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Assessing the skill of hydrology models at simulating the water cycle in the HJ Andrews LTER: Assumptions, strengths and weaknesses
Citation:
Osborne-Gowey, J., D. Bachelet, A. Hamlet, R. B. MCKANE, E. Garcia, AND C. Tague. Assessing the skill of hydrology models at simulating the water cycle in the HJ Andrews LTER: Assumptions, strengths and weaknesses. Presented at American Fisheries Society Meeting, Oregon Chapter, Bend, OR, February 22 - 25, 2011.
Impact/Purpose:
Simulated impacts of climate on hydrology can vary greatly as a function of the scale of the input data, model assumptions, and model structure.
Description:
Simulated impacts of climate on hydrology can vary greatly as a function of the scale of the input data, model assumptions, and model structure. Four models are commonly used to simulate streamflow in model assumptions, and model structure. Four models are commonly used to simulate streamflow in the Pacific Northwest US: the MC1 Dynamic Global Vegetation Model which was originally designed to simulate ecosystem processes at the regional to global scale, the Variable Infiltration Capacity (VIC) model based on the physical representation of the hydrology cycle and used for regional assessments, the Regional Hydro-Ecologic Simulation System (RHESSys) model which was designed to address local issues such as species competition for resources and deep water recharge, and the Visualizing Ecosystems for Land Management Assessments (VELMA) model which was designed to address integrated responses of vegetation, soil, and water resources. We compare the four models between themselves and to streamflow records from the HJ Andrews Long Term Ecological Research site to show differences in their representation of water dynamics at the watershed scale. We 1) document each model’s needs (soil and climate inputs, initial conditions, spinup protocols, 2) compare model results with observations and start calculating an estimate of overall uncertainy, 3) report on model strengths and weaknesses (at what scale are the models most relevant? Can models inform each other?).