TITLE:
Generalized Additive Mixed Modelling of River Discharge in the Black Volta River
AUTHORS:
Wahab A. Iddrisu, Kaku S. Nokoe, Albert Luguterah, Eric O. Antwi
KEYWORDS:
River Discharge, GAMM, Tensor Product Smooth, Space-Time Interaction, Black Volta River
JOURNAL NAME:
Open Journal of Statistics,
Vol.7 No.4,
August
9,
2017
ABSTRACT: River discharge data offer a rich source of
information for reservoir management and flood control, if modelling can
separate out the effects of rainfall, land use, soil type, relief, and weather
conditions. In this paper, we model river discharge data from the Black Volta
River, using Generalised Additive Mixed Models (GAMMs) with a space-time
interaction represented via a tensor product of continuous time and discrete
space. River discharge data from January 2000 to December 2009 for the four
gauge stations along the Black Volta River namely, Lawra, Chache, Bui and Bamboi
were obtained from the hydrological services department
of Ghana and used for model fitting. Four GAMMs were explored, two with
space-time interactions and two without space-time interactions. The comparison
of the performance of the models with space-time interactions and those without
space-time interactions based on Akaike Information Criterion (AIC) and
Bayesian Information Criterion (BIC) suggests that in this application, the
former is better overall and in particular for modelling local variations.
Further, a model with space and time main effects performed better compared
with one without space and time main effects. After model selection, checking
and validation, there is evidence for increasing river discharge from the most
upstream gauge station to the most downstream gauge station for the study
period.