Abebe N, Ogden F L, and Pradhan N R (2010) Sensitivity and uncertainty analysis of the conceptual HBV rainfall–runoff model: Implications for parameter estimation. Journal of Hydrology 389(3): 301-310
Amiri A, Salimi H (2020) Comparison of the performance of two MISDc and HBV hydrologic models in runoff simulation of Kakareza basin in Lorestan province. Journal of Water and Sustainable Development 7(4):51-60
Aronica G T, and Candela A (2007) Derivation of flood frequency curves in poorly gauged Mediterranean catchments using a simple stochastic hydrological rainfall-runoff model. Journal of Hydrology 347(1):132-142
Bergström S, and Forsman A (1973) Development of a conceptual deterministic rainfall-runoff mode. Hydrology Research 4(3):147–170
Bergstrom S (2006) Experience from applications of the HBV hydrological model from the perspective of prediction in ungauged basins. IAHS publication 307:97-107
Binaman J, Shoemaker C A (2005) An analysis of high-flow sediment event data for evaluating model performance. Journal of Hydrological Processes 19(3):605-620
Breiman L (1984) Classification and regression trees CA, Wadsworth International Groups. Handbook of Data Mining and Knowledge Discovery 248-276
Breiman L (2001) Random forests. Machine Learning 45(1):5-32
Dastorani M T, Mahjoobi J, Talebi A, and Fakhar F (2018) Application of machine learning approaches in rainfall-runoff modeling (Case Study: Zayandeh_Rood Basin in Iran). Civil Engineering Infrastructures Journal 51(2):293-310
Driessen T L A, Hurkmans R T W L, Terink W, Hazenberg P, Torfs P J J F, and Uijlenhoet R (2010) The hydrological response of the Ourthe catchment to climate change as modelled by the HBV model. Hydrology and Earth System Sciences 14(15):651–665
Fathabadi A, Salajegheh A, and Mahdavi M (2009) Streamflow forecasting using neuro-fuzzy and time series methods. Iranian Journal of Watershed Management Science and Engineering 2(5):21-30 (In Persian)
Firat M, and Güngör M (2007) River flow estimation using adaptive neuro fuzzy inference system. Mathematics and Computers in Simulation 75(3-4):87-96
Jahanshahi A, Shahidi K, Soleimani K, Moghadamnia A, and Mertes R (2022) Flow simulation in basins without statistics using zoning methods in Hamon-Jazmurian basin. Science of Water and Soil (Agriculture Science) 32(2):159-177
Hashim Isam J, Hamideh K, and Ranjan S (2020) Comparative study of conceptual versus distributed hydrologic modelling to evaluate the impact of climate change on future runoff in unregulated catchments. Journal of Water and Climate Change 11(2):341–366
Hawngi M, Masah Bavani A R (2014) Comparison of the performance of two hydrological models IHACRES and HBV light in simulation of Dez basin. National Conference on Watershed Management Science and Engineering (Sustainable Watershed Management), 18-19 February, Birjand, Iran
Konz M, and Seibert J (2010) On the value of glacier mass balances for hydrological model calibration. Journal of Hydrology 385(1-4):238- 246
Klaus V, Maik H, Axel B, and Deborah L (2018) Hydrological model parameter (in)stability– “crash testing” the HBV model under contrasting flood seasonality conditions. Journal Hydrological Sciences Journal 63(7):991-1007
Luce C (2014) Runoff prediction in ungauged basins: Synthesis across processes, places and scales: Edited by Günter Blöschl, Murugesu Sivapalan, Thorsten Wagener, Alberto Viglione, and Hubert Savenije Cambridge University Press, 2013, 465 pp., ISBN: 978-1107028180, 140(hardback), 112 (eBook). Eos, Transactions American Geophysical Union, 95(2):22-22
Lorrai M, and Sechi G M (1995) Neural nets for modelling rainfall-runoff transformations. Water Resources Management 9(4):299-313
Mohammadi M, Vagharfard H, Mahdavi Najafabadi R, Daneshkar Arasteh P, and Nazemosadat M (2021) Rainfall-runoff modelling of coastal watersheds near the Strait of Hormuz using data mining. Iranian Journal of Soil and Water Research 52(2):313-327 (In Persian)
Normand S, Konz M, and Merz J (2010) Anapplication of the HBV model to the Tamor Basin in Eastern Nepal. Journal of Hydrology and Meteorology 7(1):49-58
Radchenko I, Breuer L, Forkutsa I, and Frede H G (2014) Simulating water resource availability under data scarcity- a case study for the Ferghana Valley (Central Asia). Water 6(11):3270–3299
Razavi T, and Coulibaly P (2013) Streamflow prediction in ungauged basins: review of regionalization methods. Journal of hydrologic engineering 18(8):958-975
Santhi C, Arnold J G, Williams J, Dugas W A, and Hauck L (2001) Validation of the SWAT model on a large river basin with point and nonpoint sources. Journal of the American Water Resources Association 37(5):1169–1188
Sohrabi Geshnigani F, Mirabbasi najafabadi R, Golabl M R (2021) Rainfall- runoff modeling using HBV Model and random forest algorithm in Bazoft Watershed. Iranian Soil and Water Research 52(5):1395-1407 (In Persian)
Yaghoubi M, and Massah Bavani A (2014) Sensitivity analysis and comparison of capability of three conceptual models HEC-HMS, HBV and IHACRES in simulating continuous rainfall-runoff in SEMI-ARID Basins. Journal of the Earth and Space Physics 40(2):153-172 (In Persian)
Worland S C, Farmer W H, and Kiang J E (2018) Improving predictions of hydrological low-flow indices in ungaged basins using machine learning. Environmental Modelling and Software 101:169-182
)
