AbstractSeasonal river flow forecasting methods are currently being developed for country-wide application in the United Kingdom, using several different techniques. In this paper, methods based on persistence and historical flow analogues are presented. New 1- and 3-month forecasts are made each month using monthly river flows at 93 stations with records at least 30 years long. The method that performs best is selected for each separate month, catchment and forecast duration. The forecasts based on persistence of the previous month?s flow generally outperform the analogues approach, particularly for slowly responding catchments (mainly in the southeast) with large underground water storage in aquifers. Historical analogues make a useful contribution to the forecasts in the northwest of the country. Correlations between hindcasts and observations that exceed 0.23 and are significant at the 5\% level for a one-sided test are found for 81\% (70\%) of the station?month combinations for the 1-month (3-month) forecast. Editor Z. W. Kundzewicz Associate editor Not assigned
%0 Journal Article
%1 Svensson2016Seasonal
%A Svensson, Cecilia
%D 2016
%I Taylor & Francis
%J Hydrological Sciences Journal
%K uk climateservices seasonal precip hydrology
%N 1
%P 19--35
%R 10.1080/02626667.2014.992788
%T Seasonal river flow forecasts for the United Kingdom using persistence and historical analogues
%U http://dx.doi.org/10.1080/02626667.2014.992788
%V 61
%X AbstractSeasonal river flow forecasting methods are currently being developed for country-wide application in the United Kingdom, using several different techniques. In this paper, methods based on persistence and historical flow analogues are presented. New 1- and 3-month forecasts are made each month using monthly river flows at 93 stations with records at least 30 years long. The method that performs best is selected for each separate month, catchment and forecast duration. The forecasts based on persistence of the previous month?s flow generally outperform the analogues approach, particularly for slowly responding catchments (mainly in the southeast) with large underground water storage in aquifers. Historical analogues make a useful contribution to the forecasts in the northwest of the country. Correlations between hindcasts and observations that exceed 0.23 and are significant at the 5\% level for a one-sided test are found for 81\% (70\%) of the station?month combinations for the 1-month (3-month) forecast. Editor Z. W. Kundzewicz Associate editor Not assigned
@article{Svensson2016Seasonal,
abstract = {AbstractSeasonal river flow forecasting methods are currently being developed for country-wide application in the United Kingdom, using several different techniques. In this paper, methods based on persistence and historical flow analogues are presented. New 1- and 3-month forecasts are made each month using monthly river flows at 93 stations with records at least 30 years long. The method that performs best is selected for each separate month, catchment and forecast duration. The forecasts based on persistence of the previous month?s flow generally outperform the analogues approach, particularly for slowly responding catchments (mainly in the southeast) with large underground water storage in aquifers. Historical analogues make a useful contribution to the forecasts in the northwest of the country. Correlations between hindcasts and observations that exceed 0.23 and are significant at the 5\% level for a one-sided test are found for 81\% (70\%) of the station?month combinations for the 1-month (3-month) forecast. Editor Z. W. Kundzewicz Associate editor Not assigned},
added-at = {2018-06-18T21:23:34.000+0200},
author = {Svensson, Cecilia},
biburl = {https://www.bibsonomy.org/bibtex/26a13e04b7389d54b85c4146ebe9f523f/pbett},
citeulike-article-id = {14513966},
citeulike-linkout-0 = {http://dx.doi.org/10.1080/02626667.2014.992788},
citeulike-linkout-1 = {http://www.tandfonline.com/doi/abs/10.1080/02626667.2014.992788},
day = 2,
doi = {10.1080/02626667.2014.992788},
interhash = {5fa5eabfd1f4d2dcceeb28db9c5900a7},
intrahash = {6a13e04b7389d54b85c4146ebe9f523f},
journal = {Hydrological Sciences Journal},
keywords = {uk climateservices seasonal precip hydrology},
month = jan,
number = 1,
pages = {19--35},
posted-at = {2018-01-09 11:46:48},
priority = {2},
publisher = {Taylor \& Francis},
timestamp = {2018-06-22T18:38:30.000+0200},
title = {Seasonal river flow forecasts for the United Kingdom using persistence and historical analogues},
url = {http://dx.doi.org/10.1080/02626667.2014.992788},
volume = 61,
year = 2016
}