An intercomparison of approaches for improving operational seasonal streamflow forecasts
For much of the last century, forecasting centers around the world have offered seasonal streamflow predictions to support water management. Recent work suggests that the two major avenues to advance seasonal predictability are improvements in the estimation of initial hydrologic conditions (IHC...
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2017-07-01
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| Series: | Hydrology and Earth System Sciences |
| Online Access: | https://www.hydrol-earth-syst-sci.net/21/3915/2017/hess-21-3915-2017.pdf |
| _version_ | 1818308159955009536 |
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| author | P. A. Mendoza P. A. Mendoza A. W. Wood E. Clark E. Rothwell M. P. Clark B. Nijssen L. D. Brekke J. R. Arnold |
| author_facet | P. A. Mendoza P. A. Mendoza A. W. Wood E. Clark E. Rothwell M. P. Clark B. Nijssen L. D. Brekke J. R. Arnold |
| author_sort | P. A. Mendoza |
| collection | DOAJ |
| description | For much of the last century, forecasting centers around the world
have offered seasonal streamflow predictions to support water management.
Recent work suggests that the two major avenues to advance seasonal
predictability are improvements in the estimation of initial hydrologic
conditions (IHCs) and the incorporation of climate information. This study
investigates the marginal benefits of a variety of methods using IHCs and/or
climate information, focusing on seasonal water supply forecasts (WSFs) in
five case study watersheds located in the US Pacific Northwest region. We
specify two benchmark methods that mimic standard operational approaches –
statistical regression against IHCs and model-based ensemble streamflow
prediction (ESP) – and then systematically intercompare WSFs across a range of lead times. Additional methods include (i) statistical techniques using
climate information either from standard indices or from climate reanalysis
variables and (ii) several hybrid/hierarchical approaches harnessing both
land surface and climate predictability. In basins where atmospheric
teleconnection signals are strong, and when watershed predictability is low,
climate information alone provides considerable improvements. For those
basins showing weak teleconnections, custom predictors from reanalysis fields
were more effective in forecast skill than standard climate indices. ESP
predictions tended to have high correlation skill but greater bias compared
to other methods, and climate predictors failed to substantially improve
these deficiencies within a trace weighting framework. Lower complexity
techniques were competitive with more complex methods, and the hierarchical
expert regression approach introduced here (hierarchical ensemble streamflow prediction – HESP) provided a robust
alternative for skillful and reliable water supply forecasts at all
initialization times. Three key findings from this effort are (1) objective
approaches supporting methodologically consistent hindcasts open
the door to a broad range of beneficial forecasting strategies; (2) the use
of climate predictors can add to the seasonal forecast skill available from
IHCs; and (3) sample size limitations must be handled rigorously to avoid
over-trained forecast solutions. Overall, the results suggest that despite a
rich, long heritage of operational use, there remain a number of compelling
opportunities to improve the skill and value of seasonal streamflow
predictions. |
| first_indexed | 2024-12-13T07:09:51Z |
| format | Article |
| id | doaj.art-13aa8184bd7f4f58ae7a77d120fe76fe |
| institution | Directory Open Access Journal |
| issn | 1027-5606 1607-7938 |
| language | English |
| last_indexed | 2024-12-13T07:09:51Z |
| publishDate | 2017-07-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Hydrology and Earth System Sciences |
| spelling | doaj.art-13aa8184bd7f4f58ae7a77d120fe76fe2022-12-21T23:55:41ZengCopernicus PublicationsHydrology and Earth System Sciences1027-56061607-79382017-07-01213915393510.5194/hess-21-3915-2017An intercomparison of approaches for improving operational seasonal streamflow forecastsP. A. Mendoza0P. A. Mendoza1A. W. Wood2E. Clark3E. Rothwell4M. P. Clark5B. Nijssen6L. D. Brekke7J. R. Arnold8Hydrometeorological Applications Program, National Center for Atmospheric Research, Boulder, CO, USAnow at: Advanced Mining Technology Center (AMTC), Universidad de Chile, Santiago, ChileHydrometeorological Applications Program, National Center for Atmospheric Research, Boulder, CO, USADepartment of Civil and Environmental Engineering, University of Washington, Seattle, WA, USABureau of Reclamation, Boise, ID, USAHydrometeorological Applications Program, National Center for Atmospheric Research, Boulder, CO, USADepartment of Civil and Environmental Engineering, University of Washington, Seattle, WA, USABureau of Reclamation, Denver, CO, USAClimate Preparedness and Resilience Programs, US Army Corps of Engineers, Seattle, WA, USAFor much of the last century, forecasting centers around the world have offered seasonal streamflow predictions to support water management. Recent work suggests that the two major avenues to advance seasonal predictability are improvements in the estimation of initial hydrologic conditions (IHCs) and the incorporation of climate information. This study investigates the marginal benefits of a variety of methods using IHCs and/or climate information, focusing on seasonal water supply forecasts (WSFs) in five case study watersheds located in the US Pacific Northwest region. We specify two benchmark methods that mimic standard operational approaches – statistical regression against IHCs and model-based ensemble streamflow prediction (ESP) – and then systematically intercompare WSFs across a range of lead times. Additional methods include (i) statistical techniques using climate information either from standard indices or from climate reanalysis variables and (ii) several hybrid/hierarchical approaches harnessing both land surface and climate predictability. In basins where atmospheric teleconnection signals are strong, and when watershed predictability is low, climate information alone provides considerable improvements. For those basins showing weak teleconnections, custom predictors from reanalysis fields were more effective in forecast skill than standard climate indices. ESP predictions tended to have high correlation skill but greater bias compared to other methods, and climate predictors failed to substantially improve these deficiencies within a trace weighting framework. Lower complexity techniques were competitive with more complex methods, and the hierarchical expert regression approach introduced here (hierarchical ensemble streamflow prediction – HESP) provided a robust alternative for skillful and reliable water supply forecasts at all initialization times. Three key findings from this effort are (1) objective approaches supporting methodologically consistent hindcasts open the door to a broad range of beneficial forecasting strategies; (2) the use of climate predictors can add to the seasonal forecast skill available from IHCs; and (3) sample size limitations must be handled rigorously to avoid over-trained forecast solutions. Overall, the results suggest that despite a rich, long heritage of operational use, there remain a number of compelling opportunities to improve the skill and value of seasonal streamflow predictions.https://www.hydrol-earth-syst-sci.net/21/3915/2017/hess-21-3915-2017.pdf |
| spellingShingle | P. A. Mendoza P. A. Mendoza A. W. Wood E. Clark E. Rothwell M. P. Clark B. Nijssen L. D. Brekke J. R. Arnold An intercomparison of approaches for improving operational seasonal streamflow forecasts Hydrology and Earth System Sciences |
| title | An intercomparison of approaches for improving operational seasonal streamflow forecasts |
| title_full | An intercomparison of approaches for improving operational seasonal streamflow forecasts |
| title_fullStr | An intercomparison of approaches for improving operational seasonal streamflow forecasts |
| title_full_unstemmed | An intercomparison of approaches for improving operational seasonal streamflow forecasts |
| title_short | An intercomparison of approaches for improving operational seasonal streamflow forecasts |
| title_sort | intercomparison of approaches for improving operational seasonal streamflow forecasts |
| url | https://www.hydrol-earth-syst-sci.net/21/3915/2017/hess-21-3915-2017.pdf |
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