Using machine learning and deep learning algorithms, the authors found that the algorithms performed well and observed that the wetlands are shrinking, with areas farther from river channels becoming increasingly degraded. Wetlands cover approximately 6% of the Earth's surface, providing habitat for various species and contributing around 40% of global ecosystem services [6; 7; 8]. Ecosystem services provided by these areas include food supply, freshwater, forage, genetic and medicinal materials, as well as regulatory services such as local microclimate control, air purification, water flow regulation, nutrient cycling, soil fertility renewal, pollination, erosion prevention, and flood control, among others [6; 9; 10; 11]. The reduction of vegetation negatively impacts the water surface, as water conservation is an essential service provided by forests. However, there is a lack of studies investigating the importance of Dunnian runoff in forests, especially in tropical ones that have suffered intense devastation. A search in Google Scholar and Science Direct using the terms \"Dunnian runoff and forest\" did not return any research directly studying this correlation, with most studies focusing on hydrological flows. This runoff, crucial for water recharge and soil moisture maintenance, is underestimated [12]. With the degradation of tropical forests, understanding this phenomenon is vital for conservation and environmental recovery strategies, highlighting a critical gap in current environmental research. Therefore, this research aimed to demonstrate the importance of Dunnian runoff in the maintenance, conservation, and preservation of the remnants of the Atlantic Forest. To achieve this objective, a small watershed located on the northern coast of the state of Bahia was chosen as the pilot area. Based on fieldwork, satellite images were used for land use classification employing the Random Forest algorithm. We calculated the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Water Index (NDWI) to assess vegetation concentration and soil moisture. We also used the Digital Terrain Model (DTM) to identify areas with steeper slopes and flat areas, as pointed out by [13]. By comparing spectral indices, land use classification, and DTM, we analyzed the relationship between forest fragments and Dunnian runoff, highlighting hydrological interactions in vegetation within the context of the studied basin. The analyses identified saturated zones with potential for Dunnian runoff, especially in areas with steep slopes, occurring predominantly from the middle course to the mouth of the watershed. Higher areas showed high soil moisture levels, while lower slope areas showed low moisture [14; 15]. The results indicate a positive correlation between steeper slopes and Dunnian runoff and a negative correlation between eucalyptus plantations and soil moisture. Forest fragments with high NDVI and NDWI values suggest a positive correlation between dense vegetation and high moisture. Areas with savannization, silviculture, or no vegetation did not show high moisture levels, indicating a negative correlation. Within a watershed, areas can exhibit runoff originating from four different flow paths driven by two distinct mechanisms. The first occurs when infiltration capacity is exceeded, and the second results from complete soil saturation [16; 17; 18; 19; 20]. Riparian zones, three-dimensional ecotones, are characterized by soil saturation, primarily due to a shallow water table for most of the year. These zones are critical to the watershed for their ecological role in biodiversity, hydrology, and promoting favorable soil conditions [21]. Also known as riparian zones, their delineation can be achieved by identifying typical vegetation of saturated areas or visual soil characteristics, such as color and type [21]. These locations maintain saturated layers at reduced depths, usually near natural watercourses and gently sloping valleys [3; 7], facilitating a specific runoff type known as saturated overland flow.