Quantifying the effects of data integration algorithms on the outcomes of a subsurface–land surface processes model

Trans-disciplinary hydrologic models oriented toward practical questions must be accompanied by accurate parameterization techniques. This paper describes the effects of different choices in the integration of various data sources on outcomes of the model Process-based Adaptive Watershed Simulator c...

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Bibliographic Details
Published in:Environmental modelling & software : with environment data news Vol. 59; pp. 146 - 161
Main Authors: Shen, Chaopeng, Niu, Jie, Fang, Kuai
Format: Journal Article
Language:English
Published: Oxford Elsevier Ltd 01.09.2014
Elsevier
Subjects:
Algorithms
Animal, plant and microbial ecology
base flow
Biological and medical sciences
Carbon
CLM
Coarsening
computer software
data collection
Data integration
ecosystems
Fundamental and applied biological sciences. Psychology
General aspects. Techniques
hydrologic models
Hydrology
land use
Mathematical models
Methods and techniques (sampling, tagging, trapping, modelling...)
Parametrization
PAWS
Pedotransfer functions
Physically-based hydrologic model
Pre-processing
primary productivity
soil
stream channels
Surface–subsurface interactions
water table
Watersheds
CLM
Pre-processing
Data integration
PAWS
Physically-based hydrologic model
Surface–subsurface interactions
Pedotransfer functions
Surface-subsurface interactions
Interaction
Models
Algorithm
Subsurface
ISSN:1364-8152
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Summary:Trans-disciplinary hydrologic models oriented toward practical questions must be accompanied by accurate parameterization techniques. This paper describes the effects of different choices in the integration of various data sources on outcomes of the model Process-based Adaptive Watershed Simulator coupled with the Community Land Model (PAWS + CLM). Using our Hierarchical Stochastic Selection method, the represented land use percentages are much closer to the raw dataset, and lead to a 26% difference in carbon flux from that of the traditional dominant classes method. River bed elevations extracted using a novel algorithm agree well with the groundwater table and significantly increase baseflow contribution to streams relative to a coarse-DEM-based model. The inclusion of additional information in the soil pedotransfer functions drastically shifts ET, Net Primary Production and recharge. These results indicate that judicious treatment of input data has strong impacts on hydrologic and ecosystem fluxes. We emphasize the need to report details of data integration procedures. •Novel data pre-processing and integration algorithms are presented.•We showed the impact of River Bed Elevation extraction algorithm on simulated baseflow.•We showed the impact of a novel Hierarchical Stochastic Selection method on land use representation and carbon flux.•We showed the influence of using additional data in soil pedotransfer functions on basin-wide hydrologic and ecosystem fluxes.•We emphasize the need to include details of data integration procedures in the literature.
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ISSN:1364-8152
DOI:10.1016/j.envsoft.2014.05.006