Using the RHS Method and Neural Networks in the Study of Hydromorphological Elements of the Description of Łódź Rivers Based on the Example of Jasień and Olechówka

Urbanization has led to significant alterations in river morphology and ecological function, highlighting the need for effective tools to assess and manage these changes. Traditional hydromorphological evaluation methods often fail to capture complex relationships between physical habitat features and anthropogenic pressures. The aim of this study was to apply the River Habitat Survey (RHS) method and Interactive Activation and Competition (IAC) artificial neural networks to assess and describe the hydromorphological condition of the Jasień and Olechówka rivers, located in an urbanized area. The RHS method enables the evaluation of the physical characteristics of rivers and the impact of anthropogenic activities on their environment, in accordance with the requirements of the Water Framework Directive (WFD). Field surveys documented features such as bank structure, vegetation, channel substrate, and artificial modifications. In the subsequent phase of the study, an IAC-type neural network was employed to analyze and interpret the RHS data. This network architecture allows for the identification of hidden relationships between variables, the completion of missing data, as well as contextual analysis and generalization based on similar cases. Integrating RHS data with IAC analysis enabled the development of a model supporting the assessment of anthropogenic impacts on the hydromorphological condition of rivers. The results indicate that both rivers exhibit a high degree of modification, particularly within urban sections, which adversely affects their retention capacity and ecological function. This combined methodological approach provides an innovative and flexible tool for supporting urban river restoration and flood risk management, addressing some of the limitations of existing assessment techniques.