Msabi, Michael M.Makonyo, Michael2021-05-132021-05-132021Msabi, M. M., & Makonyo, M. (2021). Flood susceptibility mapping using GIS and multi-criteria decision analysis: a case of Dodoma region, central Tanzania. Remote Sensing Applications: Society and Environment, 21.DOI: https://doi.org/10.1016/j.rsase.2020.100445http://hdl.handle.net/20.500.12661/3055Abstract: Full Text article available at https://doi.org/10.1016/j.rsase.2020.100445Floods have become common natural disasters that lead to devastating destruction to the infrastructure and natural environment. With the eminent climate change and weather variability, it might not be possible to prevent floods. However, flood prevention and mitigation can be facilitated by flood susceptibility mapping. Dodoma Region was selected due to its susceptibility to flash floods every year. The map presented in this paper is produced based on the analytical hierarchy process methodology which is an interactive decision-making approach under multi-criteria decision analysis. The method can check the consistency of the model obtained. A total of seven influencing factors are considered for mapping the flood susceptible areas within the Dodoma region, i.e. elevation, slope, geology, drainage density, flow accumulation, land-use/cover, and soil. This study established that around 40.27% of the region (17,073.323 km2) is under high to very high, whereas, 59.73% (24,517.679 km2) accounts for very low to moderate probability of flooding, respectively. The validation process of the analytical hierarchy process is executed based on the comparison of the historical flood locations of the different flood susceptible zones on the final map and AUC of 87.24% give a significant accuracy of the model. Therefore, the flood susceptibility map presented in this paper serves as a valuable tool for key stakeholders both state and non-state actors assessing flood risks in Dodoma region and the country at large.enFlood mitigationFlood preventionFloodDisastersFlood disastersClimate changeWeather variabilityNatural environmentDodomaNatural disasterGISGeographical Information SystemArticle