Application of Reservoir Performance Indices on Kainji Reservoir System

Resilience may be defined as a yardstick that specifies the extent a reservoir recuperates when it fails previously. A reliable water resource system speedily returns to an acceptable state after a failure. Vulnerability measures severity or extent of failures or letdowns, if and once they occur. Sustainability index (SI) provides a sign of fundamental nature with respects to probable unwanted repercussions if imbalance of waters occurs. Sustainability index (SI) can also be expressed as a mean of reliability, resilience and vulnerability. This study employs commonly used indices (reliability, resilience, and Vulnerability) to assess the performance of Kainji reservoir system. To attain this, rain fall and river flow data were obtained from Kainji Hydrological station in New Bussa Nigeria. Analysis using MAKESENS software was used on the rainfall and river flows to look at the extreme events. In order to determine the performance of the reservoir system some reservoir performance indices were employed, these are; vulnerability, resilience, and sustainability index. This is achieved by adopting relevant existing equations. Reservoir flows and storages ware employed, different draft ratios were considered (0.3- 1.0). Varying demand levels were also chosen (0 – 0.8) as against the coefficient of variation to look at the monotonic behaviour of resilience against the various levels of demand. Volume reliability falls repeatedly as draft/ MAR upsurges and bigger values were attained as S/MAR rises. The analysis on the reservoir shows that as demand decreases the sustainability increases and also the higher the storage ratio the higher the sustainability index. It also shows that as draft ratio increases the resilience decreases, and because the draft ratio decreases the resilience increases. The reservoir system was classified as within year system, which suggests high resilience, less vulnerable and sustainable. The operation rule shows the need for optimization.