Geospatial products, such as digital elevation models (DEMs), are important topographic tools for tackling local flood studies. This study investigates the contribution of LiDAR elevation data in DEM generation based on fixed-wing unmanned aerial vehicle (UAV) imaging for flood applications. More specifically, it assesses the accuracy of UAV-derived DEMs using the proposed LiDAR-derived control point (LCP) method in a Structure-from-Motion photogrammetry processing. Also, the flood estimates (volume and area) of the UAV terrain products are compared with a LiDAR-based reference. The applied LCP-georeferencing method achieves an accuracy comparable with other studies. In addition, it has the advantage of using semi-automatic terrain data classification and is readily applicable in flood studies. Lastly, it proves the complementarity between LiDAR and UAV photogrammetry at the local level.

Se planteó una estrategia metodológica que solventa la escasez de datos para la modelación 2D de inundaciones en un delta. Digitalizando la elevación disponible en Google Earth^TM e integrada con secciones levantadas en el río y datos topográficos, se obtuvo una nube de puntos topográfica. Esta fue posteriormente interpolada a una red de triángulos irregular, y finalmente, la generación de un Modelo Digital del Terreno. Se simuló bidimensionalmente (IBER v2.3.2) un evento de inundación y una medida estructural (dique) para proteger una comunidad vulnerable. El desbordamiento se presentó solamente en el tramo final del cauce, por tanto, no influyó sobre el área urbana de la ciudad de Riohacha. El dique lograría evitar artificialmente las inundaciones en la zona protegida, pero aumentando el riesgo por inundación ante posibles fallas debido a crecidas de mayor magnitud. De acuerdo a los resultados, la metodología planteada es útil para el cálculo de áreas inundables en zonas deltaicas y apoyo a la toma decisiones en regiones con escases de datos.

Like many coastal lagoons in several countries, the “Navío Quebrado” lagoon (La Guajira, Colombia) is a very delicate and precious environment; indeed, it is a nationally recognized Flora and Fauna Sanctuary. Several factors, including climate change, are threatening its existence because of changes in the governing hydro-morphological and biological processes. Certainly, the first step to addressing this problem is to understand its hydrological behavior and to be able to replicate, via simulation, its recent history before inferring likely futures. These potential futures will be marked by changes in the water input by its tributary, the Camarones River, and by modified water exchange with the sea, according to a foreseen sea level rise pattern, as well as by a different evaporation rate from the free surface, according to temperature changes. In order to achieve the required ability to simulate future scenarios, data on the actual behavior have to be gathered, i.e., a monitoring system has to be set up, which to date is non-existent. Conceptually, designing a suitable monitoring system is not a complex issue and seems easy to implement. However, the environmental, socio-cultural, and socio-economic context makes every little step a hard climb. An extremely simple—almost “primitive”—monitoring system has been set up in this case, which is based on very basic measurements of river flow velocity and water levels (river, lagoon, and sea) and the direct participation of local stakeholders, the most important of which is the National Park unit of the Sanctuary. All this may clash with the latest groovy advances of science, such as in situ automatized sensors, remote sensing, machine learning, and digital twins, and several improvements are certainly possible and desirable. However, it has a strong positive point: it provides surprisingly reasonable data and operates at almost zero additional cost. Several technical difficulties made this exercise interesting and worthy of being shared. Its novelty lies in showing how old, simple methods may offer a working solution to new challenges. This humble experience may be of help in several other similar situations across the world.

This paper presents a novel methodology to generate Digital Elevation Models (DEMs) in flat areas, incorporating river channels from relatively coarse initial data. The technique primarily utilizes filtered dense point clouds derived from SfM-MVS (Structure from Motion-Multi-View Stereo) photogrammetry of available crewed aerial imagery datasets. The methodology operates under the assumption that the aerial survey was carried out during low-flow or drought conditions so that the dry (or almost dry) riverbed is detected, although in an imprecise way. Direct interpolation of the detected elevation points yields unacceptable river channel bottom profiles (often exhibiting unrealistic artifacts) and even distorts the floodplain. In our Fluvial Domain Method, channel bottoms are represented like “highways”, perhaps overlooking their (unknown) detailed morphology but gaining in general topographic consistency. For instance, we observed an 11.7% discrepancy in the river channel long profile (with respect to the measured cross-sections) and a 0.38 m RMSE in the floodplain (with respect to the GNSS-RTK measurements). Unlike conventional methods that utilize active sensors (satellite and airborne LiDAR) or classic topographic surveys—each with precision, cost, or labor limitations—the proposed approach offers a more accessible, cost-effective, and flexible solution that is particularly well suited to cases with scarce base information and financial resources. However, the method’s performance is inherently limited by the quality of input data and the simplification of complex channel morphologies; it is most suitable for cases where high-resolution geomorphological detail is not critical or where direct data acquisition is not feasible. The resulting DEM, incorporating a generalized channel representation, is well suited for flood hazard modeling. A case study of the Ranchería river delta in the Northern Colombian Caribbean demonstrates the methodology.

Over the past 50 years, coastal erosion has become an increasingly critical issue worldwide, and Colombia’s Caribbean coast is no exception. In urban areas, this challenge is further complicated by hard protection structures, which, while often implemented as immediate solutions, can disrupt sediment transport and trigger unintended long-term consequences. This study examines shoreline changes in Riohacha, the capital of La Guajira Department, over a 35-year period (1987–2022), focusing on the impacts of coastal protection structures—specifically, the construction of seven groins and a seawall between 2006 and 2009—on coastal dynamics. Using twelve images (photographs and satellite) and the Digital Shoreline Analysis System (DSAS), the evolution of both beaches and cliffs has been analyzed. The results reveal a dramatic shift in shoreline behavior: erosion rates of approximately 0.5 m/year prior to the interventions transitioned to accretion rates of up to 11 m/year within the groin field, where rapid infill occurred. However, this sediment retention has exacerbated erosion in downstream cliff areas, with retreat rates reaching 1.8 ± 0.2 m/year. To anticipate future coastal evolution, predictive models were applied through 2045, providing insights into potential risks for infrastructure and urban development. These findings highlight the need for a strategic, long-term approach to coastal management that considers both the benefits and unintended consequences of engineering interventions.

Like many coastal lagoons in several countries, “Navío Quebrado” lagoon (La Guajira-Colombia) is a very delicate and precious environment; indeed, it is a nationally recognized Flora and Fauna Sanctuary. Several factors, amongst which climate change, are threatening its existence because of changes in the governing hydro-morphological processes. A first step to address this problem certainly is to understand its hydrological behavior and to be able to replicate via simulation its recent history and then infer likely futures. These potential futures will be marked by changes in the water input by its tributary, the Camarones River, and by a modified water exchange with the sea, according to a foreseen sea level rise pattern, as well as by a different evaporation from the free surface, according to temperature changes. In order achieve the required ability to simulate future scenarios, data on the actual behavior have to be gathered, i.e. a monitoring system has to be set up, which to date is not existent. Conceptually, designing a suitable monitoring system is not a complex issue and seems easy to implement. However, the environmental and socio-cultural and socio-economic context makes every little step a hard climb. An extremely simple –almost “primitive”- monitoring system has been set up in this case which is based on very basic measurements of current velocity and water levels and a direct participation of local stakeholders, first of all the National Park unit of the Sanctuary. All this may clash with the latest groovy advances of science, like in situ automatized sensors, remote sensing, machine learning and digital twins, and certainly several improvements are possible and desirable. But it has strong positive points: it is providing surprisingly reasonable data and…it is working at almost zero additional cost. Several technical difficulties made this exercise interesting in itself and worth being shared. Its novelty lies in showing how old, simple methods may offer a working solution to new challenges. This humble experience may be of help in several other similar situations across the world.