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A platform for probabilistic Multimodel and Multiproduct Streamflow Forecasting

We develop and test a probabilistic real-time streamflow-forecasting platform, Multimodel and Multiproduct Streamflow Forecasting (MMSF), that uses information provided by a suite of hydrologic models and satellite precipitation products (SPPs). The SPPs are bias-corrected before being used as inputs to the hydrologic models, and model calibration is carried out independently for each of the model-product combinations (MPCs). Forecasts generated from the calibrated models are further bias-corrected to compensate for the deficiencies within the models, and then probabilistically merged using a variety of model averaging techniques. Use of bias-corrected SPPs in streamflow forecasting applications can overcome several issues associated with sparsely gauged basins and enable robust forecasting capabilities. Bias correction of streamflow significantly improves the forecasts in terms of accuracy and precision for all different cases considered. Results show that the merging of individual forecasts from different MPCs provides additional improvements. All the merging techniques applied in this study produce similar results, however, the Inverse Weighted Averaging (IVA) proves to be slightly superior in most cases. We demonstrate the implementation of the MMSF platform for real-time streamflow monitoring and forecasting in the Mara River basin of Africa (Kenya & Tanzania) in order to provide improved monitoring and forecasting tools to inform water management decisions.

Identiferoai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/623110
Date01 1900
CreatorsRoy, Tirthankar, Serrat-Capdevila, Aleix, Gupta, Hoshin, Valdes, Juan
ContributorsUniv Arizona, Dept Hydrol & Atmospher Sci, Department of Hydrology & Atmospheric Sciences; University of Arizona; Tucson Arizona USA, Department of Hydrology & Atmospheric Sciences; University of Arizona; Tucson Arizona USA, Department of Hydrology & Atmospheric Sciences; University of Arizona; Tucson Arizona USA, Department of Hydrology & Atmospheric Sciences; University of Arizona; Tucson Arizona USA
PublisherAMER GEOPHYSICAL UNION
Source SetsUniversity of Arizona
LanguageEnglish
Detected LanguageEnglish
TypeArticle
Rights© 2016. American Geophysical Union. All Rights Reserved
Relationhttp://doi.wiley.com/10.1002/2016WR019752

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