Small hydropower (SHP) is one of the most critical renewable energy that is well adapted to the rural localities in less developed countries across the world. Most rural communities in Nigeria are off the national power grid and are bedevilled by an inconsistent supply of electricity. The one possible panacea to the rural energy crisis is harnessing the terrain and abundant rivers and streams within their domain. This study aimed to identify and select suitable sites for the SHP dam in the upper Benue river watershed. Ten thematic layers, land use, precipitation, geology, soil, slope, elevation, stream power index, topographic wetness index, drainage density, and flow, were integrated with Geographic information system and Analytical hierarchy process. A composite suitability map created revealed that 7.5% of the watershed is of a very high suitable class, while 17.5% of the watershed is of a very low suitable class. To select an ideal location, a semi-automatic approach was developed to identify narrow valleys by intersecting contour with stream order and the suitability layer. Eighteen (18) potential dam sites were identified after a query operation was done. The developed method was validated using field data which were correlated with the model output using t-Test; paired two samples for the mean. A strong Pearson correlation of 0.71 between the field data and the semi-automatic approach was observed. The approach offers good prospects for dam site selection. Based on a field survey, the potential dam sites are feasible economically and technically for SHP dam construction that will provide cheap renewable energy to millions of inhabitants in the watershed.

小水电 (SHP) 是最重要的可再生能源之一，非常适合世界各地欠发达国家的农村地区。尼日利亚的大多数农村社区都没有国家电网，并且受到电力供应不稳定的困扰。解决农村能源危机的一种可能的灵丹妙药是利用其领域内的地形和丰富的河流和溪流。本研究旨在为贝努埃河上游流域的小水电大坝确定和选择合适的地点。土地利用、降水、地质、土壤、坡度、高程、河流动力指数、地形湿度指数、排水密度、流量等10个专题层与地理信息系统和层次分析法相结合。创建的复合适宜性图显示 7. 5% 的流域为非常高的适宜等级，而 17.5% 的流域为非常低的适宜等级。为了选择理想位置，开发了一种半自动方法，通过将等高线与河流秩序和适宜性层相交来识别狭窄的山谷。在完成查询操作后，确定了十八 (18) 个潜在的坝址。使用与使用 t 检验的模型输出相关联的现场数据对开发的方法进行了验证；将两个样本配对为平均值。观察到现场数据和半自动方法之间的强 Pearson 相关系数为 0.71。该方法为大坝选址提供了良好的前景。根据实地调查，