پهنه‌بندی تطبیقی سیلاب در حوضه آبخیز چشمه‌کیله، تنکابن

Entezari, M., Jalilian, T., & Darvish Khatouni, J. (2019). Zoning of flood susceptibility map using performance evaluation of frequency ratio and weight of evidence methods (Kermanshah province). Journal of Spatial Analysis of Environmental Hazards, 6 (4): 143-160. (In Persian)

Kia, A., Khaledi, S., & Janbazghobadi, Gh. (2021). Determination of flood potential effective factors in hydrological homogenous regions, (Case study: Se-Hezar and Do-Hezar watersheds Cheshmehkileh Tonekabon), Volume 10, Issue 38 - Serial Number 38, Pages 235-258. (In Persian)

Mohammadi, M., A., Mohammadi, F., Fakherifard, A., & Bijanvand, S. (2020). Derivation of Rule Curve for Flood Risk Zone A Case Study: Baranduz-Chay River, Volume 7, Issue 22 - Serial Number 22, Pages 87-108, (In Persian)

Madadi, A., Piroozi, E., & Aghayary, L. (2019). Flood Hazard Zonation by Combining SCS-CN and WLC Methods (Case study: Khiyave Chay Meshkinshahr Basin), Volume 5, Issue 17 - Serial Number 17 Pages 85-102. (In Persian)

Nasiri Khiavi, A., Vafakhah, M., & Sadeghi, S., H. (2021). The Impressibility of Flood Regime from Rainfall and Land Use Changes in Cheshmeh Kileh Watershed, Volume 8, Issue 1, Pages 221-234. (In Persian)

Pourghasemi, H., R., Moradi, H., R., & Mohammadi, M. (2014). Landslide Susceptibility Zoning, Using Weight   of Evidence Probabilistic Model. jgit.; 1 (2) :69-80
(In Persian)

Pornaby Darzi, S., Vafakhah, M., & Rajabi, M., R. (2021). Flood hazard zoning using HEC-RAS Hydraulic   Model and ArcGIS (Case Study: CheshmehKileh River in Tonekabon County) Volume 10, Issue 28 - Serial Number 2 September 2021 Pages 15-28. (In Persian)

Rajaei, M. (2018). Hydrogeomorphological modeling of urban flood (Case study: Tankabon Cheshmekile river) Ph.D thesis, Department of Geomorphology, Khuarazmi University. (In Persian)

Rahmani, Sh., Azizian, A., Samadi, A. (2019). Determining the Flood Hazard Level of Mazandaran Sub-Basins Using a GIS-based Distributed Method, Volume 14, Issue 1 - Serial Number 141 Pages 123-139.(In Persian)

Tahmasebipoor, N., Rahmati, O., & Ghorbani Nejad, S. (2016). Prediction of gully erosion susceptibilityin Seimare region using certainty factor model and importance analysis of conditioning factors, Volume 3, Issue 1, Pages 83-93. 10.22059/IJE.2016.59192. (In Persian)

Zayyari, K., Ebrahimipoor, M., Pourjafar, M., R., & salehi, E. (2020). Explaining Strategies for Increasing Physical Resilience against Flood (Case Study: Cheshmeh Kile River, Tonekabon River), Volume 3, Issue 1, Pages 89-105. (In Persian)

Althuwaynee, O., F., Pradhan, B., Park, H., J., & Lee, J., H. (2014). A novel ensemble bivariate statistical evidential belief function with knowledge-based analytical hierarchy process and multivariate statistical logistic regression for landslide susceptibility mapping. Catena 114, 21–36.

Chowdhuri, I., Pal Subodh, Ch., & Chakrabortty, R. (2019). Flood susceptibility mapping by ensemble evidential belief function and binomial logistic regression model on river basin of eastern India, Advances in Space Research.

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Demir, V., & Kisi, O. (2016). Flood Hazard Mapping by Using Geographic Information System and Hydraulic Model: Mert River, Samsun, Turkey, Advances in Meteorology.

Fernandez, DS., & Lutz, M., A. (2010). Urban flood hazard zoning in Tucuman Province, Argentina, using GIS and multicriteria decision analysis. Eng Geol 111:90–98

Guo E., L., Zhang Z., Q. & Ren X., H. (2014). Integrated risk assessment of flood disaster based on improved set pair analysis and the variable fuzzy set theory in central Liaoning Province, China. Nat. Hazards Journal, 74: 947–965.

Jie Yang, D., Townsend Yilmaz, C., Topal, T., & Suzen M.L. (2012). GIS-based landslide susceptibility mapping using bivariate statistical analysis in Devrek (Zonguldak-Turkey). Environmental Earth Science, 65: 2161- 2178.

Jhih, H., W., Gwo-Fong L., Yun-Ru H., I-Hang H., & Chieh-Lin C. (2022). Application of hybrid machine learning model for flood hazard zoning assessments, Stochastic Environmental Research and Risk Assessment.

Kia, MB., Pirasteh, S., Pradhan, B., Mahmud, AR., Sulaiman, WNA., & Moradi, A. (2012). An artificial neural network model for flood simulation using GIS: Johor River Basin, Malaysia. Environ Earth Sci 67:251– 264.

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Nampak, H., Pradhan, B., & Manap, M.,A. (2014). Application of GIS based data driven evidential belief function model to predict groundwater potential zonation. Journal of Hydrology, 513, pp.283-300.

Nguyen, B., D, Nguyen, Q., L., Ropesh, G., Dang, T., A, Dang, T., M.(2021).The Role of  Factors Afecting Flood Hazard Zoning Using Analytical Hierarchy Process: A Review Earth Systems and Environment King Abdulaziz University and Springer Nature Switzerland AG.

Pourghasemi, H.,R., Mohammadi, M., & Pradhan, B. (2012). Landslide susceptibility mapping using index of entropy and conditional probability models at Safarood Basin, Iran. Catena 97, 71–84.

Patra, J.,P., Kumar, R., & Mani, P. (2015). Combined fluvial and pluvial flood inundation modeling for a project site, Procedia Technology, 24: 93-100.

Reinhardt- Imjela, Ch., Imjela, R., Beolscher, J., & Schulte, A. (2018). The impact of late medieval deforestation and 20th century  forest  decline  on  extreme  flood  magnitudes  in  the Ore  Mountains  (Southeastern  Germany, Quaternary International 475.

Ramesh, V., & Sumaira S, I. (2020). Urban flood susceptibility zonation mapping using evidential belief function, frequency ratio and fuzzy gamma operator models in GIS: a case study of Greater Mumbai, Maharashtra, India, Geocarto International, DOI: 10.1080/10106049.2020.1730448

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Tehrany, M.S., Pradhan, B., Mansour, Sh., & Ahmad, N. (2015). Flood susceptibility assessment using GIS-based support vector machine model with different kernel types.125:91-101.

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