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Simulating current global river runoff with a global hydrological model: model revisions, validation, and sensitivity analysis
Author(s) -
Gosling Simon N.,
Arnell Nigel W.
Publication year - 2011
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.7727
Subject(s) - environmental science , surface runoff , precipitation , climatology , climate model , climate change , scale (ratio) , hydrological modelling , streamflow , relative humidity , drainage basin , hydrology (agriculture) , meteorology , geology , geography , ecology , oceanography , cartography , geotechnical engineering , biology
Global hydrological models (GHMs) model the land surface hydrologic dynamics of continental‐scale river basins. Here we describe one such GHM, the Macro‐scale—Probability‐Distributed Moisture model.09 (Mac‐PDM.09). The model has undergone a number of revisions since it was last applied in the hydrological literature. This paper serves to provide a detailed description of the latest version of the model. The main revisions include the following: (1) the ability for the model to be run for n repetitions, which provides more robust estimates of extreme hydrological behaviour, (2) the ability of the model to use a gridded field of coefficient of variation (CV) of daily rainfall for the stochastic disaggregation of monthly precipitation to daily precipitation, and (3) the model can now be forced with daily input climate data as well as monthly input climate data. We demonstrate the effects that each of these three revisions has on simulated runoff relative to before the revisions were applied. Importantly, we show that when Mac‐PDM.09 is forced with monthly input data, it results in a negative runoff bias relative to when daily forcings are applied, for regions of the globe where the day‐to‐day variability in relative humidity is high. The runoff bias can be up to − 80% for a small selection of catchments but the absolute magnitude of the bias may be small. As such, we recommend future applications of Mac‐PDM.09 that use monthly climate forcings acknowledge the bias as a limitation of the model. The performance of Mac‐PDM.09 is evaluated by validating simulated runoff against observed runoff for 50 catchments. We also present a sensitivity analysis that demonstrates that simulated runoff is considerably more sensitive to method of PE calculation than to perturbations in soil moisture and field capacity parameters. Copyright © 2010 John Wiley & Sons, Ltd.