Redirigiendo al acceso original de articulo en 17 segundos...
Inicio  /  Hydrology  /  Vol: 10 Par: 1 (2023)  /  Artículo
ARTÍCULO
TITULO

Soil Erosion Quantification using Machine Learning in Sub-Watersheds of Northern Portugal

Saulo Folharini    
António Vieira    
António Bento-Gonçalves    
Sara Silva    
Tiago Marques and Jorge Novais    

Resumen

Protected areas (PA) play an important role in minimizing the effects of soil erosion in watersheds. This study evaluated the performance of machine learning models, specifically support vector machine with linear kernel (SVMLinear), support vector machine with polynomial kernel (SVMPoly), and random forest (RF), on identifying indicators of soil erosion in 761 sub-watersheds and PA in northern Portugal, by using soil erosion by water in Europe, according to the revised universal soil loss equation (RUSLE2015), as target variable. The parameters analyzed were: soil erosion by water in Europe according to the revised universal soil loss equation (RUSLE2015), total burned area of the sub-watershed in the period of 1975-2020, fire recurrence, topographic wetness index (TWI), and the morphometric factors, namely area (A), perimeter (P), length (L), width (W), orientation (O), elongation ratio (Re), circularity ratio (Rc), compactness coefficient (Cc), form factor (Ff), shape factor (Sf), DEM, slope, and curvature. The median coefficient of determination (R2) for each model was RF (0.61), SVMpoly (0.68), and SVMLinear (0.54). Regarding the analyzed parameters, those that registered the greatest importance were A, P, L, W, curvature, and burned area, indicating that an analysis which considers morphometric factors, together with soil erosion data affected by water and soil moisture, is an important indicator in the analysis of soil erosion in watersheds.

 Artículos similares

       
 
Bofu Zheng, Dan Wang, Yuxin Chen, Yihui Jiang, Fangqing Hu, Liliang Xu, Jihong Zhang and Jinqi Zhu    
Background: Vegetation roots are considered to play an effective role in controlling soil erosion by benefiting soil hydrology and mechanical properties. However, the correlation between soil hydrology and the mechanical features associated with the vari... ver más
Revista: Water

 
Jarrett Wise and Mohammed F. Al Dushaishi    
Revista: Water

 
Shu Zhang, Yong Zhang, Gang Huang, Bo Zhang, Yichan Li, Xin Chen, Junkang Xu and Yujie Wei    
Granites, widely distributed in the Earth?s crust, undergo pedogenic processes, shaping diverse soil-mantled landscapes influenced by climatic factors in different regions. Investigating the geochemical signatures in granite weathering profiles across va... ver más
Revista: Water

 
Sayed Shah Jan Sadiqi, Won-Ho Nam, Kyoung-Jae Lim and Eunmi Hong    
This study investigated the effects of nonpoint source (NPS) pollution reduction and pollutant dynamics in a highland agricultural watershed in Korea. We employed the SWAT model to simulate hydrological processes and pollution transport within the waters... ver más
Revista: Water

 
Shengchun Tong, Guorong Li, Jinfang Li, Xilai Li, Chengdong Jiang, Jianyun Zhao, Haili Zhu, Yabin Liu, Wenting Chen and Xiasong Hu    
The plateau pika (Ochotona curzoniae) actively contributes to soil erosion and meadow degradation in western China?s Yellow River source zone. This study aimed to elucidate the effects of the pika mound numbers on the hydrodynamic characteristics and soi... ver más
Revista: Water