ISSN XXXX XXXX © 2019 IJESC Research Article Volume 9 Issue No. 5 Flood Susceptibility Mapping for Floodplains of Oguta Lake Watershed Obiora-Okeke, O. A1, Okoli, C.S2, Babatola, J. O3 Federal University of Technology, Akure, Nigeria Abstract: Delineating the flood zones along the tributary rivers and lakes in Oguta lake watershed is critical in managing the watershed for flood safety. The flood susceptibility mapping was achieved with Hydrologic Engineering Centre – River Analysis System (HEC-RAS) model and Arc-GIS. HEC-RAS model was used in flood simulation of peak discharges generated from 100-return period storm. The peak discharges was simulated with Hydrologic Engineering Centre – Hydrologic Modeling System (HEC-HMS) model for selected river stations along the rivers’ and lake’s center lines. The HEC-RAS model outputs were overlaid on land use and land cover maps to delineate the flood zones. The flood heights were extracted from cross-sections of flow generated by the HEC-RAS model. The maximum heights of flow for Rivers Njaba, Utu and Awbana and Oguta lake are 4.6 m, 3.4 m, 4.7 m and 5.8 m. The built-area, agricultural land and dense vegetation area susceptible to flood are 9.34 km2, 8.77 km2 and 26.23 km2. Keywords: Flood susceptibility, Delineating, Flood plains, Land use and Land cover 1. INTRODUCTION reasonable results—especially in ungauged basins (Seth et al., 1999). Lengthonget al, 2016 carried out a flood mapping on Globally floods are increasingly among the most devastating Mekong River Cambodia using the HEC-RAS and HEC-HMS natural disasters affecting human life than any other natural models. disasters. According to Abhaset al. (2012), in 2010 alone, 178 million people world-wide were affected by floods and the total The result shows that the total affected areas in both side of this financial losses in the exceptional years such as 1998 and 2010 50 km long of the river (excluding river area around 4600 ha) exceeded $40 billion. was ranged from 1,400 to 7,400 ha (made of various land use such as residential, rice field and industrial area ) while flood It is also reported by the Department for International depth was from zero to about 10 m for both sides of river. Development that one sixth of the global population (one billion people) - the majority of them among the world's low income In this study, the peak discharges output from HEC-HMS model earners - live in the potential path of a 1 in 100 year flood. was used to simulate flood geometry and exported to Arc-GIS to Flooding has adverse effects not only on the environment and delineate flood plains susceptible to flood water inundation as a infrastructural facilities, but also on the health of individuals in result of 100-year return period storm. the affected community. 2. METHODOLOGY: Serious health impacts identified to be associated with flooding are: injuries such as cuts, sprains, and lacerations; incidence of 2.1. Description of Study Area faecal-oral disease such as cholera; appearance of rodent-borne disease; an increase in vector-borne diseases such as malaria; The Oguta Lake catchment located in Imo state, Nigeria. It lies impairment of mental health manifesting in anxiety and between longitude 6o 45’ and 7o 05’ East and latitude 5o 32’ and depression; increase in post-traumatic stress manifesting as sleep 5o 52’North. The lakes catchment drains Njaba, Awbuna and disturbances, irritability and anger (Umunnakwe and Nnaji, Onu-Utu rivers. 2016). Ogutalake which has maximum and mean depths of 8.0 m and Flood susceptibility mapping (flood-prone area) is an essential 5.5 m respectively and shoreline length of 10 km is the largest step for early warning system, emergency services, prevention natural fresh water resources in Imo state, south-eastern Nigeria and mitigation of future floods and implementation of flood (Ahiarakwemet al, 2012). management strategies (Tehranyet al. 2014). The Njaba and Awbuna rivers discharge into the lake all the year In recent years, numerous researchers have shown interest in round while the perennial Utu stream flows into the Ogutalake applying geographical information system (GIS) and remote during the wet seasons. Figure 1 shows the location map of the sensing imagery to the extraction of land surface parameters, lakes catchment in Imo state and Nigeria. The Orashi river flows which, if applied to hydrological models, can be useful to obtain past the lake in its western portion (see figure 1). International Journal of Engineering Science and Computing, May 2019 22405 http://ijesc.org/ Figure.1. Location map of Oguta lake catchment Rainfall distribution in this region is bimodal, with peaks in July it falls within the Benin Formation which consists of friable and September and a two-week break in August. The rainy sands with intercalations of shale/clay lenses and some isolated season begins in March and last till October or early November. units of gravels, conglomerates and very coarse sandstones Annual rainfall varies from 1,990 mm to 2,200 mm. Annual (Ananabaet. al., 1993). The surface geology of the Oguta area mean temperature is above 20oC. The Oguta lake watershed has shows that it is characterized by ferruginized sands that are an average annual relative humidity of 75 percent which is occasionally pebbly and massively bedded (Odigi and Nwadiaro, highest during the rainy season, when it rises to about 90 1988). percent. The local geological setting of OgutaLake indicates that Figure.2. Terrain map of the study area 2.2. HEC-HMS Model 2.3. HEC-RAS Model The Hydrologic Modeling System, developed by the Hydrologic Engineering Center of the United States Army Corps of HEC RAS is a modeling program developed by the US Army Engineers, is a lumped or semi-distributed software package for Corps of Engineers and made available to the public. It models modeling rainfall-runoff processes in watershed. It is public the hydraulics‐ of flow through natural channels and other domain software developed by the US Army Corps of Engineers. channels using two different approaches, i.e. (i) Steady flow It also has a wide range of methods to set up and control simulation, and (ii) Unsteady flow simulation. variables for simulating a rainfall-runoff (USACE, 2000). International Journal of Engineering Science and Computing, May 2019 22406 http://ijesc.org/ 2.4. Hydraulic analysis of flow through tributary rivers and transverse lines intercepts(ranging from 0.30 – 0.60). Peak lake discharge values were generated for the river stations using Geometric data in HEC-RAS model was generated from HEC-HMS model. The peak discharges were generated from Arc-GIS. The flow path center line was established for all rivers. 100-year return period storm for Imo state in Nigeria. The Selected points called river stations were established along these catchment areas for the river station are shown are shown in center lines and were given altitude from terrain model. Figure 3. In order to run the flood simulation HEC-RAS, steady Transverse lines were drawn perpendicularly across the river flow analysis was used for hydraulic analysis. The sub-critical stations. The transversal lines were drawn to determine the banks flow regime was adopted. The resulting cross-section of flow of the river bed and the flood plains. These lines were measured generated for each cross-sections were verified. The top-width of 1000 m from both river banks. Cross-sections were extracted flow a river stations were overlaid on the LU and LC maps to from the altitude values of these transverse lines spaced at determine the land classifications within the flood zones. The distance 500-2000m. The cross-sectional profiles were extracted flood limits for each river stations were connected along the from altitude values extracted from terrain model for flood river longitudinal profile. The land classification of built up, plains and bathymetric survey for the river bed. Manning value agricultural land and dense vegetation areas within the flood were associated to land use and land cover classification the zones were calculated. Figure.3. Sub-watershed for river stations withinOguta lake watershed 3. RESULTS AND DISCUSSION while R. Njaba and R. Awbanais 40 km and 28 km respectively. In the figures mentioned above, it is observed that R. Utu In figure 4, the extreme flood from 100-year return period storm floodplains are the most vulnerable as the overbanks slopes are was calculated as 1606 m/s3. In figures 5, a three-dimensional mild. River Njaba has high susceptibility to flood at lower and view shows the result of hydraulic flow analysis through the mid sections while upper sections from kilometer 32 indicate tributary rivers and lake in Oguta lake watershed. The flood low vulnerability. In R. Awbana, only the lower sections from geometry is captured from the watershed divide to the outflow of km 8 indicate susceptibility to flood as mid and upper section the lake at Orashiriver. R.Utu has the greatest length of 42 km overbanks are steep. Figure.4. Flood hydrograph for 100-year return period International Journal of Engineering Science and Computing, May 2019 22407 http://ijesc.org/ Legend WS PF 2 Ground Bank Sta 40 38 36 34 32 34 42 32 30 40 30 38 28 28 36 26 26 34 24 24 30 22 22 20 26 20 18 18 22 28 16 18 24 14 12 14 20 10 14 8 10 10 6 6 6 2 Figure.5. Flow geometry in X-Y-Z perspective for 100-years return period flood Table 1 shows the maximum heights of flow for Rivers Njaba, 209 m respectively as showed in table 2.