Runoff and Soil Loss Estimation Using N-SPECT in the Rio Grande de Anasco Watershed, Puerto Rico

2015 ◽  
pp. 163-181
Author(s):  
Matilde Duque ◽  
Assefa M. Melesse
Keyword(s):  
Puerto Rico ◽  
Soil Loss ◽  
Rio Grande ◽  
Loss Estimation ◽  
Runoff And Soil Loss

ASSESSMENT OF SOIL EROSION IN VINH LINH, QUANG TRI USING RMMF MODEL (REVISED MORGAN - MORGAN - FINNEY)

2013 ◽  
Vol 83 (5) ◽  
Author(s):  
Nguyễn Quang Việt ◽  
Trương Đình Trọng ◽  
Hồ Thị Nga
Keyword(s):  
Soil Erosion ◽  
Land Cover ◽  
Soil Loss ◽  
Soil Particle ◽  
Transport Capacity ◽  
Gis Technology ◽  
Particle Detachment ◽  
Sediment Transport Capacity ◽  
Northern District ◽  
Runoff And Soil Loss

Vinh Linh, the northern district of Quang Tri province is characterized by a diversified topography with a large variety of elevations, high rainfall, and decreasing land cover due to forest exploiting for cultivation land. Thus, there is a high risk of erosion, soil fertility washout. With the support of GIS technology, the authors used the rMMF model to measure soil erosion. The input data of model including 15 coefficients related to topography, soil properties, climate and land cover. The simulations of rMMF include estimates of rainfall energy, runoff, soil particle detachment by raindrop, soil particle detachment by runoff, sediment transport capacity of runoff and soil loss. The result showed that amount of soil loss in year is estimated to vary between 0 kg/m2 minimum and 149 kg/m2 maximum and is divided into 4-classes of erosion. Light class almost covers the region researched (75.9% of total area), while moderate class occupies 8.1% of total area, strong classes only hold small area (16% of total area). Therefore, protection of the forest floor in sloping areas is one of the most effective methods to reduce soil erosion.

Runoff and Soil Loss of a Typical Subtropical Forest Stricken by Wenchuan Earthquake

2013 ◽  
Vol 19 (5) ◽  
pp. 766-773
Author(s):  
Jinniu WANG ◽  
Geng SUN ◽  
Fusun SHI ◽  
Jiceng XU ◽  
Yan WU ◽  
...  
Keyword(s):  
Wenchuan Earthquake ◽  
Soil Loss ◽  
Subtropical Forest ◽  
Runoff And Soil Loss

scholarly journals Use of satellite and modeled soil moisture data for predicting event soil loss at plot scale

2015 ◽  
Vol 19 (9) ◽  
pp. 3845-3856 ◽  
Author(s):  
F. Todisco ◽  
L. Brocca ◽  
L. F. Termite ◽  
W. Wagner
Keyword(s):  
Soil Moisture ◽  
Soil Loss ◽  
Large Scale ◽  
Central Italy ◽  
Remote Sensing Data ◽  
Loss Estimation ◽  
Balance Model ◽  
Estimation Accuracy ◽  
Soil Losses

Abstract. The potential of coupling soil moisture and a Universal Soil Loss Equation-based (USLE-based) model for event soil loss estimation at plot scale is carefully investigated at the Masse area, in central Italy. The derived model, named Soil Moisture for Erosion (SM4E), is applied by considering the unavailability of in situ soil moisture measurements, by using the data predicted by a soil water balance model (SWBM) and derived from satellite sensors, i.e., the Advanced SCATterometer (ASCAT). The soil loss estimation accuracy is validated using in situ measurements in which event observations at plot scale are available for the period 2008–2013. The results showed that including soil moisture observations in the event rainfall–runoff erosivity factor of the USLE enhances the capability of the model to account for variations in event soil losses, the soil moisture being an effective alternative to the estimated runoff, in the prediction of the event soil loss at Masse. The agreement between observed and estimated soil losses (through SM4E) is fairly satisfactory with a determination coefficient (log-scale) equal to ~ 0.35 and a root mean square error (RMSE) of ~ 2.8 Mg ha−1. These results are particularly significant for the operational estimation of soil losses. Indeed, currently, soil moisture is a relatively simple measurement at the field scale and remote sensing data are also widely available on a global scale. Through satellite data, there is the potential of applying the SM4E model for large-scale monitoring and quantification of the soil erosion process.

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