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Geography and Regional Planning: Changing Flow Regime and its Predictability with Climatic Variability in Aya Basin, South Eastern Nigeria
Abstract
Explicating the changing flow regime and its predictability by climatic variability for Aya River, the most probable explanatory determinant(s) were identified; while the implications of increasing high and low flows were also highlighted. Data on mean monthly water level, rainfall, Pan Evaporation and temperature were collected from documented sources.
Analyses techniques included time series, multiple and step-wise regression. The analyses were based on inter-annual deviations in monthly values and intra-annual deviation during the period of 24 years. That the climatic variables jointly significantly explained the general
seasonal pattern of water level regime (F > p < 0.05) was identified. This was corroborated by the significance of the explanatory coefficients of two of the variables by the multiple and step- wise regression. Thus monthly deviation in rainfall and evaporation were the most significant predictors of the monthly deviation in water level at the mean intra-annual level. At the yearly intra-annual deviation level, the most probable determinant and significant predictor of the yearly variation in changing flow was rainfall. The trend analyses shows
that the maximum flow conditions exhibited a cyclic (oscillatory) pattern (variation), while the low flow exhibited positive (increasing) trend. The implication of random fluctuation in maximum flow for agriculture is increasing vulnerability of the floodplain dependent
communities to food insecurity due to unexpected inundation of croplands. In case of the increasing low flow, reduced supply would truncate many domestic chores, while increased pressure on available sources would be heightened.
Analyses techniques included time series, multiple and step-wise regression. The analyses were based on inter-annual deviations in monthly values and intra-annual deviation during the period of 24 years. That the climatic variables jointly significantly explained the general
seasonal pattern of water level regime (F > p < 0.05) was identified. This was corroborated by the significance of the explanatory coefficients of two of the variables by the multiple and step- wise regression. Thus monthly deviation in rainfall and evaporation were the most significant predictors of the monthly deviation in water level at the mean intra-annual level. At the yearly intra-annual deviation level, the most probable determinant and significant predictor of the yearly variation in changing flow was rainfall. The trend analyses shows
that the maximum flow conditions exhibited a cyclic (oscillatory) pattern (variation), while the low flow exhibited positive (increasing) trend. The implication of random fluctuation in maximum flow for agriculture is increasing vulnerability of the floodplain dependent
communities to food insecurity due to unexpected inundation of croplands. In case of the increasing low flow, reduced supply would truncate many domestic chores, while increased pressure on available sources would be heightened.
