Identifying critical source areas of non-point source pollution to enhance water quality: Integrated SWAT modeling and multi-variable statistical analysis to reveal key variables and thresholds.

By integrating soil and water assessment tool (SWAT) modeling and land use and land cover (LULC) based multi-variable statistical analysis, this study aimed to identify driving factors, potential thresholds, and critical source areas (CSAs) to enhance water quality in southern Alabama and northwest Florida's Choctawhatchee Watershed. The results revealed the significance of forest cover and of the lumped developed areas and cultivated crops ("Source Areas") in influencing water quality. The stepwise linear regression analysis based on self-organizing maps (SOMs) showed that a negative correlation between forest percent cover and total nitrogen (TN), organic nitrogen (ORGN), and organic phosphorus (ORGP), highlighting the importance of forests in reducing nutrient loads. Conversely, Source Area percentage was positively correlated with total phosphorus (TP) loads, indicating the influence of human activities on TP levels. The receiver operating characteristic (ROC) curve analysis determined thresholds for forest percentage and Source Area percentage as 37.47 % and 20.26 %, respectively. These thresholds serve as important reference points for identifying CSAs. The CSAs identified based on these thresholds covered a relatively small portion (28 %) but contributed 47 % of TN and 50 % of TP of the whole watershed. The study underscores the importance of considering both physical process-based modeling and multi-variable statistical analysis for a comprehensive understanding of watershed management, i.e., the identification of CSAs and the associated variables and their tipping points to maintain water quality.

The spatial pattern of Scirpus mariqueter expansion and the associated mechanism of self-organization using unmanned aerial vehicles and its significance for coastal wetland restoration.

Understanding the spatial expansion process of salt marshes and quantifying the factors driving this expansion are crucial for the management and restoration of coastal wetlands. In this study, we aimed to illustrate the expansion process of Scirpus mariqueter using drone remote sensing and quantify its relationship with habitat quality. Our hypothesis was that landscape metrics could serve as valuable indicators for prioritizing habitat restoration efforts along the coast. We utilized drone remote sensing and adopted the simple Greenness Index to reflect the growth status of S. mariqueter. Using this index, we computed the standard deviation ellipse and growth center. To evaluate habitat quality, we developed a method based on our previous research and other relevant reports. We then conducted a quantitative analysis of the expansion process of S. mariqueter in areas with varying habitat quality. We found that S. mariqueter's optimal elevation was 3.7 m, with a range of 2.5 to 4.3 m. The threshold value for soil total nitrogen was 0.3 g/kg, and the tolerance threshold for soil salinity was 2500 ppm. These three factors, elevation, soil total nitrogen, and soil salinity, collectively influenced habitat quality, with weights of 0.68, 0.23, and 0.09, respectively, as determined through geodetector analysis. During the summer, we observed a dominance of dispersal in S. mariqueter, with the species primarily spreading to areas with increased habitat quality. Patch shapes tended to be compact and regular in this season. In contrast, during the autumn, a dominance of decline was observed, with S. mariqueter mainly distributing to areas exhibiting decreased habitat quality. Patch shapes tended to be complex and irregular in the autumn season. Eventually micro-geomorphic modification and patch shape filling methods based on UAV observations are proposed to aid wetland restoration. These findings are of utmost importance for the restoration of coastal wetlands and the enhancement of ecosystem resilience.