Aw Salami

Assessment of Impact of Hydropower Dams Reservoir Outflow on the Downstream River Flood Regime – Nigeria’s Experience

Over more than five decades, the energy sector in Nigeria, particularly the rural energy sector, is characterized by lack of access, low purchasing power and over-dependence on traditional fuels for meeting basic energy needs. In an attempt by the government to solving this challenge, the hydropower scheme came on stream as the forerunner in 1968, 1986 and 1990 at Kainji, Jebba and Shiroro respectively. The objective was to improve access to reliable, secure, affordable, climate friendly and sustainable energy services and to boost investment in energy in Nigeria. However, this solution seems to be characterized with some challenges at the downstream sector of the hydropower dams. The communities in the flood plains experience annual flooding when the authorities of Power Holding Company of Nigeria (PHCN) open the gates of the dams to let off water at the peak of the rains. The floods have caused damages and untold hardships to lives and properties. The occurrence of flood has great effect on communities and farming activities downstream of Jebba and Shiroro dams.

Evaluation of the Hydropower Generation Potential of a Dam Using Optimization Techniques: Application to Doma Dam, Nassarawa, in North Central Nigeria

Abstract Optimization models have been developed to maximize annual energy generation from the Doma dam, subject to the constraint of releases for irrigation, ecological purposes, the water supply, the maximum yield from the reservoir and reservoir storage. The model was solved with LINGO software for various mean annual inflow exceedence probabilities. Two scenarios of hydropower retrofitting were considered. Scenario 1, with the reservoir inflows at 50%, 75%, and 90% probabilities of exceedence, gives the total annual hydropower as 0.531 MW, 0.450 MW and 0.291 MW, respectively. The corresponding values for scenario 2 were 0.615 MW, 0.507 MW, and 0.346 MW respectively. The study also considered increasing the reservoir’s live storage to 32.63Mm3 by taking part of the flood storage so that the maximum draft increases to 7 Mm3. With this upper limit of storage and draft with reservoir inflows of 50%, 75% and 90% probabilities of exceedence, the hydropower generated increased to 0.609 MW, 0.540 MW, and 0.347 MW respectively for the scenario 1 arrangement, while those of scenario 2 increased to 0.699 MW, 0.579MW and 0.406 MW respectively. The results indicate that the Doma Dam is suitable for the production of hydroelectric power and that its generation potential is between 0.61 MW and 0.70 MW.

Morphometrical Analysis and Peak Runoff Estimation for the Sub-Lower Niger River Basin, Nigeria

Abstract This study utilized Spatial Information Technology (SIT) such as Remote Sensing (RS), a Geographical Information System (GIS), the Global Positioning System (GPS) and a high-resolution Digital Elevation Model (DEM) for a morphometrical analysis of five sub-basins within the Lower Niger River Basin, Nigeria. Morpho-metrical parameters, such as the total relief, relative relief, relief ratio, ruggedness number, texture ratio, elongation ratio, circularity ratio, form factor ratio, drainage density, stream frequency, sinuosity factor and bifurcation ratio, have been computed and analyzed. The study revealed that the contribution of the morphometric parameters to flooding suggest catchment No. 1 has the least concentration time and the highest runoff depth. Catchment No. 4 has the highest circularity ratio (0.35) as the most hazardous site where floods could reach a great volume over a small area.

A Review of Models for Evaluation of Climate Change Impact on Water Resources

The use of models to simulate or predict impact of climate change on water resources management is very vital due to continual increase in global warming which invariably affects most important natural resources in the environment. This paper provides an overview of the existing models used for evaluating climate change impact on water resources management. It also compares their relative advantages and drawbacks. It was found that no model can perform satisfactorily the assessment of climate change impact; hence it may be necessary to use one model to compliment the weakness of another. Global Circulation Model (GCM) is not easily accessible in developing countries due to sophistications and processes involved in running it. Moreso, the nature of available data and cost of acquiring it is high. The main advantage of Water Balance (WATBAL) model is that it can model climate change impact in water resources but its major drawback is that it requires many inputs of hydro-meteorological parameters. Regression and Artificial Neural Network (ANN) models are readily available and not too expensive. They can model climate change impact on water resources and hydropower operation. However, the drawback is that enormous data are required for ANN model calibration and operation. It is imperative therefore to anticipate and efficiently prepare for future water resources management and suggest necessary measures to mitigate the effect of climate change.