Habitat suitability index (HSI) is a fundamental factor in ecological river-restoration projects for assessing fish habitat to create inhabited environment for aquatic organisms. An accurate estimation of HSI requires long-term-monitored data including flow velocity, water depth, and bed materials; however, this is not easy to collect, and the dataset comprises local characteristics. Therefore, it is difficult to present a generalized method of HSI estimation with limited local and temporal data. In this study, the probability distribution was applied for HSI estimation with limited data measured in the tributaries of Han and Geum Rivers in South Korea. Log-normal distributions were applied to the water depth and velocity data of aquatic habitat for Zacco platypus, and then the developed log-normal distributions were used as the HSI. The HSIs developed by applying the log-normal distribution were compared with the HSIs developed using the instream flow and aquatic system group (IFASG) method. By using the log-normal-distribution-based HSIs, the environmental flows estimated through the physical-habitat-assessment models based on instream flow incremental methodology were also compared with the IFASG-based results. The environmental flows were determined to be similar within an optimal range in both cases of the tributaries of Han and Geum Rivers.

生境适宜性指数（HSI）是生态河流修复项目中的一个基本因素，该项目旨在评估鱼类栖息地，为水生生物创造栖息环境。对HSI的准确估算需要长期监测的数据，包括流速，水深和床料。但是，这不容易收集，并且数据集包含局部特征。因此，很难用有限的本地和时间数据来呈现一种通用的HSI估计方法。在这项研究中，将概率分布应用于韩国的汉江和锦江支流测得的有限数据的HSI估计。对数正态分布应用于Zacco platypus水生栖息地的水深和速度数据，然后将开发的对数正态分布用作HSI。将通过应用对数正态分布开发的HSI与使用河床流量和水生系统组（IFASG）方法开发的HSI进行了比较。通过使用基于对数正态分布的HSI，还将通过基于栖息地流量增量方法的自然栖息地评估模型估算的环境流量与基于IFASG的结果进行了比较。在汉江和锦江支流的两种情况下，确定的环境流量都在最佳范围内相似。