首页> 外文期刊>Civil and Environmental Research >Identification of Owan Catchment Run-of-River Hydropower Potential Sites in Benin Owena River Basin Nigeria Using GIS And RS Procedures
【24h】

Identification of Owan Catchment Run-of-River Hydropower Potential Sites in Benin Owena River Basin Nigeria Using GIS And RS Procedures

机译:使用GIS和RS程序识别贝宁Owena河流域尼日利亚河流域河流水电潜力遗址

获取原文
           

摘要

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.
机译:水电经受国际公认的是清洁,价格实惠和可靠的能源来源,这些来源是以全球能源供应组合的重要方式贡献,但不幸的是,尼日利亚的情况表明,考虑到15 GW的水电潜力,只有大约2 GW( 13%)已经利用了。尼日利亚小水电(SHP)水平低,由于每年有超过2亿人的国家提供3.5 GW SHP潜力的3.5 GW SHP潜力,每年有333亿毫米的地表用水,可用于增加能源进入2018年百分比为34.在本研究中,与遥感(RS)一起使用自然资源保护服务曲线数(NRCS-CN)计算流域中特定降雨事件的表面径流量(RS)和地理信息系统(GIS)。土地利用陆地覆盖(LULC)欧南盆地的阶级使用图像分类程序划定了Landsat 8卫星图像,并与GIS环境中的子盆地的水文土壤(HSG)集成来获得径流曲线数(CNS )对于这项研究。使用人工神经网络的远程感官信息的降水估计的估计的CN和降雨数据 - 2018年研究区域的气候数据记录(Persiann - CDR)用于计算2km间隔的125次映射点上的峰值排放量欧南河。衡量站数据将系数的系数与68%的系数相关,而与Persiann-CDR相比的尼日利亚气象学机构(Nimet)数据产生了70%的相关性。使用2%最小坡度和10M可用头部的盆湿法指示器必须在网站上考虑到ROR水电之前的两点之间,在OWAN中识别20分,功率范围为423.015kw至5,456.646kw,92%可用流动每年超越。该研究表明,NRCS-CN方法与RS和GIS结合使用,可以在没有弱水文数据的情况下使用流域水法成功地模拟排出。此外,由于观察和计算的径流之间的显着协定,这项研究的方法和模型建议用于贝宁河流域,尼日利亚的尼日利亚,其他地区,以及数据稀缺性挑战的地区。
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号