Multi-variate infilling of missing daily discharge data on the Niger basin

The Niger basin has experienced historical drought episodes and floods in recent times. Reliable hydrological modelling has been hampered by missing values in daily river discharge data. We assessed the potential of using the Multivariate Imputation by Chained Equations (MICE) to estimate both conti...

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Autores principales:	Ganiyu Titilope Oyerinde, Agnide E. Lawin, Oluwafemi E. Adeyeri
Formato:	article
Lenguaje:	EN
Publicado:	IWA Publishing 2021
Materias:	hydrology multiple imputation river discharge spatial scale trend analysis west africa Environmental technology. Sanitary engineering TD1-1066
Acceso en línea:	https://doaj.org/article/aa7b9d1d1b7a4171bc9ecec5caa212f5
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spelling	oai:doaj.org-article:aa7b9d1d1b7a4171bc9ecec5caa212f52021-11-05T21:14:41ZMulti-variate infilling of missing daily discharge data on the Niger basin1751-231X10.2166/wpt.2021.048https://doaj.org/article/aa7b9d1d1b7a4171bc9ecec5caa212f52021-07-01T00:00:00Zhttp://wpt.iwaponline.com/content/16/3/961https://doaj.org/toc/1751-231XThe Niger basin has experienced historical drought episodes and floods in recent times. Reliable hydrological modelling has been hampered by missing values in daily river discharge data. We assessed the potential of using the Multivariate Imputation by Chained Equations (MICE) to estimate both continuous and discontinuous daily missing data across different spatial scales in the Niger basin. The study was conducted on 22 discharge stations that have missing data ranging from 2% to 70%. Four efficiency metrics were used to determine the effectiveness of MICE. The flow duration curves (FDC) of observed and filled data were compared to determine how MICE captured the discharge patterns. Mann-Kendall, Modified Mann-Kendall, Pettit and Sen's Slope were used to assess the complete discharge trends using the gap-filled data. Results shows that MICE near perfectly filled the missing discharge data with Nash-Sutcliffe Efficiency (NSE) range of 0.94–0.99 for the calibration (1992–1994) period. Good fits were obtained between FDC of observed and gap-filled data in all considered stations. All the catchments showed significantly increasing discharge trend since 1990s after gap filling. Consequently, the use of MICE in handling missing data challenges across spatial scales in the Niger basin was proposed. Highlights Runoff data of the Niger basin has a large amount of missing data.; The quality of existing runoff data was improved by a multiple imputation technique.; The effectiveness of the multiple imputation algorithm was influenced by the percentage of missing data.; Trend analysis of gap-filled data shows significantly increasing trends from the 1990s.; Modified Mann-Kendall performs better than the original Mann-Kendall test.;Ganiyu Titilope OyerindeAgnide E. LawinOluwafemi E. AdeyeriIWA Publishingarticlehydrologymultiple imputationriver dischargespatial scaletrend analysiswest africaEnvironmental technology. Sanitary engineeringTD1-1066ENWater Practice and Technology, Vol 16, Iss 3, Pp 961-979 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	hydrology multiple imputation river discharge spatial scale trend analysis west africa Environmental technology. Sanitary engineering TD1-1066
spellingShingle	hydrology multiple imputation river discharge spatial scale trend analysis west africa Environmental technology. Sanitary engineering TD1-1066 Ganiyu Titilope Oyerinde Agnide E. Lawin Oluwafemi E. Adeyeri Multi-variate infilling of missing daily discharge data on the Niger basin
description	The Niger basin has experienced historical drought episodes and floods in recent times. Reliable hydrological modelling has been hampered by missing values in daily river discharge data. We assessed the potential of using the Multivariate Imputation by Chained Equations (MICE) to estimate both continuous and discontinuous daily missing data across different spatial scales in the Niger basin. The study was conducted on 22 discharge stations that have missing data ranging from 2% to 70%. Four efficiency metrics were used to determine the effectiveness of MICE. The flow duration curves (FDC) of observed and filled data were compared to determine how MICE captured the discharge patterns. Mann-Kendall, Modified Mann-Kendall, Pettit and Sen's Slope were used to assess the complete discharge trends using the gap-filled data. Results shows that MICE near perfectly filled the missing discharge data with Nash-Sutcliffe Efficiency (NSE) range of 0.94–0.99 for the calibration (1992–1994) period. Good fits were obtained between FDC of observed and gap-filled data in all considered stations. All the catchments showed significantly increasing discharge trend since 1990s after gap filling. Consequently, the use of MICE in handling missing data challenges across spatial scales in the Niger basin was proposed. Highlights Runoff data of the Niger basin has a large amount of missing data.; The quality of existing runoff data was improved by a multiple imputation technique.; The effectiveness of the multiple imputation algorithm was influenced by the percentage of missing data.; Trend analysis of gap-filled data shows significantly increasing trends from the 1990s.; Modified Mann-Kendall performs better than the original Mann-Kendall test.;
format	article
author	Ganiyu Titilope Oyerinde Agnide E. Lawin Oluwafemi E. Adeyeri
author_facet	Ganiyu Titilope Oyerinde Agnide E. Lawin Oluwafemi E. Adeyeri
author_sort	Ganiyu Titilope Oyerinde
title	Multi-variate infilling of missing daily discharge data on the Niger basin
title_short	Multi-variate infilling of missing daily discharge data on the Niger basin
title_full	Multi-variate infilling of missing daily discharge data on the Niger basin
title_fullStr	Multi-variate infilling of missing daily discharge data on the Niger basin
title_full_unstemmed	Multi-variate infilling of missing daily discharge data on the Niger basin
title_sort	multi-variate infilling of missing daily discharge data on the niger basin
publisher	IWA Publishing
publishDate	2021
url	https://doaj.org/article/aa7b9d1d1b7a4171bc9ecec5caa212f5
work_keys_str_mv	AT ganiyutitilopeoyerinde multivariateinfillingofmissingdailydischargedataonthenigerbasin AT agnideelawin multivariateinfillingofmissingdailydischargedataonthenigerbasin AT oluwafemieadeyeri multivariateinfillingofmissingdailydischargedataonthenigerbasin
_version_	1718443999656673280

Multi-variate infilling of missing daily discharge data on the Niger basin

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