2011•Hydrology Current ResearchOpen access

Establishing Flow-Catchment Interactions as Means of Regionalising Flow Characteristics of the Save Catchment in Zimbabwe

David Chikodzi

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Abstract

The research was aimed at determining the areas of equal hydrology on the Save catchment for the purposes of estimating flow characteristics on ungauged catchments.Data quality control was first done on flow station data in order identify the best stations that could be use in the formulation the catchment flow characteristics.The flow characteristics created were mean annual runoff; coefficient of variation of runoff; base flow index; coefficient of variation of low flow; coefficient of variation of high flow and the coefficient of variation of monthly wet season flow.Literature was then used to select the catchment characteristics most likely to influence runoff.Redundancy analysis was done to correlate sub zone and runoff characteristics so that the nature and significance of relationships could be determined.Cluster analysis was then used to combine the selected catchment characteristics into natural groups of similar characteristics.Validation of the created clusters was done statistically using canonical variate analysis.The results showed that catchment characteristics significant are on the catchment rainfall (r=0.96); the proportion of each subzone under grasslands (r=0.56); the mean annual evaporation rates (r=-0.74), the coefficient of variation of mean annual rainfall (r=-0.55)and the catchment area (r=-0.53).The whole of the Save catchment had three different clusters and was found to be 60% similar.Validation showed that the catchment characteristics used in the study could explain only a total of 39% of the variation in flow characteristics in their clusters.

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The research was aimed at determining the areas of equal hydrology on the Save catchment for the purposes of estimating flow characteristics on ungauged catchments.Data quality control was first done on flow station data in order identify the best stations that could be use in the formulation the catchment flow characteristics.The flow characteristics created were mean annual runoff; coefficient of variation of runoff; base flow index; coefficient of variation of low flow; coefficient of variation of high flow and the coefficient of variation of monthly wet season flow.Literature was then used to select the catchment characteristics most likely to influence runoff.Redundancy analysis was done to correlate sub zone and runoff characteristics so that the nature and significance of relationships could be determined.Cluster analysis was then used to combine the selected catchment characteristics into natural groups of similar characteristics.Validation of the created clusters was done statistically using canonical variate analysis.The results showed that catchment characteristics significant are on the catchment rainfall (r=0.96); the proportion of each subzone under grasslands (r=0.56); the mean annual evaporation rates (r=-0.74), the coefficient of variation of mean annual rainfall (r=-0.55)and the catchment area (r=-0.53).The whole of the Save catchment had three different clusters and was found to be 60% similar.Validation showed that the catchment characteristics used in the study could explain only a total of 39% of the variation in flow characteristics in their clusters.

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Available abstract

The research was aimed at determining the areas of equal hydrology on the Save catchment for the purposes of estimating flow characteristics on ungauged catchments.Data quality control was first done on flow station data in order identify the best stations that could be use in the formulation the catchment flow characteristics.The flow characteristics created were mean annual runoff; coefficient of variation of runoff; base flow index; coefficient of variation of low flow; coefficient of variation of high flow and the coefficient of variation of monthly wet season flow.Literature was then used to select the catchment characteristics most likely to influence runoff.Redundancy analysis was done to correlate sub zone and runoff characteristics so that the nature and significance of relationships could be determined.Cluster analysis was then used to combine the selected catchment characteristics into natural groups of similar characteristics.Validation of the created clusters was done statistically using canonical variate analysis.The results showed that catchment characteristics significant are on the catchment rainfall (r=0.96); the proportion of each subzone under grasslands (r=0.56); the mean annual evaporation rates (r=-0.74), the coefficient of variation of mean annual rainfall (r=-0.55)and the catchment area (r=-0.53).The whole of the Save catchment had three different clusters and was found to be 60% similar.Validation showed that the catchment characteristics used in the study could explain only a total of 39% of the variation in flow characteristics in their clusters.

Key concepts: Drainage basin, Flow (mathematics), Catchment area, Hydrology (agriculture), Environmental science, Water resource management, Geography, Geology

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