Generalized Additive Mixed Modelling of River Discharge in the Black Volta River
Generalized Additive Mixed Modelling of River Discharge in the Black Volta River作者机构：Department of Mathematics and Statistics University of Energy and Natural Resources Sunyani Ghana Department of Statistics University for Development Studies Navrongo Ghana Department of Energy and Environmental Engineering University of Energy and Natural Resources Sunyani Ghana
出 版 物：《Open Journal of Statistics》 (统计学期刊（英文）)
年 卷 期：2017年第7卷第4期
页 面：621-632页
学科分类：1002[医学-临床医学] 100214[医学-肿瘤学] 10[医学]
主 题：River Discharge GAMM Tensor Product Smooth Space-Time Interaction Black Volta River
摘 要：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.
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