原模型阻力相似是开展河工模型试验的基本要求，模型试验的糙率复核受目标值、波动幅值、模型材质及研究重点等多因素的影响，选用合理的加糙手段可大幅提升试验效率和精度。为解决现阶段河工模型试验中存在的加糙方法种类繁多、技术条件复杂、难以快速选择适宜加糙方法的问题，对国内外常用的加糙方法进行了归纳总结，将加糙方法划分为点块型加糙、条带型加糙和膜片型加糙三种方法。介绍了每种方法常用的加糙体，详细说明了各加糙方法的实现手段、优点、不足以及糙率值的可调整范围。草垫为代表的膜片型加糙可实现的糙率峰值达0.08以上，梅花十字板加糙可实现的糙率峰值约0.06，条带型加糙可实现的糙率峰值约为0.04，粘贴尼龙网、玻璃膜以及密实加糙可实现的糙率峰值约为0.02，刨坑加糙方法基本不能提高模型表面糙率。给出了相应的适用条件、加糙范围及对水流结构的影响，以及部分糙率计算方法，以期研究者可根据试验目的快速准确地选取适宜的加糙方法，提高研究效率。

Resistance similarity is an essential requirement in river model experiments. Roughness recheck is affected by the target value, fluctuation amplitude, model material, and research emphasis. A reasonable roughening method will substantially improve the experiment efficiency and accuracy. In order to help researchers quickly choose a reasonable roughening way from the various existing methods, we sorted and reviewed the commonly used roughening methods, which were classified into three types: block-type roughening, strip-type roughening, and patch-type roughening. We introduced the commonly used roughening elements of each method and described in detail the realization means, advantages, drawbacks, and adjustable roughness range of each method. The patch-type roughening methods represented by plastic grass cushions can achieve a roughness value larger than 0.08. The block-type roughening methods represented by cross plates in the form of plum blossom can obtain a peak roughness value of about 0.06. The peak roughness value of strip-type roughening methods is 0.04. Sticking nylon nets or glass film and compact roughening can generally realize a roughness value no larger than 0.02. Digging pits on the model can hardly increase its surface roughness. In addition, this paper presents the methods’ application conditions, roughening ranges, and influence on flow structure, and some roughness calculation methods. It is hoped that with this paper, researchers can determine roughening methods quickly and exactly according to their experiment goals, and improve their research efficiency.

国家自然科学基金（51609265）；国家重点研发计划（2016YFC0401808）