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Hydrological field data from a modeller's perspective: Part 1. Diagnostic tests for model structure
Author(s) -
McMillan Hilary K.,
Clark Martyn P.,
Bowden William B.,
Duncan Maurice,
Woods Ross A.
Publication year - 2010
Publication title -
hydrological processes
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.222
H-Index - 161
eISSN - 1099-1085
pISSN - 0885-6087
DOI - 10.1002/hyp.7841
Subject(s) - evapotranspiration , field (mathematics) , hydrology (agriculture) , hydrological modelling , computer science , conceptual model , environmental science , flow (mathematics) , catchment hydrology , drainage basin , calibration , precipitation , set (abstract data type) , meteorology , geology , geotechnical engineering , mathematics , statistics , cartography , database , climatology , geography , ecology , geometry , pure mathematics , biology , programming language
Hydrological scientists develop perceptual models of the catchments they study, using field measurements and observations to build an understanding of the dominant processes controlling the hydrological response. However, conceptual and numerical models used to simulate catchment behaviour often fail to take advantage of this knowledge. It is common instead to use a pre‐defined model structure which can only be fitted to the catchment via parameter calibration. In this article, we suggest an alternative approach where different sources of field data are used to build a synthesis of dominant hydrological processes and hence provide recommendations for representing those processes in a time‐stepping simulation model. Using analysis of precipitation, flow and soil moisture data, recommendations are made for a comprehensive set of modelling decisions, including Evapotranspiration (ET) parameterization, vertical drainage threshold and behaviour, depth and water holding capacity of the active soil zone, unsaturated and saturated zone model architecture and deep groundwater flow behaviour. The second article in this two‐part series implements those recommendations and tests the capability of different model sub‐components to represent the observed hydrological processes. Copyright © 2010 John Wiley & Sons, Ltd.