Event and model dependent rainfall adjustments to improve discharge predictions
(English)In: Hydrological Sciences Journal, ISSN 0262-6667, E-ISSN 2150-3435Article in journal (Refereed) Accepted
Most conceptual rainfall–runoff models use as input spatially averaged rainfall fields which are typically associated with significant errors that affect the model outcome. In this study, it is hypothesized that a simple spatially and temporally averaged event–dependent rainfall multiplier can account for errors in the rainfall input. The potentials and limitations of this lumped multiplier approach are explored by evaluating the effects of multipliers on the accuracy and precision of the predictive distributions. Parameter sets found to be behavioural across a range of different flood events were assumed to be a good representation of the catchment dynamics and were used to identify rainfall multipliers for each of the individual events. An effect of the parameter sets on identified multipliers was found, however it was small compared to the differences between events. Accounting for event–dependent multipliers improved the reliability of the predictions. At the cost of a small decrease in precision, the distribution of identified multipliers for past events can be used to account for possible rainfall errors when predicting future events. By using behavioural parameter sets to identify rainfall multipliers, the method offers a simple and computationally efficient way to address rainfall errors in hydrological modelling.
Place, publisher, year, edition, pages
UNITED KINGDOM: Taylor & Francis Group.
rainfall multiplier, rainfall input error, reliability of the predictions, precision of predictions, Topmodel, floods
Earth and Related Environmental Sciences
Research subject Earth Science with specialization in Environmental Analysis
IdentifiersURN: urn:nbn:se:uu:diva-291537DOI: www.tandfonline.com/doi/full/10.1080/02626667.2016.1183775OAI: oai:DiVA.org:uu-291537DiVA: diva2:925810
FunderSida - Swedish International Development Cooperation Agency, 54100006