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

Chaopeng Shen, Jie Niu, Kuai Fang

Research output: Contribution to journalArticle

26 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)146-161
Number of pages16
JournalEnvironmental Modelling and Software
Volume59
DOIs
StatePublished - Jan 1 2014

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All Science Journal Classification (ASJC) codes

  • Software
  • Environmental Engineering
  • Ecological Modeling

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