DOI: 10.5194/hess-19-3845-2015
Scopus记录号: 2-s2.0-84941341288
论文题名: Use of satellite and modeled soil moisture data for predicting event soil loss at plot scale
作者: Todisco F ; , Brocca L ; , Termite L ; F ; , Wagner W
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2015
卷: 19, 期: 9 起始页码: 3845
结束页码: 3856
语种: 英语
Scopus关键词: Erosion
; Mean square error
; Meteorological instruments
; Moisture
; Remote sensing
; Runoff
; Satellites
; Sediment transport
; Soil moisture
; Soils
; Determination coefficients
; In-situ measurement
; Large-scale monitoring
; Remote sensing data
; Root mean square errors
; Situ soil moistures
; Soil water balance model
; Universal soil loss equation
; Soil surveys
; accuracy assessment
; ASCAT
; field method
; model validation
; prediction
; rainfall-runoff modeling
; remote sensing
; satellite data
; soil erosion
; soil moisture
; soil water potential
; spatiotemporal analysis
; Universal Soil Loss Equation
; Italy
英文摘要: 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. © Author(s) 2015. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/78429
Appears in Collections: 气候变化事实与影响
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作者单位: Department of Agricultural, Food and Environmental Sciences, Hydraulic and Forestry Division, University of Perugia, Perugia, Italy; Research Institute for Geo-Hydrological Protection, National Research Council, Perugia, Italy; Department of Geodesy and Geoinformation, Vienna University of Technology, 10 Gusshausstr. 27-29, Vienna, Austria
Recommended Citation:
Todisco F,, Brocca L,, Termite L,et al. Use of satellite and modeled soil moisture data for predicting event soil loss at plot scale[J]. Hydrology and Earth System Sciences,2015-01-01,19(9)