A platform for probabilistic Multimodel and Multiproduct Streamflow Forecasting
AffiliationUniv Arizona, Dept Hydrol & Atmospher Sci
satellite precipitation products
MetadataShow full item record
PublisherAMER GEOPHYSICAL UNION
CitationA platform for probabilistic Multimodel and Multiproduct Streamflow Forecasting 2017, 53 (1):376 Water Resources Research
JournalWater Resources Research
Rights© 2016. American Geophysical Union. All Rights Reserved
Collection InformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at email@example.com.
AbstractWe 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.
Note6 month embargo; First published: 17 January 2017
VersionFinal published version
SponsorsNASA-USAID [11-SERVIR11-58]; International Center for Integrated Water Resources Management (ICIWaRM-UNESCO); Australian Research Council through the Centre of Excellence for Climate System Science [CE110001028]; EU [INCO-20011-7.6, 294947]