# The Influence of Hard Protection Structures on Shoreline Evolution in Riohacha, Colombia
## 3 Methodology
The Standard Error of Slope (LCI) measures the uncertainty of the LRR calculation at a 95% confidence interval, serving as an indicator of variability. Lastly, the Coefficient of Determination (LR2) assesses the goodness of fit of the regression model, with values close to 1 indicating a strong correlation between time and shoreline/cliff position, while lower values suggest \begin{table}
\begin{tabular}{c c c} \hline
**Image** & **Source** & **Date** \\ \hline IGAC1987 & Instituto Geografico Agustin Codazzi & 14 September 1987 \\ IGAC1997 & Instituto Geografico Agustin Codazzi & 12 January 1997 \\ GE2003-02 & Google Earth & February 2003 \\ GE2006-03 & Google Earth & March 2006 \\ GE2009-10 & Google Earth & October 2009 \\ GE2011-01 & Google Earth & January 2011 \\ GE2013-02 & Google Earth & February 2013 \\ GE2014-11 & Google Earth & November 2014 \\ GE2018-03 & Google Earth & March 2018 \\ GE2019-10 & Google Earth & October 2019 \\ GE2020-10 & Google Earth & October 2020 \\ GE2022-11 & Google Earth & November 2022 \\ \hline \end{tabular}
\end{table} 
Table 1: Main information from the images used in this research. greater variability. These metrics are crucial for evaluating past trends and informing future predictive models. The number of transects varies across the study area (Figure 3), with 6 in Zone 1, 14 in Zone 2, and 12 in Zone 3. In Zone 1, transects are positioned between the groins and numbered sequentially from north to south (1 to 6). The selection of 6 transects in Zone 1 corresponds to the six cells created by the groins; given the limited spatial extent and homogeneous behavior within each compartment, only one transect was placed in each cell. In Zone 2, 10 transects, spaced approximately 200 m apart, analyze cliff evolution, while 4 additional profiles assess the impact of the seawall on beach morphodynamics, with two located north and two south of the structure. In Zone 3, 12 transects examine changes in the cliff profile. Due to data availability, the analysis of Zones 2 and 3 begins in 2003, limiting their study period to 2003-2022. In contrast, the higher number of transects in Zones 2 and 3 reflects greater geomorphological complexity and spatial variability, especially related to cliff morphology. In addition, the change in the surface area of the beach or cliff can be calculated for each period between available images, using the oldest image as the reference. This analysis is performed using the GIS program ArcGIS Pro [56] by creating polygons between the different coastlines and their corresponding lateral boundaries. This method allows for the calculation of erosion or accretion surfaces over time in each zone of the study area. In Zone 1, each beach section between consecutive groins is analyzed independently. In  
Figure 3: Transects for each zone of the study area: (**A**) Zone 1; (**B**) Zone 2; (**C**) Zone 3. Red transects represent shoreline measurements, while blue transects correspond to cliff monitoring. Source: Google Earth Pro, year 2018. Zone 3, the change in cliff surface is calculated starting from 2003. The resulting data are expressed in square meters. Estimating the future position of the coastline is a challenging aspect of coastal studies, yet it plays a crucial role in urban planning and the socioeconomic development of coastal areas [57; 58]. The interplay of multiple factors at varying spatial and temporal scales leads to significant uncertainties in long-term predictions [59]. Nevertheless, several approaches can be employed to forecast coastline position, considering the inherent variability of these environments. In this research, three models have been utilized to make these predictions: historical trend analysis, extrapolation from historical data, and the Kalman filter model.