Parameter Estimation in Rainfall-Watertable Relationship Using Kalman Filter

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dc.contributor.authorOwusu-Ansah, Emmanuel
dc.contributor.authorOfori, E.,
dc.contributor.authorKyei-Baffour, N.,
dc.contributor.authorDontwi, I. K.
dc.contributor.authorAtta-Darkwa, T.
dc.date.accessioned2024-12-04T10:23:23Z
dc.date.available2024-12-04T10:23:23Z
dc.date.issued2013-01
dc.descriptionThis article is published by Global Institute for Research and Education2013 and is also available at Global https://www.researchgate.net/publication/278016283
dc.description.abstractEmploying a proper groundwater recharge estimation technique is extremely important for efficient water resource development in a groundwater basin. This paper describes the estimation of groundwater recharge in the Besease basin using the linear Kalman filter mathematical model. The physical model estimated the watertable levels and subsequently derived the infiltration parameters from rainfall inputs and groundwater levels data. The Kalman Filter method used as a recharge estimate resulted in a fit between the simulated hydraulic head and observed sub-surface water level fluctuation. The results show that the infiltration parameter varied considerably over the period of time when it was assumed as time dependent with the recharge values ranging between 0.0-1.27 % for P4 and 0.0-16.5 % for P14 of the incident rainfall. A very high infiltration factor α was obtained when considerable rain fell during June 2009, October 2009 and in June and July, 2010. However, during the periods from December 2009 to April 2010, the infiltration factor was zero which suggested that infiltrated water could not reach the water table but was retained in the unsaturated zone to replenish moisture deficit. Therefore, efficient application of irrigation water, knowledge about the moisture regime and the cropping pattern in the basin is fundamental for ensuring optimal moisture content and watertable level management.
dc.description.sponsorshipKNUST
dc.identifier.citationG.J. E.D.T., Vol. 2(1) 2013:86-95 ISSN 2319 – 7293 86
dc.identifier.urihttps://www.researchgate.net/publication/278016283
dc.identifier.urihttps://ir.knust.edu.gh/handle/123456789/16022
dc.language.isoen
dc.publisherGlobal Institute for Research and Education
dc.titleParameter Estimation in Rainfall-Watertable Relationship Using Kalman Filter
dc.typeArticle
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