The river basins of Imo state, Nigeria are presented as a natural vital resource for sustainable water resources management in the area. The study identified most of all the known rivers in Imo State and provided information like relief, topography and other geographical features of the major rivers which are crucial to aid water management for a sustainable water infrastructure in the communities of the watershed. The rivers and lakes are classified into five watersheds (river basins) such as Okigwe watershed, Mbaise / Mbano watershed, Orlu watershed, Oguta watershed and finally, Owerri watershed. The knowledge of the river basins in Imo State will help analyze the problems involved in water resources allocation and to provide guidance for the planning and management of water resources in the state for sustainable development. Citation: Okoro BC, Uzoukwu RA, Chimezie NM (2014) River Basins of Imo State for Sustainable Water Resources Management. J Civil Environ Eng 4: 134.
The study focused on the application of Flood Routing Models for Flood Mitigation in Orashi River, South-East Nigeria. Flood data were collected for the study area and subjected to statistical analysis. Three flood Routingmodels were comparatively applied including Muskingum model, Level Pool model and Modified Pul's model. Assumed routing period of 2.3 hours which helped to check excessive flood at the downstream section of the river was used. Also a dimensionless weighting factor of 0.15 was also adopted. Muskingum model and Level Pool model which represent linear relationship between measured outflow and predicted outflow for specified inflow and time change of one hour gave high and positive values of coefficients of correlations of 0.9769 and 0.9732 respectively. The Modified Pul's model which also represents a linear relationship between measured outflow and predicted outflow for specified inflow and a time change for one hour showed the highest coefficient of correlation of 0.9984 and lowest standard error of 0.1749. Though, flood models of the Muskingum method and Level Pool method exhibited good correlation, their prediction differed significantly with the corresponding models of original data sets because of high standard error and thus not adequate for field application in similar rivers. A design application was carried out using the Modified Pul's model. The values obtained for routed storage capacity was 348 m 3 while the designed capacity was 354 m 3 . It is recommended that dredging of the river is carried out to achieve the designed capacity. This would eliminate the risk of flooding. The results of the study will serve useful purposes in predicting flood events and design of flood control works in similar basins.
The rate of removal of Total Petroleum Hydrocarbon Content (TPHC) of a crude oil polluted land was investigated using field experimental data generated from the Research Farm soil at the Federal University of Technology Owerri, Imo State, Nigeria. The soil was artificially polluted in the laboratory with crude oil -bonny light -with specific gravity of 0.8323. Petroleum contaminant present in the soil was 230 mg per kilogram of soil. The treatment variables used include: inorganic fertilizer (NPK 20:10:10), poultry manure, cow dung and a mixture of the three in equal proportion. A natural treatment was allowed to occur as the control experiment. fungi as well as bacteria played an important role in the degradation of petroleum hydrocarbon. The identified crude oil degrading Fungi are Penicillium notatum, Mucor spp, Rhizopus stolonifer and Penicillum caseicolum with P. notatum and P. caseicolum (penicillum spp) as the strongest fungi degraders. The identified degrading Bacteria are Pseudomonas putida and Bacillus subtilis. These can therefore be isolated and cultured and then employed on remediation sites either as indigenous or foreign degrading microbes in the engineering of bioremediation of crude oil polluted soil using the best engineering techniques. The treatment with mixture of treatment variables proved to be a better option from the results obtained with 82.38 mg/kg after 9 weeks of remediation followed by fertilizer, 83.13 mg/kg and 86.75 mg/kg for poultry manure. Cow dung had 105.5 mg/kg and the control had least with 204.50 mg/kg.
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