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Observational uncertainties in hypothesis testing: investigating the hydrological functioning of a tropical catchment
Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL. Univ Bristol, Dept Civil Engn, Bristol BS8 1TR, Avon, England.;IVL Swedish Environm Res Inst, S-10031 Stockholm, Sweden..
Univ Aberdeen, Northern Rivers Inst, Sch Geosci, Aberdeen AB24 3UF, Scotland.;Univ Costa Rica, Dept Geog, San Jose 2060, Costa Rica..
2015 (English)In: Hydrological Processes, ISSN 0885-6087, E-ISSN 1099-1085, Vol. 29, no 23, 4863-4879 p.Article in journal (Refereed) Published
Abstract [en]

Hypothesis testing about catchment functioning with conceptual hydrological models is affected by uncertainties in the model representation of reality as well as in the observed data used to drive and evaluate the model. We formulated a learning framework to investigate the role of observational uncertainties in hypothesis testing using conceptual models and applied it to the relatively data-scarce tropical Sarapiqui catchment in Costa Rica. Observational uncertainties were accounted for throughout the framework that incorporated different choices of model structures to test process hypotheses, analyses of parametric uncertainties and effects of likelihood choice, a posterior performance analysis and (iteratively) formulation of new hypotheses. Estimated uncertainties in precipitation and discharge were linked to likely non-linear near-surface runoff generation and the potentially important role of soils in mediating the hydrological response. Some model-structural inadequacies could be identified in the posterior analyses (supporting the need for an explicit soil-moisture routine to match streamflow dynamics), but the available information about the observational uncertainties prevented conclusions about other process representations. The importance of epistemic data errors, the difficulty in quantifying them and their effect on model simulations was illustrated by an inconsistent event with long-term effects. Finally we discuss the need for new data, new process hypotheses related to deep groundwater losses, and conclude that observational uncertainties need to be accounted for in hypothesis testing to reduce the risk of drawing incorrect conclusions.

Place, publisher, year, edition, pages
2015. Vol. 29, no 23, 4863-4879 p.
Keyword [en]
observational uncertainty, hypothesis testing, catchment functioning, hydrological processes, tropics, model evaluation
National Category
Oceanography, Hydrology, Water Resources
URN: urn:nbn:se:uu:diva-267649DOI: 10.1002/hyp.10533ISI: 000363728300004OAI: oai:DiVA.org:uu-267649DiVA: diva2:874497
EU, FP7, Seventh Framework Programme, 329762
Available from: 2015-11-27 Created: 2015-11-25 Last updated: 2015-11-27Bibliographically approved

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