References
- Akter, T., Quevauviller, P., Eisenreich, S. J., & Vaes, G. (2018). Impacts of climate and land use changes on flood risk management for the Schijn River, Belgium. Environmental Science & Policy, 89, 163–175. https://doi.org/https://doi.org/10.1016/j.envsci.2018.07.002
- Ballais, J. L. (2010). Des oueds mythiques aux rivières artificielles: l'hydrographie du Bas-Sahara algérien. Physio-Géo. Géographie Physique et Environnement, 4, 107–127. https://doi.org/https://doi.org/10.4000/physio-geo.1173
- Benameur, S., Benkhaled, A., Meraghni, D., Chebana, F., & Necir, A. (2017). Complete flood frequency analysis in Abiod watershed, Biskra (Algeria). Natural Hazards, 86(2), 519–534. https://doi.org/https://doi.org/10.1007/s11069-016-2703-4
- Benkhaled, A., Bouziane, M. T., & Achour, B. (2008). Detecting trends in annual discharge and precipitation in the ChottMelghir basin in Southeastern Algeria. LARHYSS Journal, 7, 103–119.
- Bouguerra, H., Tachi, S. E., Derdous, O., Bouanani, A., & Khanchoul, K. (2019). Suspended sediment discharge modeling during flood events using two different artificial neural network algorithms. Acta Geophysica, 67(6), 1649–1660. https://doi.org/https://doi.org/10.1007/s11600-019-00373-4
- Boumessenegh, A. (2007). Les inondations dans la ville de Biskra: Causes et impacts [Unpublished thesis]. University of Batna 2.
- Bourenane, H., Bouhadad, Y., & Guettouche, M. S. (2019). Flood hazard mapping in urban area using the hydrogeomorphological approach: Case study of the Boumerzoug and Rhumel alluvial plains (Constantine city, NE Algeria). Journal of African Earth Sciences, 160, article 103602. https://doi.org/https://doi.org/10.1016/j.jafrearsci.2019.103602
- Buckley, J. J. (1985). Ranking alternatives using fuzzy numbers. Fuzzy Sets and Systems, 15(1), 21–31. https://doi.org/https://doi.org/10.1016/0165-0114(85)90013-2
- Chang, D. Y. (1996). Applications of the extent analysis method on fuzzy AHP. European Journal of Operational Research, 95(3), 649–655. https://doi.org/https://doi.org/10.1016/0377-2217(95)00300-2
- Chen, W., Hong, H., Li, S., Shahabi, H., Wang, Y., Wang, X., & Ahmad, B. B. (2019). Flood susceptibility modelling using novel hybrid approach of reduced-error pruning trees with bagging and random subspace ensembles. Journal of Hydrology. https://doi.org/https://doi.org/10.1016/j.jhydrol.2019.05.089
- Cheng, C. H. (1997). Evaluating naval tactical missile systems by fuzzy AHP based on the grade value of membership function. European Journal of Operational Research, 96(2), 343–350. https://doi.org/https://doi.org/10.1016/S0377-2217(96)00026-4
- Choubin, B., Moradi, E., Golshan, M., Adamowski, J., Sajedi-Hosseini, F., & Mosavi, A. (2019). An ensemble prediction of flood susceptibility using multivariate discriminant analysis, classification and regression trees, and support vector machines. Science of the Total Environment, 651, 2087–2096. https://doi.org/https://doi.org/10.1016/j.scitotenv.2018.10.064
- Dahri, N., & Abida, H. (2017). Monte Carlo simulation-aided analytical hierarchy process (AHP) for flood susceptibility mapping in Gabes Basin (southeastern Tunisia). Environmental Earth Sciences, 76(7), 302. https://doi.org/https://doi.org/10.1007/s12665-017-6619-4
- Das, S. (2019). Geospatial mapping of flood susceptibility and hydro-geomorphic response to the floods in Ulhas Basin, India. Remote Sensing Applications: Society and Environment, 14, 60–74. https://doi.org/https://doi.org/10.1016/j.rsase.2019.02.006
- Das, S., & Pardeshi, S. D. (2018). Integration of different influencing factors in GIS to delineate groundwater potential areas using IF and FR techniques: A study of Pravara basin, Maharashtra, India. Appl Water Sci 8, 197. https://doi.org/https://doi.org/10.1007/s13201-018-0848-x
- De Risi, R., Jalayer, F., De Paola, F., Carozza, S., Yonas, N., Giugni, M., & Gasparini, P. (2019). From flood risk mapping toward reducing vulnerability: The case of Addis Ababa. Natural Hazards. https://doi.org/https://doi.org/10.1007/s11069-019-03817-8
- Eastman, J. R. (2003). IDRISI Kilimanjaro: Guide to GIS and image processing (pp. 328). Clark Labs, Clark University.
- Falah, F., Rahmati, O., Rostami, M., Ahmadisharaf, E., Daliakopoulos, I. N., & Pourghasemi, H. R. (2019). Artificial neural networks for flood susceptibility mapping in data-scarce urban areas. In H. R. Pourghasemi (Ed.), Spatial modeling in GIS and R for earth and environmental sciences (pp. 323–336). Elsevier.
- Fenicia, F., Kavetski, D., Savenije, H. H., Clark, M. P., Schoups, G., Pfister, L., & Freer, J. (2013). Catchment properties, function, and conceptual model representation: Is there a correspondence? Hydrological Processes. https://doi.org/https://doi.org/10.1002/hyp.9726
- Fernández, D. S., & Lutz, M. A. (2010). Urban flood hazard zoning in Tucumán Province, Argentina, using GIS and multicriteria decision analysis. Engineering Geology, 111(1–4), 90–98. https://doi.org/https://doi.org/10.1016/j.enggeo.2009.12.006
- Ghosh, A., & Kar, S. K. (2018). Application of analytical hierarchy process (AHP) for flood risk assessment: A case study in Malda district of west Bengal, India. Natural Hazards, 94(1), 349–368. https://doi.org/https://doi.org/10.1007/s11069-018-3392-y
- Hong, H., Panahi, M., Shirzadi, A., Ma, T., Liu, J., Zhu, A. X., & Kazakis, N. (2018). Flood susceptibility assessment in Hengfeng area coupling adaptive neuro-fuzzy inference system with genetic algorithm and differential evolution. Science of The Total Environment, 621, 1124–1141. https://doi.org/https://doi.org/10.1016/j.scitotenv.2017.10.114
- Jakubicka, T., Vos, F., Phalkey, R., & Marx, M. (2010). Health impacts of floods in Europe: Data gaps and information needs from spatial perspective. A MICRODIS report. Centre for Research on the Epidemiology of Disasters.
- Johnson, B. E., Julien, P. Y., Molnar, D. K., & Watson, C. C. (2000). The two-dimensional upland soil erosion model CASC2D-SED. JAWRA Journal of the American Water Resources Association, 36(1), 31–42. https://doi.org/https://doi.org/10.1111/j.1752-1688.2000.tb04246.x
- Kazakis, N., Kougias, I., & Patsialis, T. (2015). Assessment of flood hazard areas at a regional scale using an index-based approach and analytical hierarchy process: Application in Rhodope–Evros Region, Greece. Science of the Total Environment, 538, 555–563. https://doi.org/https://doi.org/10.1016/j.scitotenv.2015.08.055
- Kerkez, M., Gajović, V., & Puzić, G. (2017). Flood risk assessment model using the fuzzy analytic hierarchy process. Progress in Economic Sciences, 4. https://doi.org/https://doi.org/10.14595/PES/04/019
- Khosravi, K., Pham, B. T., Chapi, K., Shirzadi, A., Shahabi, H., Revhaug, I., & Bui, D. T. (2018). A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at Haraz watershed, northern Iran. Science of the Total Environment, 627, 744–755. https://doi.org/https://doi.org/10.1016/j.scitotenv.2018.01.266
- Laarhoven, P. J., & Pedrycz, W. (1983). A fuzzy extension of Saaty’s priority theory. Fuzzy Sets and Systems, 11(1–3), 229–241. https://doi.org/https://doi.org/10.1016/S0165-0114(83)80082-7
- Li, L., Shi, Z. H., Yin, W., Zhu, D., Ng, S. L., Cai, C. F., & Lei, A. L. (2009). A fuzzy analytic hierarchy process (FAHP) approach to eco-environmental vulnerability assessment for the Danjiangkou Reservoir Area, China. Ecological Modelling, 220(23), 3439–3447. https://doi.org/https://doi.org/10.1016/j.ecolmodel.2009.09.005
- Li, X., Yan, D., Wang, K., Weng, B., Qin, T., & Liu, S. (2019). Flood risk assessment of global watersheds based on multiple machine learning models. Water, 11(8), 1654. https://doi.org/https://doi.org/10.3390/w11081654
- Luu, C., Von Meding, J., & Kanjanabootra, S. (2018). Assessing flood hazard using flood marks and analytic hierarchy process approach: A case study for the 2013 flood event in Quang Nam, Vietnam. Natural Hazards, 90(3), 1031–1050. https://doi.org/https://doi.org/10.1007/s11069-017-3083-0
- Meddi, M., Meddi, H., Toumi, S., & Mehaiguen, M. (2013). Regionalization of rainfall in north-western Algeria. GeographiaTechnica, 17(1).
- Merz, B., Thieken, A. H., & Gocht, M. (2007). Flood risk mapping at the local scale: Concepts and challenges. In S. Begum, M. J. F. Stive, & J. W. Hall (Eds.), Flood risk management in Europe (pp. 231–251). Springer.
- Modrick, T. M., & Georgakakos, K. P. (2015). The character and causes of flash flood occurrence changes in mountainous small basins of Southern California under projected climatic change. Journal of Hydrology: Regional Studies, 3, 312–336. https://doi.org/https://doi.org/10.1016/j.ejrh.2015.02.003
- Mojaddadi, H., Pradhan, B., Nampak, H., Ahmad, N., & Ghazali, A. H. B. (2017). Ensemble machine-learning-based geospatial approach for flood risk assessment using multi-sensor remote-sensing data and GIS. Geomatics, Natural Hazards and Risk, 8(2), 1080–1102. https://doi.org/https://doi.org/10.1080/19475705.2017.1294113
- Pourghasemi, H. R., Mohammady, M., & Pradhan, B. (2012). Landslide susceptibility mapping using index of entropy and conditional probability models in GIS: Safarood Basin, Iran. Catena, 97, 71–84. https://doi.org/https://doi.org/10.1016/j.catena.2012.05.005
- Pradhan, B. (2009). Flood susceptible mapping and risk area delineation using logistic regression, GIS and remote sensing. Journal of Spatial Hydrology, 9, 1–18.
- Pradhan, B., Hagemann, U., Tehrany, M. S., & Prechtel, N. (2014). An easy to use ArcMap based texture analysis program for extraction of flooded areas from TerraSAR-X satellite image. Computers & geosciences, 63, 34–43. https://doi.org/https://doi.org/10.1016/j.cageo.2013.10.011
- Rahmati, O., Pourghasemi, H. R., & Zeinivand, H. (2016). Flood susceptibility mapping using frequency ratio and weights-of-evidence models in the Golastan Province, Iran. Geocarto International, 31(1), 42–70. https://doi.org/https://doi.org/10.1080/10106049.2015.1041559
- Rogger, M., Agnoletti, M., Alaoui, A., Bathurst, J. C., Bodner, G., Borga, M., & Holden, J. (2017). Land use change impacts on floods at the catchment scale: Challenges and opportunities for future research. Water Resources Research, 53(7), 5209–5219. https://doi.org/https://doi.org/10.1002/2017WR020723
- Saaty, T. L. (1977). A scaling method for priorities in hierarchical structures. Journal of Mathematical Psychology, 15(3), 234–281. https://doi.org/https://doi.org/10.1016/0022-2496(77)90033-5
- Saaty, T. L. (1988). Multicriteria decision making, the analytic hierarchy process, planning, priority, setting, resource allocation. RWS Publications.
- Sahana, M., Rehman, S., Sajjad, H., & Hong, H. (2020). Exploring effectiveness of frequency ratio and support vector machine models in storm surge flood susceptibility assessment: A study of Sundarban Biosphere Reserve, India. Catena, 189, article 104450. https://doi.org/https://doi.org/10.1016/j.catena.2019.104450
- Samanta, S., Koloa, C., Kumar Pal, D., & Palsamanta, B. (2016). Flood risk analysis in lower part of Markham river based on multi-criteria decision approach (MCDA). Hydrology, 3(3), 29. https://doi.org/https://doi.org/10.3390/hydrology3030029
- Scientist, C. (2011). Understanding floods: Questions and answers. Australian Journal of Emergency Management and Office of the Queensland Chief Scientist, 26(3).
- Siahkamari, S., Haghizadeh, A., Zeinivand, H., Tahmasebipour, N., & Rahmati, O. (2018). Spatial prediction of flood-susceptible areas using frequency ratio and maximum entropy models. Geocarto International, 33(9), 927–941. https://doi.org/https://doi.org/10.1080/10106049.2017.1316780
- Siddayao, G. P., Valdez, S. E., & Fernandez, P. L. (2014). Analytic hierarchy process (AHP) in spatial modeling for floodplain risk assessment. International Journal of Machine Learning and Computing, 4(5), 450. https://doi.org/https://doi.org/10.7763/IJMLC.2014.V4.453
- Simonović, S. P. (2012). Floods in a changing climate: Risk management. Cambridge University Press.
- Singhal, V., & Goyal, R. (2012). A methodology based on spatial distribution of parameters for understanding affect of rainfall and vegetation density on groundwater recharge. European Journal of Sustainable Development, 1(2), 85. https://doi.org/https://doi.org/10.14207/ejsd.2012.v1n2p85
- Sonmez, O., & Bizimana, H. (2018). Flood hazard risk evaluation using fuzzy logic and weightage based combination methods in geographic information system (GIS). Scientia Iranica.
- Stieglitz, M., Rind, D., Famiglietti, J., & Rosenzweig, C. (1997). An efficient approach to modeling the topographic control of surface hydrology for regional and global climate modeling. Journal of Climate, 10(1), 118–137. https://doi.org/https://doi.org/10.1175/1520-0442(1997)010<0118:AEATMT>2.0.CO;2
- Tebbi, F. Z., Dridi, H., & Morris, G. L. (2012). Optimization of cumulative trapped sediment curve for an arid zone reservoir: Foum El Kherza (Biskra, Algeria). Hydrological Sciences Journal, 57(7), 1368–1377. https://doi.org/https://doi.org/10.1080/02626667.2012.712740
- Tehrany, M. S., Pradhan, B., & Jebur, M. N. (2013). Spatial prediction of flood susceptible areas using rule based decision tree (DT) and a novel ensemble bivariate and multivariate statistical models in GIS. Journal of Hydrology, 504, 69–79. https://doi.org/https://doi.org/10.1016/j.jhydrol.2013.09.034
- Tehrany, M. S., Pradhan, B., & Jebur, M. N. (2014). Flood susceptibility mapping using a novel ensemble weights-of-evidence and support vector machine models in GIS. Journal of Hydrology, 512, 332–343. https://doi.org/https://doi.org/10.1016/j.jhydrol.2014.03.008
- Tehrany, M. S., Shabani, F., NeamahJebur, M., Hong, H., Chen, W., & Xie, X. (2017). GIS-based spatial prediction of flood prone areas using standalone frequency ratio, logistic regression, weight of evidence and their ensemble techniques. Geomatics, Natural Hazards and Risk, 8(2), 1538–1561. https://doi.org/https://doi.org/10.1080/19475705.2017.1362038
- Yesilnacar, E., & Topal, T. (2005). Landslide susceptibility mapping: A comparison of logistic regression and neural networks methods in a medium scale study, Hendek region (Turkey). Engineering Geology, 79(3–4), 251–266. https://doi.org/https://doi.org/10.1016/j.enggeo.2005.02.002
- Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338–353. https://doi.org/https://doi.org/10.1016/S0019-9958(65)90241-X
- Zadeh, L. A. (1988). Fuzzy logic. Computer, 21(4), 83–93. https://doi.org/https://doi.org/10.1109/2.53