Development and evaluation of a hydrologic data-assimilation scheme for short-range flow and inflow forecasts in a data-sparse high-latitude region using a distributed model and ensemble Kalman filtering.
A forecasting system combining a physically-based distributed hydrological model (HYDROTEL), an Ensemble Kalman Filtering (EnKF) Data Assimilation (DA), and forecasted meteorological data (obtained from the North American Ensemble Forecast System; NAEFS) is developed to forecast short-range (0–14 da...
Published in: | Advances in Water Resources |
---|---|
Main Authors: | , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
2019
|
Subjects: | |
Online Access: | https://espace.inrs.ca/id/eprint/9556/ https://espace.inrs.ca/id/eprint/9556/1/P3531.pdf https://doi.org/10.1016/j.advwatres.2019.06.004 |
id |
ftinrsquebec:oai:espace.inrs.ca:9556 |
---|---|
record_format |
openpolar |
spelling |
ftinrsquebec:oai:espace.inrs.ca:9556 2023-05-15T17:10:30+02:00 Development and evaluation of a hydrologic data-assimilation scheme for short-range flow and inflow forecasts in a data-sparse high-latitude region using a distributed model and ensemble Kalman filtering. Samuel, Jos Rousseau, Alain N. Abbasnezhadi, Kian Savary, Stéphane 2019 application/pdf https://espace.inrs.ca/id/eprint/9556/ https://espace.inrs.ca/id/eprint/9556/1/P3531.pdf https://doi.org/10.1016/j.advwatres.2019.06.004 en eng https://espace.inrs.ca/id/eprint/9556/1/P3531.pdf Samuel, Jos, Rousseau, Alain N. orcid:0000-0002-3439-2124 , Abbasnezhadi, Kian et Savary, Stéphane (2019). Development and evaluation of a hydrologic data-assimilation scheme for short-range flow and inflow forecasts in a data-sparse high-latitude region using a distributed model and ensemble Kalman filtering. Advances in Water Resources , vol. 130 . p. 198-220. DOI:10.1016/j.advwatres.2019.06.004 <https://doi.org/10.1016/j.advwatres.2019.06.004>. doi:10.1016/j.advwatres.2019.06.004 cc_by_nc_nd_4 CC-BY-NC-ND data assimilation ensemble Kalman filter ensemble weather prediction flow forecasting HYDROTEL North American Ensemble Forecast System (NAEFS) Article Évalué par les pairs 2019 ftinrsquebec https://doi.org/10.1016/j.advwatres.2019.06.004 2023-02-10T11:45:40Z A forecasting system combining a physically-based distributed hydrological model (HYDROTEL), an Ensemble Kalman Filtering (EnKF) Data Assimilation (DA), and forecasted meteorological data (obtained from the North American Ensemble Forecast System; NAEFS) is developed to forecast short-range (0–14 days lead) flows and inflows in the Aishihik and Mayo basins in Yukon Territory, Canada. The system was assessed at three sites, including at the outlet of the Sekulmun River subbasin of the Aishihik basin for river flow forecasting, as well as at Aishihik Lake and Mayo Lake for reservoir inflow forecasting. To ensure accuracy of forecasting outputs, model development and evaluation was performed systematically by: (i) investigating the use of coupled EnKF and HYDROTEL models for improved flow and inflow estimations, (ii) evaluating NAEFS data for short-range flow and inflow forecasts, and (iii) using probabilistic and deterministic criteria to evaluate the forecast performance of the HYDROTEL-EnKF-NAEFS model at each site. Results illustrate that the DA framework significantly improves flow and inflow forecasts, and raw NAEFS data need to be spatially and temporally corrected to be used for hydrological forecasts. Based on probabilistic and deterministic scores, it was found that the developed forecasting system can provide flow and inflow forecasts at the Sekulmun River subbasin, Mayo Lake, Aishihik Lake sites with high, medium, and low accuracies, respectively. Differences in forecast accuracies at each site are possibly associated with: (i) uncertainties of forecasted meteorological data, (ii) ability of HYDROTEL to capture daily flow and inflow variations, (iii) DA algorithm used, (iv) heterogeneity in basin attributes, and (v) limited data availability particularly in the lake areas. Article in Journal/Newspaper Mayo Yukon Institut national de la recherche scientifique, Québec: Espace INRS Yukon Canada Aishihik ENVELOPE(-137.512,-137.512,61.598,61.598) Aishihik Lake ENVELOPE(-137.164,-137.164,61.454,61.454) Mayo Lake ENVELOPE(-135.046,-135.046,63.763,63.763) Advances in Water Resources 130 198 220 |
institution |
Open Polar |
collection |
Institut national de la recherche scientifique, Québec: Espace INRS |
op_collection_id |
ftinrsquebec |
language |
English |
topic |
data assimilation ensemble Kalman filter ensemble weather prediction flow forecasting HYDROTEL North American Ensemble Forecast System (NAEFS) |
spellingShingle |
data assimilation ensemble Kalman filter ensemble weather prediction flow forecasting HYDROTEL North American Ensemble Forecast System (NAEFS) Samuel, Jos Rousseau, Alain N. Abbasnezhadi, Kian Savary, Stéphane Development and evaluation of a hydrologic data-assimilation scheme for short-range flow and inflow forecasts in a data-sparse high-latitude region using a distributed model and ensemble Kalman filtering. |
topic_facet |
data assimilation ensemble Kalman filter ensemble weather prediction flow forecasting HYDROTEL North American Ensemble Forecast System (NAEFS) |
description |
A forecasting system combining a physically-based distributed hydrological model (HYDROTEL), an Ensemble Kalman Filtering (EnKF) Data Assimilation (DA), and forecasted meteorological data (obtained from the North American Ensemble Forecast System; NAEFS) is developed to forecast short-range (0–14 days lead) flows and inflows in the Aishihik and Mayo basins in Yukon Territory, Canada. The system was assessed at three sites, including at the outlet of the Sekulmun River subbasin of the Aishihik basin for river flow forecasting, as well as at Aishihik Lake and Mayo Lake for reservoir inflow forecasting. To ensure accuracy of forecasting outputs, model development and evaluation was performed systematically by: (i) investigating the use of coupled EnKF and HYDROTEL models for improved flow and inflow estimations, (ii) evaluating NAEFS data for short-range flow and inflow forecasts, and (iii) using probabilistic and deterministic criteria to evaluate the forecast performance of the HYDROTEL-EnKF-NAEFS model at each site. Results illustrate that the DA framework significantly improves flow and inflow forecasts, and raw NAEFS data need to be spatially and temporally corrected to be used for hydrological forecasts. Based on probabilistic and deterministic scores, it was found that the developed forecasting system can provide flow and inflow forecasts at the Sekulmun River subbasin, Mayo Lake, Aishihik Lake sites with high, medium, and low accuracies, respectively. Differences in forecast accuracies at each site are possibly associated with: (i) uncertainties of forecasted meteorological data, (ii) ability of HYDROTEL to capture daily flow and inflow variations, (iii) DA algorithm used, (iv) heterogeneity in basin attributes, and (v) limited data availability particularly in the lake areas. |
format |
Article in Journal/Newspaper |
author |
Samuel, Jos Rousseau, Alain N. Abbasnezhadi, Kian Savary, Stéphane |
author_facet |
Samuel, Jos Rousseau, Alain N. Abbasnezhadi, Kian Savary, Stéphane |
author_sort |
Samuel, Jos |
title |
Development and evaluation of a hydrologic data-assimilation scheme for short-range flow and inflow forecasts in a data-sparse high-latitude region using a distributed model and ensemble Kalman filtering. |
title_short |
Development and evaluation of a hydrologic data-assimilation scheme for short-range flow and inflow forecasts in a data-sparse high-latitude region using a distributed model and ensemble Kalman filtering. |
title_full |
Development and evaluation of a hydrologic data-assimilation scheme for short-range flow and inflow forecasts in a data-sparse high-latitude region using a distributed model and ensemble Kalman filtering. |
title_fullStr |
Development and evaluation of a hydrologic data-assimilation scheme for short-range flow and inflow forecasts in a data-sparse high-latitude region using a distributed model and ensemble Kalman filtering. |
title_full_unstemmed |
Development and evaluation of a hydrologic data-assimilation scheme for short-range flow and inflow forecasts in a data-sparse high-latitude region using a distributed model and ensemble Kalman filtering. |
title_sort |
development and evaluation of a hydrologic data-assimilation scheme for short-range flow and inflow forecasts in a data-sparse high-latitude region using a distributed model and ensemble kalman filtering. |
publishDate |
2019 |
url |
https://espace.inrs.ca/id/eprint/9556/ https://espace.inrs.ca/id/eprint/9556/1/P3531.pdf https://doi.org/10.1016/j.advwatres.2019.06.004 |
long_lat |
ENVELOPE(-137.512,-137.512,61.598,61.598) ENVELOPE(-137.164,-137.164,61.454,61.454) ENVELOPE(-135.046,-135.046,63.763,63.763) |
geographic |
Yukon Canada Aishihik Aishihik Lake Mayo Lake |
geographic_facet |
Yukon Canada Aishihik Aishihik Lake Mayo Lake |
genre |
Mayo Yukon |
genre_facet |
Mayo Yukon |
op_relation |
https://espace.inrs.ca/id/eprint/9556/1/P3531.pdf Samuel, Jos, Rousseau, Alain N. orcid:0000-0002-3439-2124 , Abbasnezhadi, Kian et Savary, Stéphane (2019). Development and evaluation of a hydrologic data-assimilation scheme for short-range flow and inflow forecasts in a data-sparse high-latitude region using a distributed model and ensemble Kalman filtering. Advances in Water Resources , vol. 130 . p. 198-220. DOI:10.1016/j.advwatres.2019.06.004 <https://doi.org/10.1016/j.advwatres.2019.06.004>. doi:10.1016/j.advwatres.2019.06.004 |
op_rights |
cc_by_nc_nd_4 |
op_rightsnorm |
CC-BY-NC-ND |
op_doi |
https://doi.org/10.1016/j.advwatres.2019.06.004 |
container_title |
Advances in Water Resources |
container_volume |
130 |
container_start_page |
198 |
op_container_end_page |
220 |
_version_ |
1766067091929038848 |