Babak VaheddoostMustafa Utku YilmazMir Jafar Sadegh SafariVaheddoost, BabakYilmaz, Mustafa UtkuSafari, Mir Jafar Sadegh2025-10-062023095965260959-65261879-178610.1016/j.jclepro.2023.1372462-s2.0-85153562886https://www.scopus.com/inward/record.uri?eid=2-s2.0-85153562886&doi=10.1016%2Fj.jclepro.2023.137246&partnerID=40&md5=753fa4b89de25c1c605ca5066ef55530https://gcris.yasar.edu.tr/handle/123456789/8431https://doi.org/10.1016/j.jclepro.2023.137246The mastery in forecasting the streamflow rates is of great importance in the design planning and resilience against droughts. Likewise the application of flow duration and mass flow curves in the design of the reservoir capacity energy generation water allocation etc. especially at the tributary reaches is a great challenge mostly due to the lack of information and data records. In this study we have developed a methodology to obtain the flow duration curve (FDC) and mass flow curve (MFC) in tributary stream stations with the help of estimated streamflow rates. The procedure suggests using two alternative approaches in the selection of the reference station on the mainstream. The streamflow in the reference station is decomposed into direct runoff (DR) and base flow (BF) using one-parameter digital filter method. Together with the precipitation records in the tributary station the DR and BF on the reference station are then used to estimate the FDC and MFC. The multivariate adaptive regression spline (MARS) and random forest (RF) methods are used to alternate each other and the residual of the models are simulated using the autoregressive conditionally heteroscedastic (ARCH) approach to develop the hybrid MARS-ARCH and RF-ARCH models. A data set related to Coruh River Basin in Turkey is used to confirm the methodology while results with R2 ≥ 0.92 reasonable bias and relative error in the estimation of the expected FDC and MFC rates indicated the robustness of the suggested methodology. © 2023 Elsevier B.V. All rights reserved.Englishinfo:eu-repo/semantics/closedAccessAdvanced Hydrologic Model, Coruh River, Stochastic Model, Ungauged Tributary Streams, Arches, Digital Filters, Forestry, Mass Transfer, Reservoirs (water), Runoff, Stochastic Systems, Stream Flow, Advanced Hydrologic Model, Coruh River, Flow Curves, Flow Duration Curve, Hydrologic Models, Mass Flow, Reference Stations, Stochastic-modeling, Ungaged, Ungauged Tributary Stream, Stochastic ModelsArches, Digital filters, Forestry, Mass transfer, Reservoirs (water), Runoff, Stochastic systems, Stream flow, Advanced hydrologic model, Coruh river, Flow curves, Flow duration curve, Hydrologic models, Mass flow, Reference stations, Stochastic-modeling, Ungaged, Ungauged tributary stream, Stochastic modelsCoruh RiverStochastic ModelUngauged Tributary StreamsAdvanced Hydrologic ModelArticle