Flooding is one of the most prevalent types of natural catastrophes, and it can cause extensive damage to infrastructure and the natural environment. The primary method of flood risk management is flood susceptibility mapping (FSM), which provides a quantitative assessment of a region’s vulnerability to flooding. The objective of this study is to develop new ensemble models for FSM by integrating metaheuristic algorithms, such as genetic algorithms (GA), particle swarm optimization (PSO), and harmony search (HS), with the decision table classifier (DTB). The proposed algorithms were applied in the province of Sulaymaniyah, Iraq. Sentinel-1 synthetic aperture radar (SAR) data satellite images were used for flood monitoring (on 27 July 2019), and 160 flood occurrence locations were prepared for modeling. For the training and validation datasets, flood occurrence data were coupled to 1 flood-influencing parameters (slope, altitude, aspect, plan curvature, distance from rivers, land cover, geology, topographic wetness index (TWI), stream power index (SPI), rainfall, and normalized difference vegetation index (NDVI)). The certainty factor (CF) approach was used to determine the spatial association between the effective parameters and the occurrence of floods, and the resulting weights were employed as modeling inputs. According to the pairwise consistency technique, the NDVI and altitude are the most significant factors in flood modeling. The area under the receiver operating characteristic (AUROC) curve was used to evaluate the accuracy and effectiveness of ensemble models. The DTB-GA model was found to be the most accurate (AUC = 0.889), followed by the DTB-PSO model (AUC = 0.844) and the DTB-HS model (AUC = 0.812). This research’s hybrid models provide a reliable estimate of flood risk, and the risk maps are reliable for flood early-warning and control systems.

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Over the last few years, the Global Navigation Satellite System GNSS was seen as an innovatory method in the disciplinary of geodetic engineering as compared to other classic measuring methods. It is familiar to everyone that the height acquired from GNSS observations is the ellipsoidal height (h), which is the distance over the vertical to the global datum World Geodetic System WGS84. The value of (h) is endowed with a physical meaning relating to engineering applications for identification of the orthometric height (H), after the conversion from the global datum to the local datum. So far, in the Iraqi-Kurdistan region, there is no specific local datum that can be utilized to identify the exact orthometric height over a local vertical datum. This research aims to define the relationship between the global datum WGS84 and the Iraqi local datum Karbala 1979 based on ellipsoid Clark 1880, through extracting the Digital Terrain Model DTM for both datums in the case study area (Duhok-Erbil territory). The obtained results show that there is a significant change in the relationship between the two datums over the study area, and the difference between them is propagated between (-1.751 m) up to (+4.236 m) along with this territory. It is found that the two surfaces are intersected at the midway approximately, between Erbil and Duhok.