## 4 Discussion
### Dunnian Runoff: Relationships Between NDVI and NDWI in Forested Areas  
Compared to the spectral indices NDVI and NDWI, both indices (Figure 11A,B) show positive values, indicating the significant presence of both vegetation and soil moisture. According to [59], the values of the first index suggest moderately healthy vegetation, which seems to align with studies by [60] regarding average values, as well as the dependence on rainfall patterns in the region. A view of the climatological water balance (Figure 9) for the year 2021, the date of image acquisition, reveals a 4.7% water deficit, explaining the water stress of the vegetation indicated by NDVI in the forested area. On the other hand, NDWI is associated with the relative amount of water in the soil, as described on the scale in [43; 44], because the accumulated water deficit for the period forces vegetation to adapt by seeking water necessary for survival in deeper soil layers. Adjusting NDVI models based on NDWI to a regression line (Figure 12A), a cluster of data is observed where NDWI explains around 89% of NDVI. Part of this clustering, according to [44], may be associated with confusion of NDWI between values of 0.35 and 0.40, where the model confuses moist soil with tree vegetation. However, we emphasize that for the modeled region, these values are outliers within the studied dataset, which reinforces the idea of the presence of Dunnian runoff in the region. Figure 11: Box plot comparing NDVI and NDWI for the area classified as Atlantic Forest. In (**A**), the box plot of NDVI for the forest fragments is presented, and in (**B**), the box plot of NDWI for the same area is shown. Figure 10: Relationship between NDVI and NDWI, showing a positive correlation between the two indices, presenting a value of 0.9. Duninian Runoff: Relationship Between NDVI and NDVI for Forest, Eucalyptus, Savanna, and Exposed Soil  
Although we classified using mining, we chose not to include the mining land use class in this relationship, as it presents degraded soil without vegetation. Vegetation cover seems highly dependent on soil moisture, which becomes more evident when comparing soil moisture indices with a vegetation index. In native forests, there is an approximately 89% correlation between NDWI and NDVI (Figure 12A), as previously observed. This correlation is even higher in eucalyptus, reaching 92% (Figure 12B), raising a question to be investigated in future research: how much soil moisture does silviculture accumulate? Returning to soil moisture, which influences overland flow, an 83% correlation between NDWI and NDVI can also be observed (Figure 12C) for exposed soil. However, NDWI clustering values are negative, indicating the absence of soil moisture, which in surface runoff formation would accentuate the infiltration component, whereas runoff formation would be prevalent due to lack of vegetation cover, implicating all associated environmental problems. In the forest regeneration process, the region exhibits savanna formation, where the correlation between NDWI and NDVI (Figure 12D) resembles that of exposed soil, with a 78% correlation, but with very low NDWI values falling outside  
Figure 12: The correlation between NDWI and NDVI for various sampled areas within the studied basin is presented, with NDWI plotted on the X-axis and NDVI on the Y-axis. In (**A**), the relationship between NDWI and NDVI for forest fragment samples is shown. In (**B**), the correlation between the spectral indices for the eucalyptus region is presented. (**C**) shows the correlation between NDWI and NDVI for exposed soil samples. Finally, in (**D**), the correlation between these indices for savanna area samples is presented. the moist soil range proposed by [43; 44]. This association can be explained by the fact that savannization involves exposed soil associated with vegetation, atmospheric processes, and solar radiation, leading to high soil evaporation rates.