco-hydrological equilibrium. Compared with CLM, CLM-GBHM increased the Nash Sutcliffe efficiency for daily river discharge simulation (1965–1969) from 0.03 to 0.23 and reduced the relative bias in water table depth simulations (2010–2012) from 32.4% to 13.4%. Both models were implemented in the Wudinghe River Basin (WRB), which is a semi-arid basin located in the middle reaches of the Yellow River, China. In this study, the Community Land Model version 4 (CLM4) LSM was modified with an advanced runoff generation and flow routing scheme, resulting in a new land surface-hydrology coupled model, CLM-GBHM. However, most LSMs have large uncertainties in their representations of ecohydrological processes due to deficiencies in hydrological parameterizations. Land surface models (LSMs) are widely used to understand the interactions between hydrological processes and vegetation dynamics, which is important for the attribution and prediction of regional hydrological variations.
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