Abstract
Hydropower is recognized internationally as a source of clean, affordable, and reliable energy that has contributed in a significant way to the global energy supply mix but unfortunately, this is not the case in Nigeria considering hydropower potential of 15 GW where only approximately 2 GW (13%) has been harnessed. Nigeria Small Hydropower (SHP) level is low, as less than 0.1 GW out of 3.5 GW SHP potential is available in a country of over 200 million people with potentials of 333BCM of surface water annually which can be used to increase energy access especially in the rural area where the percentage in 2018 is 34. In this study, Natural Resources Conservation Service - Curve Number (NRCS-CN) method which calculates surface runoff volume for a particular rainfall event in a watershed was applied in conjunction with Remote Sensing (RS) and Geographic Information System (GIS). Land Use Land Cover (LULC) classes of Owan Sub-basin were delineated from Landsat 8 satellite Image using Image Classification procedure and integrated with the hydrologic soil group (HSG) of the sub-basin in a GIS environment to obtain runoff Curve Numbers (CNs) for this study. The estimated CNs and rainfall data of Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks - Climate Data Record (PERSIANN – CDR) of the study area for the year 2018 were used to calculate the peak discharges over 125 mapped out points at 2km interval in Owan river. The gauging station data correlates NRCS-CN with a coefficient of 68 % while the Nigerian Meteorological Services Agency (NIMET) data compared with PERSIANN-CDR yielded a 70 % correlation. Using the basin hydrometric indicators of 2% minimum slope and 10m available head which must exist between two points before a site can be considered for ROR hydropower, 20 points were identified in Owan with power range from 423.015kW to 5,456.646kW at 92% available flow exceedance annually. This study revealed that NRCS-CN method combined with RS and GIS can simulate discharge successfully using watershed hydrometry in the absence of weak hydrological data. Also, owing to a significant degree of agreement between the observed and calculated runoff, the method, and models employed for this study are recommended for field applications in Benin-Owena River Basin, Nigeria at large, and other regions with data scarcity challenges hydrologically. Keywords : run-of-river, hydropower potential, Remote Sensing, Geographic Information System, NRCS-CN model. DOI: 10.7176/CER/12-10-05 Publication date: October 31 st 2020
Highlights
Increasing request for energy, from inexhaustible and green sources, encourages small hydropower (SHP) plants development and energizes interest in new investigation studies
This paper taking into account technical, economic, and environmental vulnerabilities of Owan sub-basin describes the application of Geographic Information System (GIS) & Remote Sensing (RS) tools together with Natural Resources Conservation Service - Curve Number (NRCS-Curve Numbers (CNs)) rainfall-runoff model in the selection of sustainable hydropower potential sites and categorizing them based on available power annually amidst insufficient comprehensive hydrological data
Owan sub-basins (Figure 2) is on 6°4'52.039" to 5°43'51.465" East longitude and 7°8'58.834" to 6°39'53.906"North latitude with elevation coverage 50 - 400m above Mean Sea Level (MSL), yearly precipitation 1630 – 2133mm, slope class 0 to 42.7%, Land Use Land Cover (LULC) that varies from dense and mixed vegetation to Build up areas with loamy and sandy loamy as the predominant soil which spans a total area of 1216.50km2
Summary
Increasing request for energy, from inexhaustible and green sources, encourages small hydropower (SHP) plants development and energizes interest in new investigation studies. According to (Dudhani et al 2006) a survey phase carefully carried out in a site gives administrators appropriate and correct details to arrive at the concluding set of choices with minimal impact of the hydropower exploitation over other activities, active infrastructure amenities, and the environment. Within this scenario, Streams in developing countries including Nigeria are poorly gauged and lacking in critical hydrological information and data even though world’s hydropower potential of about 12 % is in Africa just 5 % of this potential has been tapped (ESHA 2006); (FAO 2008). There are many streams and rivers in Nigeria, but like many developing countries SHP deployment is minimal considering that out of the evaluated 3.5GW SHP utilizable potential existing in the country, less than 0.1GW has been tapped which represents approximately 2% (ECN 2014; Bala 2019; Ochigbo 2019)
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