Topographic Elevation Research Articles

Rock glacier inventory and predictive modeling in the Mackenzie Mountains: predicting rock glacier likelihood with a generalized additive model

Rock glaciers have been the subject of extensive research in recent years due to their potential to serve as indicators of past and present climate conditions and their potential impacts on water resources. Location and descriptive rock glacier data within the Mackenzie Mountains were used to build a rock glacier inventory that will serve as a valuable resource for future research and monitoring efforts. Additionally, this study maps the likelihood of rock glacier presence using extracted variables in a generalized additive model (GAM). The model incorporates attribute data, including potential incoming solar radiation (PISR), topographic position index (TPI), slope, elevation, and lithology as controls for rock glacier development. Topographic data were compiled for three study regions of the Mackenzie Mountains from a 30 m digital elevation model (DEM). The analysis of the GAM showed that the most significant explanatory variables were PISR, elevation, slope, and TPI. The GAM model had an accuracy of 0.87 with a sensitivity of 0.92. This study provides important insights into the controls, distribution, and dynamics of rock glaciers in the Mackenzie Mountains, as well as both the limitations and the potential of statistical models in predicting their occurrence.

Topography Dominates the Spatial and Temporal Variability of Soil Bulk Density in Typical Arid Zones

Soil bulk density is a crucial indicator for assessing soil matter storage and soil quality. Due to the complexity of sampling soil bulk density, particularly in deeper layers, it is essential to study the spatial distribution patterns of soil bulk density and their influencing factors. To address the gap in large-scale studies of vertical (from surface to deeper layers) and horizontal (across a broad area) variations in soil bulk density in arid regions, this study focuses on Changji Prefecture, located in the central northern slope of the Tianshan Mountains and characterized by typical vertical zonation. By integrating classical statistics, geostatistics, and geographic information systems (GISs), this study investigates the spatial distribution patterns and driving factors of soil bulk density. The results indicate that soil bulk density in Changji Prefecture increases with soil depth, with significantly lower values in the surface layer than in deeper layers. Spatially, despite minimal variation in latitude, there is considerable elevation difference within the study area, with the lowest elevations in the central region. Soil bulk density exhibits a spatial distribution pattern of higher values in the northeast (desert areas) and lower values in the southwest (forest areas). The nugget effect in the surface layer (0–20 cm) is substantial at 44.9%, while the deeper layers (20–100 cm) show nugget effects below 25%, suggesting that the influence of both natural and anthropogenic factors on deep soil bulk density is limited and mainly affects the surface layer. Stepwise regression analysis indicates that among topographic factors, slope and elevation are the primary controls of spatial variability in soil bulk density across layers. This research demonstrates that, in arid regions, soil bulk density is influenced primarily by natural factors, with limited impact from human activities. These findings provide valuable data support and theoretical guidance for soil management, agricultural planning, and sustainable ecosystem development in arid regions.

Machine learning-based assessment of regional-scale variation of landslide susceptibility in central Vietnam.

Recurrent landslide events triggered by typhoons and tropical storms over Vietnam pose a longstanding threat to the nation's population and infrastructure. Changes in hydroclimatic conditions, especially the growing intensity and frequency of storms, have elevated landslide susceptibility in many parts of the country. This research examines the spatio-temporal variations in landslide susceptibility across central Vietnam over several years, using multi-temporal landslide inventories from Typhoon Ketsana (2009), Tropical Storm Podul (2013), and Typhoon Molave (2020). Additionally, the research explores the impact of individual landslide causative factors on the probabilistic occurrences of landslides. The post-event landslide susceptibility models of these three climate extreme events were developed using nine causative factors and a Random Forest machine learning algorithm. The results indicate a notable areal expansion of high to very high landslide susceptibility in the northern and eastern regions and a moderate reduction in the central and southern areas during the post-Molave period compared to the post-Ketsana period. These changes may be early indicators of increasing landslide susceptibility in response to changing hydro-climatic conditions. The research found that annual average rainfall and topographic elevation are the two most important variables influencing landslide prediction, showing a nonlinear relationship with landslide probability. The landslide susceptibility models achieved high Area Under the Receiver Operating Characteristic Curve (AUC) (>95%), accuracy (>89%), and sensitivity (>90%) scores, signifying the robustness of the models. Additionally, the uncertainty of the models was quantified and spatially mapped. This multi-temporal analysis of landslide susceptibility is crucial for understanding the regional susceptibility trends and identifying areas with increasing, decreasing, and consistently high susceptibility to landslides. These insights are invaluable for prioritizing mitigation and risk reduction strategies in landslide-prone regions and guiding appropriate land use planning.

Marsh topography reveals the signature of storm-surge-driven sedimentation

Salt marshes are valuable tidal landforms threatened by drowning due to increasing sea levels. Marsh accretion supported by sediment settling during repeated flooding potentially offsets the relative elevation loss. Although tidal flooding is commonly depicted as the main mechanism delivering the sediment to marshes, storm surges and waves may deeply affect tidal flow conditions and sediment reworking in shallow tidal systems, thus raising questions on the relative contribution of these processes to salt-marsh accretion. Here we show that storm surges substantially sustain the marsh sediment budget, locally contributing up to 90% of sedimentation, and critically influence depositional patterns by analyzing a 3-yr-long measurement record of sedimentation on the marshes in the Venice Lagoon (Italy). Surge-enhanced water levels promote wind-wave-driven sediment fluxes directly across the tidal flat-marsh transition, altering tidal sedimentation patterns and, thus, affecting marsh topographic elevation and morphology. By comparing sedimentation patterns and topographic profiles, we show that the signature of storm-surge sedimentation can be found in marsh topography, which we suggest therefore as an easily detectable indicator of the relative contribution of the different physical processes driving marsh vertical evolution. The comparison with other marshes worldwide, characterized by different tidal ranges and wave exposure, consistently supports the link between the salt-marsh topographic profile and the physical processes controlling marsh evolution.

Geospatial analysis and AHP for flood risk mapping in Quetta, Pakistan: a tool for disaster management and mitigation

The 2022 flood events in Quetta, Pakistan, caused severe damage to the economy, properties, and lives. Therefore, flood risk mapping to identify flood-prone areas is essential for planners and decision-makers to take critical protective measures to control the effects of flooding. This study focuses on mapping flood-prone regions in the Quetta district of Pakistan using an analytical hierarchy process (AHP) and a geographic information system (GIS). The factors influencing flood used in the present study were topographic witness index (TWI), elevation, slope, land use, land cover, precipitation, stream distance, drainage density, and soil type. Weights and ranks were allocated separately to all factors through AHP and were interpreted in a GIS environment. The produced flood hazard model of the study area depicted four zones. These zones ranged from low (19.49%), moderate (43.34%), high (28.30%), to very high (8.87%). The model was further validated through previous flood events in the study area. Around 90% of flood hazard events in the past took place mainly in the produced model's very high and high zones, which is why the current model is reliable. Finally, integrating geospatial approaches with AHP in flood hazard mapping is a quick, reliable, and affordable method that may be utilized in the area.

Post-fire vegetation dynamic patterns and drivers in Greater Hinggan Mountains: Insights from long-term remote sensing data analysis

Fire has become a major disturbing factor in boreal forests, and giant forest disturbances play a vital role in regulating the climate under global warming. Therefore, it is essential to investigate the spatiotemporal patterns and main drivers of post-fire vegetation recovery for forest ecological research and post-fire recovery management. However, previous studies have focused on the post-fire forest change within the entire fire perimeter, lacking separate analysis and comparison of the burned zone (BZ) and unburned zone (UNBZ). Here, we propose the utilization of Moderate Resolution Imaging Spectroradiometer land cover type and vegetation index data to monitor vegetation dynamics and explore its drivers after the most serious forest fire in the history of P.R. China in the Greater Hinggan Mountains (GHM). The temporal and spatial patterns of vegetation recovery in the BZ/UNBZ in the GHM were analyzed using the Sen & Mann-Kendall method, Hurst index and coefficient of variation, and their driving mechanisms were explored using GeoDetector and geographically weighted regression. The results showed that there were significant differences in the spatial distribution and fluctuation of vegetation between the BZ and UNBZ, and that the BZ exhibited higher productivity and vigor. Vegetation recovery was influenced by different dominant factors and changed over time, in which land surface temperature and precipitation dominated all the time, whereas topographic relief and elevation had a more significant contribution to vegetation recovery in the BZ and UNBZ, respectively. This study provides a scientific basis for the protection and management of vegetation in disturbed forested areas, particularly after fires.

Climate change scenarios predict reduction in suitable habitats and range shifts for Ophiocordyceps sinensis (Berk.) in Hindu Kush Himalaya

The Hindu Kush Himalayan region has seen a faster pace of anthropogenic climate warming than the global average during the last 50 years. Since 1980s this region is experiencing intense climatic events notably elevation-dependent warming. Given its unique evolutionary background, rich variety of species, and significant endemism, it is crucial to comprehend the effects of climate change on species distributions in this area. Of particular interest are the fungi, which have been the subject of much fewer studies on how they will respond to climate change, despite the fact that they may have a significant role in the functioning and stability of ecosystems. We therefore selected Ophiocordyceps sinensis an alpine fungus species for predicting the effects of climate change on its distribution in Hindu Kush Himalaya. Regarded as one of the most expensive natural resources used in oriental medicine, Ophiocordyceps and its surrounding habitats are under threat from various ecological and anthropogenic factors. We used Species Distribution Modeling software Maxent 3.3.4 and a set of uncorrelated climatic (temperature and precipitation) and topographical (elevation, slope and aspect) variables at a spatial resolution of 2.5 arc minutes to model the suitable habitats. To predict the future distribution of O. sinensis we used future climate data from BCCCSM2- HR global circulation model for three emission scenarios of the shared socioeconomic pathways (SSPs) (SSP126, SSP245 and SSP585). Maxent model predicted current and future habitats with high accuracy. Current potential distribution map of O. sinensis shows that high suitability areas occur in India, China, Nepal and Bhutan. Prediction maps under all three scenarios showed a large reduction in suitable habitats as compared to current climatic conditions. Analysis of range change reveals that species exhibits both range expansion and range contraction under climate change scenarios. Range contraction is noticeably more than range expansion causing overall reduction in the suitable habitats occupied by O. sinensis. ‘Centroid Range Shift’ analysis revealed potential suitable habitats will shift to South-West direction under all future scenarios with almost overlapping centroids.

Phosphorus dynamics in volcanic soils of Weizhou Island, China: implications for environmental and agricultural applications

The dynamics of phosphorus are intricately governed by geological and ecological processes. Examining phosphorus dynamics in volcanic islands can enhance our comprehension of its behavior within such unique geological systems. However, research on phosphorus dynamics in volcanic islands remains limited. We investigated the phosphorus content of volcaniclastic rocks and basalt soils from Weizhou Island, China, to understand the influencing factors on phosphorus dynamics. The results indicate that in the volcaniclastic profile, phosphorus concentrates at 20–40 cm (17 mg/kg), decreases at 40–60 cm (11.9 mg/kg), and increases at 80–200 cm up to 46.4 mg/kg proximate to the bedrock, for the basalt profile, phosphorus content increases from the surface (80.2 mg/kg) towards the bedrock (83.9 mg/kg). The differences in phosphorus distribution between volcaniclastic rocks and basalts reflect the influence of parent material, rock weathering degree, carbonate content, topographic elevation, sea level changes, and geological activities. A strong positive correlation (R = 0.96907) between total and available phosphorus has been observed, suggesting that total phosphorus content effectively predicts available phosphorus content. Volcaniclastic rocks in wharves and high-elevation areas show low total phosphorus, while forest land with dense vegetation and neutral to alkaline soil supports higher total phosphorus due to enhanced bioavailability for plant absorption and utilization. Overall, the basalt soil of the volcanic island Weizhou Island demonstrates superior long-term fertility compared to the volcaniclastic soil. Despite its low total phosphorus content, it mainly exists in a highly bioavailable form, facilitating plant absorption, which is crucial for enhancing agricultural yields and ecosystem restoration on volcanic islands.

Exploring the Influencing Factors of Net Ecosystem Productivity (NEP) Based on Random Forest and SHAP

As global climate change intensifies, Net Ecosystem Productivity (NEP) serves as a crucial indicator for measuring the carbon absorption and release of ecosystems, playing a vital role in understanding the carbon cycle and shaping climate policy. The Northwestern region of China, characterized as a typical inland arid and semi-arid area, is particularly sensitive to global changes. Understanding the environmental drivers of NEP in this region is critical for both regional ecological protection and global environmental management. This study utilized environmental data from five provinces in Northwestern China, applying the Random Forest (RF) model and SHapley Additive exPlanation (SHAP) method to analyze the primary environmental factors influencing NEP. The research integrated climatic data (including temperature, precipitation, wind speed, and solar radiation), soil characteristics such as pH, organic carbon content, and soil texture, topographic attributes elevation and slope, and a Human Footprint. The RF model identified significant environmental factors impacting NEP, and SHAP values were used to explain the specific contributions of these factors. Furthermore, multiple linear regression analysis revealed interactions among environmental factors. The results indicate that solar radiation (Srad), precipitation, topsoil reference bulk density (T_REF_BULK), temperature, and the topsoil clay fraction (T_CLAY) significantly influence NEP. Notably, interactions between aspect and T_CLAY, aspect and T_REF_BULK, as well as the human footprint (HFP) and Srad, also show significant impacts on NEP. This study confirms that solar radiation, precipitation, soil characteristics, and human activities are the primary environmental drivers of NEP in the Northwest region of China, with solar radiation playing the most critical promotional role. The findings not only provide a scientific basis for the management of ecosystems in Northwestern China but also offer references for formulating global climate change mitigation strategies and estimating the global carbon budget. Future research should further explore the specific mechanisms and interactions of these drivers across different ecosystems to more comprehensively understand and predict the trends in NEP changes.

Conceptual Modflow Model Application with Boundary Condition Analysis

In this study, groundwater flow modeling of the aquifer in the Porsuk Basin, located in the Eskisehir province of Turkey, was conducted using the MODFLOW modeling method and the Groundwater Modeling System (GMS) software interface. The modeling was performed using the finite difference method under the assumption of steady flow, incorporating well data, aquifer boundaries, topographic elevations, riverbed data, and hydraulic parameters from the 1971 water year. This study provided insights into changes in groundwater over time and yielded a comprehensive water budget. By creating a three-dimensional solid model of the Porsuk Basin aquifer, general information about the region's hydrogeology was obtained. The results are expected to play a significant role in identifying potential drilling areas for groundwater extraction. Since the modeling utilizes objects from geographic information systems, it will enhance visualization of the regional structure for researchers, allowing them to observe the topographic features of the area in three dimensions. Additionally, it is anticipated that the groundwater conceptual model will inform drilling studies and serve as a foundation for research on groundwater transport and pollution.

Enhanced precipitation responses over the Tibetan Plateau following future Tambora-size volcanic eruption

Hydroclimate over the Tibetan Plateau (TP) notably influences the eco-environment of the Northern Hemisphere. Given its high elevation and complex topography, the climate in the TP shows a high sensitivity to anthropogenic warming and volcanic-induced cooling. The mechanism by which a future volcanic or similar radiative perturbation affects precipitation in the TP under an anthropogenic warming climate must be addressed not only to enable regional adaptation but deepen our understanding of how a climate system evolves under such a dual force. Here, based on the Community Earth System Model version 1.2 and ensemble simulations under pre-industrial and RCP8.5 scenarios, we showed that a Tambora-sized volcanic perturbation led to severe rainfall reduction over the south TP in the following summer (June–August). Evaporation response accounted for a minor and relatively constant share of precipitation reduction following the Clausius–Clapeyron scaling, whereas dynamic processes triggered an El Niño-like response in the eastern equatorial Pacific, which suppressed the Walker and Hadley circulation and contributed to drying anomalies. Global warming renders the post-Tambora hydroclimate responses with 30% higher severity as a result of the increased climatological moisture content and intensified El Niño response, which enhanced hydroclimate sensitivity and attenuated monsoon circulation. The results illustrate the amplification effect of global warming on the plateau's hydroclimate responses to external forcings, which may add another layer of uncertainty on climate adaptation in this already complex region.

Application of active MASW study on irregular and undulated sloping terrain: a case study

ABSTRACT Multichannel Analysis of Surface Waves (MASW) is a geophysical technique used for deciphering subsurface profiling by the determination of shear wave velocity. It is increasingly utilized in sloping terrain; however, its accuracy is limited by the presence of undulating or irregular topography. The study analysed the impact of undulating topography on sloping terrain using models of depressed and elevated topography. The surface waves lose more energy as depth, width, and steepness of the undulated topography increased. The study revealed that the elevated topography had a greater influence than depressed topography. The undulating topography in close proximity to the source resulted in a decrease in resolution dispersion, however the terrain located further away did not have a substantial impact. The study aims to identify suitable configurations that must be taken into account while identifying the subsurface characterization of a sloping terrain using the MASW.

Heavy Minerals Distribution and Provenance in Modern Beach and Fluvial Sands of the Betic Cordillera, Southern Spain

This study uses heavy detrital minerals to determine actualistic fluvial and beach sand provenance across the Betic Cordillera (Spain), along the coast from Almeria to Marbella. The Betic Cordillera, primarily composed of metamorphic rocks to the east, supply an assemblage dominated by almandine and graphite, with a longshore dispersal from Almeria to Malaga. Buergerite and hypersthene indicate the provenance of calcalkaline lavas east of Cabo de Gata. The western part of the Betic Cordillera, which comprises the Ronda Peridotite Complex, supplies a chromite and diopside assemblage, with a dispersal from Marbella to Algeciras. Considering these mineralogical suites, the effects of source rock compositions and weathering are evaluated. The heavy mineral species mirror the mineralogy of the source rocks of local outcrops and wider source terranes. The fluvial heavy mineral suites do not differ significantly from those in the beaches except for some unstable species. Unstable species such as olivine, pyroxene, and amphibole do not show evidence of loss because of elevated topography and semiarid climate, which do not affect heavy minerals. This contribution also evaluates the potential of some heavy detrital species as ideal pathfinders in searching for diamonds.

Extracting an accurate river network: Stream burning re-revisited

Extracting river networks that are both accurate and topologically connected is important for applications that involve correct routing of material, for example water and sediment, through such networks. We combined water and sediment extraction using radar and multispectral imagery from Sentinel-1 and Sentinel-2 to create both water and sediment masks over a range of study areas. These were then used to condition topographic Digital Elevation Models (DEMs) by lowering the elevation of pixels with both water and sediment present, in a process known as stream burning. We examined how stream burning could improve accuracy of extracted networks and identified the most effective method of burning for optimal results. We find deeper burning depths improved accuracy, with diminishing returns: we suggest burning 40 to 50 meters. We find sediment burning improves accuracy in humid and temperate landscapes, but arid landscapes should be burned using only water pixels. We find accuracy of extracted networks is significantly better on the COP30 global topographic dataset compared to the NASADEM dataset, mainly due to the time of collection. The AW3D30 DEM and FABDEM datasets have accuracies just below that of the COP30 DEM.

Hillside urban expansion exacerbates nature and semi-nature habitat landscape fragmentation in China

ABSTRACT Hillside urban expansion (HUE) force nature and semi-nature habitats (referred as nature habitats) to migrate to higher slope areas, potentially resulting in modifications to the landscapes of these habitats, and affect biodiversity and human well-being. To date, few studies have considered the implications of HUE on nature habitat landscapes across different scales. Thus, a spatial identification framework was developed for HUE through the utilization of multisource data. Landscape metrics and spatial econometric models were employed to quantify and assess the impacts of HUE on nature habitat landscapes in China at the city, county, and grid scales, respectively. Results reveal that HUE accounted for 43.25% of urban expansion in China from 2000 to 2020. At the city scale, low HUE was found to have the most significant impact on nature habitat landscape fragmentation. Medium HUE and heavy HUE had more impact of specific landscape metrics with smaller areas at detailed spatial resolutions, and medium HUE have the more considerable impact and surpassed that of low HUE and heavy HUE. HUE exhibited a more pronounced impact on nature habitat landscape fragmentation in regions with larger city sizes and population densities, as well as lower topographic relief and elevations.

Evaluation of elevation parameter determination by Global Navigation Satellite Systems’ sports receivers: A preliminary study

Introduction: Sports Global Navigation Satellite Systems’ receivers have been providing athletes, coaches, and scientists with valuable information on movement for over two decades. As these receivers are specific measuring instruments, there is a need to determine their accuracy. This paper presents a relatively simple methodology for assessing sports receivers of this type regarding their elevation determination. Material and methods: The methodology was based on the Digital Terrain Model of Poland, a discrete representation of the topographic elevation of the land surface. Three wearable devices from different years of manufacture were selected for the preliminary study by calculating the Root Mean Square (RMS), mean elevation error, and Total Elevation Gain (TEG) measures. The testing was conducted on two sections of varying length and elevation differences. Results: During the first trial, an instrument from 2019 came closest to the actual elevation (RMS = 7.0 m; mean error = -6.5 m), while during the second trial, it was an instrument from 2014 (2.5, -1.6 m, respectively). All the receivers overestimated the TEG factor during both trials. Conclusions: The applied methodology allowed the receivers to be distinguished. Due to the preliminary, pilot nature of the study, it is subject to certain limitations and recommendations listed at the end of the article.

A conversion of the geoid to the quasigeoid at the Hong Kong territories

A levelling network was readjusted and a new geoid model compiled within the framework of geodetic vertical datum modernization at the Hong Kong territories. To accomplish all project objectives, the quasigeoid model has to be determined too. A quasigeoid model can be obtained from existing geoid model by applying the geoid-to-quasigeoid separation. The geoid-to-quasigeoid separation was traditionally computed as a function of the simple planar Bouguer gravity anomaly, while disregarding terrain geometry, topographic density variations, and vertical gravity changes due to mass density heterogeneities below the geoid surface. We applied this approximate method because orthometric heights of levelling benchmarks in Hong Kong were determined only approximately according to Helmert’s theory of orthometric heights. Considering a further improvement of the accuracy of orthometric heights by applying advanced numerical procedures, we determined the geoid-to-quasigeoid separation by applying an accurate method. The comparison of the accurately and approximately computed values of the geoid-to-quasigeoid separation revealed significant differences between them. The approximate values are all negative and reach -2.8 cm, whereas values from the accurate method vary between -4.1 and + 0.2 cm. In addition, we assessed the effect of anomalous topographic density on the geoid-to-quasigeoid separation by employing a newly developed digital rock density model. According to our estimates the effect of anomalous topographic density reaches a maximum value of 1.6 cm, reflecting a predominant presence of light volcanic rocks and sedimentary deposits at the Hong Kong territories. Our numerical findings indicate that the conversion between geoid and quasigeoid models should be done accurately, even in regions with a moderately elevated topography.

Groundwater Potential Zone Assessment Using Remote Sensing, Geographical Information System (GIS), and Analytical Hierarchy Process (AHP) Techniques in Fogera Woreda, South Gondar Zone, Ethiopia

The study was conducted to know the groundwater potential zones in Fogera Woreda, south Gondar zone, Ethiopia. Through the utilization of the analytical hierarchy process (AHP), remote sensing, and geographic information system (GIS), the study identified groundwater potential zones. Ten thematic layers were analyzed to delineate the groundwater potential zones, including land use and land cover (LULC), topographic wetness index (TWI), drainage density, lineament density, geology, slope, rainfall, elevation, and soil texture. By determining the relative importance of each thematic layer through AHP and combining all thematic layers through overlay analysis in a GIS environment, the study revealed a spatial variation in the distribution of groundwater potential zones. The results showed that excellent groundwater potentials cover 2.02% of the study area, moderate groundwater potentials cover 45.54%, poor groundwater potentials cover 51.2%, and extremely poor groundwater potentials cover 1.24% of the study area. The study provides valuable information that can be used for decision-making processes and the development of appropriate groundwater management strategies in the region.

The bending of a supra-subduction zone produced crustal thickening and arc migration of the Mongolian Orocline

Orogenic curvatures have been widely recognized along global convergent plate boundaries. Understanding the impact of such curvatures on the tectonic evolution of orogens and their three-dimensional architecture has been challenging. Here we address this issue by studying magmatism around the tightly curved Mongolian Orocline in Central Asia. Our results show that during the Permian–Triassic, arc magmatism around the inner hinge of the orocline became younger towards the core of the orocline. During the same period, the crust was thickened, as indicated by Lanthanum-Ytterbium ratio proxy. These findings, together with the observation that the present-day hinge zone of the Mongolian Orocline is wider, indicate that this zone was subjected to significant crustal-scale contraction. This contractional deformation accounts for the relatively thicker crust around the inner hinge of the Mongolian Orocline, and offers a novel perspective on the formation of elevated topography around the hinge of curved plate boundaries.

Google Earth Engine and Machine Learning for Flash Flood Exposure Mapping—Case Study: Tetouan, Morocco

Recently, the earth’s climate has changed considerably, leading to several hazards, including flash floods (FFs). This study aims to introduce an innovative approach to mapping and identifying FF exposure in the city of Tetouan, Morocco. To address this problem, the study uses different machine learning methods applied to remote sensing imagery within the Google Earth Engine (GEE) platform. To achieve this, the first phase of this study was to map land use and land cover (LULC) using Random Forest (RF), a Support Vector Machine (SVM), and Classification and Regression Trees (CART). By comparing the results of five composite methods (mode, maximum, minimum, mean, and median) based on Sentinel images, LULC was generated for each method. In the second phase, the precise LULC was used as a related factor to others (Stream Power Index (SPI), Topographic Position Index (TPI), Slope, Profile Curvature, Plan Curvature, Aspect, Elevation, and Topographic Wetness Index (TWI)). In addition to 2024 non-flood and flood points to predict and detect FF susceptibility, 70% of the dataset was used to train the model by comparing different algorithms (RF, SVM, Logistic Regression (LR), Multilayer Perceptron (MLP), and Naive Bayes (NB)); the rest of the dataset (30%) was used for evaluation. Model performance was evaluated by five-fold cross-validation to assess the model’s ability on new data using metrics such as precision, score, kappa index, recall, and the receiver operating characteristic (ROC) curve. In the third phase, the high FF susceptibility areas were analyzed for two-way validation with inundated areas generated from Sentinel-1 SAR imagery with coherent change detection (CDD). Finally, the validated inundation map was intersected with the LULC areas and population density for FF exposure and assessment. The initial results of this study in terms of LULC mapping showed that the most appropriate method in this research region is the use of an SVM trained on a mean composite. Similarly, the results of the FF susceptibility assessment showed that the RF algorithm performed best with an accuracy of 96%. In the final analysis, the FF exposure map showed that 2465 hectares were affected and 198,913 inhabitants were at risk. In conclusion, the proposed approach not only allows us to assess the impact of FF in this study area but also provides a versatile approach that can be applied in different regions around the world and can help decision-makers plan FF mitigation strategies.