Increase land use change is one of the consequences of rapid population growth of cities in developing countries with its negative consequences on the environment. This study generates previous and present land use of Ala watershed and project the future land use using Markov chain model and ArcGIS software (version 10.2.1). Landsat 7, Enhanced Thematic mapper plus (ETM+) image and Landsat 8 operational land imager (OLI) with path 190 and row 2 used to generate land use (LU) and land cover (LC) images for the years 2000, 2010 and 2019. Six LU/LC classes were considered as follows: developed area (DA), open soil (OS), grass surface (GS), light forest (LF), wetland (WL) and hard rock (HR). Markov chain analysis was used in predicting LU/LC types in the watershed for the years 2029 and 2039. The veracity of the model was tested with Nash Sutcliffe Efficiency index (NSE) and Percent Bias methods. The model results show that the study area is growing rapidly particularly in the recent time. This urban expansion results in significant decrease of WL coverage areas and the significant increase of DA. This implies reduction in the available land for dry season farming and incessant flood occurrence. Keywords: Land cover, land use change, Markov chain, ArcGIS, watershed, urbanization

Increased rainfall amounts are projected in the humid southern parts of Nigeria due to climate change. The consequence of higher rainfall in future years would result to higher peak runoffs and flood stages in streams in these parts. The focus of this study is to simulate peak runoff at the outlet of Ogbese river watershed for future years of 2030, 2040, 2050 and 2060. Local twenty years (2000-2019) historical rainfall depths were used to statically downscale General Circulation Model outputs in the future for RCP 4.5 climate scenario. Downscaled rainfall depths were inputted in HEC-HMS model version 4.2 for rainfall-runoff simulation. The watershed was delineated with DEM in ArcGIS while four land use and land cover classifications were extracted with QGIS. Maximum rainfall depths projected in years 2030, 2040, 2050 and 2060 were 38.5mm/hr, 39mm/hr, 42mm/hr and 46mm/hr respectively. Peak runoff discharge simulated for RCP 4.5 climate scenario in years 2030, 2040, 2050 and 2060 are 1771m3/s, 1826 m3/s, 1897 m3/s and 2200 m3/s respectively. This represents 24.2% increase peak discharge between 2030 and 2060. Land area delineated for the catchment is 1946.2 km2. The LULC classification areas for urban area, forest, rock outcrop and bare land are 81.59 km2, 1721.84 km2, 146.27 km2 and 4.11 km2 respectively. The soil types are sandy clay loam (92.51 %), sandy loam (6.84 %), and clay (0.65 %). Curve Number and Initial abstraction parameter values are 70.27 and 2.89 respectively. Keywords- Climate change, GCM, HEC-HMS , Ogbese river, Peak runoff

No abstract

No abstract

Land use and land cover (LULC) changes in Ogbese watershed due to urbanization implies increased areas of low infiltration. This results to higher flow rates downstream the watershed. This study estimates the changes in peak flow rates at the watershed’s outlet for present and future LULC. Rainfall-runoff simulation was achieved with Hydrologic Engineering Centre-Hydrologic Modeling System (HEC-HMS) version 4.2 while future LULC was projected with Markov Chain model. Rainfall inputs to the hydrologic model were obtained from intensity-duration-frequency curves for Ondo state. Landsat 7, Enhanced Thematic mapper plus (ETM+) image and Landsat 8 operational land imager (OLI) with path 190 and row 2 were used to generate LULC images for the years 2002, 2015 and 2019. Six LULC classes were extracted as follows: built up area, bare surface, vegetation, wetland, rock outcrop and waterbody.  Future LULC in year 2025 and 2029 were projected with Markov Chain model. The model prediction was verified with Nash Sutcliffe Efficiency index (NSE). NSE value of 0.79 was calculated indicating LULC changes in the watershed was Markovian. Results show that built up area cover in 2019 is projected to increase by 26.1% in 2024 and 39.9% in 2029 and wetland is projected to decreased by 1.2% in 2024 and 2.3% by 2029. Runoff peaks for these LULC projections indicate increase by 0.24% in 2024 and 1.19% in 2029 at the watershed’s outlets for 100-year return period rainfall.