صابر چناری، ک.، بهرهمند، ع. ر.، شیخ، و. ب.، و کمکی، چ. ب.، 1395. پهنهبندی خطر فرسایش خندقی با استفاده از مدل دمپسترـ شفر در حوضه آبخیز قرناوه، استان گلستان، اکوهیدرولوژی، دوره 3، شماره 2، ص 219-231.
عابدینی، م.، و یعقوبنژاد اصل، ن.، 1397. ارزیابی و پهنهبندی خطر فرسایش خاک در حوضه آبخیز رودخانه بالیخلو (سدیامچی) با استفاده از مدل فازی، پژوهشهای ژئومورفولوژی کمّی، دوره 6، شماره 1، ص 137-155.
قربانینژاد، س.، رحمتی، ا.، و نورمحمدی، ف.، 1396. مدلسازی پتانسیل رخداد فرسایشهای آبکندی در منطقهی سیمره با استفاده از مدلهای آنتروپیشانون و شاخص آماری، پژوهشهای فرسایش محیطی، دوره 7، شماره 1، ص 69-89.
قربانینژاد، س.، زینیوند، ح.، حقیزاده، ع.، و طهماسبی، ن.، 1397. بررسی کارایی مدل دمپستر-شافر در پتانسیلیابی مناطق مستعد فرسایش خاک حوضه آبخیز کاکارضا در استان لرستان، سنجشازدور و سامانه اطلاعات جغرافیایی در منابع طبیعی، دوره 9، شماره 3، ص 100-114.
محمد خان، ش.، پیرانی، پ.، ریاهی، س.، و گراوند، ف.، 1398. ارزیابی کارایی مدل آنتروپی در پهنهبندی میزان فرسایش با رویکرد ژئومورفولوژیکی. مطالعه موردی: حوضۀ آبخیز کند در بالادست سد لتیان، آمایش جغرافیایی فضا، دوره 9، شماره 34، ص 85-98.
یمانی، م.، و عربعامری، ع. ر.، 1397. کارایی آنالیز کمی پارامترهای ژئومورفومتریک در تهیه نقشه حساسیت فرسایش خاک (مطالعه موردی: حوضه منج)، جغرافیا و مخاطرات محیطی، دوره 7، شماره 2، ص 1-22.
AbdulKadir, T. S., Muhammad, R. M., Khamrruzaman, W. Y., & Ahmad, M. H. (2017). Geo-statistical based susceptibility mapping of soil erosion and optimization of its causative factors: A conceptual framework. Journal of Engineering Science and Technology, 12(11), 2880-2895.
Alexakis, D. D., Hadjimitsis, D. G., & Agapiou, A. (2013). Integrated use of remote sensing, GIS and precipitation data for the assessment of soil erosion rate in the catchment area of “Yialias” in Cyprus. Atmospheric Research, 131, 108-124.
Andualem, T. G., Hagos, Y. G., Kefale, A., & Zelalem, B. (2020). Soil erosion-prone area identification using multi-criteria decision analysis in Ethiopian highlands. Modeling Earth Systems and Environment, 6(3), 1407-1418.
Arabameri, A., Cerda, A., & Tiefenbacher, J. P. (2019). Spatial pattern analysis and prediction of gully erosion using novel hybrid model of entropy-weight of evidence. Water, 11(6), 1129.
Arabameri, A., Chandra Pal, S., Costache, R., Saha, A., Rezaie, F., Seyed Danesh, A., ... & Hoang, N. D. (2021). Prediction of gully erosion susceptibility mapping using novel ensemble machine learning algorithms. Geomatics: Natural Hazards and Risk, 12(1), 469-498.
Arar, A., & Chenchouni, H. (2014). A “simple” geomatics-based approach for assessing water erosion hazard at montane areas. Arabian Journal of Geosciences, 7(1), 1-12.
Aslam, B., Maqsoom, A., Alaloul, W. S., Musarat, M. A., Jabbar, T., & Zafar, A. (2021). Soil erosion susceptibility mapping using a GIS-based multi-criteria decision approach: Case of district Chitral, Pakistan. Ain Shams Engineering Journal, 12(2), 1637-1649.
Chakrabortty, R., Pal, S. C., Sahana, M., Mondal, A., Dou, J., Pham, B. T., & Yunus, A. P. (2020). Soil erosion potential hotspot zone identification using machine learning and statistical approaches in eastern India. Natural Hazards, 104, 1259-1294.
Chen, X., & Chen, W. (2021). GIS-based landslide susceptibility assessment using optimized hybrid machine learning methods. Catena, 196, 104833.
Conforti, M., Aucelli, P. P., Robustelli, G., & Scarciglia, F. (2011). Geomorphology and GIS analysis for mapping gully erosion susceptibility in the Turbolo stream catchment (Northern Calabria, Italy). Natural hazards, 56, 881-898.
Costache, R. (2019). Flood susceptibility assessment by using bivariate statistics and machine learning models-a useful tool for flood risk management. Water Resources Management, 33(9), 3239-3256.
Das, B., Bordoloi, R., Thungon, L. T., Paul, A., Pandey, P. K., Mishra, M., & Tripathi, O. P., (2020). An integrated approach of GIS, RUSLE and AHP to model soil erosion in West Kameng watershed, Arunachal Pradesh. Journal of Earth System Science, 129, 1-18.
Das, B., Paul, A., Bordoloi, R., Tripathi, O. P., & Pandey, P. K. (2018). Soil erosion risk assessment of hilly terrain through integrated approach of RUSLE and geospatial technology: a case study of Tirap District, Arunachal Pradesh. Modeling Earth Systems and Environment, 4, 373-381.
Fallah, M., Kavian, A., & Omidvar, E. (2016). Watershed prioritization in order to implement soil and water conservation practices. Environmental Earth Sciences, 75, 1-17.
Gayen, A., & Saha, S. (2017). Application of weights-of-evidence (WoE) and evidential belief function (EBF) models for the delineation of soil erosion vulnerable zones: a study on Pathro river basin, Jharkhand, India. Modeling Earth Systems and Environment, 3(3), 1123-1139.
Getnet, T., & Mulu, A. (2021). Assessment of soil erosion rate and hotspot areas using RUSLE and multi-criteria evaluation technique at Jedeb watershed, Upper Blue Nile, Amhara Region, Ethiopia. Environmental Challenges, 4, 100174.
Ghosh, A., & Maiti, R. (2021). Soil erosion susceptibility assessment using logistic regression, decision tree and random forest: study on the Mayurakshi river basin of Eastern India. Environmental Earth Sciences, 80, 1-16.
Haidara, I., Tahri, M., Maanan, M., & Hakdaoui, M. (2019). Efficiency of Fuzzy Analytic Hierarchy Process to detect soil erosion vulnerability. Geoderma, 354, 113853.
Halefom, A., & Teshome, A. (2019). Modelling and mapping of erosion potentiality watersheds using AHP and GIS technique: a case study of Alamata Watershed, South Tigray, Ethiopia. Modeling Earth Systems and Environment, 5(3), 819-831.
Halefom, A., Ahmad, I., & Dar, M. A. (2022). Soil loss rate estimation using a hybrid model of geographic information system coupled with fuzzy logic technique. International Journal of Environmental Science and Technology, 19(1), 421-432.
Hembram, T. K., Paul, G. C., & Saha, S. (2019). Comparative analysis between morphometry and geo-environmental factor based soil erosion risk assessment using weight of evidence model: a study on Jainti river basin, eastern India. Environmental processes, 6(4), 883-913.
Jennifer, J. J., Saravanan, S., & Abijith, D. (2021). Application of frequency ratio and logistic regression model in the assessment of landslide susceptibility mapping for Nilgiris district, Tamilnadu, India. Indian Geotechnical Journal, 51(4), 773-787.
Kashiwar, S. R., Kundu, M. C., & Dongarwar, U. R. (2022). Soil erosion estimation of Bhandara region of Maharashtra, India, by integrated use of RUSLE, remote sensing, and GIS. Natural Hazards, 110(2), 937-959.
Liu, H., Li, X., Meng, T., & Liu, Y. (2020). Susceptibility mapping of damming landslide based on slope unit using frequency ratio model. Arabian Journal of Geosciences, 13, 1-19.
Ma, J., Wang, X. & Yuan, G. (2023). Evaluation of Geological Hazard Susceptibility Based on the Regional Division Information Value Method. ISPRS International Journal of Geo-Information, 12(1), 17.
Maqsoom, A., Aslam, B., Hassan, U., Kazmi, Z. A., Sodangi, M., Tufail, R. F., & Farooq, D. (2020). Geospatial assessment of soil erosion intensity and sediment yield using the revised universal soil loss equation (RUSLE) model. ISPRS International Journal of Geo-Information, 9(6), 356.
Meliho, M., Khattabi, A., & Mhammdi, N. (2018). A GIS-based approach for gully erosion susceptibility modelling using bivariate statistics methods in the Ourika watershed, Morocco. Environmental Earth Sciences, 77, 1-14.
Mihi, A., Benarfa, N., & Arar, A. (2020). Assessing and mapping water erosion-prone areas in northeastern Algeria using analytic hierarchy process, USLE/RUSLE equation, GIS, and remote sensing. Applied Geomatics, 12(2), 179-191.
Mitra, R., Saha, P., & Das, J. (2022). Assessment of the performance of GIS-based analytical hierarchical process (AHP) approach for flood modelling in Uttar Dinajpur district of West Bengal, India. Geomatics, Natural Hazards and Risk, 13(1), 2183-2226.
Mondal, S., & Mandal, S. (2019). Landslide susceptibility mapping of Darjeeling Himalaya, India using index of entropy (IOE) model. Applied Geomatics, 11, 129-146.
Ouma, Y. O., Lottering, L., & Tateishi, R. (2022). Soil erosion susceptibility prediction in railway corridors using RUSLE, soil degradation index and the new normalized difference railway erosivity index (NDReLI). Remote Sensing, 14(2), 348.
Pei, T., Qin, C. Z., Zhu, A. X., Yang, L., Luo, M., Li, B., & Zhou, C. (2010). Mapping soil organic matter using the topographic wetness index: A comparative study based on different flow-direction algorithms and kriging methods. Ecological Indicators, 10(3), 610-619.
Pournader, M., Ahmadi, H., Feiznia, S., Karimi, H., & Peirovan, H. R. (2018). Spatial prediction of soil erosion susceptibility: an evaluation of the maximum entropy model. Earth Science Informatics, 11, 389-401.
Puente, C., Olague, G., Trabucchi, M., Arjona-Villicaña, P. D., & Soubervielle-Montalvo, C. (2019). Synthesis of vegetation indices using genetic programming for soil erosion estimation. Remote Sensing, 11(2), 156.
Rahman, M. R., Shi, Z. H., & Chongfa, C. (2009). Soil erosion hazard evaluation—an integrated use of remote sensing, GIS and statistical approaches with biophysical parameters towards management strategies. Ecological Modelling, 220(13-14), 1724-1734.
Rehman, A., Song, J., Haq, F., Mahmood, S., Ahamad, M. I., Basharat, M., ... & Mehmood, M. S. (2022). Multi-hazard susceptibility assessment using the analytical hierarchy process and frequency ratio techniques in the Northwest Himalayas, Pakistan. Remote Sensing, 14(3), 554.
Saha, S., Gayen, A., Pourghasemi, H. R., & Tiefenbacher, J. P. (2019). Identification of soil erosion-susceptible areas using fuzzy logic and analytical hierarchy process modeling in an agricultural watershed of Burdwan district, India. Environmental Earth Sciences, 78, 1-18.
Saranaathan, S. E., Mani, S., Ramesh, V., & Prasanna Venkatesh, S. (2021). Landslide susceptibility zonation mapping using bivariate statistical frequency ratio method and GIS: a case study in part of SH 37 Ghat Road, Nadugani, Panthalur Taluk, The Nilgiris. Journal of the Indian Society of Remote Sensing, 49, 275-291.
Seutloali, K. E., Dube, T., & Mutanga, O. (2017). Assessing and mapping the severity of soil erosion using the 30-m Landsat multispectral satellite data in the former South African homelands of Transkei. Physics and Chemistry of the Earth, Parts A/B/C, 100, 296-304.
Shirzadi, A., Bui, D. T., Pham, B. T., Solaimani, K., Chapi, K., Kavian, A., ... & Revhaug, I. (2017). Shallow landslide susceptibility assessment using a novel hybrid intelligence approach. Environmental Earth Sciences, 76, 1-18.
Sinshaw, B. G., Belete, A. M., Tefera, A. K., Dessie, A. B., Bizuneh, B. B., Alem, H. T., ... & Moges, M. A. (2021). Prioritization of potential soil erosion susceptibility region using fuzzy logic and analytical hierarchy process, upper Blue Nile Basin, Ethiopia. Water-Energy Nexus, 4, 10-24.
Tehrany, M. S., Shabani, F., Javier, D. N., & Kumar, L. (2017). Soil erosion susceptibility mapping for current and 2100 climate conditions using evidential belief function and frequency ratio. Geomatics. Natural Hazards and Risk, 8(2), 1695-1714.
Vijith, H., & Dodge-Wan, D. (2019). Modelling terrain erosion susceptibility of logged and regenerated forested region in northern Borneo through the Analytical Hierarchy Process (AHP) and GIS techniques. Geoenvironmental Disasters, 6(1), 1-18.
Wang, Q., Li, W., Yan, S., Wu, Y., & Pei, Y. (2016). GIS based frequency ratio and index of entropy models to landslide susceptibility mapping (Daguan, China). Environmental Earth Sciences, 75, 1-16.
Wubalem, A., Getahun, B., Hailemariam, Y., Mesele, A., Tesfaw, G., Dawit, Z., & Goshe, E. (2022). Landslide susceptibility modeling using the index of entropy and frequency ratio method from Nefas-Mewcha to Weldiya Road Corridor, Northwestern Ethiopia. Geotechnical and Geological Engineering, 40(10), 5249-5278.
Yetemen, O., Istanbulluoglu, E., & Duvall, A. R. (2015). Solar radiation as a global driver of hillslope asymmetry: Insights from an ecogeomorphic landscape evolution model. Water Resources Research, 51(12), 9843-9861.
Zhou, P., Luukkanen, O., Tokola, T., & Nieminen, J. (2008). Effect of vegetation cover on soil erosion in a mountainous watershed