Hydro-environmental flow classification of rivers (case study: Beshar River, Iran)

• We proposed a new hydrological classification for determining minimum environmental flow in rivers. • We assessed fish habitat needs based on optimal water depth and flow velocity. • We evaluated hydrological methods for estimating environmental flow in the Beshar River. From 2013 to 2017, the Beshar River near Yasouj city effectively turned into a dry river during the summer, and only a small subsurface flow was flowing down from it. In the present study, a novel Hydrological Flow Classification (HFC) framework was developed for southern Iranian rivers, capturing flow variability during both wet and drought periods. Based on this classification, two new flow-based indices HFC EFwet and HFC EFdry were introduced to estimate environmental flow (EF) requirements under wet and dry hydrological conditions, respectively. Various hydrological methods including the Tennant method, Tessmann method, and the Global Environmental Flow Calculator (GEFC) methods, were used to estimate the environmental needs of the Beshar River. The HFC method showed a higher accuracy for estimating EF in the Beshar River, with the lowest MAE (0.94). However, the GEFC-C and GEFC-B methods are also recommended for rivers with similar hydrological and climatic conditions. Subcritical flow conditions, characterized by higher depth-to-velocity ratios, are essential for maintaining suitable habitats for Cyprinidae species. This study emphasizes the importance of the critical dry season (July–October) for accurate EF assessment, and effective habitat conservation. Hydrodynamic analysis of twelve river cross-sections indicated a predominantly subcritical flow regime, with Froude Number ( Fr ) values consistently below 1. Optimal ecological conditions were observed when Fr ranged between 0.35 and 0.45, indicating suitable habitat hydraulics. Finally, the ongoing Tang-Sorkh Dam construction threatens the river’s ecology, highlighting the need for adaptive, seasonally adaptive flow management.