## 3 Results  
The results of this work reveal significant insights into how the CRW was affected by different meteorological phenomena during the timespan of the datasets. These findings are discussed in Section 4. Table 2 presents a general overview of what occurred at the CRW from a large point of view. However, these should not be considered as average values. For example, the years 2020 and 2017 are relatively close in terms of the highest values of ET, but on a full scale, it is known that the average ET value for 2020 is greater than that for 2017. Figure 3 shows NDVI 16-day interval data. NDVI 16-day values were greater in comparison with daily NDVI values. Daily values of NDVI were calculated using Landsat 8-9 OLI-TRIS with the near-infrared band and red band. NDVI datasets for a decade will help us estimate the health and changes in land use for Culebrinas ecosystems. These datasets help determine plant health across the watershed, and we can use these parameters to determine the resilience of ecosystems within the CRW. We also compared NDVI with the other evaluated parameters during the time of study. NDVI values for 2017 were the lowest values of NDVI for the decade evaluated. Hurricane Maria's strong winds, floods, and landslides also had a negative effect on the vegetation in Puerto Rico. The biggest impact on health and vegetation cover for 2017 was seen in regions closer to the coast or urban areas where the ecosystem was already weakened. Coastal areas are more prone to significant changes in vegetation after a hurricane, due to the type/amount of vegetation. The type of vegetation closer to the coast is mainly grassland, whereas in the mountain range, we can find forest areas with denser vegetation. Because of the density of the vegetation in the mountain range, loss of vegetation is less prone to happen. Additionally, 16-day NDVI values from MODIS have a pixel resolution of 250 m and have been available since 2000 to present. We can use values of NDVI to see trends and the effect that atmospheric events have on vegetation cover. For example, as shown in Figure 3, the trend for 2020 was that greater values of NDVI were present at lower temperatures. Lastly, the map of September 2022 shows NDVI values during a prolonged dry season in Puerto Rico. This is associated with the correlation of LST and NDVI (Figure 4). \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline  & \multicolumn{2}{c}{**NDVI**} & \multicolumn{2}{c}{**LST**} & \multicolumn{2}{c}{**ET**} & \multicolumn{2}{c}{**GPP**} \\ \cline{2-9}  & \multicolumn{4}{c}{**UNITS**} \\ \cline{2-9}
**Year** & \multicolumn{2}{c}{**-**} & \multicolumn{2}{c}{\({}^{\circ}\)**C**} & \multicolumn{2}{c}{**mm/day**} & \multicolumn{2}{c}{**kg/\({}^{\circ}\)C/day**} \\ \cline{2-9}  & **Low** & **High** & **Low** & **High** & **Low** & **High** & **Low** & **High** \\ \hline
2012 & 0.0981 & 0.986 & - & - & 1.8374 & 7.8125 & 0.0116 & 3.2762 \\
2013 & 0.2229 & 0.9195 & 19.1045 & 33.2603 & 1.2250 & 7.1500 & 0.0235 & 3.2762 \\
2014 & 0.265 & 0.9176 & 22 & 34 & 2.2000 & 7.3375 & 0.0372 & 3.2762 \\
2015 & 0.2403 & 0.9373 & 22.6019 & 39.3491 & 1.5625 & 8.0375 & 0.0115 & 3.2762 \\
2016 & 0.1296 & 0.9941 & 20.6582 & 34.6485 & 1.9875 & 6.8375 & 0.0145 & 3.2762 \\
2017 & 0.0774 & 0.9768 & 22 & 35.4926 & 1.9375 & 5.8375 & 0.0147 & 3.2762 \\
2018 & 0.4147 & 0.9119 & 23.3586 & 35.6335 & 1.3750 & 4.6125 & 0.0128 & 3.2762 \\
2019 & 0.3045 & 0.9622 & 23 & 34 & 1.3999 & 6.1750 & 0.0241 & 3.2762 \\
2020 & 0.2037 & 0.9885 & 21.1934 & 35 & 1.8125 & 5.5008 & 0.0089 & 3.2762 \\
2021 & 0.2328 & 0.9346 & 22.9827 & 34.1233 & 1.5000 & 8.4250 & 0.0121 & 3.2762 \\
2022 & 0.2909 & 0.9323 & 22.8446 & 35.9824 & 2.2000 & 8.3125 & - & - \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Estimated range of NDVI, LST, ET, and GPP for WRC from 2012 to 2022. High values of GPP, 3.2762 kg, correspond to land cover assigned as urban. The LST estimates were computed using Landsat 8-9 datasets.